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Informanté on Instagram: "Namibia urged to harness growing space science opportunities Staff Reporter NAMIBIA is positioning itself to benefit from the growing space economy through new satellite infrastructure, proposed legislation and expanded education and training opportunities, with young people urged to pursue science, technology, engineering and mathematics (STEM) careers. This was said by Dr Lisho Mundia, Deputy Executive Director for the Department of Higher Education, Training, Research and Innovation, who represented Education Minister Sanet Steenkamp at the official opening of World Space Week Namibia 2026 at the Windhoek High School Stadium on Monday. This year’s World Spac
1 likes, 0 comments - informante_news on October 10, 2026: "Namibia urged to harness growing space science opportunities Staff Reporter NAMIBIA is positioning itself to benefit from the growing space economy through new satellite infrastructure, proposed legislation and expanded education and training opportunities, with young people urged to pursue science, technology, engineering and mathematics (STEM) careers. This was said by Dr Lisho Mundia, Deputy Executive Director for the Department of Higher Education, Training, Research and Innovation, who represented Education Minister Sanet Steenkamp at the official opening of World Space Week Namibia 2026 at the Windhoek High School Stadium on Monday. This year’s World Space Week is being held under the theme “Rocket Revolution”, reflecting the transformation of space technology from the first human-made satellite launched in 1957 to modern spacecraft, satellites, space stations and missions beyond Earth. Full story: https://informante.web.na/?p=401904 Photo: National Commission on Research, Science and Technology - (NCRST)".
Does written language speed up or slow down cultural change?
The written word has been revolutionary in preserving ideas from the past, and transmitting new ones in the present. But does it favor tradition or change?
Nets’ Wolf, Traoré Taking Sophomore Leaps in Preseason
Explosive driving and elite playmaking from Brooklyn's rising sophomores signal a potential bench revolution, transforming last season's developmental growing pains into a formidable second-unit strength.
Mike Ditka tributes pour in from former President Obama, Chicago's sports teams and around the NFL
Mike Ditka was “Iron Mike” as a player who revolutionized the tight end position and later became the easily recognizable and often imitated fiery, mustached and sweater vest-wearing “Da Coach” of the Chicago Bears during a Super Bowl-winning tenure.Ditka died Friday at 86, his family announced in a statement.
What Happens When Science Leads Us in an Unexpected Direction? - Revolution Medicines
What Happens When Science Leads Us in an Unexpected Direction? - Revolution Medicines / cancer, Jan Smith, OncoDaily, Oncology, Revolution Medicines
HOMETOWN ENTERTAINMENT: Comedy about the French Revolution opens this week at Showtimers Community Theatre
French Revolution-themed comedy opens at Roanoke theatre.
50 years ago, my colleagues and I pursued basic research science that became revolutionary
“Basic studies led to clinical and translational advances that no one could have predicted,” Robert Gallo writes of his work with interleukin-2.
Science Museum Oklahoma helps reunite Revolutionary War remains
Science Museum Oklahoma transferred Revolutionary War gunboat Philadelphia remains for reunion and military burial in New York.
Verana Health and Bitfount Collaborate to Simplify Prescreening for Ophthalmic Clinical Trials
/PRNewswire/ -- Verana Health®, a digital health company dedicated to revolutionizing patient care and clinical research through real-world data (RWD), has...
The Science Behind the Nobel-Winning Technology That Controls Neurons With Light
Optogenetics revolutionized neuroscience, but its origins come from an entirely brainless organism—an alga.
Kansas’ 94-year streak is unlike anything else in American politics
Democrats are dreaming of a revolution in Kansas in November, trying to believe in polling that shows a tight race in the Senate contest there between the Democrat, Rev. Adam Hamilton, and the Republican incumbent, Sen. Roger Marshall.
The AI tune is changing: From a wave of hype to business realism
The AI revolution is not an overnight upheaval, but a calculated evolution. In the coming years, companies will not win simply because they adopted AI; they will win because they knew how to manage it optimally.
Xbox sale round-up October 6, 2026
New Xbox sales are now live, with big discounts on Halo Wars 2, Dead Cells, Sid Meier's Civilization Revolution, Batman: The Telltale Series, The Gunk, Batman: The Enemy Within - The Telltale Series, The Escapists and more
Top Iranian official admits dire state of the economy: Report
A top Iranian official reportedly admitted that Iran’s economy is in dire straits due to the war and the U.S. blockade of the country. Mohsen Rezaei, secretary of the Supreme National Security Council and former commander in chief of the Islamic Revolutionary Guard Corps, made the admission Saturday at a high-level government meeting focused on […]
Jobs in health care. Jobs for women. The US labour market is segmenting. Chernobyl’s radiation and Lenin’s love of literature.
Thank you for opening your Chartbook email. Elmer Bischoff, Two Figures at the Seashore, 1957 The only really dynamic job-creator in the US economy is health care: The largest crunch has come in Federal government, which has shed 2.7 m jobs. Source: tchouvkov on Twitter Tech is struggling. [ Joey Politano 🏳️🌈@JosephPolitano The US tech sector continues bleeding jobs in official data released today—overall, employment decreased by 17k last month and is down 69k over the last year That's nearly as bad as the worst of the 2024 tech-cession, and much worse than the 2022 boom or even pre-2020 norms 12:42 PM · Oct 2, 2026 · 15.2K Views 15 Replies · 47 Reposts · 390 Likes ](https://x.com/JosephPolitano/status/2106001807847940232?s=20) The new jobs are all for women. [ Justin Wolfers@JustinWolfers I'm not sure who saw this coming, but so far nearly all the jobs created during the second Trump administration have gone to women. 1:09 PM · Oct 2, 2026 · 33K Views 70 Replies · 146 Reposts · 644 Likes ](https://x.com/JustinWolfers/status/2106008723533533601?s=20) Meanwhile, real wages are being eaten up by modest over-target inflation. [ Heather Long@byHeatherLong The financial pain is real: Wage growth fell to 3% (y/y) in September. That's the lowest in 5 years. Wage growth: 3% Inflation: ~3.4% Inflation has eaten up all wage gains for the average worker since April. Many people are having to make hard choices about what to buy and what … 1:24 PM · Oct 2, 2026 · 37K Views 24 Replies · 275 Reposts · 533 Likes ](https://x.com/byHeatherLong/status/2106012367712620728?s=20) 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. If you are persuaded to click, please consider the annual subscription of $60. 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 Elmer Bischoff, Bathers, 1960 Americans are disillusioned with higher ed. For contributing subscribers only. Subscribe Where the Chernobyl radiation went. h/t Simon Kuestenmacher aka simongerman600 How Lenin’s love of literature shaped the Russian Revolution - Tariq Ali This, then, was the intellectual atmosphere in which Lenin came of age. His father, a highly cultured conservative, was the chief inspector of schools in his region and much respected as an educationalist. At home, Shakespeare, Goethe and Pushkin, among others, were read aloud on Sunday afternoons. It was impossible for the Ulyanov family – “Lenin” was a pseudonym adopted to outwit the tsarist secret police – to escape high culture. At high school, Lenin fell in love with Latin. His headteacher had high hopes that he might become a philologist and Latin scholar. History willed otherwise, but Lenin’s passion for Latin, and taste for the classics, never left him. He read Virgil, Ovid, Horace and Juvenal in the original, as well as Roman senatorial orations. He devoured Goethe during his two decades in exile, reading and rereading Faust many times. Lenin put his knowledge of the classics to good use in the time leading up to the October revolution of 1917. In April of that year, he broke with Russian social-democratic orthodoxy and, in a set of radical theses, called for a socialist revolution in Russia. A number of his own close comrades denounced him. In a sharp riposte, Lenin quoted Mephistopheles from Goethe’s masterwork: “Theory, my friend, is grey, but green is the eternal tree of life.” Source: The Guardian Elmer Bischoff, The River, 1953 If you’ve scrolled this far, you know you want to click: Subscribe
Here’s what Gen Z actually means by “socialism”
They’re interested. But don’t sign them up for the revolution just yet.
Juventus prepare squad’s Italian revolution as targets identified
Serie A side Juventus did improve in the Serie A after an initial roadblock in the campaign but they’re now looking to initiate an Italian revolution in the squad.Today, La Gazzetta dello Sport delv...
AI's race to transform the world before the money runs out
Never has so much cash flowed into a new technology as is pouring into AI, eclipsing the sums splurged on railways or the internet when those technological revolutions sucked in capital.
