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AI panel shares business strategy, cybersecurity insights
NJBIZ panelists share strategies for adopting AI, managing cybersecurity risks and improving business efficiency.
Small Business Technology News This Week: AI Shopping Searches Surges, Thryv And Wix Partner, Gemini Notebook Gets An Upgrade
AI adoption is accelerating across commerce and industry, as new partnerships and tools help businesses improve sales, cash flow, productivity and efficiency.
Experts share MRI efficiency strategies that could raise revenue by upward of 60%
Workflow redesigns have the potential to improve MRI throughput by 20%, while AI-based protocol optimization could boost efficiencies by another 35%, experts write in Clinical Imaging.
Delaware Keeps Business Filing Edge as Texas Starts Fast Service
Although the creation of the Texas Express service is an improvement for Texas entities, the Delaware Division of Corporations still provides a superior level of speed, responsiveness, efficiency, and cost, write Francis G.X. Pileggi and Aimee Czachorowski.
The Beauty Of Settled Science
Commenters convinced me I made a subtle mis-step in my framing of Psychology Research Is Mostly Fine. My framing emphasized that social priming studies had failed to replicate, but that many other subfields of psychology hadn’t. This naturally led commenters to point to failed replications in other subfields. Although none of these were as bad as social priming, few or none were entirely problem-free. Instead of emphasizing the difference between social priming and other subfields, I should have emphasized the difference between settled science and novel research. Here are some of my favorite psychology findings: The brain is sculpted by reinforcement learning, and a key driver of this learning is a prediction-error-based algorithm located in the nucleus accumbens and implemented through dopamine. Psychedelic drugs exert their effects through 5-HT2A receptors, pointing to a role for these receptors in some sort of construct like the balance between priors and new evidence. Certain cognitive functions are localized to certain brain areas (for example, impulse control to the frontal lobes; linguistic structure to Broca’s area, linguistic meaning to Wernicke’s area. But injure one of these areas, or render a certain function useless (eg a blind person having no more use for their visual cortex), and these mappings can gradually shift - suggesting that neurons are general-purpose compute whose specialization is a contingent fact about convenience and efficiency rather than a necessity. Most personality traits and general capabilities are about 50% genetic and 50% random, with little role for family environment or childhood history, with a few notable exceptions like partisan preference. Recent research complicates this story, but the further you go from this basic picture, the gnarlier the chains of indirect causation you require. Neurons fire together in “brain waves”, whose exact frequency corresponds with the character of consciousness; These divide neurons into natural subpopulations and linked graphs. The gamma rhythm corresponds surprisingly well to items in conscious awareness. GABA receptors seem to be involved in something like relaxation. By hitting different GABA receptors in different ways, you can modulate the exact type of relaxation you produce. Hitting GABA-A directly is too powerful and can cause dangerous levels of sedation, but allosteric modulation of GABA is an incredibly fruitful strategy that underlies drugs from benzos to barbituates to alcohol. If you know your GABA-A subunits, you can target specific subtypes of relaxation; for example, Ambien hits GABA-A1 and induces sleep. Memory divides somewhat fuzzily into bins of immediate-sensory, short-term, and long-term, with separate retrieval and storage functions, and separate systems for declarative vs. procedural learning. These can be harmed selectively, usually by hippocampal injury, so that some patients can remember their life stories but not form new long-term memories, or learn new skills like bike-riding but not new facts. The exact substrate of memory is unclear but seems to involve new synaptic connections between neurons in at least some way. The ability of modern psychology and psychiatry to treat mental illness is real but limited. SSRIs work for half or slightly fewer than half of patients; antipsychotics work with extreme side effects; benzodiazpines work but produce addiction and tolerance in many (not all) people. Most supplements are stuck in Poor Quality Study Replication Crisis Hell, but melatonin and l-theanine stand out as especially promising. Psychotherapy works with moderate effect size, but (with a few exceptions) seems to be more about the relationship with the provider than the details of the therapy itself. Mental hospitalization can sometimes defuse immediate crises but work less well than mental hospitals would like, with some studies showing overall negative effects. Schizophrenia is mostly genetic, but risk also increases with prenatal infection (especially rubella) and obstetric complications; there is suggestive evidence for roles of social stress and drug use (with psychedelics and marijuana making things worse, and nicotine if anything making things better). Bipolar and schizophrenia are so closely linked on a pathophysiological level that it seems like they might be the same disease; on the clinical level, they do seem to follow two separate courses/prognoses but can sometimes surprise clinicians by eg someone who seemed condemned to permanent schizophrenia unexpectedly recovering. The brain’s native reinforcement learning algorithms cash out in the phenomena of classical and operant conditioning; different reinforcement schedules reinforce at different levels, which can be exploited by bad actors to make especially compelling products (eg slot machines). None of these are immune to doubt. A few are speculative; one or two are genuinely unorthodox. But they’re all a step above one p = 0.049 paper that might not replicate. If they get overturned, they’ll be overturned by the same sort of genuine scientific shift that replaced Ptolemy with Copernicus or Lamarck with Darwin, not some sort of sordid discovery about someone entering random numbers into a spreadsheet. In 2008, Eliezer Yudkowsky wrote about The Beauty Of Settled Science: If you only care about scientific issues that are controversial, you will end up with a head stuffed full of garbage. The media thinks that only the cutting edge of science is worth reporting on. How often do you see headlines like “General Relativity still governing planetary orbits” or “Phlogiston theory remains false”? So, by the time anything is solid science, it is no longer a breaking headline. “Newsworthy” science is often based on the thinnest of evidence and wrong half the time—if it were not on the uttermost fringes of the scientific frontier, it would not be breaking news. Scientific controversies are problems so difficult that even people who’ve spent years mastering the field can still fool themselves. That’s what makes for the heated arguments that attract all the media attention. Worse, if you aren’t in the field and part of the game, controversies aren’t even fun. Don’t be embarrassed to read elementary science textbooks, either. If you want to pretend to be sophisticated, go find a play to sneer at. If you just want to have fun, remember that simplicity is at the core of scientific beauty [...] A steady diet of science news is bad for you: You are what you eat, and if you eat only science reporting on fluid situations, without a solid textbook now and then, your brain will turn to liquid. Psychology isn’t centrally the new paper in Annals Of Recently-Breaking News saying that an n=5 study showing that large portion sizes increase support for terrorism. Psychology is centrally ideas like brain waves, GABA receptors, reinforcement learning, twin studies, and connectionism. People who think differently are worrying too much about BREAKING NEWS!!!, and should stop. The key distinction isn’t “recent research in social psychology” vs. “recent research in cognitive/bio/behavioral psychology”, as my essay last week unfortunately implied. It’s recent research in general vs. the deposit of settled science, battle-tested hypotheses, and carefully-earmarked speculation. And part of the reason social priming in particular was such a disaster was that it defied that heuristic, building itself up over hundreds of studies until it approached or even entered the pantheon of settled science - before collapsing (5-HTTLPR was also sort of like this). This isn’t a claim that settled science is always right - Freud was “settled science” for a long time - just that there’s an intuitive distinction between the level of credence you should have in the existence of power posing vs. the existence of Broca’s Area. (I compounded this error by calling the last post “Psychology Research Is Mostly Fine”, which suggested I was talking about the new research rather than the settled science. I actually meant to distinguish between research-psychology-the-field vs. clinical-psychology-aka-therapy, but this framing unintentionally pushed against the point I wanted to make) Some commenters on the previous article understood this point, but challenged its weight. It’s very cool, they said, to know how many neurons are in which brain lobe, but the main way that Psychology affected their lives was through bad clickbait studies used to buttress dumb policies; some p = 0.049 study says that exposure to microaggressions makes minorities’ brains shrivel into raisins, and now their company has to implement punitive DEI or be sued for hazardous work conditions. I won’t dispute this as an accurate description of how the sausage gets made, but it’s worth examining the trains of thought that connect this observation to a campaign against psychology in general: The dumb woke psychology was wrong and bad, and I don’t have good heuristics for distinguishing dumb woke psychology from other psychology, so I’m going to assume it’s all wrong and bad. The dumb woke psychology was wrong and bad; it seems useful to punish/discredit psychology as a whole to assist my campaign against it, so for propaganda purposes I will try to discredit psychology as a whole. To people in the first camp, my response is: come on, your heuristics aren’t that bad. “Microaggressions makes minorities’ brains shrivel up like raisins” is in the woke category; “the hippocampal theta rhythm seems to be associated with both memory and pathfinding, suggesting an unexpected yet surprisingly compelling relationship between the two” is in the not-woke category, don’t play dumb here. To people in the second camp, my response is: deliberately exaggerated propaganda campaigns are bad and this is a confession, not an excuse. Inability to view science through anything but a political lens was what got us into this problem; doubling down on it is a temporary solution but a recipe for permanent disaster. If you pronounce entire fields of science to be acceptable collateral damage in your campaign against bad political actors, you will alienate not just scientists but patients, clinicians, and general lovers of truth. Instead, you can say the thing you mean - that woke partisans shouldn’t try to occupy and exploit the otherwise-noble science of psychology for their own political gain - and wage the same campaign with a halo rather than a comic-book-villain goatee. From the font of oracular wisdom that is Weird Sun Twitter: [ Vessel Of Spirit@VesselOfSpirit i love you all conditionally but i love the good part of you unconditionally. even if it becomes a very small part 2:11 AM · Jan 22, 2015 1 Reply · 5 Reposts · 29 Likes ](https://x.com/VesselOfSpirit/status/558084551772471298) This is how I feel about psychology1, too, but with a touch more optimism. The good part of psychology is enormous, a hoard of endless treasures. You just have to look past the headlines! 1 To play devil’s advocate - should one always be so magnamious? Astrology? Phrenology? These seem different in that their entire orientation was flawed from the start; they didn’t simply fail to find the correct constellation-personality connections, the whole project of searching for connections between constellations and personality was doomed from the start. More difficult might be asking the same question about education research, which is notoriously bad. I don’t know enough about education research to know if there’s some settled science of correct and enlightening results lurking in the background beyond the day-to-day froth of poorly-conducted and politically-motivated studies. I think if it’s 90% bad, 10% good, it’s correct to call it bad as a compact way of communicating a useful truth; I think psychology is better than that, but admit it’s a tough judgment call.
Perry Johnson touts business experience, efficiency in bid for Michigan governor
The businessman is making his second bid for the Republican nomination.
Microsoft Promises Better Windows 11 Memory Efficiency
Following large-scale dissatisfaction with the overall Windows experience, Microsoft in March 2026 issued a statement explaining that it would be working to deliver "smoother navigation and more reliable performance for everyday tasks." Now, over four months later, Pavan Davaluri, President of...
New Fallout Game in Early Development at "RPG Specialist" inXile Entertainment
It was recently revealed that Xbox would be leaning into inter-studio collaborations to increase output and efficiency at its in-house game studios, and this seems to be the case now. In a recent podcast, Windows Central journalist and notable industry insider, Jez Corden, commented that he had...
New AMD Linux patch boosts low-end gaming performance on Steam Deck
Improved efficiency in EPP mode leads to ~32% jump in "1% low" frame rates.
Beyond Content Creation: How Wizstar Helps Enterprises Scale AI Across Business
As AI adoption continues to expand across enterprises, businesses are seeking more efficient, intelligent, and scalable ways to create content and streamline operations. Addressing these evolving needs, Wizstar provides a comprehensive AI digital human solution covering AIGC video generation, real-time interactive avatars, and AI-powered live streaming. Designed for marketing, customer service, training, and live commerce, the platform helps organizations improve content production efficiency, e
ServiceNow cuts jobs amid global restructuring and AI focus
Amid industry pressure, ServiceNow, overseen by CEO Bill McDermott, reduces workforce while focusing on AI investment and operational efficiency.
Investment in energy efficiency can strengthen your business
Discover how DTE Energy rebates support modernization, operational performance and long-term business value.
How AI Economics Is Changing For Startups And Small Businesses
AI’s efficiency fuels demand, not cuts it; Jevons Paradox drives rapid growth, reshaping pricing, access, and sustainability in the AI economy.
Cheaper, open and intelligent: Chinese AI models gain ground, as they make inroads in the US
Chinese AI models are gaining popularity in the U.S. for their affordability and efficiency.
Cheaper, open and intelligent: Chinese AI models gain ground, as they make inroads in the US
Chinese AI models are gaining popularity in the U.S. for their affordability and efficiency.
Fast-tracked, but falling short? Mamdani’s efficiency measures head to NYC voters
Mayor Zohran Mamdani’s government-efficiency panel unanimously approved five proposed City Charter changes for the November ballot Thursday evening, setting
Patriots training camp preview: Running backs searching for efficiency
Taking a closer look at New England’s backfield entering training camp.
Zohran Mamdani puts his democratic-socialist version of DOGE to the test
The New York mayor’s government efficiency effort is a potential path forward for Democrats around the country. But some are concerned he’s moving too fast.
AMD Ryzen 7 7700X3D Review
The AMD Ryzen 7 7700X3D delivers fantastic gaming performance thanks to 3D V-Cache. Priced at $330, it offers more FPS than the Intel Core Ultra 7 270K Plus, at a similar price point. Energy efficiency is impressive with low temperatures, making it an strong choice for gamers wanting high-tier CPU performance without breaking the bank.
