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Science Writer Takes Aim at Many Universes Theory
What these speculations point to is the way new findings have destroyed classical materialism. Materialism isn’t so much dying out as breaking up.
Private clubs cost thousands to get in
If the walls of The Sloane Club could talk, they probably wouldn’t stop. The private members’ club, founded in 1922 by one of Queen Victoria’s daughters, has witnessed a great deal of history in London’s ritzy Chelsea district.
A Watch Brand Focused on Mental Health
Every sale since Split debuted in mid-2025 has generated a donation equivalent to the cost of an hour’s therapy, its co-founder said.
Apple plans to change its Hide My Email privacy feature that could make it less effective
In the coming weeks, Apple will move anonymously generated emails addresses to a different domain.
Evers celebrates record-breaking tourism year at bike shop in West Bend
The annual report, released earlier this month, showed the state generated $27 billion in economic impact.
Sign in with Apple and Hide My Email are getting a new shared email domain
Apple announced today that it will soon use a single shared domain for private email addresses generated by Sign in with Apple and iCloud+ Hide My Email.
Scientists just found a hidden weakness in forever chemicals
Researchers discovered that hydrogen radicals generated by intense UV light can break down stubborn PFAS “forever chemicals” without added chemicals. The breakthrough reveals a key mechanism that could lead to greener and more effective technologies for permanently destroying these pollutants.
Apple to Unify Sign in With Apple and Hide My Email on One Domain
Apple is planning to unify the email domains used by Sign in with Apple and iCloud+ Hide My Email under a single private.icloud.com domain. Addresses generated for both features will be issued on the new domain, Apple says. Sign in with Apple addresses currently use the privaterelay.appleid.com domain, while iCloud+ uses icloud.com. Later this summer, both will use the same private.icloud.com domain.
Steam Next Fest Is Flooded With AI Games And It Sucks
The event has been flooded by games containing AI-generated content
Is SMIC N+3’s Metal Pitch Smaller than Intel 18A’s?
Almost four years ago, we published that SMIC had started shipping 7 nm (N+1) chips. Now, SMIC is shipping its third-generation 7 nm (N+3) process in Huawei’s Kirin 9030, with a minimum metal pitch of 32.5 nm, about 10% tighter than the 36 nm minimum metal pitch shipping in Intel’s latest Panther Lake CPUs on 18A. The headline is true, but incomplete cherry picked metric. N+3 reaches the density of TSMC N6 through aggressive DUV multi-patterning and design-technology co-optimization (DTCO), but it pays for that in complexity, efficiency and process control. We found this and more in our reverse engineering and teardown where we cover SMIC’s N3 process technology, Huawei’s packaging, memory, architecture, and more. SemiAnalysis has been building a state-of-the-art teardown lab in Oregon capable of analyzing the world’s most advanced and important chips over the last year and half. We have already generated revenue on advanced datacenter chip teardowns including our recent reverse engineering of a major TSMC customer’s COUPE CPO optical engine + EIC 3D stack. This is the first public report from the SemiAnalysis Teardown Engineering & Evaluation Lab, or STEEL for short. The lab is aggressively scaling up and out and we’re excited to announce it publicly. This is a bit of inconvenient timing for TechInsights as they are private equity owned and currently being sold while having enjoyed virtually no credible competition for decades. This has led to TechInsights underinvesting in CAPEX. SemiAnalysis exceeds TechInsights in revenue despite no venture or private equity ownership and being founded only 6 years ago. Because we have no external investors and are founder led, we move faster, build faster, and we can release client chip teardowns for free regularly, while focusing on datacenter for our major clients. Here’s the first public image from our lab, the HiSilicon Kirin 9030 Pro SoC: This report will detail our teardown of the Kirin 9030 and our findings on SMIC’s N+3 process, the most advanced in China. For comparison, we’ll show our teardown of the MediaTek Helio G99, made on TSMC N6. Through this comparison, we can look at the effect of export controls – SMIC N+3 and TSMC N6 are comparable nodes, but one is heavily export-controlled, the other free to use the West’s most advanced equipment. Here we see both China’s progress and constraints. SMIC N+3 reaches TSMC N6-class logic density, but it requires far more aggressive DUV multi-patterning, so it does not match N6 on process maturity or cost. The Kirin 9030 Pro performs similarly to three-year-old Android flagships, and trails far behind the current flagship SoCs from Apple, Qualcomm, MediaTek, and Samsung. The efficiency gap is even wider. Export controls have not stopped Huawei and SMIC from shipping advanced silicon, but they have forced a different path. Without EUV, SMIC is leaning harder on DUV multi-patterning, DTCO, and increasingly complex integration. The roadmap continues forward through tighter design rules and backside power, but each step adds cost and process risk. Huawei’s τ scaling and LogicFolding show another path: stacking active logic and recovering density through advanced packaging and system-technology co-optimization (STCO). To understand the Kirin 9030, we must first understand Huawei’s SoC history. HiSilicon is Huawei’s chip design arm, responsible for the Kirin smartphone SoCs, Kunpeng server CPUs, Ascend AI accelerators, and switch/router networking