Studying Science in an Anti-Scientific Time
This Chronicle Review Deep Cut was first published in 2025. By Julianne Werlin Thanks for reading The Chronicle Review! Subscribe for free to receive new posts and support my work. Subscribe The last two decades have not been kind to science studies. Already bruised and battered by the “science wars” of the 1990s, by the 2000s sociologists of science — who had long argued that science had to be understood in its human context — were encountering the funhouse-mirror version of their own views in right-wing critiques of climate scientists. It was enough to give some prominent scholars pause. “Was I wrong to participate in the invention of this field known as science studies?” asked Bruno Latour, the most famous sociologist of science in the world, in 2003. “Should we apologize for having been wrong all along? Or should we rather bring the sword of criticism to criticism itself and do a bit of soul-searching here: What were we really after when we were so intent on showing the social construction of scientific facts?” In response, Latour proposed a change of method and attitude. Science studies, now chastened and contrite, would no longer seek to strip facts of their authority, but to enrich and enhance them. What this meant in practice was never fully clear. But his diagnosis of problems resonated, even if his solutions did not. Latour’s exercise in public hand-wringing signaled a shift in mood. By 2016, with the first election of Donald Trump, the idea that skepticism of science was a right-wing position, not a left-wing one, had become a commonplace, discussed eagerly in The New York Times. For liberals, vaccine denial during the Covid era and Trump’s second-term attacks on the funding of scientific research, covered extensively in these pages, added a new urgency to the defense of science on both practical and principled grounds. There was little appetite for a sociology or philosophy of science that emphasized the messiness and missteps of the scientific process rather than its integrity and triumphs. The distinguished historian of science Peter Dear’s new book, The World as We Know It: From Natural Philosophy to Modern Science (Princeton University Press, 2025), which seeks to tell the story of 18th- and 19th-century science for a general public, may seem comfortably remote from these bitter contests. In its 16 short chapters, Dear draws swift, sure sketches of major discoveries from Newton to Einstein, ably guiding the reader through debates on stellar nebulae, animal taxonomy, atomic chemistry, evolution, and other flashpoints in the history of science. But though a work of history, Dear’s book must still negotiate our polarized present. In a blurb on its back cover, the historian of biology Lynn K. Nyhart alludes to the “present moment, when scientific knowledge is being swamped by misinformation and its institutions are under siege.” Dear himself, in his conclusion, refers to the “yard signs” and “bumper stickers” that proclaim “Science Is Real.” One antidote to both anti-science propaganda and to reductive slogans in science’s defense is a robust history and philosophy of science: exactly what Dear’s scholarship has long offered. But his new book illustrates how difficult such work has become. Dear, an emeritus professor of history at Cornell University, is best known as a creative and philosophically minded historian of the Scientific Revolution. His edited volume The Literary Structure of Scientific Argument (1991) analyzed the rhetoric of Galileo’s thought experiments to brilliant effect. Discipline and Experience: The Mathematical Way in the Scientific Revolution (1995) was a major contribution to the analysis of scientific experiments in early modern Europe and beyond, while Revolutionizing the Sciences: European Knowledge in Transition, 1500-1700 (2001), now in its third edition, remains one of the best overviews of the profound epistemological upheavals of 16th- and 17th-century science. But Dear has also ventured into later periods. Nearly two decades ago, in The Intelligibility of Nature: How Science Makes Sense of the World (2006), he turned to the 18th and 19th centuries to sketch a history and theory of scientific knowledge. Aimed at a generalist audience, Dear’s simple prose belied serious philosophical ambitions. Science, Dear argued, has two aspects: “natural philosophy,” the quest to understand the true nature of the universe, and “instrumentality,” the applied skills and technologies that allow us to manipulate the world for human advantage. Both strands are ancient, but the innovation of the phenomenon we call “science” was to yoke them together. As Francis Bacon wrote, “Human knowledge and human power meet in one; for where the cause is not known, the effect cannot be produced,” an insight typically abridged to “knowledge is power.” Or, in Bertrand Russell’s characteristically blunt phrase, science has two functions, “1. to enable us to know things, and 2., to enable us to do things.” So far, so conventional. But Dear took issue with this familiar story in one respect. Bacon’s formula implied that theory and practice could be fused in a single method. In fact, Dear argued, the quest to understand nature and the desire to manipulate it were coupled only loosely. They could come together, but they could also pull apart. Focusing on natural philosophy, the “knowing” half of the scientific circle, he used a series of case studies from cosmology, taxonomy, chemistry, electromagnetism, and quantum theory to show how theories changed over time, in dialogue with practice, but never reducible to it. Take the case of matter, the basic substrate of the physical world. In the 18th and 19th centuries, scientists not only disagreed about what it was, but also about how well it could be known. In 1789, the chemist Antoine Lavoisier dismissed speculation about the atomic composition of chemicals as “discussions entirely of a metaphysical nature,” as he sought to orient chemistry away from philosophical abstraction and toward laboratory results. But in the 19th century, atoms returned with a vengeance in the atomic chemistry of John Dalton, who wanted to explain the underlying structure of nature. It was not just that Dalton and Lavoisier had a different set of experimental results, or even a different theory, Dear showed. What counted as an explanation had changed. In arguing that scientific theories depended on their intelligibility to human beings with complex arrays of beliefs and commitments, Dear was in sympathy with science studies. Key figures such as the sociologist Steven Shapin emphasized the importance of psychological mechanisms like trust in the formation and acceptance of scientific ideas. But in focusing on the scientific pursuit of knowledge, not its politics or economics, Dear resisted the more cynical perspective of some of his colleagues. The Intelligibility of Nature strikes a very different note than Shapin’s collection of a few years later, Never Pure: Historical Studies of Science as If It Was Produced by People With Bodies, Situated in Time, Space, Culture, and Society, and Struggling for Credibility and Authority (2010), to name just one example. Walking a very fine line, Dear depicted science as driven at once by complex social dynamics and by the intellectual power of real discoveries. It was a testament not only to his own acumen but also to the vitality of the field that he was able to do so. Nearly two decades later, The World as We Know It returns to the questions broached in The Intelligibility of Nature. Like Dear’s earlier study, it begins with the Newtonian cosmos and ends with debates between Einstein and Bohr on quantum physics. Beyond its terminal figures, many of the same characters appear in both studies, including the naturalists John Ray and the Comte de Buffon; the chemists Étienne François Geoffroy, Antoine Lavoisier, and John Dalton; as well as Charles Darwin and Michael Faraday, among others. Its subject is nearly identical: As in The Intelligibility of Nature, The World as We Know It considers natural philosophy as opposed to instrumentality, here defined as the “desire to create a picture of what the world is really like — the world as God knows it — rather than simply having instrumental or operational control over it.” The two books also overlap in insights — and sometimes even in language. The reader who has learned in The Intelligibility of Nature that Buffon’s method of classifying animals “reflected his belief in the importance of the senses and empiricism in learning about nature (a doctrine associated with Newton and the philosopher John Locke)” will experience a sense of déjà vu on reading, in The World as We Know It, that the classification “reflects Buffon’s commitment to the epistemological stance of Newton and his philosophical underlaborer John Locke, who stressed the role of the senses in creating natural knowledge.” Later in the passage, we read that, “because of its stress on understanding the ways of life of animals in their environments, Buffon’s approach could almost be labeled (anachronistically) as ‘ecological.’” And again, “an anachronistic way of putting it would be to say that Buffon recommends an ecological mode of understanding.” Likewise, in The Intelligibility of Nature we read of Dalton that he was initially drawn to meteorology, and that: He did a bit of experimental work on these things, especially having to do with the water-holding capacity of gases, but his real interest lay in understanding what, at an underlying natural-philosophical level, was really going on physically.” Whereas, in The World as We Know It: He did experimental work on these things, especially concerning the water-holding capacity of gases — although not at a very refined level quantitatively — but he was continually trying to develop a theoretical conception of what was happening physically. The final full chapter of each book closes on the same resigned note. Intelligibility: These days, most serious work on the natural philosophical underpinnings and implications of quantum mechanics is performed not by physicists but by philosophers of science. Among scientific practitioners themselves, Bohr’s attempt to use instrumentality as sufficient grounds for a respectable science has met with a high degree of success. And again, in The World as We Know It: Bohr’s and Einstein’s concerns are now questions that are mostly discussed by philosophers of science rather than by physicists themselves. The marginalization of these sorts of questions amounts to the demise of natural philosophy, at least in physics, in the 20th century. Quantum mechanics “works,” and that’s good enough for most scientists who encounter it. Examples could be multiplied. When handling the same subject matter, some echoes are inevitable. Scholars should not feel that because they have written “Isaac Newton died in 1727” in one book, in the next they must describe him as perishing, expiring, or meeting his maker. But the repetitions of language and arguments (not to mention six reproduced images) threaded throughout The World as We Know It are more extensive than that. They should have been caught by Princeton University Press or its reviewers, and revised. Because the two books have so much in common, it is easy to see where they diverge. The World as We Know It is a less theoretical work than its predecessor. The sociology of knowledge that organized The Intelligibility of Nature has been reduced in scale and folded into readings and examples. The taut interplay between history and theory, which gave the earlier study so much interest, is there, but it is subtle. In the earlier book, the case studies demonstrated theoretical claims about the character and development of science. In the later work, each narrative of discovery is an end in itself. Insights emerge from the history, but they do not control the organization of the study. With the theory muted, it can be hard to understand the logic uniting Dear’s sprawling history of more than two centuries of scientific knowledge. The 16 brisk chapters cover an enormous amount of material. But the closer the volume edges to comprehensiveness, the more obvious the missing elements become. A chapter on “Institutions and Pedagogy,” describing the birth of the research university, illustrates the problem. Inserted roughly halfway through the book, the unnumbered chapter is designed as an “entr’acte,” in acknowledgement that it does not fit the study’s organization around scientific discoveries. Yet as Dear is well aware, no general history of the development of modern science can bracket its 19th-century institutionalization and professionalization. It was the 19th-century university, after all, that gave us the “scientist,” a term coined by the Cambridge philosopher William Whewell. Dear’s history of scientific discoveries implies a wider social and institutional history, but it remains largely subterranean, only occasionally extruded under the pressure of the narrative. It must be said that the balance is not all on the side of the earlier study. There are some advantages to the more historical, less theoretical organization of The World as We Know It. Dear’s accounts of paradigm shifts are remarkably lucid, no small accomplishment given that they span fields and centuries. He makes excellent use of the wealth of new scholarship on Darwin and his influences, to which he has himself contributed. It is satisfying to see puzzle pieces from Buffon’s natural history, Georges Cuvier’s animal taxonomy, Thomas Robert Malthus’s demography, and Charles Lyell’s geology recombined seamlessly in the Darwinian jigsaw. Likewise, Dear’s discussion of stellar nebulae, divided between chapters two and 15, shows vividly how Newton, Kant, Herschel, and Hubble reimagined insights and observations as they sought to discover whether the diffuse light that filtered through early telescopes was a glowing, gaseous substance or discrete but distant stars. Yet despite such pleasures, the book remains a more modest work than The Intelligibility of Nature. Dear has clearly not changed his views about the history of science. But in the two decades that have elapsed, the discipline and the world around it have changed, making it harder to write a sociologically and philosophically ambitious history of science for the general reader. That is a shame, because in the age of Silicon Valley and biotechnology, both the reciprocity and the tensions Dear identified between the epistemological and instrumental ambitions of science are more evident than ever. In recent years, some of the most exciting new books on the history of science in early modernity have focused precisely on this pressure point. Important studies such as Pamela H. Smith’s From Lived Experience to the Written Word (2022), James Poskett’s Horizons: The Global Origins of Modern Science (2022), and Vera Keller’s The Interlopers: Early Stuart Projects and the Undisciplining of Knowledge (2023) all shed new light on how early modern science negotiated the relationship between its instrumental and epistemological ambitions, or in Russell’s phrase, knowing and doing. There is every opportunity for a philosophically informed approach to draw new insights from this wealth of material. Dear, unfortunately, has not done so in The World as We Know It. But for future scholars of the history of science, his body of work over nearly four decades may provide just the model. Julianne Werlin is an associate professor of English at Duke University. Thanks for reading The Chronicle Review! Subscribe for free to receive new posts and support my work. Subscribe
PBS doc 'Asco: Without Permission' on L.A. Chicano artists
The documentary 'Asco: Without Permission' premieres on PBS on Oct. 2. It follows the '70s and '80s East L.A. revolutionary art group Asco and the next generation of L.A. Chicano artists.
Verana Health Introduces Significant Data and AI Enhancements to Support Ophthalmologic Research and Treatment Optimization
/PRNewswire/ -- Verana Health®, a digital health company dedicated to revolutionizing patient care and clinical research through real-world data (RWD),...
Coloradans’ revolution against the two-party system
Our major Colorado news outlets have been desultory, even derelict, about reporting on a revolution in our electorate. The result is voters don’t get the information they need to consider the full range of substantive candidates. Here are the numbers. As of September, unaffiliated voters make up 51.8% of Colorado’s registered voters. Voters 18 to […]
Scientists Just Discovered Millions of Ancient ‘Batteries’ Hiding on the Bottom of the Ocean
They could herald an energy revolution—but may come with a big risk.
New Cancer Drugs Are Revolutionary. Why Don’t More Patients Get Them?
Targeted gene therapies are highly effective at stopping cancers, but the very abundance of the treatments, plus cost and sluggish change, are hindering access.