Matthew Stafford's 2025 pocket efficiency put him in rare company
Matthew Stafford was one of three quarterbacks in 2025 who rated efficiently inside and outside the pocket.
Amazon's Next Business Is Hiding Inside Its Delivery Network
Amazon launches Supply Chain Services to offer cheaper parcel delivery and boost logistics efficiency. Click here to read my most recent analysis of AMZN.
I Bought the $3,000 Fitness Suit That Electrocutes You. I’m Sending It Back
Celebrities like George Clooney have praised the expensive Katalyst suit. For me, it derailed my other exercises and made me reassess my obsession with fitness and efficiency.
Energy efficiency that delivers measurable business results
Lower costs, improve reliability and boost productivity with DTE Energy rebates, financing and customized energy efficiency solutions.
5 4-Cylinder Engines That Deliver V6 Power
Powerful vehicles used to require powerful engines, but thanks to newer technology and improved efficiency, a 4-cylinder can perform just as well as a v6.
New Energy Efficiency Program Helps Small Businesses Save Energy!
FOR IMMEDIATE RELEASEJuly 8, 2026New Energy Efficiency Program Helps Small Businesses Save Energy!CHARLOTTESVILLE, VA – The City of Charlottesville and Community Climate Collaborative (C3)
Dedicated ‘coffee crew’ credits camaraderie, teamwork for success of Aspinwall business
A java dream team brings fun and efficiency to work at Aspinwall Beans ‘N’ Cream. The crew of eight full-timers and one part-timer at Aspinwall Beans ‘N’ Cream — dubbed ABC by locals — shares more than 100 years of combined food and beverage experience while serving up hometown hospitality
Explosive Growth Anticipated: Generative AI in Media and Entertainment Market Set to Surpass $8 Billion by 2030
Key market opportunities in generative AI for media and entertainment include integration with VR/AR, cloud-based AI services, real-time personalization, and growth in interactive gaming. Trends involve AI-powered content creation, personalization, and storytelling. The market seeks innovation to enhance user experiences and content efficiency. Generative AI in Media and Entertainment Market Generative AI in Media and Entertainment Market Dublin, July 07, 2026 (GLOBE NEWSWIRE) -- The "Generative
Sony leadership says AI tools are "an important foundational technology supporting our strategy"
"This is less about cost efficiency and more about improving quality and development speed"
AI Is Changing How Customers Choose Your Business
As AI increasingly mediates how customers research, evaluate, and choose suppliers, competitive advantage is shifting from direct customer understanding to managing AI-shaped interactions. Drawing on the experiences of three small-to-medium sized businesses they worked with, the authors show how firms can adapt. A manufacturer improved sales efficiency by screening AI-generated inquiries before investing engineering time in quotations. A boutique hotel learned to monitor how AI tools described its business and revised public content to improve accuracy and differentiation. A B2B software company replaced periodic customer reviews with continuous monitoring of customer feedback and AI-generated market perceptions. Across all three cases, the lesson is that firms must treat AI as a new intermediary in the customer relationship. Winning companies will not necessarily spend the most on technology; they will build systems for continuously listening, interpreting signals, and adapting strategy in markets where both customers and the information they rely on are increasingly AI-mediated.
Jaguars’ QB Lawrence Outperformed His Salary Last Season
An MVP finalist campaign and elite efficiency metrics prove Jacksonville’s $275 million investment is paying off as the star signal-caller climbs into the league’s upper echelon of quarterbacks.
Businesses Are Stuck in an Efficiency Illusion — Here's Why More Decks Don't Mean Better Decisions
In an AI-accelerated workplace where output is increasingly easy to generate, real professional value comes from judgment, restraint and clarity. Here's why professionals must move beyond volume-based execution and learn to deliver the strategic conviction leaders actually trust.
How cognitive automation can transform your business
Zapier reports that cognitive automation enhances business efficiency by enabling machines to interpret information and make decisions, unlike traditional automation.
Unisun Sports Commences, Kicking Off 2026-27 Season
JACKSONVILLE, Fla. - Unisun Sports, the groundbreaking strategic alliance between the Atlantic Sun Conference (ASUN) and the United Athletic Conference (UAC), has officially commenced as of July 1, 2026. Unisun Sports will serve both conferences, designed to significantly enhance operational efficiency, foster deeper collaboration, and drive innovation across both NCAA Division I organizations.
Unisun Sports Commences, Kicking Off 2026-27 Season
Unisun Sports, the groundbreaking strategic alliance between the Atlantic Sun Conference (ASUN) and the United Athletic Conference (UAC), has officially commenced as of July 1, 2026. Unisun Sports will serve both conferences, designed to significantly enhance operational efficiency, foster deeper collaboration, and drive innovation across both NCAA Division I organizations.
Healthy but Sedentary Individuals Show Early Decline in Cellular Energy Production
Healthy but Sedentary Individuals Show Early Decline in Cellular Energy Production
The role customer relationship management plays in small business growth and efficiency
Nutshell reports that small businesses benefit from CRM systems, improving customer retention and sales, while starkly contrasting with larger firms' efficiency.
Samsung Unveils Industry’s Fastest UFS 5.0 Solution for Next-Gen On-Device AI Applications
Samsung’s UFS 5.0 solution achieves the industry's highest data transfer speed of 10.8GB/s, enabling faster storage and processing in mobile memory Enhanced power efficiency and smaller package to provide optimal mobile AI experiences
‘Unbelievable’ waste and inefficiency at MoD, says ex-defence minister Al Carns
Exclusive: Carns, who quit last week, says he was angered by unwillingness to confront sunk costs of legacy programmes
College football's most experienced offenses: Ranking all 138 FBS units ahead of the 2026 season
A full breakdown of rushing, passing and receiving efficiency for every FBS roster
The Apple Watch Ultra 4 Finally Addresses Its Only Major Flaw
Apple addresses size complaints with the Ultra 4, offering a thinner profile while adding advanced hypertension detection and improved battery efficiency.
Smarter workflows give physicians time back for patient care
Northwell Health is reworking the EHR, inbox and team workflows to cut physician busywork and give doctors more time with their patients.
Energy shocks push Italian businesses to decarbonise
Companies are pressing ahead with emissions cuts to boost efficiency and competitiveness
Is SMIC N+3’s Metal Pitch Smaller than Intel 18A’s?
Almost four years ago, we published that SMIC had started shipping 7 nm (N+1) chips. Now, SMIC is shipping its third-generation 7 nm (N+3) process in Huawei’s Kirin 9030, with a minimum metal pitch of 32.5 nm, about 10% tighter than the 36 nm minimum metal pitch shipping in Intel’s latest Panther Lake CPUs on 18A. The headline is true, but incomplete cherry picked metric. N+3 reaches the density of TSMC N6 through aggressive DUV multi-patterning and design-technology co-optimization (DTCO), but it pays for that in complexity, efficiency and process control. We found this and more in our reverse engineering and teardown where we cover SMIC’s N3 process technology, Huawei’s packaging, memory, architecture, and more. SemiAnalysis has been building a state-of-the-art teardown lab in Oregon capable of analyzing the world’s most advanced and important chips over the last year and half. We have already generated revenue on advanced datacenter chip teardowns including our recent reverse engineering of a major TSMC customer’s COUPE CPO optical engine + EIC 3D stack. This is the first public report from the SemiAnalysis Teardown Engineering & Evaluation Lab, or STEEL for short. The lab is aggressively scaling up and out and we’re excited to announce it publicly. This is a bit of inconvenient timing for TechInsights as they are private equity owned and currently being sold while having enjoyed virtually no credible competition for decades. This has led to TechInsights underinvesting in CAPEX. SemiAnalysis exceeds TechInsights in revenue despite no venture or private equity ownership and being founded only 6 years ago. Because we have no external investors and are founder led, we move faster, build faster, and we can release client chip teardowns for free regularly, while focusing on datacenter for our major clients. Here’s the first public image from our lab, the HiSilicon Kirin 9030 Pro SoC: This report will detail our teardown of the Kirin 9030 and our findings on SMIC’s N+3 process, the most advanced in China. For comparison, we’ll show our teardown of the MediaTek Helio G99, made on TSMC N6. Through this comparison, we can look at the effect of export controls – SMIC N+3 and TSMC N6 are comparable nodes, but one is heavily export-controlled, the other free to use the West’s most advanced equipment. Here we see both China’s progress and constraints. SMIC N+3 reaches TSMC N6-class logic density, but it requires far more aggressive DUV multi-patterning, so it does not match N6 on process maturity or cost. The Kirin 9030 Pro performs similarly to three-year-old Android flagships, and trails far behind the current flagship SoCs from Apple, Qualcomm, MediaTek, and Samsung. The efficiency gap is even wider. Export controls have not stopped Huawei and SMIC from shipping advanced silicon, but they have forced a different path. Without EUV, SMIC is leaning harder on DUV multi-patterning, DTCO, and increasingly complex integration. The roadmap continues forward through tighter design rules and backside power, but each step adds cost and process risk. Huawei’s τ scaling and LogicFolding show another path: stacking active logic and recovering density through advanced packaging and system-technology co-optimization (STCO). To understand the Kirin 9030, we must first understand Huawei’s SoC history. HiSilicon is Huawei’s chip design arm, responsible for the Kirin smartphone SoCs, Kunpeng server CPUs, Ascend AI accelerators, and switch/router networking silicon. Before export controls, Huawei was TSMC’s largest customer – the only customer on TSMC’s first EUV node, N7+, and among the first on N5, alongside Apple. That ended in late 2020. Huawei switched to Qualcomm SoCs in its flagship smartphones, though export controls limited them to 4G-only variants. In late 2023, Huawei returned to in-house silicon with the Kirin 9000s, a successor to the Kirin 9000, fabricated on SMIC N+2 instead of TSMC N5. In the following years, they released the Kirin 9010 and 9020 on the same N+2 process. These chips used Huawei’s in-house TaiShan CPU cores and Maleoon GPU. We have not torn down a Kirin 9020 ourselves, so the predecessor die shot is from Kurnal. The die shots show how Huawei spent its silicon budget: which functional blocks are where, and how their areas compare to the predecessor. First, a quick guide to the major blocks on the die. The total die area is nearly identical, but the 9030 uses that area more aggressively. A denser process lets Huawei fit an extra middle CPU core, more GPU and NPU cores, and larger caches into the same footprint. In contrast, the Helio G99 is a much smaller, low-cost SoC, built for budget smartphones rather than a flagship device. While the Kirin 9030 is ~140 mm², the G99 is only ~29 mm², roughly one-fifth the area. The underlying TSMC process technology, however, is directly comparable as a baseline for analyzing SMIC’s. The Kirin 9030 is an evolutionary refresh, not a clean-sheet design. Its CPU, GPU and NPU cores carry over the 9020’s families, and the gains come from three levers: the SMIC N+2-to-N+3 process step, DTCO and floorplan work, and incremental microarchitecture. Area is where the first two show up, and the 9030 scales well here. Performance and efficiency are the harder test. Huawei’s design holds up better than its node would suggest, but the chip still trails, both because N+3 sits behind the leading-edge nodes and because its cores, while competent, remain a few generations behind the newest designs. The new prime core is an incremental update. The main changes are a 10% frequency increase from 2.5 GHz to 2.75 GHz and a doubling in the L2 cache from 1 MiB to 2 MiB. Despite the increased cache, the core size decreased by 7.6%. Excluding the private L2 cache, the core size decreased by 21%. This is a large reduction for an incremental node. Compared with the TaiShan New V120 core in the Kirin 9020, the Kirin 9030’s middle core is almost unchanged architecturally, yet each core shrinks by ~22%. Most of that comes from the move from N+2 to N+3, with layout likely accounting for the rest. Visually, the most noticeable change is the increase from 3 middle cores to 4. There is also a 20% increase in the shared L3 cache of the big cluster. This helps to improve multi-core performance without sacrificing much in terms of area. Even with each core shrinking, the big CPU cluster’s total area is essentially unchanged. The per-core savings went back into an additional middle core and larger caches. The tiny cores shrank less than the prime core (excluding its L2 cache) and less than the middle cores. This is likely because fixed overhead is a larger share on a small core. We cannot resolve any architectural changes from the die shot alone, but the per-clock and efficiency gains shown below point to more than pure process and layout scaling. The area reduction was offset by a doubling of the shared L2 cache from 2 MiB to 4 MiB, leaving the total tiny CPU cluster area slightly larger. Area is the easiest improvement to see from a die shot, but it is only one part of PPA (power, performance, area). For modern logic, power and performance matter just as much, and often more. Since Dennard scaling broke down in the mid-2000s, voltage and frequency have not scaled in step with transistor dimensions, so each node has had to fight harder for gains in performance and efficiency. The starkest comparison is not Kirin 9020 versus Kirin 9030 Pro. Apple’s efficiency cores run circles around Huawei’s prime core. Apple’s low-power core delivers 20% higher integer performance while drawing only 1 W, compared with 4.5 W for Huawei’s prime core. N+3 matches TSMC N6, but N6 is several generations old. Apple and Qualcomm build on N4 and N3P, which are denser and sit on a better voltage-frequency curve, giving them a larger transistor budget and more performance per watt. The 9030’s own cores did improve. The middle and tiny cores gained 17% and 14% in per-clock integer performance over the 9020, with floating-point flat on the middle core and up 11% on the tiny. The tiny core improves cleanly, with performance rising while power falls and efficiency increases by 45% in integer and 24% in floating point. The middle core is mixed: integer performance rises but power rises faster, cutting integer efficiency by 