silicon. Before export controls, Huawei was TSMC’s largest customer – the only customer on TSMC’s first EUV node, N7+, and among the first on N5, alongside Apple. That ended in late 2020. Huawei switched to Qualcomm SoCs in its flagship smartphones, though export controls limited them to 4G-only variants. In late 2023, Huawei returned to in-house silicon with the Kirin 9000s, a successor to the Kirin 9000, fabricated on SMIC N+2 instead of TSMC N5. In the following years, they released the Kirin 9010 and 9020 on the same N+2 process. These chips used Huawei’s in-house TaiShan CPU cores and Maleoon GPU. We have not torn down a Kirin 9020 ourselves, so the predecessor die shot is from Kurnal. The die shots show how Huawei spent its silicon budget: which functional blocks are where, and how their areas compare to the predecessor. First, a quick guide to the major blocks on the die. The total die area is nearly identical, but the 9030 uses that area more aggressively. A denser process lets Huawei fit an extra middle CPU core, more GPU and NPU cores, and larger caches into the same footprint. In contrast, the Helio G99 is a much smaller, low-cost SoC, built for budget smartphones rather than a flagship device. While the Kirin 9030 is ~140 mm², the G99 is only ~29 mm², roughly one-fifth the area. The underlying TSMC process technology, however, is directly comparable as a baseline for analyzing SMIC’s. The Kirin 9030 is an evolutionary refresh, not a clean-sheet design. Its CPU, GPU and NPU cores carry over the 9020’s families, and the gains come from three levers: the SMIC N+2-to-N+3 process step, DTCO and floorplan work, and incremental microarchitecture. Area is where the first two show up, and the 9030 scales well here. Performance and efficiency are the harder test. Huawei’s design holds up better than its node would suggest, but the chip still trails, both because N+3 sits behind the leading-edge nodes and because its cores, while competent, remain a few generations behind the newest designs. The new prime core is an incremental update. The main changes are a 10% frequency increase from 2.5 GHz to 2.75 GHz and a doubling in the L2 cache from 1 MiB to 2 MiB. Despite the increased cache, the core size decreased by 7.6%. Excluding the private L2 cache, the core size decreased by 21%. This is a large reduction for an incremental node. Compared with the TaiShan New V120 core in the Kirin 9020, the Kirin 9030’s middle core is almost unchanged architecturally, yet each core shrinks by ~22%. Most of that comes from the move from N+2 to N+3, with layout likely accounting for the rest. Visually, the most noticeable change is the increase from 3 middle cores to 4. There is also a 20% increase in the shared L3 cache of the big cluster. This helps to improve multi-core performance without sacrificing much in terms of area. Even with each core shrinking, the big CPU cluster’s total area is essentially unchanged. The per-core savings went back into an additional middle core and larger caches. The tiny cores shrank less than the prime core (excluding its L2 cache) and less than the middle cores. This is likely because fixed overhead is a larger share on a small core. We cannot resolve any architectural changes from the die shot alone, but the per-clock and efficiency gains shown below point to more than pure process and layout scaling. The area reduction was offset by a doubling of the shared L2 cache from 2 MiB to 4 MiB, leaving the total tiny CPU cluster area slightly larger. Area is the easiest improvement to see from a die shot, but it is only one part of PPA (power, performance, area). For modern logic, power and performance matter just as much, and often more. Since Dennard scaling broke down in the mid-2000s, voltage and frequency have not scaled in step with transistor dimensions, so each node has had to fight harder for gains in performance and efficiency. The starkest comparison is not Kirin 9020 versus Kirin 9030 Pro. Apple’s efficiency cores run circles around Huawei’s prime core. Apple’s low-power core delivers 20% higher integer performance while drawing only 1 W, compared with 4.5 W for Huawei’s prime core. N+3 matches TSMC N6, but N6 is several generations old. Apple and Qualcomm build on N4 and N3P, which are denser and sit on a better voltage-frequency curve, giving them a larger transistor budget and more performance per watt. The 9030’s own cores did improve. The middle and tiny cores gained 17% and 14% in per-clock integer performance over the 9020, with floating-point flat on the middle core and up 11% on the tiny. The tiny core improves cleanly, with performance rising while power falls and efficiency increases by 45% in integer and 24% in floating point. The middle core is mixed: integer performance rises but power rises faster, cutting integer efficiency by 7%, while lower power lifts floating-point efficiency 16%. Per-clock gains at the same or lower frequency are microarchitectural, so the cores are tuned, not just shrunk. Both also failed to hold their rated maximum frequencies, pointing to thermal, power, or stability limits. Per clock, the middle core sits around Arm Cortex-A720 and the tiny core near the Cortex-A520; absolute performance trails because Huawei clocks them much lower. The prime core is roughly Cortex-X2 class per clock, a 2021 design. Apple’s 2020 M1 Firestorm core is still 35% higher per clock and 57% faster in absolute integer performance at a similar 4.5 W. The current leading edge is further ahead again: the Apple M5 P-core is 60% higher per clock and 2.7× faster, the Arm C1 Ultra 45% higher and 2× faster. Matching older high-end cores per clock is a genuine design achievement. What Huawei cannot match is the voltage-frequency curve