'Revolutionary scenario' - German women's Bundesliga mulls play-offs
The German women's Bundesliga is considering introducing play-offs for the championship, promotion and relegation after launching the sale of media rights for the first time since announcing a split from the German Football Federation. The split will fully come into force at the start of next season and the Bundesliga has issued TV rights tenders including a "revolutionary scenario" featuring play-off games for the first time.
Today’s Papers – Pride and redemption as Italy bounce back
La Gazzetta dello SportRonaldo’s sunset: he finds himself on the benchFlower of ItalyAzzurri relaunch, goals and beautiful playing style in TurkeyThe revolution works. Pio and Seba Esposito together...
Leader: Enemy’s Hoped-for Past Will Never Return
TEHRAN (Tasnim) – Leader of the Islamic Revolution Ayatollah Seyed Mojtaba Hosseini Khamenei said the era Iran’s enemies seek to restore has ended forever, stressing that Iran has moved from dependence and humiliation to independence, strength and a prominent position in the Islamic world.
IRGC Reaffirms Commitment to Resistance Path on Nasrallah’s Martyrdom Anniversary
TEHRAN (Tasnim) – The Islamic Revolution Guards Corps reaffirmed its commitment to the path of Hezbollah late Secretary General Sayyed Hassan Nasrallah, saying his legacy continues to strengthen the resistance front and Lebanon’s Hezbollah.
‘The Régis Revolution’: Assessing Le Bris’ Impact At Sunderland
Calm, measured and charismatic…just how impactful has our French gaffer been at the Stadium of Light?
IRGC Navy Seizes Second US Military Underwater Drone
TEHRAN (Tasnim) – The Islamic Revolution Guards Corps (IRGC) Navy said on Sunday that it has seized a second underwater remotely operated vehicle (UROV) belonging to the US military in the Strait of Hormuz.
Maha split shows all is not well with Kennedy’s US health revolution
Republicans worry Make America Healthy Again is an electoral liability while activists claim it has abandoned its values
Revolution’s win streak snapped in loss to Real Salt Lake
Sergi Solans scored two goals for RSL to beat the Revolution, snapping its own 13-game winless skid on Saturday.
Intel Panther Lake Teardown, 18A, BSPD, GAAFET, SemiAnalysis STEEL
Panther Lake debuts the first commercial implementation of backside power delivery (BSPDN), introduces Intel’s first iteration of gate-all-around (GAA) transistors, and showcases their advanced packaging capabilities with its Foveros-S assembly. With Panther Lake, Intel’s manufacturing arc has shifted from nebulous roadmaps to shipped silicon, a significant milestone on their long road back to competitive semiconductor manufacturing. To evaluate the extent of Intel’s comeback, we tore down Panther Lake. The SemiAnalysis STEEL teardown lab breaks down advanced datacenter and AI hardware. To learn more about our pipeline or to commission a teardown, contact sales@semianalysis.com. WE’RE HIRING: Architecture, floorplan, packaging, manufacturing, and labs experts. Opportunities from system to transistor and everywhere in between. Check out our Careers page. Our teardown traces 18A from its four-sheet RibbonFETs (Intel’s marketing name for GAAFETs) and gate stacks through contacts, frontside and backside wiring, and the bonded carrier. We explain how these material and integration choices improve gate control and reduce resistance, while adding capacitance, thermal resistance, and process complexity. Our measurements put Panther Lake’s 18A compute logic and TSMC N3E GPU logic at similar logic density. However, 18A does not lead TSMC N3P, N2 or Samsung SF2 in peak density. Panther Lake’s CPU cores are incremental updates, and the high-end GPU still uses TSMC N3E. Panther Lake assembles one compute tile, one GPU tile, and one I/O tile atop a passive base tile using Intel’s Foveros-S advanced packaging. Both compute tile variants use Intel 18A. The Xe3 GPU options are a 4-core GT1 tile on Intel 3 and a larger 12-core GT2 tile on TSMC N3E. Both I/O tile variants use TSMC N6. [1], [2] Our analysis centers on the PTL-U compute tile, both the 4-core and 12-core GPU tiles, as well as the 12-lane I/O tile. In conventional chips, power and signal are routed through the same frontside metal stack towards the device frontend. Power rails consume scarce routing resources near the transistors, while tall via stacks carry VDD and VSS from the coarse upper wires to local rails. Backside power delivery (BSPD) moves the main power network behind the transistor layer, to the backside, separating it from frontside signal routing. We covered BSPD and its impacts in 2024. [3], [4], [5] Intel’s BSPD implementation, branded as “PowerVia”, routes power through dedicated backside metals to nano-TSVs, which connect those rails to local source/drain (S/D) contacts. Implementing that separation requires Intel to build the interconnect stacks from both sides of the wafer. The frontside comprises the M0-M14 signal stack, while the backside comprises the BM0-BM5 power stack. M0 and BM0 are closest to the transistors. The nano-TSVs connect the two sides, but Intel patterns and etches each via from the front after forming the contacts. A narrow via runs from the side of the contact deep into the silicon substrate. Intel then completes the frontside signal metal stack, bonds the wafer to a carrier, flips it and removes the original substrate until the buried via tips are exposed. The backside metal stack is then deposited directly on the revealed vias. The nano-TSV and backside-via profiles taper in opposite directions because Intel forms them from opposite sides of the wafer. The transistor structures form the FEOL. Local contacts and nano-TSVs connect them to the wiring. M0 begins the frontside interconnect stack. The silicon carrier remains attached above the frontside interconnects. It supports the device wafer during substrate removal and backside processing and remains part of the finished chip’s thermal path. PowerVia removes the main power distribution from the congested frontside metals, routing supply through shorter and wider backside wires. Its lateral landing still occupies area in the standard cell, so it recovers less cell area than a direct backside contact. [3] Nano-TSVs beside the logic devices carry VDD or VSS from the backside power network, while signal connections continue upward through the frontside metals. Backside Interconnects Samsung SF2 data is included for comparison to Panther Lake’s within this article. SF2 is the incumbent GAA foundry node but lacks BSPD, serving as a useful reference to evaluate 18A. A full teardown of Samsung’s S26 products, processed on SF2, will be shared soon.Nanosheet-cut EDS comparison. The PowerVia supply path runs from the backside Cu rails through Mo-lined W nano-TSVs to the local transistor contacts. In this cross section, the tapered connection spans roughly 150 nm from the contact level to BM0. The Ta liner confines Cu and promotes adhesion to the surrounding stack; the AlOₓ etch stop controls the next dielectric etch above the rail. Dielectric beneath the ribbons electrically separates the devices from the backside wiring and removes the conducting silicon body below the channel. [6] AlOₓ serves as an etchstop (ES), enabling endpointing and protecting the underlying layers. Low-volatility aluminum fluoride reaction products resist the fluorinated plasma, allowing a thin AlOₓ film to protect the metal while the surrounding low-k dielectric is removed. [6], [7]. While the BM0 and layers above the M1 lines show double AlOx layers, Our SMIC N+3 teardown showed single AlOₓ layers. SMIC uses a simpler local AlOₓ substack, while the remaining cap and etch sequence provide the required landing protection. So why double layers? The closely spaced AlOₓ doublets provide two protected endpoints in the etch sequence. Intel documents an AlOₓ/SiN/AlOₓ stack that explains the benefit. The main dielectric plasma etch stops on the first AlOₓ film; a selective wet clear opens that film; a second plasma etch removes the intermediate SiN and stops on the second AlOₓ film. The final wet clear exposes the metal landing surface. SiN is the intermediate dielectric in Intel’s published example. [8] The second stop protects the metal through a cap breakthrough. Wide openings can etch faster than narrow ones, and etch depth varies across the wafer. Metal under an early-clearing opening would otherwise be exposed while other openings still need more etching. Staged protection widens the process window and reduces metal erosion, corrosion and void formation. [8] TSMC documents AlN/AlOₓ/SiOC/AlOₓ above Cu, with AlN blocking Cu diffusion, and a simpler AlN/SiOC/AlOₓ variant that omits one AlOx film. [9] Levels with different opening sizes, aspect ratios, pattern densities and cap materials need different etch margins. A double AlOx stop is useful where another protected endpoint justifies the added processing. The extra film adds formation, selective opening and cleaning steps, plus another set of interfaces to control adhesion, moisture, and stress. These blanket films are opened through the existing via pattern, so each film does not require another lithography mask. AlOₓ adds parasitic capacitance when it replaces lower-k dielectric; two thin AlOₓ films can nevertheless contain less AlOₓ than one thick film. Total thickness, placement, and theintermediate dielectric determine the electrical cost. Deposition chemistry also changes AlOx permittivity and residual hydroxyl content, which can oxidize the underlying metal. [7], [8], [10], [11] The backside stack separates into relatively fine BM0-BM2 wiring near the devices and coarser BM3-BM5 power distribution. The largest pitch increase occurs between BM2 and BM3. BM0’s pitch closely matches the logic-row height, fitting local power delivery to the cell rows. Higher levels aggregate current through larger conductors: routing density becomes less important than low resistance and current capacity as the network approaches the package. This hierarchy provides wide power wiring for the power delivery network without consuming scarce frontside signal-routing resources. [3] The SemiAnalysis STEEL teardown lab breaks down advanced datacenter and AI hardware. To learn more about our pipeline or to commission a teardown, contact sales@semianalysis.com. WE’RE HIRING: Architecture, floorplan, packaging, manufacturing, and labs experts. Opportunities from system to transistor and everywhere in between. Check out our Careers page. Frontside Interconnects Intel 18A combines Mo-lined W contacts and nano-TSVs with a separate backside Cu power network. Samsung SF2 keeps power on the frontside, using Ti-based contact interfaces and Ta-based barriers and Co liners around Cu wiring. In 18A standard-cell rows, backside power rails supply the devices through nano-TSVs within the cells, freeing frontside routing resources. Samsung’s M0 accommodates both power and signal connections. From the device toward M0, the connection runs through a Ti-based S/D interface, W contact fill, a Mo-lined W via, and the Cu M0 wire. Mo supplies a conductive nucleation and adhesion layer for W, replacing the resistive TiN liner used in conventional W integration. This increases the effective conduction volume within the feature while retaining W fill and its established polishing, cleaning and etching processes. Intel’s Mo/W patent describes this integration tradeoff. The nano-TSV uses the same Mo-lined W construction in the backside supply path. [12] The move from TiN to Mo is an incremental change. While a full Co or Mo fill can also reduce the volume lost to liners in very small features, it requires new integration schemes that increase complexity and risk. Cu remains attractive for wider wires due to its low resistance. As wires and vias shrink, the diffusion barrier consumes an increasing fraction of their cross-section. [12], [12], [14] Intel uses Co/Ru liners at M0-M1, Co at M2-M4, and Nb at M5-M9. The lower-level liners help Cu adhere and reduce void formation during trench fills. Applied Materials’ Endura has new thermal control that facilitate wetting process, so the thin film continuity is good enough that good capillary pressure will drive Cu atoms to the via bottom without voiding. Intel’s choice to use Nb is particularly interesting. Intel’s Nb patent describes a conductive diffusion barrier intended to reduce the barrier’s contribution to resistance relative to conventional Ta-based barriers, particularly at via bottoms where all current crosses the barrier. The patent pairs Nb in coarser levels with the option of lower-cost PVD processing. [15], [16] The upper metal layers support thicker barriers formed through physical vapor deposition (PVD) despite its worse coverage and uniformity. Meanwhile, the lower metal layers require thinner barriers deposited through conformal atomic layer deposition (ALD). Co/Ru adds another material interface and requires controlled deposition and Cu fill. Changing liners and barriers by metal layer allows Intel to optimize interconnect resistance, process complexity, and reliability. [15, 16] RibbonFET, Intel’s name for its gate-all-around FETs (GAAFETs), replaces the FinFET’s vertical fins with four stacked horizontal silicon nanosheets, allowing the gate to surround the channel on every side. The path to GAAFET begins with the planar transistor. A planar MOSFET places the gate above the channel between its source and drain. Pairing an NMOS with a PMOS transistor creates a CMOS inverter, in which the NMOS pulls the output low for a high input, and the PMOS pulls it high for a low input. The gate must retain electrostatic control of the channel to ensure clean switching. As gate lengths shrank, the drain began to compete with the gate for that control, increasing off-state leakage. Electrostatic control was restored through an architectural evolution that raised the channel into a vertical fin and wrapping the gate around three sides. Called “FinFET”, this new architecture packed more effective channel width into a smaller footprint. Further scaling made it harder to maintain both drive current and leakage within smaller cells, and reintroduced the same problems planar MOSFETs faced. Nanosheet GAAFETs close the fourth side by replacing the vertical fin with a stack of horizontal nanosheets, each surrounded by the gate. The tighter electrostatic control suppresses leakage at shorter gate lengths while stacking adds effective channel width within the cell footprint. In a FinFET process, channel width changes in discrete steps as designers must add or remove whole fins. Nanosheet width can instead be adjusted continuously within the process’s design rules. Wider sheets increase drive current, while narrower sheets reduce capacitance at the cost of drive current. Intel 18A uses stacks of four nanosheets each and varies their widths across logic and SRAM. At the process level, adding more sheets to each stack increases effective channel width and drive current, but complicates fabrication. RibbonFET vs MBCFET Samsung began GAAFET production in 2022 with SF3E, following with SF3 and now SF2. Its ‘MBCFET’ provides a useful structural comparison with Intel’s first RibbonFET implementation. [17] STEEL is digging deeper into SF2, used in the Exynos 2600, and TSMC’s GAAFET N2, used in Apple’s A20 Pro, in upcoming newsletter articles. We’re throwing some teasers on X. Let’s compare Samsung SF2’s MBCFET with Intel 18A’s RibbonFET. Subscribe Even to the untrained eye, Intel’s extra nanosheet is obvious. Intel stacks four ribbons to Samsung’s three. Samsung’s sheets are much wider in these fields, so both sheet count and width matter to the available channel perimeter. Sheet width also changes which silicon surfaces carry current. On conventional (001) silicon, wide nanosheets emphasize the broad top and bottom surfaces, favoring electron transport; the larger sidewall contribution in a narrow sheet favors hole transport. Thinner sheets improve gate control but increase confinement and scattering. This makes width and thickness part of the NMOS/PMOS balance, alongside strain and threshold voltage. [18], [19] GAAFET designs like 18A use different work-function-metal (WFM) stacks for NMOS and PMOS. Around each ribbon, a thin SiOx interfacial layer separates the silicon channel from the HfOx high-k dielectric, with La providing dipole tuning and the WFM wrapping the dielectric. NMOS uses a TiAl-based stack, while PMOS uses TiN WFM. W fills the remaining gate trench, providing a lower-resistivity path where the work-function layers are no longer needed. In this field, the PMOS stacks leave room for W between ribbons, while the NMOS stacks occupy more of those gaps. A silicon-based dielectric marks the P/N boundary, allowing the PMOS and NMOS gates, sharing the same gate trench, to be processed sequentially. Fast logic paths, retention circuits, and SRAM need a family of threshold options. Changing threshold without substantially changing device dimensions, capacitance or fabrication complexity is valuable. FinFET processes typically use different work-function-metal stacks. In a four-ribbon GAA stack, the narrow sheet-to-sheet gap limits how much WFM can fit around each channel. La in the gate dielectric creates interfacial dipoles at the SiOx/HfOx boundary, shifting effective work function and tuning threshold voltage. This gives Intel another control alongside its NMOS and PMOS WFM stacks. Low-threshold devices improve critical-path drive; higher thresholds reduce leakage elsewhere. Dipole tuning is especially useful in GAA because it changes threshold without consuming the narrow intersheet gap with thicker WFM. Precise control of La incorporation, diffusion and interface quality has long been a challenge, limiting viability in high volume production but is now seen from every leading-edge foundry. Intel’s patent describes depositing a dipole-forming oxide above HfOx and annealing it toward the interfacial oxide before completing the work-function and fill metals. This separates threshold tuning from the space available for metal. Newer research addresses the thermal cost: imec’s 2026 dipole-middle research inserts the shifter between two HfOx depositions, shortening the diffusion path while protecting SiOx during patterning. [20], [21]Matched-cut EDS, Intel 18A (left) vs. Samsung SF2 (right). Intel retains raised source/drain epi beneath its contacts, while Samsung recesses W deep into the epi to form a V-shaped Ti-lined interface. The deeper contact increases metal-to-semiconductor area and shortens the current path from the lower sheets, reducing contact and spreading resistance. It also removes epi volume and brings the contact etch closer to the channel ends. Retaining more epi preserves the material available for strain transfer, especially from SiGe into PMOS. These geometries balance contact access against stress engineering and etch margin. [22], [23] Samsung stacks three sheets to Intel’s four ribbons, and both processes use sheet width to tune drive strength. In our Samsung cross-sections, widths range roughly from 19 to 30 nm in the NPU rows and 37 to 50 nm in the CU cell. The Samsung nanosheets taper, with the widest sheet at the bottom and the narrowest at the top. Both processes use HfOx gate dielectric and Ti-based work-function stacks, with Al in the NMOS stack. In the Samsung devices shown here, the dielectric and WFM occupy the intersheet gaps, leaving W above the top sheet. Intel’s PMOS stack leaves more room between ribbons, and W fills those gaps while the thicker NMOS stack leaves W mainly in the upper trench. Gate-stack EDS maps. The W between Intel’s PMOS ribbons provides a conductive path close to the lower gates. Where WFM fills the entire gap, the gate still surrounds the channel, but voltage reaches it through the more resistive work-function films. Thinner WFM and dipole tuning preserve room for low-resistivity fill; Mo and Ru are alternative fill metals being developed for further scaling. [24] A masked, sequential WFM flow explains the different gate heights and inter-nanosheet fill. The proposed sequence below shows how separate NMOS and PMOS work-function steps produce that geometry. Enabled by the BSPDN process, Intel replaces the dense-logic silicon subfin with dielectric, removing the parasitic conduction path below the ribbons and reducing substrate-related capacitance. A retained silicon body as in classical, non-SOI, planar and FinFET designs needs junction and punchthrough-stop engineering to suppress leakage. Dielectric isolation makes that leakage less sensitive to the subfin doping profile but adds removal and fill steps. It also weakens the direct thermal path through silicon, making the contacts, metal stacks and package more important for heat extraction. [24], [26] Fluorine is concentrated around selected Intel device structures in the maps. WF6 is a standard precursor for W nucleation and fill, while barrier films protect adjacent dielectrics from fluorine attack. Low-fluorine W processes reduce the residual-F burden. Chloride-based precursors avoid introducing F during W deposition, but require control of chlorine attack, nucleation and fill quality. The integration target is a continuous, low-resistance W path with a thin protective liner and minimal chemical damage to the surrounding stack. [20], [27], [28] The SemiAnalysis STEEL teardown lab breaks down advanced datacenter and AI hardware. To learn more about our pipeline or to commission a teardown, contact sales@semianalysis.com. WE’RE HIRING: Architecture, floorplan, packaging, manufacturing, and labs experts. Opportunities from system to transistor and everywhere in between. Check out our Careers page. We measured cell height, gate pitch, metal geometry, and ribbon dimensions at the XTEM sites shown below. The tables group these dimensions by site and device polarity. Our “sheet cuts” cross the silicon channel and show the ribbons end-on. “gate cuts” run along the channel through successive gates. The 18A logic cell dimensions point to a five-track logic library while the N3E and Intel 3 cell dimensions evidence a seven-track logic library. The DDR-PHY uses wider M0 wires and much larger spacing than core logic. That trades routing density for lower wire resistance and weaker coupling between neighboring nets. The geometry suits the current delivery and coupling requirements of analog, clock, and I/O circuitry. PowerVia lets 18A combine a compact cell height with wider M0 geometry by moving the main power rails off the signal-routing tracks. That relaxes local wire scaling while preserving a small cell footprint. Cell height and gate pitch set the geometric density; pin access and routability determine how much of it a real block can use. [29] The biggest takeaway from our gate-pitch measurements is that Intel 18A compute logic and TSMC N3E GPU logic have similar density in the Bohr representative-cell model. The 18A example is 18.6% denser than the Intel 3 GPU example. Gate pitches are nearly identical across the three sites, so cell height drives most of the difference. The Bohr model combines a four-transistor NAND2 spanning three gate pitches and a 32-transistor scan flip-flop (SFF) spanning nineteen pitches, weighting their densities 60:40. The sensitivity column shows how independently changing cell height and gate pitch by ±1 nm changes the result. This compares representative cell geometries; whole-die density also depends on cell mix and placement. The 18A P-core gives M0 substantially more metal cross section than the N3E vector engine. Treating each profile as a trapezoid gives 2.63 times the area per line and 1.84 times the area after normalization by routing pitch. The larger section reduces the geometric contribution to line resistance and lowers current density for a given current. Taller and wider wires also add capacitance, so circuit delay depends on the balance of resistance and capacitance. The DDR-PHY has less metal area per routing width than the 18A core fields, while remaining above N3E. [30] Area = height × (top CD + bottom CD) / 2, including liners. Area/pitch normalizes by routing width. Taper is the symmetric sidewall angle from vertical, with the largest angle belonging to the DDR-PHY. Compute tile The measurements show how ribbon dimensions and gate-stack geometry vary across the compute tile and between NMOS and PMOS to balance channel drive, gate load and the space needed for the dielectric/WFM stack across logic, SRAM and the DDR-PHY. Width mainly changes available channel perimeter; thickness also changes electrostatic control and carrier confinement. Gate-stack thickness then determines the space left for low-resistivity fill P-core and LP E-core logic Both the P-core and LP E-core use multiple nanosheet widths. Widths are measured on high-magnification XTEMs while wider-field images demonstrate additional width choices within the LP E-core. Multiple widths are expected even within an LP E-core. Timing-critical paths, buffers and cells with different fanout need different drive strengths. The lower-magnification fields show this width diversity beyond the sites quantified in the table. L2 and L3 SRAM GAA gives SRAM designers another way to balance the pull-up (PU), pass-gate (PG), and pull-down (PD) transistors. FinFET bitcells set device strength through fin count while GAA adds nanosheet width as a sizing knob. In a 6T SRAM cell, a strong pull-down relative to the pass-gate limits read disturbance, while a strong pass-gate relative to the pull-up improves writability. During a write, the pass-gate and write driver pull the node storing “1” below the inverter trip point. During a read, the pull-down holds the node storing “0” low. Bias, threshold voltage, mismatch and assist circuitry