7%, while lower power lifts floating-point efficiency 16%. Per-clock gains at the same or lower frequency are microarchitectural, so the cores are tuned, not just shrunk. Both also failed to hold their rated maximum frequencies, pointing to thermal, power, or stability limits. Per clock, the middle core sits around Arm Cortex-A720 and the tiny core near the Cortex-A520; absolute performance trails because Huawei clocks them much lower. The prime core is roughly Cortex-X2 class per clock, a 2021 design. Apple’s 2020 M1 Firestorm core is still 35% higher per clock and 57% faster in absolute integer performance at a similar 4.5 W. The current leading edge is further ahead again: the Apple M5 P-core is 60% higher per clock and 2.7× faster, the Arm C1 Ultra 45% higher and 2× faster. Matching older high-end cores per clock is a genuine design achievement. What Huawei cannot match is the voltage-frequency curve and transistor budget of leading-edge nodes, which let Apple, Qualcomm and others spend more transistors in the same area on wider cores, larger caches and deeper buffers while running at lower voltage. Huawei’s LogicFolding roadmap is one answer, stacking active logic to recover density and shorten signal paths. We return to it later. The GPU compute units (CUs) changed more visibly than the CPU cores, moving to a more rectangular layout for both the arithmetic logic unit (ALU) clusters and the CU overall. Even with ray-tracing support added, a CU shrank ~28%. However, that shrink is offset by the increase from 4 to 6 CUs and the area outside the CUs grew 33%. Overall, the GPU cluster is larger by ~10%. The GPU is where Huawei makes its biggest gains. The Maleoon 935 is not competitive with current flagships, but it is a large step up from the 920 and reaches older-flagship territory. In 3DMark it is 70% faster in Wild Life Extreme (WLE) and 79% faster in Steel Nomad Light (SNL) than the 920; with 11% higher clocks and 50% more CUs, the ~67% theoretical uplift roughly matches WLE and is beaten by SNL. It edges ahead of the Snapdragon 8+ Gen 1 in WLE and SNL, and the Dimensity 9200 and Apple A16 in WLE, but stays far behind newer parts: the Snapdragon 8 Elite Gen 5 and Dimensity 9500 are ~2.4–2.6× faster in WLE and ~3.2× faster in SNL. The Maleoon 935 is Huawei’s first GPU with hardware-accelerated ray tracing; there it lands slightly ahead of the Exynos 2200, and on par with the Apple A16, with current flagships up to 3.7× faster. The Neural Processing Unit (NPU) saw the largest structural changes of any block, moving from a Lite and a Tiny core in the Kirin 9020 to a Lite and two Tiny cores in the Kirin 9030. Both core types also show significant layout changes. This is a reversal in Huawei’s NPU design. The Kirin 9000 5G, its last flagship chip on TSMC N5, used two Lite and one Tiny core. The series of SoCs on SMIC N+2 moved to one Lite and one Tiny core, likely for area savings. With the Kirin 9030, Huawei has shifted back toward a larger multi-core NPU cluster, but with the additional area going to a Tiny core rather than a Lite core. We’re diving deep into the most advanced datacenter and AI hardware hitting the market. To learn more about what’s in the pipeline or to commission a custom teardown, contact sales@semianalysis.com. Interested in joining us on this ride and think you can be a difference maker? Check out our Careers page. Before diving into the process stack, the package and memory are worth separating from the SoC itself. The Pro variant of the Kirin 9030 carries 12 GB of Samsung DRAM, with two stacks of four dies each. The dies were identified as the K4L2E165YD, a 12 Gb LPDDR5X-9600 device fabricated on Samsung’s 1a node, the fourth generation of its 10 nm-class DRAM after 1x, 1y and 1z. 1a has shipped in volume since 2022, so this is current memory rather than older-node inventory. The 16 GB Pro Max variants we obtained were found with both CXMT and Samsung packages. The CXMT package is marked CXDD7JEDM, with two stacks of four dies, packaged in week 45 of 2025. The inferred die dimensions from X-ray computed tomography (CT) are consistent with a known density of ~0.3 Gib/mm² for the CXMT G4 process, roughly equivalent to other manufacturers’ 1z processes. The Kirin 9030 uses a typical integrated package-on-package (iPoP) stack: multiple DRAM dies in a memory package sit above an organic redistribution layer (RDL) interposer, which sits above the SoC and package substrate. The full package is then mounted to the printed circuit board (PCB) through ball-grid array (BGA) solder bumps. The memory package substrate is a thin bismaleimide-triazine (BT) laminate carrying the LPDDR5X stack. The organic RDL interposer over the SoC routes the PoP signals around the die and carries possible dummy thermal copper pillars. The package substrate, a thicker Ajinomoto Build-up Film (ABF) build-up over a BT core, fans the flip-chip bumps out to BGA pitch and embeds the power planes. The whole stack is organic. The only silicon is the SoC and the LPDDR5X dies; there is no silicon interposer. Keeping it all-organic brings the package’s coefficient of thermal expansion (CTE) close to the PCB’s, reducing board-level warpage, and avoids the cost of a silicon interposer the SoC’s bandwidth does not need. In an iPoP stack, the memory package connects to the organic RDL interposer through an array of solder bumps. Underfill fills the gap around those bumps, adding stiffness and protecting the joints from mechanical stress. The Pro and Pro Max variants differ here, which we cover behind the paywall. The die shot and architecture tell us how Huawei allocated its silicon budget. The process tells us what SMIC can manufacture. We use the Helio G99 as the process reference for TSMC N6. Both SMIC N+3 and TSMC N6 are evolutions of previous 7 nm-class nodes. We used targeted TEM cross-sections through logic and memory regions, imaged in both fin-cut and gate-cut directions. Each cross-section caption gives its horizontal field width (HFW), the real width of the imaged area. We start at the transistor fins, then move up through standard cells, local interconnect, and SRAM. SMIC has not overtaken Intel or TSMC. It uses aggressive DUV scaling and DTCO to reach N6-class density, but that density doesn’t translate into comparable performance and efficiency, for two reasons: the node gap to leading-edge nodes, and Huawei’s core designs. Fin Profile One of the most important knobs in a FinFET process is the fin profile: the shape of an individual fin and the channel where current passes from source to drain. The ideal fin is tall, narrow, and nearly vertical. A taller fin increases effective channel width, while a narrower fin improves electrostatic control by thinning the body the gate must control. Push either too far, and the process pays for it: weaker drive current, fragile fins, taper, footing and line-edge variation that hit yield and device variability. The Intel 22 nm, 14 nm, and 10 nm fin cross-sections show how FinFET nodes have improved over time. 22 nm fins were a first-generation structure, relatively short, wide and strongly tapered. The shape limits current density and reduces gate control uniformity across the height of the fin. At 14 nm and 10 nm, Intel pushed the fins taller and narrower while also making the sidewalls more vertical. Rather than shrinking the device, these changes increase the effective channel width per fin and improve electrostatic control. The trade-off is that taller fins at tighter pitches are much more difficult to manufacture. Now, let’s compare the Helio G99 on TSMC N6 with the Kirin 9030 on SMIC N+3. Both processes are in the same class, with fin pitch of 30-32 nm on N+3 and 34 nm in our N6 cross-section. The pitch for N6 is especially interesting as N7’s HD library is generally listed with a 33 nm fin pitch, and N6 did not shrink pitches directly. Its density gains came from DTCO instead of tighter pitches. The 34 nm pitch was stable across our sampled region and serves more as a comparison against the SMIC N+3 we have not investigated further. Pinning down N+3’s fin patterning scheme takes more than one core unit. The CPU cores show a dense ~32 nm pitch, with the pitch between N-P fin pairs alternating between 78 and 88 nm. Logic alone may be consistent with dual-pitch mandrels of 120 and 110 nm, but this is a complex and unusual approach. Combining the pitch from the the 8T SRAM, which has more complex repeat unit, with the CPU core sequence allows us to reverse engineer the patterning steps with more confidence. As both the logic and SRAM should share the same base grid, a single CD mandrel lithography pattern with 128 nm pitch undergoing SAQP produces a die-wide ~32 nm grid (128 nm/4), which supports the pitch sequencing seen in both logic and SRAM cells. In the sampled cross-sections, N+3 shows a taller, narrower, higher-aspect-ratio fin than N6. The measured fin aspect ratio is ~9.5:1 on N+3 versus 7.8:1 on N6. N+3 also shows less top rounding, with an estimated radius of ~2 nm, compared with 2.8 nm on N6. Even though the fin widths differ, the ratio of top rounding to fin width tells the same story, with N+3 at 0.37 and N6 at 0.44. In a geometric sense, lower is better; a perfectly rectangular fin would have no top-rounding penalty. These are single-digit-nanometer features measured from a handful of cuts, so treat the absolute numbers as approximate. The important result is the relative gap: N+3’s fins are consistently taller, narrower and less rounded than N6’s. We’re diving deep into the most advanced datacenter and AI hardware hitting the market. To learn more about what’s in the pipeline or to commission a custom teardown, contact sales@semianalysis.com. Interested in joining us on this ride and think you can be a difference maker? Check out our Careers page. Standard Cell A standard cell is the basic building block of chip layout: a fixed-height row pairing one NMOS and one PMOS transistor that share a gate, tiled in a grid to build logic blocks. The key dimensions are contacted gate pitch (CGP), cell height (CH), fin count, and the lower-metal routing grid. To measure density, we use the Bohr metric: a weighted average of NAND2 gate area (60%) and scan flip-flop area (40%). This represents a realistic mix of combinational and sequential logic. This metric has its limitations, especially for complex cell layouts like TSMC’s FinFLEX, which alternates cells with different fin counts. Even so, it is the best metric for a pure process-level comparison. Another important measurement is the fin pitch; it refers to the distance between two fins of the same transistor. In a FinFET process, multiple fins are used in each transistor to increase the drive current and thus performance. TSMC N6 ships both a high-density (HD) library with 2 PMOS and 2 NMOS fins per cell, and a high-performance (HP) library with 3 of each. More fins under the shared gate mean more effective channel width. HP cells switch harder at the cost of area. Designers mix the two on a die, primarily spending HP cells on timing-critical paths, and matching their PPA targets. In the Cortex-A55 core of the Helio G99, we found a cell height of 240 nm for the HD cell. MediaTek has used HD cells in the G99 to minimize die size and thus cost. As an SoC for budget smartphones at ~$100, this is essential. By contrast, we found only one library in the Kirin 9030, with 2 NMOS and 2 PMOS fins. This suggests a narrower library strategy than TSMC N6, where both HD and HP libraries are widely used. This likely reflects the smaller customer base and the more constrained domestic design and electronic design automation (EDA) ecosystem. In all three CPU cores of the Kirin 9030, we found cell heights of 228 nm, 5% smaller than on N6. This is also a reduction of 9.5% over SMIC N+2’s cell height of 252 nm. SMIC N+3 and TSMC N6’s HD library both feature a CGP of 57 nm. For SMIC, this is a 9.5% shrink over N+2. In the past, CGP and cell height alone may have been enough to compare transistor density. Now, however, we must consider scaling boosters and DTCO as well. SMIC’s density gain does not come from EUV. It comes from using every available DTCO booster aggressively. First is fin depopulation: reducing the number of NMOS and PMOS fins in each cell. The first FinFET nodes started with 3 or 4 fins for each transistor. SMIC N+3 and TSMC N6 HD both use only 2 fins per transistor, trading drive strength for density. Next is contact over active gate (COAG). By landing the gate contact directly over the active gate, instead of out over the isolation region, the cell height drops. N+3 integrates COAG while N6 does not. Our N+3 gate-cut cross-sections indicate COAG, with the gate contact sitting over the active region, while N6 shows an off-gate contact. Last is single diffusion break (SDB). Diffusion breaks are inserted between cells in the same row to provide electrical isolation, but they also introduce local layout effects (LLE), layout-dependent shifts in electrical characteristics. In the past, a double diffusion break was used, consuming the space of two CGPs. SMIC N+3 and TSMC N6 instead use SDB, saving area but increasing LLE sensitivity. This must be controlled at the process level and accurately modeled in the process design kit (PDK) so that EDA tools can account for it. Overall, SMIC N+3 has a transistor density of 113.4 MTr/mm², slightly above TSMC N6 at 107.7 MTr/mm². Even without EUV, SMIC has achieved density beyond TSMC’s mature N6 node which utilizes EUV. Metal Stack The smallest critical dimension in the teardown is M0; SMIC N+3 uses a 32.5 nm local metal pitch. That is smaller than the 36 nm M0 pitch on Intel 18A in Panther Lake. However, this does not mean that SMIC has a better process than Intel 18A or TSMC N3P. M0 is a local intra-cell routing layer. Its usefulness depends on the full interconnect stack: M1 and M2 pitch, track count, via and line resistance, design rules, mask count, overlay control, and routing flexibility. The 32.5 nm M0 is consistent with self-aligned quadruple patterning (SAQP), whose four-population line-width loading we read coarsely as alternating widths of 21.5 to 24 nm; M1 and M2, at 38 and 40 nm, are consistent with self-aligned double patterning (SADP), a single A/B split. On TSMC N6, M0, M2, and M3 sit at a relaxed ~40 nm and are consistent with SADP-class double patterning, with no need for quadruple patterning. That said, we measure M2 for example at ~43 nm, likely inflated by sparse routing. We do not assign any specific layer to EUV from our cross-sections; the distinction we can draw is double versus quadruple patterning, not lithography wavelength. Transistor-level density in the front-end-of-line (FEOL) sets an upper bound, but the design is ultimately limited by what the interconnect stack can route. The lowest metals are the most important for standard-cell density, but the semi-global and global layers determine how usable that density is at the block and chip level. Two axes are commonly used for chip cross-sections: the fin-cut and the gate-cut. The micrograph above is a fin-cut and shows metals 0 through 3. This axis lets us see the even-numbered metals, with M0 right above the fins. There are two kinds of M0 lines. The first are the power rails; these are wide wires for the VDD and VSS running