and transistor budget of leading-edge nodes, which let Apple, Qualcomm and others spend more transistors in the same area on wider cores, larger caches and deeper buffers while running at lower voltage. Huawei’s LogicFolding roadmap is one answer, stacking active logic to recover density and shorten signal paths. We return to it later. The GPU compute units (CUs) changed more visibly than the CPU cores, moving to a more rectangular layout for both the arithmetic logic unit (ALU) clusters and the CU overall. Even with ray-tracing support added, a CU shrank ~28%. However, that shrink is offset by the increase from 4 to 6 CUs and the area outside the CUs grew 33%. Overall, the GPU cluster is larger by ~10%. The GPU is where Huawei makes its biggest gains. The Maleoon 935 is not competitive with current flagships, but it is a large step up from the 920 and reaches older-flagship territory. In 3DMark it is 70% faster in Wild Life Extreme (WLE) and 79% faster in Steel Nomad Light (SNL) than the 920; with 11% higher clocks and 50% more CUs, the ~67% theoretical uplift roughly matches WLE and is beaten by SNL. It edges ahead of the Snapdragon 8+ Gen 1 in WLE and SNL, and the Dimensity 9200 and Apple A16 in WLE, but stays far behind newer parts: the Snapdragon 8 Elite Gen 5 and Dimensity 9500 are ~2.4–2.6× faster in WLE and ~3.2× faster in SNL. The Maleoon 935 is Huawei’s first GPU with hardware-accelerated ray tracing; there it lands slightly ahead of the Exynos 2200, and on par with the Apple A16, with current flagships up to 3.7× faster. The Neural Processing Unit (NPU) saw the largest structural changes of any block, moving from a Lite and a Tiny core in the Kirin 9020 to a Lite and two Tiny cores in the Kirin 9030. Both core types also show significant layout changes. This is a reversal in Huawei’s NPU design. The Kirin 9000 5G, its last flagship chip on TSMC N5, used two Lite and one Tiny core. The series of SoCs on SMIC N+2 moved to one Lite and one Tiny core, likely for area savings. With the Kirin 9030, Huawei has shifted back toward a larger multi-core NPU cluster, but with the additional area going to a Tiny core rather than a Lite core. We’re diving deep into the most advanced datacenter and AI hardware hitting the market. To learn more about what’s in the pipeline or to commission a custom teardown, contact sales@semianalysis.com. Interested in joining us on this ride and think you can be a difference maker? Check out our Careers page. Before diving into the process stack, the package and memory are worth separating from the SoC itself. The Pro variant of the Kirin 9030 carries 12 GB of Samsung DRAM, with two stacks of four dies each. The dies were identified as the K4L2E165YD, a 12 Gb LPDDR5X-9600 device fabricated on Samsung’s 1a node, the fourth generation of its 10 nm-class DRAM after 1x, 1y and 1z. 1a has shipped in volume since 2022, so this is current memory rather than older-node inventory. The 16 GB Pro Max variants we obtained were found with both CXMT and Samsung packages. The CXMT package is marked CXDD7JEDM, with two stacks of four dies, packaged in week 45 of 2025. The inferred die dimensions from X-ray computed tomography (CT) are consistent with a known density of ~0.3 Gib/mm² for the CXMT G4 process, roughly equivalent to other manufacturers’ 1z processes. The Kirin 9030 uses a typical integrated package-on-package (iPoP) stack: multiple DRAM dies in a memory package sit above an organic redistribution layer (RDL) interposer, which sits above the SoC and package substrate. The full package is then mounted to the printed circuit board (PCB) through ball-grid array (BGA) solder bumps. The memory package substrate is a thin bismaleimide-triazine (BT) laminate carrying the LPDDR5X stack. The organic RDL interposer over the SoC routes the PoP signals around the die and carries possible dummy thermal copper pillars. The package substrate, a thicker Ajinomoto Build-up Film (ABF) build-up over a BT core, fans the flip-chip bumps out to BGA pitch and embeds the power planes. The whole stack is organic. The only silicon is the SoC and the LPDDR5X dies; there is no silicon interposer. Keeping it all-organic brings the package’s coefficient of thermal expansion (CTE) close to the PCB’s, reducing board-level warpage, and avoids the cost of a silicon interposer the SoC’s bandwidth does not need. In an iPoP stack, the memory package connects to the organic RDL interposer through an array of solder bumps. Underfill fills the gap around those bumps, adding stiffness and protecting the joints from mechanical stress. The Pro and Pro Max variants differ here, which we cover behind the paywall. The die shot and architecture tell us how Huawei allocated its silicon budget. The process tells us what SMIC can manufacture. We use the Helio G99 as the process reference for TSMC N6. Both SMIC N+3 and TSMC N6 are evolutions of previous 7 nm-class nodes. We used targeted TEM cross-sections through logic and memory regions, imaged in both fin-cut and gate-cut directions. Each cross-section caption gives its horizontal field width (HFW), the real width of the imaged area. We start at the transistor fins, then move up through standard cells, local interconnect, and SRAM. SMIC has not overtaken Intel or TSMC. It uses aggressive DUV scaling and DTCO to reach N6-class density, but that density doesn’t translate into comparable performance and efficiency, for two reasons: the node gap to leading-edge nodes, and Huawei’s core designs. Fin Profile One of the most important knobs in a FinFET process is the fin profile: the shape of an individual fin and the channel where current passes from source to drain. The ideal fin is tall, narrow, and nearly vertical. A taller fin increases