set the remaining margin. FinFET high-current cells commonly use a PU:PG:PD fin-count pattern of 1:2:2, a device-sizing ratio rather than a current ratio. Ribbon width lets Intel balance SRAM strengths without adding whole fins. The L2 cell uses its narrowest ribbons for PU and widest for PD, improving writability and read stability respectively. Intel’s disclosed HCC operates without assist; its denser HDC uses negative-bitline write assist. Pulling the selected bitline briefly below ground increases pass-gate overdrive so it can overpower the pull-up at lower supply voltage. That buys density and low voltage writability at the cost of boosting circuitry, switching energy, and additional voltage stress that must be controlled. [31], [32] Four rectangular ribbons give the perimeter = 8 × (width + thickness), before corner rounding. PG/PU is 1.49 and PD/PG is 1.16. The L3 structures closely resemble L2 in layout and cell height. Fewer L3 nanosheet widths are tabulated because fewer high-magnification images were available. DDR PHY The DDR-PHY trades density for controlled analog behavior and reliable off-chip signaling. It contains drivers, receivers, delay circuits, and calibration logic that set drive strength, sampling time, and voltage margin. Repeated four-sheet devices with similar widths fit the use of regular transistor units for matching and programmable drive. Its wider local wiring provides room for current delivery and separation of sensitive signals, while consuming more area than a dense core-logic grid. The layout serves the memory channel’s electrical requirements as well as digital logic density. [33] The SemiAnalysis STEEL teardown lab breaks down advanced datacenter and AI hardware. To learn more about our pipeline or to commission a teardown, contact sales@semianalysis.com. WE’RE HIRING: Architecture, floorplan, packaging, manufacturing, and labs experts. Opportunities from system to transistor and everywhere in between. Check out our Careers page. Intel 3 GPU devices Vector engine logic Intel 3’s XVE logic uses two-fin PMOS and NMOS devices with power rails in M0. Its cell height and M0 pitch give a seven-track geometry, two tracks more than the 18A logic. One-fin groups also appear among the two-fin devices. Intel 3 L2 SRAM The Intel 3 L2 SRAM uses the familiar HCC sizing pattern: one PU fin, two PG fins, and two PD fins. N3E GPU devices Vector engine logic The N3E XVE field contains repeated two-fin devices with seven-track cell geometry. N3E remains a FinFET process, giving Panther Lake a direct FinFET-to-RibbonFET comparison. N3E L2 SRAM The N3E L2 SRAM uses the same PU:PG:PD fin-count pattern of 1:2:2. Panther Lake-U follows Lunar Lake’s floorplan quite closely. Both pair 4 P-cores with 4 LP E-cores and NPU, media and display engines in similar locations. Lunar Lake also uses Xe2, the direct predecessor to Panther Lake’s Xe3 GPU. This makes Lunar Lake the most direct basis for our comparisons. Arrow Lake differs in core count and uses the older Xe-LPG GPU architecture, so we only use it where it offers a more direct component-level comparison. Compute tile Panther Lake compute-tile floorplans remain sparse even months after launch. Intel 18A’s backside metal and dielectric stack must be removed without damaging the underlying structures before a clean transistor-level floorplan can be imaged. Most published die shots hide or heavily process the background, but we are quite proud of the die shot we achieved and are excited to show the work we have done. We measured the areas of the key components on the compute tile and compared them with their Lunar Lake predecessors on TSMC N3B. These help us to capture changes in block area and compare the two chips across process nodes and designs. Our total tile areas exclude the scribe-line area. The compute-plus-GPU subtotal below uses the PTL-U compute tile and GT1 GPU; it excludes the I/O tile and passive base. Individual block areas use the boundaries marked on the floorplans The compute-plus-GPU row is recomputed from the displayed PTL-U and GT1 areas. Component rows use their stated per-region counts and are not an additive partition of the whole tile. The P-core area remains almost unchanged between Lunar Lake and Panther Lake, despite L2 capacity increasing from 2.5 MiB to 3 MiB. Arrow Lake uses the same Lion Cove core as Lunar Lake but also has a 3 MiB L2. Cougar Cove fits 20% more L2 into the same P-core area. The larger private cache keeps more of each core’s working set close to its execution units, reducing access to shared L3 and DRAM. Extra capacity adds storage leakage and lookup energy, so designers balance it against avoided lower-level accesses. The shared P-core L3 cache also shrank by 14.8%. [2] Cougar Cove combines a similar footprint with Intel’s reported power-efficiency improvements. RibbonFET’s tighter channel control reduces leakage, while PowerVia reduces supply droop and allows tighter voltage guardbands. [1] Darkmont’s four-core LP E-core cluster is 5.0% smaller than Skymont’s on Lunar Lake, with most of the reduction in its L2 regions. The 1 MiB region shrank by 8.4% and the 1.5 MiB region by 14.9%. The tag arrays also use one fewer visible row. Tags identify which memory addresses the data array holds, so rearranging them changes the cache’s layout and wiring without requiring less data capacity. [2] The LP E-cores share one L2. This pools capacity and avoids duplicating all the cache machinery, but the four cores contend for its banks and bandwidth. Their separate cluster also keeps light work away from the performance cluster and its L3, allowing that larger domain to sleep. [1], [2] Cache area includes more than the storage cells. Tags identify each line, decoders select rows, sense amplifiers read the small bitline signal, and wires connect to the banks. Splitting an array into smaller sections shortens wordlines and bitlines, improving access speed, but duplicates peripheral circuits. Panther Lake’s smaller cache regions therefore reflect the complete memory implementation, including how much of each region is devoted to storage. [34] Unlike Meteor Lake and Arrow Lake, Panther Lake has no separate SoC tile. The NPU, LP E-cores, memory controllers, PHYs, media and display engines now share the compute tile. This removes an active die and keeps CPU memory traffic on one die. The cost is moving PHY and I/O-related circuitry onto 18A: drivers, receivers and analog circuits must still meet external voltage, loading and signal-integrity requirements, so their area does not shrink like dense digital logic. [1], [2] The biggest shrink comes from the NPU, which occupies 36.9% less area. NPU 5 consolidates the same total INT8 MAC count into half as many neural compute engines. Each of the three NCEs has a larger MAC array to make the complete NCE envelope 22.6% larger than an NPU 4 engine. Consolidation also halves the number of scratchpads and SHAVE DSPs, from 12 to 6. The MAC array handles matrix multiplication and convolution, while SHAVE executes vector and custom operations that fit the array poorly. [1], [2], [35] The paired floorplans identify each NCE envelope and its scratchpad, MAC, and SHAVE regions. Each measured MAC polygon is counted once per NCE in the area accounting below. The scratchpads store weights, activations, and intermediate results near the MAC arrays, allowing repeated use without fetching them again from DRAM. Halving their number delivers the largest measured area saving but leaves less local storage for the same total MAC count. Layers that no longer fit locally require smaller working tiles or more transfers of intermediate data. The benefit depends on keeping the enlarged arrays busy while managing that tighter storage budget. [36] NPU 5 also adds native FP8. Using half the operand width of FP16 reduces storage and transfer demand, helping workloads fit the smaller local memory budget. Lower precision and format-dependent range make scaling and model validation part of deployment. Hardware activation functions further reduce work that would otherwise occupy the programmable DSPs. [1], [2] Microsoft requires an NPU to deliver at least 40 TOPS for Copilot+ PCs. Both Lunar Lake and Panther Lake meet this threshold, but Panther Lake uses significantly less silicon. GPU tiles Panther Lake is Intel’s first product with Xe3, its latest GPU architecture. It offers two different GPU tiles: a smaller GT1 tile with 4 Xe3 cores on Intel 3 and a larger GT2 tile with 12 Xe3 cores on TSMC N3E. Panther Lake allows us to compare the same GPU architecture across both Intel 3 and TSMC N3E. Wildcat Lake adds a third Xe3 implementation on Intel 18A. A future newsletter will detail Xe3 and its implementation differences across all three process nodes. GT2 scales Xe3 to a different physical layout, with render slices arranged vertically instead of GT1’s horizontal arrangement. Slice placement sets the distances to shared cache banks and the D2D interface. Those wires consume area and add delay, so scaling the number of Xe cores also requires a new balance of cache placement, routing and timing. [1] What’s immediately obvious is that the GT2 tile on TSMC N3E has much smaller Xe cores than GT1. These block areas include logic, caches, and routing. An Xe core on the GT1 tile is ~69% larger than one on Lunar Lake, and ~55% larger than one on GT2. Intel 3 therefore uses substantially more area per Xe core. The block-area gap exceeds the measured logic and SRAM density gaps, bringing routing, timing targets, cell mix, and floorplan allocation into the comparison. The measured vector/matrix engine region is almost unchanged between Lunar Lake and Panther Lake’s GT2 tile. Xe3 retains eight 512-bit vector engines and eight 2048-bit XMX engines per core. Its gains also come from feeding those engines more effectively: more resident threads hide stalls, and variable register allocation lets shaders trade registers per thread against the number of threads kept active. [1] The shared L1/SLM capacity increased by 33% from 192 KiB to 256 KiB, while its area increased only 5%, raising effective density by 27%. L1 retains reused cache lines, while software-managed SLM lets a thread group share data locally. Both reduce traffic to more distant memory. Allocating more SLM per group can also limit how many groups reside on a core at once. [1], [37] The GT1 tile carries 4 MiB of L2 against 16 MiB on the GT2 tile. GT1 divides its L2 cache into four 1 MiB banks, while GT2 uses eight 2 MiB banks. Each bank contains 128 macros, but each N3E macro stores 16 KiB, twice the Intel 3 macro’s 8 KiB capacity. The N3E macro is only 54% larger while holding twice as many bits, giving it 30% higher density: ~23.7 Mbit/mm² versus 18.3 Mbit/mm². Including bank-level circuitry, the gap widens to ~16.9 Mbit/mm² on GT2 versus ~10.4 Mbit/mm² on GT1. GT2 gains density with its macros storing more bits per unit area, and those macros occupy more of each cache bank. Larger macros spread decoder and sense-amplifier overhead across more storage, while a more compact bank layout reduces the share spent on control and routing. The compromise is longer wordlines and bitlines that carry more capacitance. [34] I/O tile Panther Lake uses two I/O tile variants, both fabricated on TSMC N6. The smaller one provides 4 PCIe 5.0 and 8 PCIe 4.0 lanes and serves lower-tier systems as well as those without a discrete GPU, while the larger one adds 8 PCIe 5.0 lanes, bringing the total to 20 lanes, for discrete-GPU connectivity. Panther Lake SKUs with the larger 10- or 12-Xe GPUs use the smaller I/O tile. [38] The smaller I/O tile adds a PCIe 4.0 block and a Thunderbolt block to Lunar Lake’s I/O layout, providing four additional PCIe 4.0 lanes and another Thunderbolt 4 port. Its repeated N6 blocks retain nearly identical areas and layouts. Reusing these proven PHYs and controllers avoids porting and requalifying external interfaces on 18A, where faster digital logic offers less benefit to circuits constrained by the off-chip link. [38] SemiAnalysis’s teardown lab (STEEL) dives deep into the world’s advanced datacenter and AI hardware. To learn more about our pipeline or to commission a teardown, contact sales@semianalysis.com. We’re hiring technical experts from system to transistor and everywhere in between. Check out our Careers page. Panther Lake offers scalability and modularity through its disaggregated packaging that partition compute, GPU, and I/O silicon into separate tiles allowing for a suite of tile configurations. This partitioning makes the package part of Intel’s node economics as it determines how much leading-edge wafer area each product consumes, which functions can remain on other processes, and how much configuration freedom Intel can offer from a shared set of tiles. Furthermore, fabricating the compute and GPU tiles separately confines the new 18A process to the compute tile and allows