horizontally at the top and bottom edges of each standard cell. The wide wires measure 55 nm across, more than double the other M0 lines. Their width minimizes resistance and reduces IR drop. The second kind are intra-cell wires, short segments within the cell that connect terminals to M1. These have alternating widths between 21.5 and 24 nm. The M0 pitch is 32.5 nm, a 19% reduction versus N+2 and N6. At this pitch, DUV patterning requires more aggressive multi-patterning, increasing mask count, overlay sensitivity, process complexity and cost. M0 is below what a single DUV-defined spacer (SADP) can resolve, so SMIC cascades a second spacer step (SAQP). The cross-section reflects the cost: the M0 trenches are visibly more re-entrant (narrower at the bottom than the top) than M1 or M2 on the same chip and carry a bright barrier-rich foot where the trench meets the etch-stop layer. That shape is partly the intended damascene profile, as a slightly narrow bottom helps void-free copper fill, but its magnitude at M0 is driven by the tight pitch and the higher trench aspect ratio. Intel 18A supports an M0 pitch of 32 nm, although Panther Lake has only shipped with a looser 36 nm pitch. This is due to Intel’s heavy usage of HP libraries. Among leading-edge nodes, 18A has the loosest M0 pitches due to PowerVia. With power routing moving to the backside, congestion is reduced, and the entire front-side metal stack can be used for signal routing. M2 is the first true inter-cell routing layer. It runs horizontally like M0 but spans across multiple cells to carry block-level signals. The M2 pitch sets the cell’s track height – the number of M2 tracks that fit between the VDD and VSS rails, defining what the library calls a 6-track or 7.5-track cell. This layer is the most important, limiting the routing of entire blocks. SMIC N+3 features a 5.7-track cell. The M2 pitch is 40 nm, a 5% decrease over N+2 and the same as N6. This shrink keeps the pitch at the edge of what is possible with double patterning. Future nodes will need to increase the number of masks for M2 as reducing the number of tracks is much harder due to the limitations in routing. The micrograph above is in the perpendicular direction, the gate-cut, and shows metals 0 through 4. This allows us to see and measure the odd-numbered vertical metal layers. The M1 pitch is 38 nm, 9.5% less than N+2 and 33% less than N6. The M1-to-gate ratio matters because it sets local routing flexibility. N+2 and N+3 use a 3:2 ratio, while N6 uses a 1:1 ratio, explaining the huge differences in M1 pitch. The more M1 lines there are compared with the gates, the more flexibility there is for power and signal crossing within the cell. Routing flexibility enables more complex and better cells. Clean fractional ratios are also preferred as a grid is periodic and improves layouts. The 3:2 ratio gives SMIC more local routing flexibility than a strict 1:1 grid, but it also complicates layout and patterning. This is a DTCO choice, with SMIC increasing process complexity to recover density and routability without EUV. This 3:2 ratio is not very popular in the leading-edge nodes. TSMC has only used it on N7+, the N5 family, and the short-lived N3(B). They have switched back to a 1:1 ratio for N3E. Intel has only used it on the 10 nm/Intel 7 family, with Intel 4, 3 and 18A all using a 1:1 ratio. Samsung is the only one still using a 3:2 ratio at the leading edge, using it in the SF4 and SF3 families. It remains to be seen if SMIC will remain at a 3:2 ratio or move to a 1:1 ratio with its future nodes. The industry is still actively exploring these local-routing ratios. At VLSI 2026, imec will be presenting work on even higher ratios, including a 2:1 scheme that can reduce area by up to 14%. We will be covering the conference in a future newsletter article. Subscribe We’re diving deep into the most advanced datacenter and AI hardware hitting the market. To learn more about what’s in the pipeline or to commission a custom teardown, contact sales@semianalysis.com. Interested in joining us on this ride and think you can be a difference maker? Check out our Careers page. The final local interconnect layer for N+3 is M3, with a pitch of 44 nm. The M3 pitch is the same as on N+2 and 10% larger than on N6. The semi-global layers carry the majority of block-level signal routing. They have a coarser pitch than the lower local layers. On leading-edge nodes, they are designed to sit at the limit of DUV single patterning. M4 through M11 pitches were found divided between 80–82 nm (M4–M6), 128 nm (M7–M10), and 148 nm (M11). Given limited sampling, it is possible these are divided further in dense routing areas. At the top are two giant metal layers, M12 and M13. These have kept the same pitches as N+2 at 1920 nm and 4600 nm respectively. While the lower layers’ pitches are generally fixed by the process and library, the upper layers vary much more in pitch and count, depending on the design. Even two smartphone SoCs on the same process can have wildly different metal stacks. The Helio G99 carries fewer routing layers, reaching coarse metal pitches of 850 nm by M9, while the larger and higher-performance Kirin 9030 keeps fine pitches until M11. SRAM At the leading edge, SRAM is much more difficult to scale than logic. TSMC’s latest nodes have seen little to no bitcell scaling, while logic still has more DTCO levers to pull. While looking for other logic libraries in the GPU compute units, we stumbled upon the SRAM. The most common type of SRAM has 6 transistors (6T), but this cell had 8 transistors (8T) instead. 8T SRAM adds two transistors to form a dedicated read port. Unlike a 6T cell, where reading disturbs the storage, the decoupled read port removes read-disturb, improving read stability and letting the cell be pushed harder for performance. At first glance, the cut looked like an unusual logic library, with each cell row having 3 fins of one polarity and 5 fins of another. The rows also alternated in orientation. Energy-dispersive X-ray spectroscopy (EDS) resolved our confusion. The cut had not landed on the GPU logic, but on the SRAM macro beside it. The unusual fin pattern was due to the SRAM library. We return to EDS in the process flow analysis behind the paywall. SRAM libraries are not like traditional logic libraries. Due to the unequal number of PMOS and NMOS transistors, they require specialized rules and layout libraries. They do not need the flexibility of logic libraries, so they are hyper-optimized for one purpose: dense, reliable memory. The SRAM cell we found is a 1:2:2-2:2 cell. This means there is 1 fin per pull-up (PU) PMOS transistor, and 2 fins per pull-down (PD) and pass-gate (PG) NMOS transistor. These 2 PU, 2 PD and 2 PG transistors would usually form a single 6T high-current cell (HCC). An 8T HCC adds a read-pull-down (RPD) and a read-pass-gate (RPG) NMOS transistor, each with two fins. We measured a cell height of 406 nm, which brings the bitcell size to 0.0463 µm². That is a theoretical peak density of 21.6 Mib/mm². We estimate that a 6T HCC would have a cell height of 292 nm and a size of 0.0337 µm². This is ~12% larger than a 6T HCC on Intel 3 and 4. We also estimate the 6T high-density cell (HDC) to have a cell height of 228 nm and a size of 0.0260 µm². This is coincidentally the same as the logic standard-cell height measured earlier. The estimate puts the cell near Samsung 7LPP/5LPP and slightly below TSMC N7/N6. That is a theoretical peak density of 38.5 Mib/mm². 6T HDC is arguably the most important cell as it is used for the largest caches in a chip, the L3 caches and system-level cache (SLC). Both the Kirin 9020 and 9030 have split the SLC into 4 banks to raise total SLC bandwidth. In the Kirin 9030, the SLC increased from 2 MiB to 3 MiB per bank. Correspondingly, the number of arrays within the bank also increased by 50%, from 16 to 24. Each array can store 128 KiB and forms an orderly pattern on the die shot. From the Kirin 9020 to the Kirin 9030, the area of a 128 KiB SLC array decreased from 0.0477 mm² to 0.0392 mm², an 18% shrink. The achieved density is 25.5 Mib/mm², 66% of the theoretical maximum. While the SLC was quite similar across both chips, the L3 has seen some major changes, particularly in terms of its layout. The total capacity also went up from 10 MiB to 12 MiB. Much like the SLC, the L3 is also split into 4 banks. In the Kirin 9020, an L3 bank consisted of 16× 128 KiB arrays and 16× 32 KiB arrays. However, an L3 bank in the Kirin 9030 instead consists of 48× 64 KiB arrays. In the Kirin 9020 L3, a 128 KiB array was 0.0513 mm² and a 32 KiB array was 0.0154 mm². The size of the 128 KiB array is different on the L3 and SLC as the assist circuitry for the two arrays differs depending on their purpose. In the Kirin 9030 L3, a 64 KiB array is 0.0210 mm². Although not a like-for-like comparison, normalized for capacity, it is 18% smaller than the 9020’s 128 KiB L3 array and 31% smaller than its 32 KiB L3 array. The achieved density is slightly lower than the SLC, at 23.8 Mib/mm², 62% of the theoretical maximum. Unlike the L3 and SLC, the prime cores’ private L2 cache uses a 2-bank design. As the prime cores’ L2 is latency-critical, it likely uses 6T HCC instead of 6T HDC. The 9020 has 16 arrays in each bank while the 9030 has 32. Each array has a capacity of 32 KiB. A 32 KiB array in the L2 shrank from 0.0171 mm² to 0.0142 mm², ~17% smaller. The density is 17.6 Mib/mm², ~59% of the theoretical maximum for 6T HCC. SRAM scaled well from N+2 to N+3, shrinking by ~19%, close to the theoretical logic shrink. The caveat is that N+2’s bitcells were unusually large, bigger than comparable 7 nm-class nodes, so part of the gain is catch-up rather than true scaling. With the insights from STEEL’s teardowns, we will be doing a deep dive into SRAM in a future newsletter article. Subscribe Everything above came out of a single STEEL teardown: die annotation, block-level area analysis and TEM cross-sections through logic and SRAM. We’re diving deep into the most advanced datacenter and AI hardware hitting the market. To learn more about what’s in the pipeline or to commission a custom teardown, contact sales@semianalysis.com. Future Roadmap The same cross-sections that pin down N+3 also show where SMIC can go next. Although N+3 is already close to the practical limits of DUV multi-patterning in several layers, SMIC still has a few scaling levers left. A theoretical N+4 would likely start with cell height. N+3 uses 5 M0 tracks between its power rails. Moving to 4 M0 tracks, as on SMIC N+2 and TSMC N6, could reduce cell height by roughly 15%. The routing grid is only one side of the shrink; the front end also must fit into the smaller cell. One possible FEOL lever is reducing the p-to-n isolation spacing from two diffusion grid units to one. Intel used this scaling booster on Intel 4, and TSMC did so on its N3 family. This path trades layout flexibility for density. Fewer M0 tracks reduce local routing resources, while tighter p-to-n spacing raises integration and design-rule difficulty. M2 is also constrained by the cell height shrink. For SMIC to maintain a ~5.7-track cell, M2 would need to move toward ~35 nm. That would move another layer into SAQP territory. SMIC could also reduce the CGP from 57 nm to 54 nm. Intel reached a similar CGP on Intel 10 nm/Intel 7 without EUV. The local interconnect is also tougher. If SMIC keeps the 3:2 M1-to-gate ratio, M1 would need to shrink to 36 nm and would likely require SAQP as well. If SMIC moves to a 1:1 ratio, M1 could relax to 54 nm, but it would give up routing flexibility. Under this theoretical path, we estimate that SMIC N+4 could reach a cell height of 198 nm and a CGP of 54 nm, implying a Bohr density of 137.8 MTr/mm², on par with TSMC N5 or Samsung SF4. However, the difficulty is cumulative. Each step is individually plausible, but together they make N+4 harder than the transition from N+2 to N+3. It will likely take longer, cost more, and carry less process margin. A theoretical N+5 would require a larger integration shift. One possible path is backside contacts (BSCon), moving power routing and source/drain contacts to the backside, which would reduce front-side routing pressure and enable another reduction in cell height. The front-side metal pitches could relax to reduce the process complexity. M0 would likely relax slightly to ~34 nm, and M2 and M4 pitches could relax further. CGP is unlikely to shrink much further. Even with EUV, 48 nm has been the practical limit for yield and process control. This approach would allow N+5’s cell height to fall to 170 nm and its CGP to 53 nm. This implies a Bohr density of 163.6 MTr/mm², on par with Intel 18A’s HP library. However, this would not make N+5 cost-competitive with the leading edge. It would reach a similar density through a much more expensive route. The integration difficulty rises sharply, with new process flows for backside alignment, wafer thinning, contact reveal, and backside metallization. Past this point, standard density and interconnect scaling become increasingly unattractive. That is where Huawei’s roadmap stops looking like a normal foundry roadmap and starts looking like a packaging roadmap. At ISCAS 2026, Huawei unveiled its tau (τ) scaling law, reframing process scaling in the time domain. τ is the time cost of data movement and processing: switching delays in transistors, RC signal propagation delays in circuits, compute, memory, and networking latency. Outside Huawei’s terminology, this is called system-technology co-optimization. This is Huawei’s answer to its lack of EUV lithography. Without EUV, planar density cannot keep pace with TSMC, Intel, or Samsung. If transistor density cannot shrink further, Huawei’s alternative is to shorten wires, reduce buffering, and stack logic vertically. “LogicFolding”, Huawei’s implementation of this new scaling idea, is, in practice, an aggressive 3D stacking approach. AMD V-Cache places SRAM above or below a CPU die. AMD’s MI350X places active interposer dies (AIDs) underneath accelerator and compute dies (XCDs), with the AIDs handling cache, IO interfaces, the network-on-chip (NoC) and embedded metal-insulator-metal (MIM) capacitors. With LogicFolding, parts of the same logic block are split across multiple active dies bonded face-to-face at ultra-fine pitch. This allows Huawei to shorten some critical paths and reduce buffer overhead, not merely add cache capacity or offload the IO and interconnect. Shortening wires is where the higher clocks come from. A large share of a modern core’s delay and energy budget goes into driving long interconnects and the repeater buffers along them. LogicFolding distributes a block’s critical-path gates across multiple stacked tiers bonded at a very fine pitch, so the bond interface behaves like an additional metal layer and the longest paths get shorter. That is how Huawei expects to recover frequency and efficiency it cannot get from the process alone. Huawei’s roadmap shows its intent. Prime core frequency is targeted to rise from 2.75 GHz in the Kirin 9030 to roughly 5 GHz by 2031, far beyond what planar scaling alone could deliver. Prime cores with 3.1 and 3.39 GHz clocks are being tested in its labs, although their power consumption is unknown. Beyond that, chips are in the design, simulation or