effective channel width, while a narrower fin improves electrostatic control by thinning the body the gate must control. Push either too far, and the process pays for it: weaker drive current, fragile fins, taper, footing and line-edge variation that hit yield and device variability. The Intel 22 nm, 14 nm, and 10 nm fin cross-sections show how FinFET nodes have improved over time. 22 nm fins were a first-generation structure, relatively short, wide and strongly tapered. The shape limits current density and reduces gate control uniformity across the height of the fin. At 14 nm and 10 nm, Intel pushed the fins taller and narrower while also making the sidewalls more vertical. Rather than shrinking the device, these changes increase the effective channel width per fin and improve electrostatic control. The trade-off is that taller fins at tighter pitches are much more difficult to manufacture. Now, let’s compare the Helio G99 on TSMC N6 with the Kirin 9030 on SMIC N+3. Both processes are in the same class, with fin pitch of 30-32 nm on N+3 and 34 nm in our N6 cross-section. The pitch for N6 is especially interesting as N7’s HD library is generally listed with a 33 nm fin pitch, and N6 did not shrink pitches directly. Its density gains came from DTCO instead of tighter pitches. The 34 nm pitch was stable across our sampled region and serves more as a comparison against the SMIC N+3 we have not investigated further. Pinning down N+3’s fin patterning scheme takes more than one core unit. The CPU cores show a dense ~32 nm pitch, with the pitch between N-P fin pairs alternating between 78 and 88 nm. Logic alone may be consistent with dual-pitch mandrels of 120 and 110 nm, but this is a complex and unusual approach. Combining the pitch from the the 8T SRAM, which has more complex repeat unit, with the CPU core sequence allows us to reverse engineer the patterning steps with more confidence. As both the logic and SRAM should share the same base grid, a single CD mandrel lithography pattern with 128 nm pitch undergoing SAQP produces a die-wide ~32 nm grid (128 nm/4), which supports the pitch sequencing seen in both logic and SRAM cells. In the sampled cross-sections, N+3 shows a taller, narrower, higher-aspect-ratio fin than N6. The measured fin aspect ratio is ~9.5:1 on N+3 versus 7.8:1 on N6. N+3 also shows less top rounding, with an estimated radius of ~2 nm, compared with 2.8 nm on N6. Even though the fin widths differ, the ratio of top rounding to fin width tells the same story, with N+3 at 0.37 and N6 at 0.44. In a geometric sense, lower is better; a perfectly rectangular fin would have no top-rounding penalty. These are single-digit-nanometer features measured from a handful of cuts, so treat the absolute numbers as approximate. The important result is the relative gap: N+3’s fins are consistently taller, narrower and less rounded than N6’s. We’re diving deep into the most advanced datacenter and AI hardware hitting the market. To learn more about what’s in the pipeline or to commission a custom teardown, contact sales@semianalysis.com. Interested in joining us on this ride and think you can be a difference maker? Check out our Careers page. Standard Cell A standard cell is the basic building block of chip layout: a fixed-height row pairing one NMOS and one PMOS transistor that share a gate, tiled in a grid to build logic blocks. The key dimensions are contacted gate pitch (CGP), cell height (CH), fin count, and the lower-metal routing grid. To measure density, we use the Bohr metric: a weighted average of NAND2 gate area (60%) and scan flip-flop area (40%). This represents a realistic mix of combinational and sequential logic. This metric has its limitations, especially for complex cell layouts like TSMC’s FinFLEX, which alternates cells with different fin counts. Even so, it is the best metric for a pure process-level comparison. Another important measurement is the fin pitch; it refers to the distance between two fins of the same transistor. In a FinFET process, multiple fins are used in each transistor to increase the drive current and thus performance. TSMC N6 ships both a high-density (HD) library with 2 PMOS and 2 NMOS fins per cell, and a high-performance (HP) library with 3 of each. More fins under the shared gate mean more effective channel width. HP cells switch harder at the cost of area. Designers mix the two on a die, primarily spending HP cells on timing-critical paths, and matching their PPA targets. In the Cortex-A55 core of the Helio G99, we found a cell height of 240 nm for the HD cell. MediaTek has used HD cells in the G99 to minimize die size and thus cost. As an SoC for budget smartphones at ~$100, this is essential. By contrast, we found only one library in the Kirin 9030, with 2 NMOS and 2 PMOS fins. This suggests a narrower library strategy than TSMC N6, where both HD and HP libraries are widely used. This likely reflects the smaller customer base and the more constrained domestic design and electronic design automation (EDA) ecosystem. In all three CPU cores of the Kirin 9030, we found cell heights of 228 nm, 5% smaller than on N6. This is also a reduction of 9.5% over SMIC N+2’s cell height of 252 nm. SMIC N+3 and TSMC N6’s HD library both feature a CGP of 57 nm. For SMIC, this is a 9.5% shrink over N+2. In the past, CGP and cell height alone may have been enough to compare transistor density. Now, however, we must consider scaling boosters and DTCO as well. SMIC’s density gain does not come from EUV. It comes from using every available DTCO booster aggressively. First is fin depopulation: reducing the number of NMOS and PMOS fins in each cell. The first FinFET nodes started with 3 or 4 fins for each transistor. SMIC N+3 and TSMC N6 HD both use only 