graphics and I/O to use other, more established, and more cost-effective processes. For Panther Lake, the GPU and I/O tiles are assembled alongside the compute tile on a passive silicon base using Foveros-S. Intel’s current technology brief lists a nominal 36 µm pitch for Foveros-S. Through-silicon vias (TSVs) in the base connect the fine wiring above to the larger package connections below. The functional tiles sit side by side on that passive base in a 2.5D configuration. [39] Our cross-section through the compute and GPU tiles shows the package’s wiring hierarchy. Microbumps connect each active tile to the passive silicon base; its fine redistribution layer (RDL) carries the short, dense tile-to-tile links. TSVs carry connections through the base to the package substrate, which fans them out to the much coarser motherboard solder joints. The base supplies interconnect, while computation remains in the active tiles above it. [39] At the compute-tile edge, the higher-magnification inset shows a local microbump spacing of approximately 25.24 µm and a feature width of 12.33 µm. These local spacings are finer than Intel’s nominal Foveros-S value. The X-ray fields further confirm tighter neighboring bumps, consistent across every die-to-die area found on each tile. Additional X-ray analysis is offered after the paywall. Putting the memory controller beside the CPU removes the D2D transfer that CPU memory requests required in Meteor Lake and Arrow Lake. This avoids the extra transmitter, receiver, and link traversal, saving interface energy and latency. Panther Lake’s separate GPU still crosses a D2D link to reach DRAM, so its larger local caches also help contain package traffic. [1], [40] Smaller dies are less likely to contain a random fatal defect, and screening them before assembly prevents one bad tile from consuming a complete package of good silicon. Reuse also spreads design and qualification work across more products. Against those gains, Intel pays for the passive base, D2D circuits, extra bonding and test steps, and losses during assembly. Cost per working product across the portfolio captures the combined effect of wafer yield, reuse, test, and assembly. [29] Wildcat Lake packaging Intel launched Core Series 3, formerly Wildcat Lake, on 16 April 2026 for value mobile and edge systems. Wildcat Lake keeps 18A but removes the passive base and combines more functions on one die to simplify the package. The two products therefore reveal two distinct ways to commercialize the same leading-edge process. [41] Wildcat Lake’s 18A die combines up to two Cougar Cove P-cores, four Darkmont LP E-cores, two Xe3 cores and a smaller NPU. A separate platform-controller die supplies I/O, connected through UCIe, Intel’s first processor implementation of the standard. Consolidating graphics remove a tile boundary and the passive base, reducing assembly complexity for a modest-bandwidth value product. It also ties CPU and graphics scaling to the same die, giving up Panther Lake’s ability to swap in a much larger GPU. [42], [43] In July 2021, Intel CEO Pat Gelsinger set out an ambitious process roadmap aimed at regaining performance leadership by 2025, later described as five nodes in four years. Five years and one CEO later, Intel’s comeback story is not as unambiguously positive as Pat may have hoped. [44], [45] Intel once set the pace for process technology, bringing high-k metal gate technology and FinFETs into volume production years ahead of the rest of the industry. Its 22 nm FinFET process reached consumers with Ivy Bridge in 2012. [46] Intel’s integrated device manufacturing (IDM) model allowed its architects and process engineers to co-optimize products and processes. Starting with Sandy Bridge, Intel dominated x86, while AMD struggled with Bulldozer. That lead faltered at 14 nm and broke at 10 nm. Intel targeted a massive 2.7× density increase, but the node arrived years late and required several revisions before it could support Intel’s full lineup. This delay forced Intel to stretch 14 nm across six generations, while TSMC moved ahead in process technology and AMD recovered in x86. By 2019, Intel was still shipping 14 nm across most of its product stack, with its 10 nm client ramp focused on Ice Lake mobile processors. Meanwhile, TSMC was shipping N7 and N7+, and AMD’s Zen 2 compute chiplets used N7 to raise core counts and improve efficiency. Intel’s process failures were central to its decline, but unsound business decisions furthered their downward slide. Product delays compounded product mistakes, pushing client, server, and FPGA roadmaps off schedule. Several attempts to enter AI (Nervana and Gaudi) and networking (Tofino) also failed to establish lasting businesses. Intel’s recovery has focused on consumer CPUs and advanced packaging. Tiger Lake, Alder Lake, Lunar Lake and now Panther Lake have restored Intel’s consumer roadmap. On the process side, Intel 4 shipped with Meteor Lake, Intel 3 with Granite Rapids and Sierra Forest, and Intel 18A with Panther Lake. Intel has also made advanced packaging part of its foundry offering. However, Intel is still playing catch-up in servers. Several Xeon generations arrived years late and trailed contemporary AMD and Arm server CPUs in performance, efficiency, and core count. The process roadmap is back, but Intel does not hold the same process-technology leadership position it held prior to 10 nm. The introduction of gate-all-around nanosheets and backside power delivery are two of the biggest changes to transistor integration in a decade. Intel took on both changes at once: 18A paired its first RibbonFET with PowerVia in Panther Lake. Panther Lake is a substantial manufacturing milestone. Our cross-sections show how RibbonFET and PowerVia reshape local contacts and wiring, while the floorplans show where architectural consolidation and process choices save area. A sustained competitive lead depends on product performance, cost, yield, and the next implementation. The SemiAnalysis STEEL teardown lab breaks down advanced datacenter and AI hardware. To learn more about our pipeline or to commission a teardown, contact sales@semianalysis.com. WE’RE HIRING: Architecture, floorplan, packaging, manufacturing, and labs experts. Opportunities from system to transistor and everywhere in between. Check out our Careers page.. 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Is metascience being co-opted?
In July, the White House released a report that argued academia is deeply dysfunctional and in need of radical reform.Science: A New Golden Age sets out a litany of problems many academics will recognise: interminable waits for grants; short-term funding rather than support for longer, more ambitious projects; ballooning administrative requirements; pressure to publish, and many more. “The scientific machine is getting bogged down,” it says. At least on the face of it, Science: A New Golden Age is a triumph for the metascience movement, a loose-knit, global group of academics, philanthropists and think tankers that want far more testing and experimentation in how we fund public research and innovation. The report tells US research funders to set up internal metascience units to do just this. But it has also set alarm bells ringing that metascience is being conveniently deployed to help justify the defunding of US universities, which US vice president JD Vance has openly labelled “the enemy.” “Just because you have an issue with your plumbing in your house doesn't mean you light the entire house on fire and burn it to the ground,” said Colette Delawalla, chief executive of Stand Up for Science, a group campaigning against what it says are attacks on scientists by the Trump administration. No one is arguing that academia doesn’t need reform, but there’s debate over how far and how fast the system should be shaken up. Does public R&D need slow and steady evidence-based adjustment, or radical new experiments?One of the key arguments in Science: A New Golden Age is that there’s not enough funding for what it calls “mid-level” science: engineering-heavy projects that require tens of millions of dollars, involve ten to a hundred people, and last around five years. Such a project might develop a brain-computer interface for people with Alzheimer's disease, for example. As such, the US National Science Foundation (NSF) has already announced $1.5 billion to set up so-called X-Labs, effectively new research organisations to pursue breakthroughs in areas such as quantum sensing and new scientific instruments. Funding divertedBut there’s a catch: this money has squeezed NSF budgets for more traditional, fundamental research grants, Science reported in June, likely meaning less cash for university-based scientists. Science: A New Golden Age also makes various swipes at universities, accusing them of extracting overheads from scientists to fund administrative bloat. “We have become dependent on a narrow set of legacy institutions,” it says. The report doesn’t mention it, but the US government is simultaneously seeking greater powers over federal funding, which would allow political appointees at funding agencies to screen or cancel research grants mid-project. The White House is also seeking to slash the NSF’s budget by more than half in 2027, although similar cuts proposed for 2026 were blocked by Congress. Convenient hookThis has worried some that the metascience agenda could be misused as a kind of smokescreen to further weaken universities. James Wilsdon, executive director of the Research on Research Institute at University College London, said that the report contains lots of “interesting ideas” and agrees that in places, academia is a “pretty broken system.” But the risk is that metascience is being deployed as a “convenient hook” to support cuts and a “political land grab” to transfer grant power from scientists to political appointees in US funding agencies.So far, the metascience agenda hasn’t been seized on by radical right parties in Europe. But Wilsdon worries it will cross the Atlantic, politicising research reform efforts and making them more difficult to carry out. The report is already making some in Europe sceptical of the entire idea. “The system is not without flaws, but the metascience discussion is not likely to improve the system but rather to generate munition to undermine it,” said Claes de Vreese, a professor of AI and society at the University of Amsterdam. Peter Thiel protégéOfficially, Science: A New Golden Age has just one named author: Michael Kratsios, the director of the Office of Science and Technology Policy and a former chief of staff to Silicon Valley mogul Peter Thiel. He also served as chief financial officer of Thiel’s Clarium Capital Management. Since the 1990s, Thiel has criticised US universities for moving away from teaching what he views as the classic works of western civilisation, and drifting towards “anti-Western zealotry.” And since 2011, he has offered two-year fellowships of $250,000 to young people to skip or drop out of university, and instead start companies or pursue scientific research. “College can be good for learning about what’s been done before, but it can also discourage you from doing something new,” according to the Thiel Fellowships website. In other areas, the Trump administration has promoted academics with a longstanding interest in metascience. For example, the head of the National Institutes of Health, Jay Bhattacharya, in 2020 co-authored a study arguing the funder backs overly conservative proposals, although he achieved wider prominence as a critic of pandemic lockdowns. Careless talk costs fundingEven before the Trump administration embraced the metascience agenda, some metascientists privately wondered whether they should be careful not to overstate dysfunctions in academia, in case this gets used as ammunition against universities. But others think being cautious with criticism is pointless. After all, last year, the Trump administration sought to cut funding from US universities on an entirely different premise: supposed antisemitism on campus. “I don't think these governments need a technical metascientific excuse to attack the universities, they will want to do so anyway,” said Will Stone, a researcher at Science Works, a new think tank advocating for a “metascience revolution” in the UK. “I think researchers should report what they find, even when the findings may be used to advance policies they disagree with,” echoed Russell Funk, a researcher at the University of Minnesota, who in 2023 co-authored a highly influential paper that argued scientific papers were becoming less disruptive over time. No justificationThat said, Funk thinks that metascientific research certainly doesn’t justify a weakening of universities. Instead, scientists need “time, resources and stability to pursue unfamiliar ideas,” he said. “Taking away those conditions works