pathfinding phase, meaning the frequencies are targets. However, the direction matters more: LogicFolding also helps with performance, not just density. The catch is that Huawei’s density claim is not directly comparable to foundry densities. A stacked design can report more transistors per package footprint by adding active layers, even if each patterned die remains well behind TSMC or Intel in front-end density. This is how Huawei can claim to reach foundry 14A-equivalent density by 2031. This is not a like-for-like foundry comparison, with Huawei using stacked logic and measuring density per package footprint. On a normalized Bohr-density basis, SMIC N+3 is ~114 MTr/mm², 38% less than Intel 18A’s HD library. Huawei’s 3D roadmap closes the gap by stacking active logic, reaching 215 MTr/mm² by 2030. In 2031, the roadmap density jumps to 295 MTr/mm², implying either a third active layer, partial EUV insertion or aggressive planar DUV scaling. Huawei’s methodology makes other foundries look much denser as well. Applying it to AMD’s MI450X with an N2 top die on an N3P base die yields a theoretical density of 460.2 MTr/mm² in 2026, compared with Huawei’s 295 MTr/mm² in 2031. This Kirin 9030 does not use LogicFolding, remaining in a conventional mobile SoC package. Instead, it forms the baseline for how far Huawei and SMIC can push planar scaling. Future teardowns of Kirin and Ascend chips will show both planar logic density and Huawei’s hybrid bonding solutions. Export controls changed China’s optimization problem rather than ending it. EUV restrictions raised the cost and complexity of leading-edge manufacturing without freezing it. SMIC reaches N6-class logic density through DUV immersion, SAQP and DTCO, while Huawei shifts more of the burden onto architecture, packaging and system-level integration. Future nodes will be tougher. N+3 still had room to tighten local metals and reduce cell height and CGP. Further scaling without EUV leaves fewer levers. More aggressive multi-patterning adds masks and overlay error. SMIC can keep pushing DUV, but each step will get more expensive and less forgiving. The design side is just as critical. Huawei had domestic EDA tools and flows before the Kirin 9030, with the Kirin 9000s, 9010 and 9020 making that clear. Huawei was able to ship multiple consumer SoCs on SMIC N+2 and N+3 while cut off from the Western EDA stack. US export controls restricted EDA tools for advanced chips in 2022 but did not target tools for more mature chips. In 2025, the US government briefly placed much broader restrictions on EDA software from Synopsys, Cadence, and others, before lifting them less than two months later as part of a trade deal tied to rare earths. Huawei has been unable to access those tools because it remains on a US trade blacklist. That forced Huawei, SMIC and Chinese academic institutions to build their own tools and flows. Researchers at Peking University recently announced a prototype EDA tool for Huawei’s LogicFolding architecture, which requires a new flow to handle the multilayer layout and floorplan. This is not the same as replacing the full Synopsys or Cadence stack, but it shows where domestic EDA is headed: toward tighter co-optimization between architecture, process and packaging. These advances are also diffusing into the Chinese ecosystem. SMIC is licensing its N+2 and N+3 processes to HLMC/Hua Hong at the government’s direction rather than by choice. If the same process learning feeds into Ascend accelerators for AI training and inference, the choke point shifts from one named fab to an ecosystem. Alibaba’s T-Head silicon arm and Cambricon, a Chinese AI chip designer that is expected to supply ByteDance, could also be major beneficiaries. Sanctions aimed at SMIC alone become less effective once the manufacturing knowledge has spread to other fabs and design houses. China is not closing the gap with Intel, Samsung and TSMC. The teardown shows the opposite in several places: no EUV, no backside power, higher process complexity, and visible trade-offs. But China is still advancing. If domestic chips become good enough for phones, inference, networking and security-sensitive workloads, they can matter strategically without matching TSMC at the leading edge. Behind the paywall, we show what else STEEL can do, with material and process flow analysis of SMIC N+3, and analysis of the Kirin 9030 package. We’re diving deep into the most advanced datacenter and AI hardware hitting the market. To learn more about what’s in the pipeline, access the full Kirin 9030 and SMIC N+3 analysis or to commission a custom teardown, contact sales@semianalysis.com.
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Don't call it DOGE: What NYC thinks of Mamdani's efficiency effort
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This Is the Dangerous Trap Making Businesses Bland, Forgettable and Easy to Ignore
Here's how years of shared best practices, optimization and AI-driven efficiency have made differentiation and loyalty harder to sustain.
AI boosts Lazer Logistics' efficiency in yard management
Lazer Logistics' AI tool, Uncle Phil, revolutionizes yard management by providing site managers with Phil Newsome's decades of logistics expertise.
Xbox CEO outlines strategy to prioritise cost-efficiency and exclusive titles over premium hardware
"We will continue to look at new business models – that's what is needed rather than premium, high-performance consoles," says Asha Sharma
From Classroom to Racetrack: How Charlie Baur is Building a Motorsports Career in a Business Discipline
Charlie Baur can trace his racing story back to a Christmas morning in Michigan — the kind that starts with snow on the ground and ends with a throttle in a kid’s hands. “I remember being 3 years old and then for Christmas that year, my parents had gotten me a 120 cc snowmobile,” Baur said. Long before sprint cars, he was a Michigan kid on snowmobiles, dirt bikes, four-wheelers and jet skis — and a regular at car shows and races with his family. Photo courtesy of Charlie Baur That early exposure became a calling. At 12, he sat in a sprint car for the first time and knew he’d found the next chapter. He started in quarter midgets, moved to go-karts, and the day before he turned 16 — one day shy of the minimum age required by track insurance — he made his first sprint car start after convincing officials to let him race. Five years later, Baur is still pushing forward, now racing sprint cars on both pavement and dirt while pursuing an automotive business education at Northwood University — with a clear-eyed understanding that motorsports encompasses more than what happens under the lights on Saturday night. “It’s a business,” said Charlie, a 20-year-old who calls Fenton, Michigan, home when he’s not at a racetrack or at Northwood’s residential campus in Midland, Michigan. Photo courtesy of Charlie Baur Racing is the product — but preparation is the job To the average fan, race day begins around dinner time. For a team, race day can be a 12-hour shift — plus the work that came before it. And Baur’s racing operation is a family affair. “The team is my parents and myself,” he said, explaining they own the cars, maintain equipment and manage the business side — from sponsor relations to budgeting. On race weekends, the core group includes Baur and his parents (Eric and Stefanie), plus a couple of additional hands (Alex Photiou and Robert Flannigan) who help with the intensity and pace of trackside work. That structure has shaped how he thinks about efficiency and professionalism. “We’ve always kind of had the mentality of we’re never working on the car for maintenance at the track,” he said. “Our goal is to do as little work as possible to the car because it should be ready when that car rolls out of the trailer to go racing.” That mindset shows up in routines: bolt checks, tire procedures, safety equipment and a repeatable process designed to limit errors. “Once I fire the car up and put my helmet on, that’s when it’s go time,” he said. “You can plan as much as possible for how the race is going to play out, but until you take the green flag … you don’t know how it’s going to go.” Photo courtesy of Charlie Baur First-generation driver, student of the game In racing, “first-generation” matters — and Baur wears that label with pride. “A lot of the drivers are third or fourth generation,” he said. “My family has never been in motorsports. So for me, we’ve always looked at it as we’re new to it and we want to be as different as possible. From a marketing standpoint, it helps us stand out.” It also pushes him to seek out mentors — especially veteran drivers who have seen every scenario, solved every problem and won in multiple eras. Baur credits accomplished driver Jason Blonde, a 10-time champion, for becoming his driver coach and helping him develop as a competitor. “To me, learning from Jason helps me because he has had lots of success and knows what to do,” Baur said. “You have to humble yourself and say, ‘I don’t know what to do; can you help me out?’” That willingness to learn extends off the track, too. Baur says one of his biggest challenges is not a mechanical limitation, but credibility. “It’s my age,” he said. “Some people won’t take me seriously because I’m so young. Even though … I do know what we’re talking about and have a general idea.” His answer has been to out-prepare, out-communicate and treat the operation like a real enterprise — because it is. Photo courtesy of Charlie Baur Northwood’s role: Turning passion into a plan Baur is majoring in automotive aftermarket management and pursuing an accelerated path that pairs undergraduate study with graduate work. He’s also exploring how to align his studies with motorsports-focused coursework as Northwood advances related programs and pathways. He sees the value clearly: motorsports needs business-literate professionals who understand budgets, sponsorship, marketing, operations and long-term strategy — and who can translate between the language of the shop and the language of the boardroom. That’s why his Northwood experience isn’t limited to the classroom. He has been involved with the Northwood University International Auto Show and serves as motorsports chair — a leadership role that demands outreach, contracts, coordination and a steady professional demeanor. “There’s so much outside work that makes the auto show successful that people don’t realize,” he said. “And it is truly student led.” He’s also participated in industry experiences through Northwood at major events such as AAPEX, SEMA and PRI, along with other automotive networking events — opportunities he describes as a fast track to understanding how business really gets done. “You learn a lot in the classroom,” he said. “But if you learn it and you can’t apply it to the real world, it loses its value. Or if you learn it and can apply it, but you don’t know anyone, it is still of no value.” In his words, Northwood helps him win because it “gives me the tools to succeed” — including flexibility and faculty support as he balances travel and racing commitments with academics. Photo courtesy of Charlie Baur Racing as an ecosystem — and a talent gap waiting to be filled Baur is blunt about what he sees across the motorsports world: a deep bench of experienced professionals, and not enough young talent entering the pipeline. “I go to car shows, I go to these different events, and typically … the average age is between 45 to 55,” he said. “There’s not a lot of young people going into the motorsports world.” That reality reinforces Northwood’s communications focus: positioning motorsports not as a narrow lane, but as a wide ecosystem of business careers — sponsorship, logistics, data, media, leadership, hospitality and innovation — with real demand for prepared graduates. It also shapes how Baur talks to younger students who love racing but aren’t sure what their future looks like. “If you have a passion for motorsports, there’s gonna be a spot for you somewhere,” he said, emphasizing that driving is only one of many career paths — and that local tracks and hands-on experience are often the best first step. But if someone is interested in driving as a career path, it will take a team to make that happen. Baur’s team includes Stahl’s Motors and Music Experience, Rhino Racing, Randy Wise Buick GMC Chevrolet, Western Michigan Fleet Parts, Mother’s Polish, Schaeffer’s Oil, Hepfner Racing Products, Ameriguard Storage Centers, Justice Brothers, Race 1 Wraps, TBM Brakes, Behind Your Design, CharlieBaur.com and Northwood University. “There are so many people who invest not only in myself but in my race team and who believe in us to succeed,” he added. Pictured: Charlie Bauer’s sprint race car. Looking ahead: A headline worth chasing Ask Baur to imagine 2035, and he’ll give you two answers — one dream, one blueprint. “In a perfect world,” he said, “winning the Indy 500.” Realistically, he wants to build a life where business ownership and racing reinforce each other and where he can pay forward the help he has received by mentoring younger drivers, especially those trying to break into motorsports without a family legacy. “When I retire from full-time racing, I want to be able to provide the same opportunities that were presented to myself to the next generation of drivers,” Baur said. “I know how difficult it is to get your foot in the door.” For now, the focus is simple: keep building the operation, keep learning the business, and keep showing up prepared — because in sprint car racing, as in life, process matters. And once the helmet goes on? “It’s go time,” Baur said. Photo courtesy of Charlie Baur Learn more Students interested in motorsports careers — whether in competition, team operations, marketing, finance, sponsorship, data, or management — can explore opportunities through Northwood University’s Center for Automotive and Mobility Studies. For Charlie Baur’s latest motorsports adventures, follow Charlie_Baur and Charlie Baur Racing on social media. To learn more about Northwood’s Bachelor of Business Administration in Automotive and Mobility Studies and motorsports management concentration, visit www.northwood.edu/programs/automotive-mobility-studies/. Photo courtesy of Charlie Baur Pictured: Charlie Baur at Butler Motor Speedway on May 31, 2026. Share this page
“Tech-Driven Prosperity & Right-Wing Racist Politics”: Quinn Slobodian on Elon Musk and SpaceX IPO
Ahead of the initial public offering for SpaceX, we speak with historian Quinn Slobodian, author of Muskism: A Guide for the Perplexed. He says Elon Musk is “creating a situation where he becomes deeply reliant on state contracts” as the U.S. government then becomes reliant on Musk. “It’s not about demolishing the government,” Slobodian says of his work with DOGE, the so-called Department of Government Efficiency that Musk led for the Trump administration. “It’s about making the government more compatible, ready for the kind of products that Musk offers, and to make him then an indispensable part of the infrastructure.” Slobodian goes on to warn that Musk’s wealth is helping to fuel his anti-immigrant, racist political ideology. “We really should be worried about the possibility of those things to live together: tech-driven prosperity and right-wing racist politics.”