2 fins per transistor, trading drive strength for density. Next is contact over active gate (COAG). By landing the gate contact directly over the active gate, instead of out over the isolation region, the cell height drops. N+3 integrates COAG while N6 does not. Our N+3 gate-cut cross-sections indicate COAG, with the gate contact sitting over the active region, while N6 shows an off-gate contact. Last is single diffusion break (SDB). Diffusion breaks are inserted between cells in the same row to provide electrical isolation, but they also introduce local layout effects (LLE), layout-dependent shifts in electrical characteristics. In the past, a double diffusion break was used, consuming the space of two CGPs. SMIC N+3 and TSMC N6 instead use SDB, saving area but increasing LLE sensitivity. This must be controlled at the process level and accurately modeled in the process design kit (PDK) so that EDA tools can account for it. Overall, SMIC N+3 has a transistor density of 113.4 MTr/mm², slightly above TSMC N6 at 107.7 MTr/mm². Even without EUV, SMIC has achieved density beyond TSMC’s mature N6 node which utilizes EUV. Metal Stack The smallest critical dimension in the teardown is M0; SMIC N+3 uses a 32.5 nm local metal pitch. That is smaller than the 36 nm M0 pitch on Intel 18A in Panther Lake. However, this does not mean that SMIC has a better process than Intel 18A or TSMC N3P. M0 is a local intra-cell routing layer. Its usefulness depends on the full interconnect stack: M1 and M2 pitch, track count, via and line resistance, design rules, mask count, overlay control, and routing flexibility. The 32.5 nm M0 is consistent with self-aligned quadruple patterning (SAQP), whose four-population line-width loading we read coarsely as alternating widths of 21.5 to 24 nm; M1 and M2, at 38 and 40 nm, are consistent with self-aligned double patterning (SADP), a single A/B split. On TSMC N6, M0, M2, and M3 sit at a relaxed ~40 nm and are consistent with SADP-class double patterning, with no need for quadruple patterning. That said, we measure M2 for example at ~43 nm, likely inflated by sparse routing. We do not assign any specific layer to EUV from our cross-sections; the distinction we can draw is double versus quadruple patterning, not lithography wavelength. Transistor-level density in the front-end-of-line (FEOL) sets an upper bound, but the design is ultimately limited by what the interconnect stack can route. The lowest metals are the most important for standard-cell density, but the semi-global and global layers determine how usable that density is at the block and chip level. Two axes are commonly used for chip cross-sections: the fin-cut and the gate-cut. The micrograph above is a fin-cut and shows metals 0 through 3. This axis lets us see the even-numbered metals, with M0 right above the fins. There are two kinds of M0 lines. The first are the power rails; these are wide wires for the VDD and VSS running horizontally at the top and bottom edges of each standard cell. The wide wires measure 55 nm across, more than double the other M0 lines. Their width minimizes resistance and reduces IR drop. The second kind are intra-cell wires, short segments within the cell that connect terminals to M1. These have alternating widths between 21.5 and 24 nm. The M0 pitch is 32.5 nm, a 19% reduction versus N+2 and N6. At this pitch, DUV patterning requires more aggressive multi-patterning, increasing mask count, overlay sensitivity, process complexity and cost. M0 is below what a single DUV-defined spacer (SADP) can resolve, so SMIC cascades a second spacer step (SAQP). The cross-section reflects the cost: the M0 trenches are visibly more re-entrant (narrower at the bottom than the top) than M1 or M2 on the same chip and carry a bright barrier-rich foot where the trench meets the etch-stop layer. That shape is partly the intended damascene profile, as a slightly narrow bottom helps void-free copper fill, but its magnitude at M0 is driven by the tight pitch and the higher trench aspect ratio. Intel 18A supports an M0 pitch of 32 nm, although Panther Lake has only shipped with a looser 36 nm pitch. This is due to Intel’s heavy usage of HP libraries. Among leading-edge nodes, 18A has the loosest M0 pitches due to PowerVia. With power routing moving to the backside, congestion is reduced, and the entire front-side metal stack can be used for signal routing. M2 is the first true inter-cell routing layer. It runs horizontally like M0 but spans across multiple cells to carry block-level signals. The M2 pitch sets the cell’s track height – the number of M2 tracks that fit between the VDD and VSS rails, defining what the library calls a 6-track or 7.5-track cell. This layer is the most important, limiting the routing of entire blocks. SMIC N+3 features a 5.7-track cell. The M2 pitch is 40 nm, a 5% decrease over N+2 and the same as N6. This shrink keeps the pitch at the edge of what is possible with double patterning. Future nodes will need to increase the number of masks for M2 as reducing the number of tracks is much harder due to the limitations in routing. The micrograph above is in the perpendicular direction, the gate-cut, and shows metals 0 through 4. This allows us to see and measure the odd-numbered vertical metal layers. The M1 pitch is 38 nm, 9.5% less than N+2 and 33% less than N6. The M1-to-gate ratio matters because it sets local routing flexibility. N+2 and N+3 use a 3:2 ratio, while N6 uses a 1:1 ratio, explaining the huge differences in M1 pitch. The more M1 lines there are compared with the gates, the more flexibility there is for power and signal crossing within the cell. Routing flexibility enables more complex and better cells. Clean fractional ratios are also preferred as a