against the very goal the reforms are supposed to achieve.”The Institute for Progress, a Washington DC-based innovation policy think tank that has championed X-Labs and metascience units, also says that reforms should complement, not supplant, universities. “Unpredictable, unreliable, and reduced federal funding to researchers is destabilising to the very foundations of research and development and is bad,” said Jenn Gustetic, the institute’s director of metascience and R&D policy.Evolution or revolution?This points to a much bigger divide in the metascience community: how far and how fast should public R&D be shaken up? Does it need evolution or revolution? For example, Science: A New Golden Age says the science system relies too heavily on traditional “workhorse” project grants, the type that pay out around $250,000 a year to fund “hypothesis-driven science by small teams on tractable questions.” However, in criticising project grants, the report “decisively picks one side of a debate that is far from settled,” David Hilmer Rex, a metascientist based in Denmark, has written. In June, Pierre Azoulay, a metascientist at the Massachusetts Institute of Technology, defended project grants, saying that the alternative of X-Labs “merits scepticism.”A-B testingOne challenge in metascience is that it’s easier to generate evidence for some types of change than others. Most straightforwardly, research funders can run A-B tests on different ways of awarding money. For example, Germany’s Volkswagen Foundation recently trialled distributed peer review, where applicants rate each other’s proposals, and measured its results against traditional review panels. Distributed peer review made quicker decisions, although awarded money to largely different ideas. However, much of the focus of the metascience movement has been on founding fast-moving and free-acting new research organisations and funders, in contrast to the alleged stodginess of mainstream academia or public innovation grants. A culture of speed and freedom are the animating principles behind Germany’s Sprind or the UK’s Advanced Research and Invention Agency (Aria).Related articlesViewpoint: it's time to experiment with how Europe funds science European researchers sound the alarm that Trump rule changes will hit cooperationHowever, while it’s possible to closely study previously successful bodies, such as the US Defense Advanced Research Projects Agency (Darpa), for historical clues to their secret sauce, it’s impossible to guarantee in advance that the likes of Sprind or Aria will actually work as hoped. But advocates of new organisations say this inherent uncertainly shouldn’t stop us trying. “If we wait for definitive proof that something will work before we try it, I don't know where your proof is coming from,” said Stone. Trade-offsUp until now, experiments in metascience haven’t generally come with hard trade-offs over money. In the US, new ideas such as focused research organisations have often been funded by billionaire philanthropists. In Europe, new innovation agencies such as Sprind and Aria, or the Netherland’s new National Agency for Disruptive Innovation, haven’t needed explicit cuts elsewhere in the research system. But with the $1.5 billion establishment of X-Labs by the NSF, the trade-offs are becoming clearer. Some metascientists privately wonder whether a smaller pilot would have been more appropriate, given that the idea is untested. The Institute for Progress counters that the $1.5 billion X-Labs budget is spread out over a decade, so will account for less than 2% of the NSF’s annual budget. “It’s important to remember that [Darpa] was once an institutional experiment as well. Now it’s one of the most cited innovative funding models in the world,” said Gustetic.As for Europe?The US isn’t the only country placing metascience at the heart of its research strategy. Science: A New Golden Age looks admiringly at the UK, which in 2024 set up a Metascience Unit to scrutinise how it funds research. In Brussels, it’s more of a mixed picture. In 2018, the EU set up the European Innovation Council to funnel grants and equity to start-ups, although it’s sometimes criticised for awarding money too slowly. Recently, the council has started experimenting with challenges, where teams of inventors compete to overcome a technological challenge. The European Commission also wants to experiment with partially randomising grant winners, to cut down on bureaucracy. However, the Commission’s own advisers have said the EU’s own research schemes are too conventional. They want the Commission to establish a new dedicated unit to scrutinise and experiment with funding. But there’s no sign of a such unit emerging in Brussels’ plans for the next Horizon Europe programme, which from 2028 is set to distribute more than €160 billion over seven years. Sam Bogerd, director of breakthrough innovation at the Brussels-based Arq Foundation, an AI-focused think tank that also looks at metascience, says that Europe might have the opposite problem to the US: universities and basic research funding are still reasonably well supported, but there’s not enough experimentation. “We're not taking a close enough look at where this money can achieve the most, and I am worried that the good ideas around metascience will be tainted politically by their association with the Trump administration,” he said. He’s still lobbying for the Commission to set up an experimental unit. But in the meantime, the Arq Foundation plans to do its own research, and is currently hiring two metascience researchers to run the rule over how Brussels spends research funding.
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Microsoft may soon show ads during downtime moments in PC and Xbox games, similar to free-to-play mobile games.
Banqup and Post Business Solutions partner to revolutionize digital financial workflows for Austrian businesses
LA HULPE, BELGIUM – 21 September 2026, 7:00 a.m. CEST – Banqup Group SA (Euronext: BANQ) (Banqup, Company), a European fintech provider that simplifies financial flows through an innovative secured platform for e-invoicing, e-payment, e-reporting and e-trust solutions with built-in compliance at its core, announces a new meaningful collaboration with Post Business Solutions, an Austrian based leader in innovative digital and physical business process solutions. The new partnership marks a signif
Nathan Cofnas's revolution: Science, heredity, and the values of liberal society
The Jason Arday scandal broke after Cofnas ran Arday’s doctoral thesis through plagiarism detection software.
Engrams Embedding Entendre: Codesign for Efficient DRAM/SSD Offloading
Engram extends standard token embeddings with learned multi-token lookups. Recurring local patterns retrieve vectors directly, reducing the need to reconstruct them through attention and feed-forward layers. With Engram model architecture optimization, it allows for lower HBM capacity to be needed for models at the same quality. This does not mean there won’t be an insane demand for HBM but it just means that model architecture will continue to innovate around constraints. This model architecture design is naturally codesigned for parameter offloading: each token accesses a few embedding rows whose addresses depend on token IDs, not hidden states. The runtime can prefetch those rows from host DRAM while earlier layers compute, keeping the table outside HBM without transferring entire weight matrices. Our Memory model contains our latest estimates of quarter by quarter HBM, DRAM, & NAND supply and demand. Offloading frees HBM for model weights and KV cache, potentially supporting larger batches or more concurrent sessions. When DRAM becomes the next constraint, NVMe offers another tier. Recommendation systems already cache frequently or recently accessed embedding rows in faster memory while backing colder rows with SSDs. After NVIDIA roadmap had to change due to massively despec’ing Rubin Ultra from 1024GB to now ~200GB of HBM per chip, model architecture optimizations like emgram maybe helpful. Our DeepSeek-V4.1-Flash configuration uses roughly 189 GiB of memory for Engram. We replace it with a memory-mapped (mmap) file and measure serving performance with offload to SSD. Later on in our report, we will show our Engram offloading experiments along with the official InferenceX agentic inference serving results on Engram models like DeepSeekv4.1 Flash across all 6 NVIDIA GPU SKUs along with MI355X. Unsurprisingly, the CUDA Moat is still mogging MI355X on the ultra popular DeepSeekV4.1 Flash model. We also show how even on high capacity HBM SKUs, offloading emgrams to DRAM could result in even better performance for most of the pareto than keeping the emgram in HBM. Our benchmark has been widely reproduced, validated and/or supported by almost every major buyer of compute from Google Cloud to Microsoft Azure to Oracle, to Meta and many more. Furthermore, it has the support of the ML community including from vLLM, LMCache, SGLang, PyTorch, Huggingface and the support of major labs like OpenAI, MiniMax, ZAI, Qwen, Moonshot Kimi, etc. Star the InferenceX GitHub repository if you find the open-source benchmark and data useful!. InferenceX is the only inference benchmark in the world to have TPUv7, Jalapeño, Nvidia Rubin NVL72, AMD, and soon, SambaNova and Trainium. Due to how realistic AgentX scenario is to real world agentic inference workloads, AMD has committed to collaborating on MI455X UALoE72 too. DeepSeek did not release the original paper’s two trained Engram models. We replicated its setup on fineweb-edu using the released code and training hyperparameters, at an estimated 6E18 FLOPs per run. We observed the same U-shape scaling: Engram improved performance over pure MoE baselines. We also reproduced DeepSeek’s results, where earlier-layer representations with Engram resembled those of later layers. Like the original Engram paper, it is possible to probe Engram’s gate scores to see what n-grams DeepSeek-V4.1-Flash makes the most use of. Our gate scan finds names, code fragments, relational phrasing, and boilerplate. These examples prioritize interesting-ness over gate strength. One unexpected result was Wright : Ace Attorney. These examples suggest learned memory optimizes the training objective, not a judgment of which facts deserve storage. Licenses, bibliography fragments, API scaffolding, and website furniture can provide prediction shortcuts, so the value of additional Engram capacity may depend on what survives data preparation. This does not show that table capacity is “wasted”: the evaluation-corpus scan establishes neither training exposure nor the capacity occupied by each category. For offloading, strong gates do not identify cache-hot rows. Low gates do not automatically save reads either: computing the gate requires the retrieved key and undoes the performance gain of a fused kernel. Skipping reads would require a separate usefulness predictor before retrieval. In the original paper’s inference-time ablation, factual-knowledge benchmarks retained just 29–44% of their original performance, while reading comprehension retained 81–93%. This is due to the training–inference mismatch. The resulting degradation therefore measures this trained model’s dependence on Engram, not the performance difference between models trained with and without it. In our ablations, suppressing Engram worsens token likelihood across all evaluated domains, especially encyclopedia text and several code corpora. Surprisingly, GSM8K accuracy stays within measured run-to-run variation and removing Engram has no effect. Engram is not a detachable dictionary beside an unchanged MoE. Removing it changes downstream features and expert selection. We tested whether rerouting hurts or compensates by holding tokens fixed in a teacher-forced experiment on CRUXEval, a code-reasoning benchmark of small Python functions where the model predicts a function’s output from its code and an input, and scoring the reference answer. Removing Engram raised answer loss from 0.2848 to 0.3093 bits/token. Forcing the ablated model to use the original Engram-on expert choices made it worse still, at 0.3375 bits/token. Rerouting partially compensates for the missing memory. Memory features and expert selection work together, rather than following a clean “memory stores facts; experts reason” division. On the same CRUXeval, removing Engram during either phase reduced accuracy and increased generated tokens; removing it throughout produced the largest changes. Keeping Engram for prefill leads to more correct answers than keeping for decode likely due to semantically richer KV cache transferred to decode workers, allowing it to mitigate some of the performance loss. Engram’s table is large, but each lookup is small. DeepSeek-V4.1-Flash requests 24 rows at each of two Engram layers, about 12.4 KiB per processed