Office of Economic Development continues to provide small business energy efficiency grants
“Reducing energy use benefits individual businesses and strengthens our community as a whole as we reduce our reliance on the electrical grid,” said Kauaʻi County Office of Economic Development Director Nalani Bru.
GKBA: Business Growth, Technology & Innovation with ITva Technologies
On this episode hosted by Carlos Ribero, Chairman of the Greater Kendall Business Association, guest Maricel Miranda, Director of Business Development at ITva Technologies, joins the conversation to discuss business growth, technology solutions, and innovation in today’s evolving marketplace. They explore how businesses can leverage technology to improve efficiency, strengthen operations, and remain competitive in
Why AI is not the magic fix for healthcare
AI can improve healthcare efficiency, but systemic barriers and misaligned incentives remain the real problem.
Google's new open source Gemma 4 12B analyzes audio, video — and runs entirely locally on a typical 16GB enterprise laptop
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Intel warns of "crazy" price: Arc G3 Extreme tramples AMD Ryzen Z2 Extreme for expensive price
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This strange crystal acts like metal and glass at the same time
A remarkable crystal called molybdenum oxychloride could help make futuristic technologies like smart contact lenses and ultrathin AR glasses a reality. Scientists have created the first detailed experimental map of its optical properties, revealing the strongest light-bending effect ever measured in a natural material. The crystal can act either like a reflective metal or transparent glass, allowing it to manipulate light with extraordinary efficiency while being thousands of times thinner than a human hair.
The Missing Variable In Every AI Business Case: Your Customer
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A quantum metasurface breakthrough could finally close the terahertz gap
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Mamdani launched his own version of DOGE
Mayor Zohran Mamdani is launching his own government efficiency effort to cut red tape and reduce unnecessary spending in NYC.
Fix fragmented HR systems to limit payroll errors and compliance risks
Fragmented HR systems cost US companies millions through payroll errors. Switch to HR automation to drive payroll accuracy and operational efficiency.
Holding the Veterans Affairs Secretary Accountable for the Severely Damaged Veterans’ Health Care System | American Postal Workers Union
In February 2025, representatives from Elon Musk’s Department of Government Efficiency (DOGE) began working with the newly appointed Department of Veterans Affairs (VA) Secretary Doug Collins to identify alleged wasteful contracts and improve VA operations. DOGE cancelled hundreds of VA contracts and carried out thousands of staffing reductions, including the dismissal of probationary employees, under […]
Semiconductor decoupling. Powell's politics. Industrializing Ogaden. Free trade and the Magna Carta.
Thank you for opening your Chartbook email. Feliks Topolski, 1907-1989 8th Army’s Front, Italy 1944 Semiconductor decoupling Source: FT One thing that Jerome Powell deeply understood is that chairing the Fed under current conditions is a deeply political job. “Powell has successes and mistakes to his name. But he stands out as having thought more carefully about the Fed’s democratic legitimacy than any chair since Paul Volcker,” said Paul Tucker, a former deputy governor at the Bank of England, referring to the Fed chair who successfully fought the great inflation of the 1970s and early 1980s. … While Powell was at the Treasury in the early 1990s, he watched Alan Greenspan build relationships within the government. That convinced Powell he needed to follow the former Fed chair’s lead and spend more time in Congress than his predecessors Yellen and Bernanke. “The accountability for the Fed runs through Congress,” said Claudia Sahm, a former Fed official who is now chief economist at New Century Advisors. “That’s not just about having people on speed dial — it’s answering questions, explaining policy and getting feedback.” Source: FT Ethiopia’s PM Abiy and Nigerian business tycoon, with Chinese engineering, are driving industrialization in Ogaden/Somali region of Ethiopia. - Michael Masri’s reporting for Africa Report if fascinating. Ethiopia has launched a cluster of large industrial schemes in the Somali region, laying foundation stones for a urea plant and an oil refinery in Gode while opening the first two phases of the Ogaden LNG project. Abiy Ahmed framed the push as part of a broader strategy to link energy, agriculture and industry. “These projects embody more than industrial growth,” he said. “They represent our shared responsibility to harness opportunities, strengthen co-operation and promote peace.” The Gode urea plant, backed by Dangote Group and Ethiopian Investment Holdings (EIH), is designed for 3m tonnes a year. Dangote owns 60%, while EIH holds 40%. Officials say Dangote’s equity totals about $2.5bn, while the state provides land and implementation oversight. Gas from the Calub fields will be piped 108km to the site. Construction is slated for 40 months, with operations targeted for 2028. Ethiopia imports most of its fertiliser, spending more than $1.2bn a year for 1.5m–2m tonnes. Usage was roughly 1.7m tonnes in 2023, almost half of it urea, and demand for 2024–25 is put above 2.4m tonnes. If delivered on time, the Gode plant could cover domestic needs and allow exports to neighbours. Brook Taye, chief executive of EIH, called the venture “a significant milestone in the journey toward industrial self-sufficiency”. Dangote told the groundbreaking crowd that the complex would be integrated with gas supply and a polypropylene unit to support local inputs. He pointed to Ethiopia’s Grand Ethiopian Renaissance Dam (GERD), with a capacity of more than 5,000MW, and noted his group’s cement operations and expansion plans. The Gode refinery is being developed by Golden Concord Group of China. It is designed to process 3.5m tonnes a year of crude and condensate from the Hilala field, with associated storage. Backers say it will ease foreign-exchange pressure from fuel imports and anchor further industrial activity, including a proposed steel smelting site in Dire Dawa. GCL’s chair, Zhu Gongshan, cast the project as “a key step in Ethiopia’s path to energy sovereignty”, underscoring the Beijing–Addis ties. Financing details are still being finalised, but the refinery is central to the government’s energy-security narrative. Source: The Africa Report Dangote’s Ethiopian vision: Dangote began with cement. His crown jewel, Dangote Cement, dominates Nigeria’s market and has 10 operations in other nations in Africa. The formula has been consistent: identify sectors with chronic shortages – cement, fertiliser, sugar – commit massive local investments, and scale up to serve regional demand. Ethiopia was a natural extension of that model. In 2015, Dangote launched the Mugher Cement Plant outside Addis Ababa at a cost of $600m, with an annual capacity of 2.5 million tonnes. The investment gave him a firm foothold in one of Africa’s fastest-growing construction markets. But success came with risks. In May 2018, violent unrest led to the killing of Dangote’s country manager and temporary shutdowns at Mugher. While other investors might have retreated, Dangote doubled down. Today, he is preparing to spend $400m to expand Mugher’s capacity to 5 million tonnes, alongside a new grinding unit near Addis Ababa. Cement is just one market Dangote is targeting. Ethiopia’s enormous state-controlled sugar industry, long plagued by inefficiency and debt, has struggled for years to reform. Its Omo Kuraz Sugar Development Project, touted as one of the continent’s largest initiatives, continues to face delays and mismanagement. … The most ambitious venture of all is the planned fertiliser production complex in Gode, Somali region. Publicised on 28 August 2025, the Dangote Group and Ethiopian Investment Holdings (EIH) deal plans one of the world’s largest single-site urea manufacturing plants. The project costs an estimated $2.5bn and has an estimated capacity of 3 million metric tonnes annually, a rate that would not only render Ethiopia independent, but even a net exporter of fertiliser. EIH, the state wealth fund of Ethiopia, will hold 40%, while 60% is held by Dangote Group. … For Dangote, Ethiopia is a trifecta: Cement demand is projected to grow by 10% annually, its sugar consumption is growing with rapid urbanisation, and fertiliser demand is all but insatiable, given that farming supports the livelihood of 70% of Ethiopians. Source: The Africa Report The stakes for Abiy are high: For Addis Ababa, the $4bn fertiliser project in Ethiopia’s Somali region is no longer simply a manufacturing investment. It is increasingly being framed as a strategic state project tied to food sovereignty, import substitution and the government’s broader attempt to build economic resilience under mounting fiscal pressure. “Becoming self-sufficient in food is our main agenda,” Abiy says during the visit. “Land is needed; we have it. Water is needed; we have it. Human resources are needed; we have it.” The scale is enormous even by African industrial standards. Once operational, the plant is expected to produce three million metric tonnes of urea annually, potentially making it one of the continent’s largest fertiliser complexes. Ethiopian officials say the project now includes a 110km gas pipeline, a 120MW power plant, a polypropylene packaging facility and a two-million-tonne NPK blending plant. For a government grappling with chronic foreign exchange shortages, ballooning import bills and pressure on agricultural productivity, the numbers matter politically as much as they do economically. The decision to anchor the project in Gode is deliberate. Long viewed as peripheral to Ethiopia’s industrial economy, the Somali region is now being repositioned by the federal government as a future irrigation and agro-industrial corridor. Officials argue that the area’s vast land reserves and access to water could eventually support large-scale commercial farming capable of reshaping Ethiopia’s food economy. The government is simultaneously building housing infrastructure for about 5,000 residents near the plant, while officials project broader industrial expansion along the corridor. Abiy goes further, comparing the long-term revenue potential of the Gode development zone with Ethiopia’s flagship state enterprise. “The investments we are making in this Gode area, combined, will generate high revenue for Ethiopia, at par with Ethiopian Airlines,” he says. Source: The Africa Report Feliks Topolski 1907-1982 Topolski’s Chronicle, ‘Nazi Revival’, Vol. 8, Is. 1-2, 1960 HEY READERS, THANK YOU for opening the Chartbook email. I hope it brightens your day. I enjoy putting out the newsletter, but tbh, what keeps this flow going is the generosity of those readers who clicked the subscription button. Photo by Jakub Dziubak on Unsplash If you are persuaded to click, please consider the annual subscription of $50. It is both better value for you and a much better deal for me, as it involves only one credit card charge. Why feed the payments companies if we don’t have to. Subscribe Grim vision of drone warfare by Sylvie Kaufmann For contributing subscribers only. Subscribe The state of the art in Colbert-studies. Jean-Baptiste Colbert was Louis XIV chief minister from 1661 to 1683 and traditionally seen as an architect of absolutism and mercantilism. Alexander Hamilton later cited him as an inspiration in 1782. Now his legacy is disputed. Daniel Dessert, the chief critic, sees Colbert as the orchestrator not so much of an absolutist state as of an elite cabal. Would be great to have a good English-language review of this important debate. Source: lhistoire Didn’t know that the Magna Carta included free trade provisions Fighting for the right to the beach in Oregon in 1967: Source: Research Gate RAF Station – British and Polish Flags, c. 1940-45, The Ingram Collection Feliks Topolski, 1907-1989 ink and wash If you’ve scrolled this far, you know you want to click: Subscribe
Narayana Institute of Cardiac Sciences becomes India's first HIMSS AMAM Stage 6 hospital
The organisation says analytics and AI became essential to balancing affordability, efficiency, and clinical outcomes in India's predominantly self-pay healthcare environment.
Texas Continues Raising the Bar on Regulatory Efficiency
At the Texas Association of Business (TAB), we’ve consistently advocated for pro-business policies that strengthen Texas’ competitive edge. Cutting red tape, improving government efficiency, and streamlining regulations are essential to keeping Texas the nation’s leader in job creation, business expansion, entrepreneurship, and corporate relocations. Last week, Texas took another meaningful step in advancing our state’s…
Optical condensation using a fiber-based photothermal module
The system achieves about tenfold higher collection efficiency than conventional approaches, enabling the assembly of approximately 10,000 microparticles or bacteria in just 60 seconds.
The “impossible” LED that could change everything
Scientists at the University of Cambridge have achieved what was once considered impossible by electrically powering insulating nanoparticles to create a completely new kind of LED. Using tiny organic “molecular antennas,” the team found a way to funnel energy into materials that normally cannot conduct electricity, producing ultra pure near infrared light with remarkable efficiency.