grid is periodic and improves layouts. The 3:2 ratio gives SMIC more local routing flexibility than a strict 1:1 grid, but it also complicates layout and patterning. This is a DTCO choice, with SMIC increasing process complexity to recover density and routability without EUV. This 3:2 ratio is not very popular in the leading-edge nodes. TSMC has only used it on N7+, the N5 family, and the short-lived N3(B). They have switched back to a 1:1 ratio for N3E. Intel has only used it on the 10 nm/Intel 7 family, with Intel 4, 3 and 18A all using a 1:1 ratio. Samsung is the only one still using a 3:2 ratio at the leading edge, using it in the SF4 and SF3 families. It remains to be seen if SMIC will remain at a 3:2 ratio or move to a 1:1 ratio with its future nodes. The industry is still actively exploring these local-routing ratios. At VLSI 2026, imec will be presenting work on even higher ratios, including a 2:1 scheme that can reduce area by up to 14%. We will be covering the conference in a future newsletter article. Subscribe We’re diving deep into the most advanced datacenter and AI hardware hitting the market. To learn more about what’s in the pipeline or to commission a custom teardown, contact sales@semianalysis.com. Interested in joining us on this ride and think you can be a difference maker? Check out our Careers page. The final local interconnect layer for N+3 is M3, with a pitch of 44 nm. The M3 pitch is the same as on N+2 and 10% larger than on N6. The semi-global layers carry the majority of block-level signal routing. They have a coarser pitch than the lower local layers. On leading-edge nodes, they are designed to sit at the limit of DUV single patterning. M4 through M11 pitches were found divided between 80–82 nm (M4–M6), 128 nm (M7–M10), and 148 nm (M11). Given limited sampling, it is possible these are divided further in dense routing areas. At the top are two giant metal layers, M12 and M13. These have kept the same pitches as N+2 at 1920 nm and 4600 nm respectively. While the lower layers’ pitches are generally fixed by the process and library, the upper layers vary much more in pitch and count, depending on the design. Even two smartphone SoCs on the same process can have wildly different metal stacks. The Helio G99 carries fewer routing layers, reaching coarse metal pitches of 850 nm by M9, while the larger and higher-performance Kirin 9030 keeps fine pitches until M11. SRAM At the leading edge, SRAM is much more difficult to scale than logic. TSMC’s latest nodes have seen little to no bitcell scaling, while logic still has more DTCO levers to pull. While looking for other logic libraries in the GPU compute units, we stumbled upon the SRAM. The most common type of SRAM has 6 transistors (6T), but this cell had 8 transistors (8T) instead. 8T SRAM adds two transistors to form a dedicated read port. Unlike a 6T cell, where reading disturbs the storage, the decoupled read port removes read-disturb, improving read stability and letting the cell be pushed harder for performance. At first glance, the cut looked like an unusual logic library, with each cell row having 3 fins of one polarity and 5 fins of another. The rows also alternated in orientation. Energy-dispersive X-ray spectroscopy (EDS) resolved our confusion. The cut had not landed on the GPU logic, but on the SRAM macro beside it. The unusual fin pattern was due to the SRAM library. We return to EDS in the process flow analysis behind the paywall. SRAM libraries are not like traditional logic libraries. Due to the unequal number of PMOS and NMOS transistors, they require specialized rules and layout libraries. They do not need the flexibility of logic libraries, so they are hyper-optimized for one purpose: dense, reliable memory. The SRAM cell we found is a 1:2:2-2:2 cell. This means there is 1 fin per pull-up (PU) PMOS transistor, and 2 fins per pull-down (PD) and pass-gate (PG) NMOS transistor. These 2 PU, 2 PD and 2 PG transistors would usually form a single 6T high-current cell (HCC). An 8T HCC adds a read-pull-down (RPD) and a read-pass-gate (RPG) NMOS transistor, each with two fins. We measured a cell height of 406 nm, which brings the bitcell size to 0.0463 µm². That is a theoretical peak density of 21.6 Mib/mm². We estimate that a 6T HCC would have a cell height of 292 nm and a size of 0.0337 µm². This is ~12% larger than a 6T HCC on Intel 3 and 4. We also estimate the 6T high-density cell (HDC) to have a cell height of 228 nm and a size of 0.0260 µm². This is coincidentally the same as the logic standard-cell height measured earlier. The estimate puts the cell near Samsung 7LPP/5LPP and slightly below TSMC N7/N6. That is a theoretical peak density of 38.5 Mib/mm². 6T HDC is arguably the most important cell as it is used for the largest caches in a chip, the L3 caches and system-level cache (SLC). Both the Kirin 9020 and 9030 have split the SLC into 4 banks to raise total SLC bandwidth. In the Kirin 9030, the SLC increased from 2 MiB to 3 MiB per bank. Correspondingly, the number of arrays within the bank also increased by 50%, from 16 to 24. Each array can store 128 KiB and forms an orderly pattern on the die shot. From the Kirin 9020 to the Kirin 9030, the area of a 128 KiB SLC array decreased from 0.0477 mm² to 0.0392 mm², an 18% shrink. The achieved density is 25.5 Mib/mm², 66% of the theoretical maximum. While the SLC was quite similar across both chips, the L3 has seen some major changes, particularly in terms of its layout. The total capacity also went up from 10 MiB to 12 MiB. Much like the SLC, the L3 is also split into 4 banks. In the Kirin 9020, an L3 bank consisted of 16× 128 KiB arrays and 16× 32 KiB arrays. However, an L3 bank in the Kirin 9030 instead consists of 48× 64 KiB