token position across the model, or 3.1 KiB per GPU when split across four GPUs. Currently as of Day 7 since Model Release, MI355X is still 2-4x worse performance per dollar compared to B200 even when normalized by Mi355X’s lower TCO. Our full total cost of ownership breakdown comes from our AI Cloud TCO Model along with monthly market surveys of over 100+ gpu clouds & gpu cloud customers. On the Day 0 release of DeepSeekv4.1 Flash, NVIDIA vLLM works out of the box with zero issues across all 6 SKUs: H100, H200, B200, B300, GB200, GB300! This was thanks to the amazing work by the NVIDIA & Interact teams! In comparison, AMD vLLM did not work on day 0 for DeepSeekv4.1 Flash.Source: SemiAnalysis InferenceX AMD’s vLLM documentation points to using vllm/vllm-openai-rocm:deepseekv41-flash-0909, but from hour 0 of the model release to hour 23, AMD has not publicly released the image. AMD claims, “SPEED IS THE MOAT,” yet it has still not released it by the 23rd hour. We wish that, going forward, the AMD team has a better process for hour 0 model releases. Eventually when they did publicly release for “day 0” image support, performance-wise, it is currently up to 14.8x worse perf per dollar than H200 and up to 42x worse perf per dollar than B200/B300. The power of the CUDA MOAT is NVIDIA’s collaboration with its massive 6 million-developer community ecosystem including most of the vLLM & SGLang & Tokenspeed maintainers which means that CUDA is optimized on day 0. Overall, AMD did make significant improvements but the performance per dollar is still currently 2-4x worse than B200. AgentX Engram DRAM Offloading Improving Performance The HBM and DRAM offload use the same GPU kernel to select and dequantize rows. With HBM, it reads GPU memory; with Unified Virtual Addressing (UVA), it reads pinned host memory directly. Both support full decode graphs. Moving the table into HBM accelerates only the sparse lookup, leaving decoder computation and communication unchanged, resulting in little overall benefit while consuming memory otherwise available to KV cache. Another benefit of Engram offloaded to DRAM which means you can reduce the communication overhead by using less HBM GPUs per replica. For example, when enabling Engram offloading on B300, we are able to switch from TP4 to now TP2 which improves the pareto curve by up to 1.6x. When iso-model quality, less HBM is required as the engrams could be offloaded to host DRAM. Thus HBM bandwidth matters way more than HBM capacity. For inference workloads where memory bandwidth matters the most, 4-hi HBM provides the best $/bandwidth and therefore lowest cost per token. If China continues to make more and more revolutionary model architecture innovations, soon it could potentially 0Hi HBM stacks. [ ](https://newsletter.semianalysis.com/p/long-live-the-short-king-why-4-hi) [ Long Live the Short King: Why 4-hi HBM Wins ](https://newsletter.semianalysis.com/p/long-live-the-short-king-why-4-hi) Myron Xie, Bryan Shan, and 3 others · Sep 13 [ Read full story ](https://newsletter.semianalysis.com/p/long-live-the-short-king-why-4-hi) Moreover, on B300 and week-0 stack, moving the Engram table back to HBM did not improve results and stay within run-to-run variance. This is a result of the work optimizing DRAM offload, such as async, and overlap. SSD Offloading On B200, we created a unoptimized vLLM fork and stored the Engram tables in memory-mapped files on local SSDs. File backing lets the OS reclaim table pages when other applications need RAM. Pages already cached in memory can be served without reading the SSD again. Furthermore, note that we were unable to turn on GDS The unoptimized SSD implementation changes how rows reach the GPU. It copies row IDs to the CPU, deduplicates them, gathers the requested rows into pinned buffers, copies those rows back to the GPU and dequantizes them. This work runs between segments of the GPU execution graph. Native UVA performs row selection and dequantization directly on the GPU, avoiding the CPU round trip. A warm filesystem cache removes physical SSD reads, but leaves the coordination, row gathering and transfers. This is why a file already cached in RAM can still perform worse than a pinned DRAM table. The comparison measures the whole serving path; it does not separate the time spent on each of these operations. B200 DRAM dominates both measured SSD serving curves in total tokens per dollar and P90 interactivity. Near 125 tokens/s/user, DRAM delivers 121 million total tokens per dollar versus 52 million for SSD. For production serving, SSD offloading is likely not worth the tradeoff. On the B200 configurations we measured, SSD offloading loses on both measures: every observed SSD point has a DRAM alternative that delivers higher P90 interactivity and more total tokens per dollar. The only points where Cheaper storage does not automatically produce a cheaper inference service. Moving Engram to SSD leaves the same four expensive GPUs and the rest of the server in place. Reclaiming RAM only creates an economic benefit if it enables a cheaper server configuration or additional useful capacity. The current unoptimized path provides neither benefit, and the filesystem cache still consumes RAM when table pages are resident. Next we will look at the mechanisms and specific implementation of ngrams from DeepSeekv4.1 Flash, LongCat, Qwen3.8 Flash Next.
Guest Post — The Quantum Inflection Point: Charting a Science-First Roadmap for the Nation
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Helio and You: A Fresh Perspective on the Sun
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Assassination of Sunni Cleric Shows US, Israel’s Frustration: IRGC Chief
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Steuben Players plan Revolutionary War comedy
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Webinar Highlights from the "Unfinished Revolution: Social Movements, Freedom Struggles, and American Democratic Development" -
In the APSA Public Scholarship Program, graduate students in political science produce summaries of new research in the American Political Science Review. This piece, written by Deborah Saki, covers the webinar highlights from “Unfinished Revolution: [...]
Steam Frame: The Ars Technica review
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Peyton Miller stars in huge New England Revolution win
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The Benefits And Risks Every Business Leader Needs To Understand About AI
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The Benefits And Risks Every Business Leader Needs To Understand About AI
Businesses that consciously embrace AI, seizing its revolutionary advantages while skillfully and strategically handling its risks
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Letter: Rural representation in Deschutes County politics
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NMSU FIRE Venture Fellow completes summer internship with El Paso health innovation startup
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Can true horror really make it on Broadway? A stage version of ‘Paranormal Activity’ hopes so
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Can true horror really make it on Broadway? A stage version of 'Paranormal Activity' hopes so
Movie producer Jason Blum, known for revolutionizing horror films, praises a stage adaptation of his “Paranormal Activity” franchise | 830 WCCO
Can true horror really make it on Broadway? A stage version of 'Paranormal Activity' hopes so
Movie producer Jason Blum, known for revolutionizing horror films, praises a stage adaptation of his “Paranormal Activity” franchise.
Why Is China Betting Billions on a Secret Science Almost No One Knows? - Futura-Sciences
The Silent Quantum Revolution In the shadows of headline debates about semiconductors and artificial intelligence, a quieter, subtler scientific revolution is underway between global superpowers. In the spring of 2025, China unveiled its ambitious strategy to dominate quantum metrology—the ultra-precise science quietly governing our technological world. This marks a frenetic...
AI optimism vs. anxiety — podcasters debate this every night
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The Pixel 11 Pro should be a disappointment, but after 3 weeks with the phone I can't put it down
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Gloria Steinem appreciation: Celebrating a rock star of revolution
Gloria Steinem always listened more than she spoke, which is one reason her words had such lasting impact.
Life evolved thanks to an giant poop explosion, say scientists
This so-called ‘faecal revolution’ could have been key for the emergence of life on Earth as we know it, according to a recent study
Newcastle 2.0 Underway After Transformative Transfer Window
Matthias Jaissle’s tactical revolution takes shape at St James’ Park as marquee signing Matias Fernández-Pardo headlines a ruthless squad overhaul built on youth, intensity, and strategic identity.
How Small Businesses Are Quietly Leading a Retirement Revolution
Retirement benefits can send a signal to employees that you’re building something more than a business — you're building something that lasts.
One flash of red light could check health of bioprinted tissue and implants
Using 3D printers to create complex structures from biocompatible materials that can include living cells has the potential to revolutionize medicine. This process—3D bioprinting—has powered breakthroughs ...
US military carries out new strikes on Iranian targets
The US military conducted additional strikes against Islamic Revolutionary Guard Corps targets in Iran on Tuesday, in response to recent attempted attacks against commercial shipping in the Strait of Hormuz and American troops deployed to the region, according to US Central Command.
How Innovation Could Reshape Chemistry by 2050
Chemistry and chemical engineering are fundamental to technologies that could revolutionize energy production, quantum computing, and materials and manufacturing over the coming decades. At a recent workshop, participants from academia, industry, and government considered the future of the chemical sciences, exploring scientific challenges that researchers should prioritize, where strategic investments could enable breakthroughs, and how the chemical sciences community can prepare for emerging capabilities.
FDA approves once-daily pill for deadly cancer after patients' survival rates nearly double
Revolution Medicines' Rasonque targets the RAS protein driving 95% of pancreatic adenocarcinoma cases, offering a critical option after chemotherapy fails.
Alfred University faculty, students, and alumni among team to win prestigious research award
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Secret Service says it is aware of Iranian state media video threatening Barron Trump
The footage, reportedly released by media linked to Iran’s Islamic Revolutionary Guard Corps, claimed a $10 million bounty had been placed on the president’s youngest son.
American revolution 2.0: how Trump has changed the US, and why it was powerless to stop him
Trump defies all we thought we knew about the US political system and the way electoral democracies work around the world.
Transistors Changed Everything. Here’s How They Work
How a tiny little electronic switch sparked the computer revolution.
AMD Ryzen 7 5800X3D 10th Anniversary Review
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Impinj Set To Revolutionize Logistics With Tracking Chips. CEO Eyes 'Gigantic Opportunity.'
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High touch, not merely high tech
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Experimenting with Science and Structure in Government
"What excites me is that it's very tempting to be very discouraged, and say, ‘Oh, we've got these archaic institutions that are calcified and you could never change them.’ But I think we're in the middle of a technological revolution that will upend lots of things, and does provide a window."
Tommy John, Dr. Frank Jobe changed sports and medicine
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Center-right politics between two revolutions
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ICYMI: here's the week's 7 biggest tech news stories from the Google Pixel 11 launch to Honor's revolutionary Robot Phone
Here's your firmware update for August 15, 2026
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The AI takeover of mathematics has begun
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Insight: US fuel sales to Cuban business bring a glimpse of capitalism to Havana
Gasoline at $38 a gallon sold from cramped apartments. Diesel hawked on Instagram by a celebrity model to a reggaeton soundtrack. Six decades after Fidel Castro’s revolution, all of a sudden, capitalist cracks are appearing in Cuba’s communist energy sector.