Retailers are making expensive bets that shoppers still want to go to stores
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Now What? With Carbon Pricing Eroded and Pipeline Politics Advancing, Here Are the Pathways for Climate Success
At the end of a whirlwind week of news on carbon pricing and electricity strategy, capping a madcap year of pretty much non-stop, dramatic change, the word across much of Canada’s climate and energy transition community is that climate policy in this country has been shredded. Eviscerated. Hit with a sledgehammer by policy rollbacks that have pushed the country’s 2050 net zero target “well out of reach”. That means it’s never been more important to look for the rays of hope and glimmers of possibility. To glimpse the seeds of the next set of strategies to get Canada’s climate pollution under control and the country into the accelerating global dash away from fossil fuels. And then, once we’ve spotted those possibilities, get on with the hard, day-to-day slog of trying to make them a reality. Nothing takes away from the frustration and the deep disappointment so many climate and energy hawks are expressing, the sense of betrayal by the author of Value(s) and the former UN special envoy for climate action and finance. But we knew two things as the week drew to a close. We’re looking at the world as it most definitely is. And we don’t get to give up finding the pathways to confront climate change and deliver faster, deeper carbon cuts that leave no one else behind. So really, the first question we all have to ask ourselves is: What’s next? Subscribe All the Oxygen in the Room The outpouring of anger and grief over the carbon pricing deal between Prime Minister Mark Carney and Alberta Premier Danielle Smith has been absolutely understandable. So much of the climate community poured years, more than a decade, into dragging the current federal pricing regime across the finish line, then defending it from a deluge of three-syllable rhymes after the Trudeau government proved utterly incapable of delivering its own message. The policy foisted on us by neo-classical economists took up all the oxygen in the room, burned through years of climate response time that we won’t get back, while cornering climate hawks into the position that the best response to the crisis of our lifetimes is a new tax…in an era of historic anti-tax sentiment. I mean, really—what could possibly have gone wrong? Against that history, let’s appreciate columnist Max Fawcett’s point that even a modest carbon pricing agreement with a government as off-the-wall libertarian/conspiracist as Danielle Smith’s—those adjectives are mine, not Max’s—is a win worth savouring (as long as Smith keeps her promises for a change). But part of living in the world as it is (no, I’m not letting that go) is to be clear-headed about what we can and can’t control. And one thing we get to decide, after seeing this week’s carbon price festivities take up all the oxygen yet again, is whether we want to keep letting that happen. Particularly when success down that road depends on a factor that no one with a climate agenda can control or influence—a provincial carbon pricing mechanism that has been manipulated and eroded beyond its lowest possible denominator. Thankfully, that’s not the way it has to go. Not when we have so many other powerful, practical tools at our disposal, including the ones still available to us through this abominable Memorandum of Understanding (MOU) between Canada and Alberta. Tools In Our Toolbox When I started roughing out this list, I didn’t expect it to grow to nearly a dozen bullet points. It’s probably still incomplete. Some of the greatest hits in today’s climate solutions toolbox include: • No Carbon Capture, No Pipeline: On Friday, Prime Minister Mark Carney explicitly stated that there’s been no change to the MOU provision that there will be no West Coast pipeline without an industry commitment to build its massive, $16.5-billion carbon capture and storage (CCUS) hub in Northern Alberta, and vice versa. The two megaprojects were joined at the hip when the MOU was signed Nov. 27, and the implementation agreement this week affirmed that they still are. A parade of independent analysts have spent years pointing to the economic and technical flaws in CCUS, while the industry kept postponing its investment decision until it could arm-twist the government for more “clarity” (by which it meant even more lavish taxpayer subsidies) on the project. Now the industry itself is running away from the CCUS hub and insisting the pipeline should proceed without it, but Carney doesn’t seem to be budging from a central tenet of the MOU to which Smith has signed on. • No Subsidies, No Investors: Climate analysts and advocates have quite rightly been hammering away at Carney and his team, insisting that any new capacity the industry wants to build must proceed without new subsidies. The government has responded with a growing collection of funding and financing mechanisms for the very wide menu of industrial development and nation-building projects they say they want to take on, and that menu always includes fossil fuel infrastructure. But it’s hard to see how even the combined fiscal clout of the federal and supportive provincial governments will deliver the financial backing private investors would need when the business case for new fossil fuel development is evaporating before their eyes. Particularly when… • No Market, No Demand, No Investors: As our friend Markham Hislop at Energi Media (our apparently sleepless friend, given the massive volume of great material he’s been churning out) points out this morning, the biggest vulnerability in any pipeline deal is the assumption that Asian buyers will want the oil or liquefied natural ga that our fossil industry is so keen to send them. Hislop writes in part: Ottawa and Alberta are effectively betting that countries like China and India will continue increasing oil imports for decades as their economies grow and energy consumption rises. That assumption underpins the entire economic rationale for expanding oil sands production and building billions of dollars in new export infrastructure. But Asian energy systems are changing rapidly… China, India, South Korea, and other major hydrocarbon importers are now investing hundreds of billions of dollars into electricity systems built around wind, solar, batteries, nuclear, hydro, and expanded transmission infrastructure. Domestic “energy sovereignty” is increasingly replacing the old energy-security model based on stable oil and gas imports. Those investments are expected to sharply slow oil demand growth and eventually reverse it, even as overall energy consumption continues rising. There are also refining constraints. Many Asian refineries and petrochemical complexes are already optimized to process discounted heavy crude from the Middle East and Latin America. That raises serious questions about how much additional Canadian bitumen Asian markets can absorb at profitable prices. Small wonder that there’s still no private sector investor for the project, despite Smith’s government desperately beating the bushes to put together a deal. For now, Alberta is acting as proponent and covering early start-up costs for a pitch to the federal Major Projects Office, which could actually turn into the next tough hurdle for Smith and her pipeline to jump. • Canada Day Looms: How ironic that Canada’s birthday this year could become a major chokepoint for the provincial premier who’s been working so diligently to tear the country apart! The July 1 target date for Alberta’s pipeline proposal is baked into the MOU, was reaffirmed by the implementation plan, but it hadn’t dawned on me that it cuts both ways. As one very smart colleague wrote in an email yesterday, “they’ve thrown the ball into Alberta’s court to get the project proposal on the table really quickly and to have to do a whole pile of work to put together a massive, complicated project that would typically take years to assemble, and they’ve given them weeks to do it.” That makes July 1 a looming deadline that Smith won’t be able to run away from politically, especially with the separatists in her party and her caucus breathing down her neck. (See previous ref to off-the-wall.) But if Alberta comes in with a sloppy, incomplete submission, even after Carney bent over backwards to simplify the application process and the rules that govern it, it may be harder for the province or the industry to blame Ottawa and insist on the faster process they claim their investors are demanding. (Oh, wait—which investors would those be??) • We’ll See You In Court (Then We’ll See You Again): If Carney did cave, that would be just one more reason for Indigenous and other affected communities to take the government and the process to court—Just as Alberta First Nations did, successfully, in response to Smith’s half-baked separation referendum. Veterans of the Harper era have been warning that a shoddy process around fossil fuel infrastructure or other major projects will be a recipe for the very delays that process seeks to avoid. And now more than ever, with renewable energy and energy storage eating fossil fuels’ lunch in import markets around the world, a delayed pipeline or LNG terminal may be as good as a cancelled one. • Charged Up, Ready to Go: With its goal of doubling Canada’s electricity supply to meet a doubling of demand by 2050, the national electricity strategy that Carney unveiled Thursday has a lot to like. With its explicit language about speeding the shift from fuels to more efficient and affordable electricity, global investment and deployment patterns that already favour that shift, an emerging bidirectional power grid, the role of front-line options like rooftop solar and heat pumps, the emergence of electric vehicles as behind-the-meter energy storage, and the domestic jobs and manufacturing to make it all happen, the document doubles down on the essential cornerstone of a faster shift off fossil fuels. The strategy envisions a more prominent role for gas and nuclear power. But some of those provisions were already in the Clean Electricity Regulations that climate hawks are now fighting so hard to defend, inserted as a compromise in a futile attempt to mollify the industry and its political representatives in Alberta and Saskatchewan. But once again, gas will be a tougher sell when it’s more expensive and now so much more unpredictable than the clean alternatives. The new nuclear technologies are still speculative and deeply vulnerable to cost overruns. Increasingly, utilities, developers, and investors know it. Carney declared Thursday that “it doesn’t do us good to be sitting in court all the time with provinces. It doesn’t do us good to be talking past each other. What does do us good is to come together with specific projects.” There are no guarantees, but so much of the language and narrative-building in the electricity strategy suggests the lion’s share of those projects will be renewable. • The Party Has Already Started: The electricity strategy only rarely digs down to specific projects, but provinces representing three-quarters of Canada’s population are already embracing a faster transition. Hydro-Québec is working on a 10-year, $185-billion renewable energy and grid buildout by 2035. Ontario recently brought 10 provinces and territories together in a National Energy Corridor Agreement to boost interprovincial and -territorial transmission infrastructure. And the MOU implementation agreement commits Alberta to facilitate investment in renewable energy projects, a big step back from its continuing, punitive restrictions on renewables development. The electricity strategy envisions much of the financing and infrastructure that will be needed to pull those advances together into an integrated whole. • Delivering on Affordability: The MOU implementation plan has little or nothing to say about affordability (are you surprised?), but the electricity strategy does, with a top-line pledge to reduce home energy costs for seven out of 10 Canadian households by 2050, a total saving of $15 billion across the board. It’s just a start, but it puts affordability on the government’s narrative map. If they’re serious and deliberate about patching together a least-cost energy strategy, it’ll have little if any room for oil, gas, or nuclear—not with powerful evidence, for example, that electricity prices are higher when those prices are set by gas. • Smith Proves that Canada Works: By signing a deal that makes it harder to claim the federal government is blocking a new pipeline, Smith has helped prove Carney’s constant anti-separatist refrain that “Canada works”—incurring the rage, no doubt, of her own political base. Canada also needs to work for anyone who depends on a clean environment, healthy and thriving ecosystems, and safe, stable climate. But with Smith and her separatist constituents setting up as a fifth column for annexation by Donald Trump’s United States, let’s set aside any notion that 51st state status for Canada is a recipe for anything other than climate disaster (and so much else). Resisting and withstanding Trump (just 170 more sleeps until mid-term elections, which is a damn sight better than the 730 we started with) doesn’t mean a free pass for a pipeline, but we can still appreciate it that keeping Canada whole and sovereign is still Carney’s Job One. • The Words Not Spoken: Apart from a commitment to export a million barrels of “low-emission” Alberta bitumen per day (memo to Smith and Carney: You realize that that’s less than the industry is already exporting??), the MOU implementation plan says nothing about the international trade and economic sovereignty deals that Carney has been travelling the world to negotiate. It didn’t have to. Carney doesn’t need permission from Danielle Smith, her American enablers, or her separatist allies to continue building the alliances that will ratchet down our economic dependency on our unstable, unreliable neighbour to the south. But every connection he builds with countries outside North America helps align our economy and our future with a faster shift off fossil fuels. Little if any of this was on our bingo cards a year or two ago. But it’s the pathway that has opened up to us. And if it gives Canada any climate or energy gains at all in an era still dominated by Trump and his increasingly ridiculous tariffs, his loutish trade negotiations and his continuing annexation threats, we have to take the wins. Not least because they’ll be the point of departure for what we can achieve in 2027, 2029, and beyond, as Trump’s grip and this era begin to loosen and then fade. What is Carney Doing? If this line of thought is right—and it’s a possibility, not a prediction—it means that Carney’s actions and decisions are largely about buying time. Time for Trump’s power to wane. Time for Alberta’s separatist/conspiracist virus to spread, mutate, die out, or at least die back, with help from a vaccine of federal steadiness and calm (appropriate enough, for a movement populated largely by vaccine deniers) that no conspiracy theory can dismiss. And time for the government’s trade and investment agenda to deliver results—even knowing that some of those results will bring impacts that front-line communities will not and should not accept. In the immediate moment, none of this changes the way the wider climate community has to respond, from campaigners to investors to front-line practitioners. All of our voices are still essential. But those voices will be stronger and more confident if we have a clearer sense of the brutal game we’ve been pulled into, and a plausible path (or two it three) for playing it to the win we need. This conversation also underscores our biggest task for the remaining years of what was supposed to be the “decisive” decade for climate response: if we can shift the energy narrative in Canada, make it a mainstream view that the country’s preoccupation with oil and gas has us falling farther behind a changing world, we’ll see far better results in the 2030s and beyond. For many veteran climate advocates, taking on that part of the fight will begin with recognizing that most of our friends and family, neighbours and colleagues already understand that climate change is real and right in front of us: they’re looking away and staying silent because they don’t have what climate communicator Katharine Hayhoe calls “efficacy”. As Hayhoe recently pointed out in a feature interview with The Energy Mix, it amounts to science denial to keep hammering away at the dire news about global warming without also helping audiences understand what they can do about it, with multiple studies telling us why that won’t work. Far better to open those conversations with the dominant crises like energy security, food security, emergency preparedness and business continuity, affordability, and financial security that have knocked climate change far lower on the list of public priorities, and will likely keep it there. We Knew This Would Happen Climate hawks have always known this day would come. For decades, we warned that everyone had to pay attention to climate change right now, because