arrays. In the Kirin 9020 L3, a 128 KiB array was 0.0513 mm² and a 32 KiB array was 0.0154 mm². The size of the 128 KiB array is different on the L3 and SLC as the assist circuitry for the two arrays differs depending on their purpose. In the Kirin 9030 L3, a 64 KiB array is 0.0210 mm². Although not a like-for-like comparison, normalized for capacity, it is 18% smaller than the 9020’s 128 KiB L3 array and 31% smaller than its 32 KiB L3 array. The achieved density is slightly lower than the SLC, at 23.8 Mib/mm², 62% of the theoretical maximum. Unlike the L3 and SLC, the prime cores’ private L2 cache uses a 2-bank design. As the prime cores’ L2 is latency-critical, it likely uses 6T HCC instead of 6T HDC. The 9020 has 16 arrays in each bank while the 9030 has 32. Each array has a capacity of 32 KiB. A 32 KiB array in the L2 shrank from 0.0171 mm² to 0.0142 mm², ~17% smaller. The density is 17.6 Mib/mm², ~59% of the theoretical maximum for 6T HCC. SRAM scaled well from N+2 to N+3, shrinking by ~19%, close to the theoretical logic shrink. The caveat is that N+2’s bitcells were unusually large, bigger than comparable 7 nm-class nodes, so part of the gain is catch-up rather than true scaling. With the insights from STEEL’s teardowns, we will be doing a deep dive into SRAM in a future newsletter article. Subscribe Everything above came out of a single STEEL teardown: die annotation, block-level area analysis and TEM cross-sections through logic and SRAM. We’re diving deep into the most advanced datacenter and AI hardware hitting the market. To learn more about what’s in the pipeline or to commission a custom teardown, contact sales@semianalysis.com. Future Roadmap The same cross-sections that pin down N+3 also show where SMIC can go next. Although N+3 is already close to the practical limits of DUV multi-patterning in several layers, SMIC still has a few scaling levers left. A theoretical N+4 would likely start with cell height. N+3 uses 5 M0 tracks between its power rails. Moving to 4 M0 tracks, as on SMIC N+2 and TSMC N6, could reduce cell height by roughly 15%. The routing grid is only one side of the shrink; the front end also must fit into the smaller cell. One possible FEOL lever is reducing the p-to-n isolation spacing from two diffusion grid units to one. Intel used this scaling booster on Intel 4, and TSMC did so on its N3 family. This path trades layout flexibility for density. Fewer M0 tracks reduce local routing resources, while tighter p-to-n spacing raises integration and design-rule difficulty. M2 is also constrained by the cell height shrink. For SMIC to maintain a ~5.7-track cell, M2 would need to move toward ~35 nm. That would move another layer into SAQP territory. SMIC could also reduce the CGP from 57 nm to 54 nm. Intel reached a similar CGP on Intel 10 nm/Intel 7 without EUV. The local interconnect is also tougher. If SMIC keeps the 3:2 M1-to-gate ratio, M1 would need to shrink to 36 nm and would likely require SAQP as well. If SMIC moves to a 1:1 ratio, M1 could relax to 54 nm, but it would give up routing flexibility. Under this theoretical path, we estimate that SMIC N+4 could reach a cell height of 198 nm and a CGP of 54 nm, implying a Bohr density of 137.8 MTr/mm², on par with TSMC N5 or Samsung SF4. However, the difficulty is cumulative. Each step is individually plausible, but together they make N+4 harder than the transition from N+2 to N+3. It will likely take longer, cost more, and carry less process margin. A theoretical N+5 would require a larger integration shift. One possible path is backside contacts (BSCon), moving power routing and source/drain contacts to the backside, which would reduce front-side routing pressure and enable another reduction in cell height. The front-side metal pitches could relax to reduce the process complexity. M0 would likely relax slightly to ~34 nm, and M2 and M4 pitches could relax further. CGP is unlikely to shrink much further. Even with EUV, 48 nm has been the practical limit for yield and process control. This approach would allow N+5’s cell height to fall to 170 nm and its CGP to 53 nm. This implies a Bohr density of 163.6 MTr/mm², on par with Intel 18A’s HP library. However, this would not make N+5 cost-competitive with the leading edge. It would reach a similar density through a much more expensive route. The integration difficulty rises sharply, with new process flows for backside alignment, wafer thinning, contact reveal, and backside metallization. Past this point, standard density and interconnect scaling become increasingly unattractive. That is where Huawei’s roadmap stops looking like a normal foundry roadmap and starts looking like a packaging roadmap. At ISCAS 2026, Huawei unveiled its tau (τ) scaling law, reframing process scaling in the time domain. τ is the time cost of data movement and processing: switching delays in transistors, RC signal propagation delays in circuits, compute, memory, and networking latency. Outside Huawei’s terminology, this is called system-technology co-optimization. This is Huawei’s answer to its lack of EUV lithography. Without EUV, planar density cannot keep pace with TSMC, Intel, or Samsung. If transistor density cannot shrink further, Huawei’s alternative is to shorten wires, reduce buffering, and stack logic vertically. “LogicFolding”, Huawei’s implementation of this new scaling idea, is, in practice, an aggressive 3D stacking approach. AMD V-Cache places SRAM above or below a CPU die. AMD’s MI350X places active interposer dies (AIDs) underneath accelerator and compute dies (XCDs), with the AIDs handling cache, IO interfaces, the network-on-chip (NoC) and embedded metal-insulator-metal (MIM) capacitors. With LogicFolding, parts of the same logic block are split across