it would be much tougher to respond once the crisis itself started affecting our daily lives. We were right, and here we are. But now, thanks to decades of hard work, communities and countries have an alternative to doubling down on fossil fuels. “In 10 years everyone will have ‘always known’ that solar and batteries were going to win,” Morgan Solar Executive Chair Mike Andrade writes on LinkedIn. With the disruption in the Strait of Hormuz roiling energy priorities around the world, Canada and the United States are among the shrinking number of countries that are still very keen on fossil fuel development. Understanding that gap is a first, essential step in spotting the opportunities ahead, and averting the deep economic as well as environmental and social risk we face if we don’t seize them. Thanks for reading The Energy Mix Weekender! Subscribe for free to receive new posts and support our work. Subscribe Mitchell Beer traces his background in renewable energy and energy efficiency back to 1977, in climate change to 1997. Now he and the rest of the Energy Mix team scan 1,200 news headlines a week to pull together The Energy Mix and The Energy Mix Weekender. Chart of the Week BYD Eyes 20 Dealership Locations After Canada Greenlights Chinese EV Imports ‘Sledgehammer’ Carbon Price Deal Boosts Emissions by 230Mt, Aims for Fall 2027 Pipeline Approval ‘Worse Than Harper’: Regulatory Rollback Would Stop Canada from Assessing Project Impacts, Critics Warn Electricity Strategy Aims for Doubling by 2050, Allows ‘Flexibility’ for Gas Power Plants Opposition Mounts as O’Leary’s Data Centre Approved in Drought-Stricken Utah Diluted Carbon Price Misses ‘Reality of the World We’re In’, Could Impede Diversified Trade: Climate Institute $200B in Clean Energy Investment Will Need On-Time Delivery, Reliable Policies, Trade Association Says ‘Sovereign Pipeline’: CEO Pitches to Keep Trans Mountain in Government Hands What a Supercharged El Niño Could Mean for Canada Canada’s future is electric, and here’s how a power grid superhighway would get us there (Toronto Star) The Perilous Waters of Hecate Strait (Globe and Mail) Saudi Aramco profits jump despite conflict in Middle East (The Guardian) Farmers confront rising cost of fertilizer and fuel as spring seeding under way (Canadian Broadcasting Corporation) Clarkson forecasts 24% decline in offshore oil, gas capital expenditures (Oil & Gas Journal) Pipe Dreams: How Oil and Gas Fail to Deliver Economic Development in Africa (Oil Change International) Developing countries must hold the pen to script the fossil fuel transition (Climate Home News) Iran war threatens the dream of a post-oil economy in the Gulf (Washington Post) U.S. Oil, Gas Work Force Hits Lowest Level Since 2022 (Rigzone) Why Polestar Is Doubling Down on Net Zero as Rivals Pull Back on EVs (Bloomberg) Why this Michigan utility plans to sell its hydro dams for $13 (E&E News/Politico) Levees can no longer save New Orleans (Vox)
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‘The reality, for better or worse’: Columbia comp sci students and faculty grapple with AI’s disruption of the field
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As Genawi began to see the effects of AI trickle into her classroom, she turned to guidance from her home state’s Department of Education, which she said she found “outdated and inaccessible.” Genawi spent the rest of her high school career dedicated to the issue, including writing a 15-page memo exploring varying AI policies across Indiana schools, which she sent to every Indiana state senator and representative whose contact information she was able to find. She later helped draft a bill that would have required public high schools to establish and share their own AI policies with students in an accessible format. But with so many other bills already awaiting referral, hers never made it to committee. When Genawi arrived at Columbia to study computer science, she found that the gaps she had spent years trying to address in Indiana had followed her there. Many students and professors were also grappling with what AI meant for the field. Across Columbia’s undergraduate schools, computer science has become the most popular major—accounting for around 11 percent of degrees awarded in Columbia College, 32 percent in the School of Engineering and Applied Science, and 12 percent in the School of General Studies in 2024. While the number of computer science majors in SEAS grew from 166 to 173 during the 2024-25 academic year, the total number across the three schools fell around 4.5 percent from 393 to 375, driven by declines at Columbia College and General Studies. At Barnard, it has grown to become the second most popular major as of 2025, up from third the year prior. The number of degrees awarded have grown fivefold since 2016. Faculty members and students in the department told Spectator that the surge in the major’s popularity has been driven in large part by its apparent promise of a secure, well-paid career path. However, they noted that the recent rise of generative AI has compromised the sense of stability that once defined the field, even as interest in technical skills among students persists. According to data from the Federal Reserve Bank of New York in 2024, out of 74 majors tracked, computer science had the fifth highest unemployment rate among majors at 7 percent, while computer engineering had the second highest at 7.8 percent. “Anecdotally, people are moving away from CS as a major,” Daniel Bauer, a senior lecturer in the computer science department, said. “They’re still taking some of our classes, right, because they think they need that, but they’re instead majoring in other things.” Bauer described a field that had shifted from what he called a “nerdy outlier discipline” to one that “everyone needs,” a sign that technical skills have become a baseline expectation across industries with the emergence of AI. “A lot of people thought, ‘Oh, it’s a guaranteed path to a stable income. You get a six-figure job right out of your undergrad,’” Bauer said. Now, companies may see AI as a way to reduce demand for entry-level programmers, especially in what he calls “code monkey jobs,” roles where a large number of employees are “just writing out code nine-to-five.” Chris Murphy, a senior lecturer in the computer science department, described the current moment as the convergence of two forces: the downturn of the job market and generative AI coming onto the scene. “Things kind of started to really pick up in 2014, 16,” he said, recalling the years after the weaker 2010 market. Murphy added that this was also a period where “students were getting more experience outside of class than they were inside of class” through internships, jobs, and side projects. Murphy suggested that the earlier momentum helped make computer science feel like both an academic program and a reliable pathway into work. That feeling is harder to sustain now as the industry reconfigures, which is a shift that students are seeing firsthand. Rebecca Yu, SEAS ’27, said that during a recent internship in Big Tech, she saw that “every single tech company was racing to integrate” large language models. She added that her manager said her intern class was the first to complete their assigned projects, which she attributed to the increased efficiency that comes with AI. Frank Liu, SEAS ’29, said that with AI lowering the barrier to coding, companies now expect everyone to write code. “A lot of companies outright say if you’re not using coding in your job, you might get fired for not being productive enough,” Liu said. Yu similarly expressed that students increasingly have to accept AI being a part of industry workflow, adding that many also “make use of it to maximize their productivity.” Richard Li, CC ’28, described a “franticness” among his peers as the pace of change accelerates. He explained how “some new tool” is released regularly, noting that tools rise and fall in prominence within weeks. He has come to believe that he doesn’t need to “match that speed all the time” and keep up with every development. Li has learned that AI tools allow him to “take a breath” and “get back into the loop much easier than before” when he needs to. While some companies specifically target Columbia when hiring, sending representatives to campus career fairs and recruiting large numbers from Columbia, a computer science degree cannot be treated as a static credential, Yu described. “You can’t just get your degree and stop learning after that. You have to always be learning,” Yu said. “That is something you basically have to expect for your job.” AI has not only affected students’ decisions to major in computer science, but also reshaped how the subject is taught. Across departments, faculty members no longer treat work done outside the classroom as a reliable measure of understanding, shifting instead toward in-person exams, quizzes, and attendance checks. While homework once made up as much as 60 to 70 percent of a student’s grade in computer science classes, Murphy said that breakdown has since flipped, with exams and quizzes now accounting for the majority. “The assumption—especially among pessimists—is that they’re using it to do their homework,” Murphy said. “They take the homework assignment. They put it into generative AI. Out comes the solution. Submit solution. The end.” Murphy said that faculty members ranged in their responses from fully prohibiting AI use to actively teaching students how to effectively work with AI. He said he shifted his approach this year after his teaching assistants called his belief that students weren’t using the technology “naïve,” and now permits students to use AI on assignments. His surveys of students in his introductory classes have told a more complicated story than the one so-called pessimists offer: Around 60 to 70 percent of students who reported using AI said they used it to have concepts explained to them, to clarify assignment instructions, to generate test cases, or to create practice questions. “Those are all ways that you might have had a tutor in the past to do that, and now you have this AI essentially as your tutor,” he said. Bauer has taken a different approach, teaching students how to use AI productively without sacrificing the core principles of the discipline. “People who are trained to actually use AI tools productively, while being in charge of designing the overall project, will be very much in demand in the next couple of years,” he said. Over the past year, a working group of computer science faculty has been redesigning the introductory and intermediate programming sequence to integrate generative AI as both a subject and a tool, representatives from SEAS wrote in a statement to Spectator. The effort is “coordinated” across the department, “not course-by-course,” with a systematic assessment of how AI integration is affecting student outcomes underway to shape the next round of changes. The goal, the department explained, is for students to be able to “read, verify, and reason about code, whether they or a model wrote it.” Tony Dear, senior lecturer in the computer science department, is piloting individualized AI feedback in a discrete mathematics course, while a machine learning course is also testing a Socratic AI dialogue system designed to “guide inquiry rather than supply answers,” the statement reads. Beyond individual courses, SEAS funded seven cross-departmental faculty projects in generative AI this past academic year, spanning biomedical engineering, chemical engineering, industrial engineering, and computer science, according to the statement. This phenomenon extends beyond the computer science department. SEAS’ new AI minor, which it announced in November 2025, reflects the University’s attempt to adapt. The minor is specifically designed for noncomputer science majors and aims to provide “essential AI knowledge” while emphasizing practical and responsible use across disciplines, according to the SEAS website. At the center of the minor is AI in Context, a course taught by a team of faculty from the departments of computer science, applied mathematics, philosophy, music, literature, and the Writing Center, the representatives told Spectator. Bauer described it as targeted at students who want to bring AI into fields like economics or biology, rather than as a path into software engineering itself. At the graduate level, SEAS announced a new Master of Science in artificial intelligence in February, with the inaugural cohort starting in the fall. While recognizing how AI has helped them navigate coursework, students also described its rise as isolating, even among members of the Application Development Initiative, one of Columbia’s largest computer science clubs. “As people start to ask AI for questions that they would normally ask students and members, it starts to isolate people” Li said. Alexa Kafka, BC ’27, echoed Li’s sentiment, pointing out that computer science has always been a collaborative discipline with code reviews and pull requests, even as AI makes independent work easier. Despite this, Kafka noted that she hasn’t been to office hours “in at least a year.” Bauer added that faculty are exploring long-term solutions to the assessment problem. “One of the things that we’re trying to do at the department or school level is to maybe move towards computerized testing facilities,” Bauer said, referring to ideas in the department to revitalize computer labs as an alternative to pen-and-paper exams. “We have to accept that this is the reality, for better or worse.” But more exams, students say, does not mean better learning, nor does it reflect how computer science is actually done. “Code is so variable and can be approached in so many directions, there’s never just going to be one correct answer. There can be multiple optimal solutions,” Kafka said. Students also expressed concern that the shift toward exam-heavy grading pulls focus away from the applied, project-based work that better reflects both discipline and industry expectations. ADI has tried to respond more quickly than the curriculum can. Through a vibe coding workshop this past semester, club members said they wanted to help students understand not just that AI exists, but how to use it deliberately. “Vibe coding” refers to the practice of prompting AI to write code for a task or project, and has become widespread enough that ADI felt the gap in formal instruction was worth addressing, according to Sophia Huang, BC ’29. The workshop introduced students to the concept of context engineering, which Shaina Sahu, SEAS ’27, described as not just writing a prompt, but optimizing “the rest of the relevant information that you would feed into the model.” Without that, students said that AI-generated code can fail at scale or introduce difficult-to-detect bugs. Genawi said the shift toward AI has changed what it means to be good at computer science. “I think the shift has kind of gone towards what can you create and what can you do, instead of, what do you know,” she said. Indeed, during ADI DevFest, its annual hackathon, Li said more teams are trying to complete their projects than in years past. While sign-ups have historically outpaced submissions, Li said this is beginning to change because teams “have a tool that completes the vision for them.” While many students see AI as an equalizer that lowers the barrier to entry for coding and technical work, Murphy said it also creates new equity concerns inside the classroom around who can afford stronger tools and who already knows how to use them. “The equity issues I worry about are students who have access to paid versions of things versus free versions of things,” he said. Although popular AI models like ChatGPT and Claude have free versions available, both have paid models that can reach over $100 per month, which output different qualities of code. Murphy also pointed to differences in prior exposure to AI literacy itself. “Students who go to high schools or K-12 education, where they’re taught AI literacy, prompt engineering, context engineering, they understand how to do this, as opposed to students who go to schools who don’t teach that,” he said. “Then they come in, and then they’re somehow expected to know how to use these tools.” For Genawi, those disparities begin long before students arrive on campus. “It’s very interesting to consider how lucky you were geographically,” she said. “To be born where you were is influencing your ability to get access to these spaces.” Students like Yu, though broadly apprehensive about the future of computer science, are not without hope. “I’m optimistic, because I think if you’re truly passionate about CS, there will definitely be a place in the field to do something you want to do,” she said. Senior Staff Writer Ria Vasishtha can be contacted at ria.vasishtha@columbiaspectator.com. Follow Spectator on X @ColumbiaSpec. Staff Writer Arjun Menon can be contacted at arjun.menon@columbiaspectator.com. Follow Spectator on X @ColumbiaSpec. Want to keep up with breaking news? Subscribe to our email newsletter and like Spectator on Facebook. Produced with Spectate by Emily Ta
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