multiple active dies bonded face-to-face at ultra-fine pitch. This allows Huawei to shorten some critical paths and reduce buffer overhead, not merely add cache capacity or offload the IO and interconnect. Shortening wires is where the higher clocks come from. A large share of a modern core’s delay and energy budget goes into driving long interconnects and the repeater buffers along them. LogicFolding distributes a block’s critical-path gates across multiple stacked tiers bonded at a very fine pitch, so the bond interface behaves like an additional metal layer and the longest paths get shorter. That is how Huawei expects to recover frequency and efficiency it cannot get from the process alone. Huawei’s roadmap shows its intent. Prime core frequency is targeted to rise from 2.75 GHz in the Kirin 9030 to roughly 5 GHz by 2031, far beyond what planar scaling alone could deliver. Prime cores with 3.1 and 3.39 GHz clocks are being tested in its labs, although their power consumption is unknown. Beyond that, chips are in the design, simulation or pathfinding phase, meaning the frequencies are targets. However, the direction matters more: LogicFolding also helps with performance, not just density. The catch is that Huawei’s density claim is not directly comparable to foundry densities. A stacked design can report more transistors per package footprint by adding active layers, even if each patterned die remains well behind TSMC or Intel in front-end density. This is how Huawei can claim to reach foundry 14A-equivalent density by 2031. This is not a like-for-like foundry comparison, with Huawei using stacked logic and measuring density per package footprint. On a normalized Bohr-density basis, SMIC N+3 is ~114 MTr/mm², 38% less than Intel 18A’s HD library. Huawei’s 3D roadmap closes the gap by stacking active logic, reaching 215 MTr/mm² by 2030. In 2031, the roadmap density jumps to 295 MTr/mm², implying either a third active layer, partial EUV insertion or aggressive planar DUV scaling. Huawei’s methodology makes other foundries look much denser as well. Applying it to AMD’s MI450X with an N2 top die on an N3P base die yields a theoretical density of 460.2 MTr/mm² in 2026, compared with Huawei’s 295 MTr/mm² in 2031. This Kirin 9030 does not use LogicFolding, remaining in a conventional mobile SoC package. Instead, it forms the baseline for how far Huawei and SMIC can push planar scaling. Future teardowns of Kirin and Ascend chips will show both planar logic density and Huawei’s hybrid bonding solutions. Export controls changed China’s optimization problem rather than ending it. EUV restrictions raised the cost and complexity of leading-edge manufacturing without freezing it. SMIC reaches N6-class logic density through DUV immersion, SAQP and DTCO, while Huawei shifts more of the burden onto architecture, packaging and system-level integration. Future nodes will be tougher. N+3 still had room to tighten local metals and reduce cell height and CGP. Further scaling without EUV leaves fewer levers. More aggressive multi-patterning adds masks and overlay error. SMIC can keep pushing DUV, but each step will get more expensive and less forgiving. The design side is just as critical. Huawei had domestic EDA tools and flows before the Kirin 9030, with the Kirin 9000s, 9010 and 9020 making that clear. Huawei was able to ship multiple consumer SoCs on SMIC N+2 and N+3 while cut off from the Western EDA stack. US export controls restricted EDA tools for advanced chips in 2022 but did not target tools for more mature chips. In 2025, the US government briefly placed much broader restrictions on EDA software from Synopsys, Cadence, and others, before lifting them less than two months later as part of a trade deal tied to rare earths. Huawei has been unable to access those tools because it remains on a US trade blacklist. That forced Huawei, SMIC and Chinese academic institutions to build their own tools and flows. Researchers at Peking University recently announced a prototype EDA tool for Huawei’s LogicFolding architecture, which requires a new flow to handle the multilayer layout and floorplan. This is not the same as replacing the full Synopsys or Cadence stack, but it shows where domestic EDA is headed: toward tighter co-optimization between architecture, process and packaging. These advances are also diffusing into the Chinese ecosystem. SMIC is licensing its N+2 and N+3 processes to HLMC/Hua Hong at the government’s direction rather than by choice. If the same process learning feeds into Ascend accelerators for AI training and inference, the choke point shifts from one named fab to an ecosystem. Alibaba’s T-Head silicon arm and Cambricon, a Chinese AI chip designer that is expected to supply ByteDance, could also be major beneficiaries. Sanctions aimed at SMIC alone become less effective once the manufacturing knowledge has spread to other fabs and design houses. China is not closing the gap with Intel, Samsung and TSMC. The teardown shows the opposite in several places: no EUV, no backside power, higher process complexity, and visible trade-offs. But China is still advancing. If domestic chips become good enough for phones, inference, networking and security-sensitive workloads, they can matter strategically without matching TSMC at the leading edge. Behind the paywall, we show what else STEEL can do, with material and process flow analysis of SMIC N+3, and analysis of the Kirin 9030 package. We’re diving deep into the most advanced datacenter and AI hardware hitting the market. To learn more about what’s in the pipeline, access the full Kirin 9030 and SMIC N+3 analysis or to commission a custom teardown, contact sales@semianalysis.com.
Sharon O'Keefe
As president of the University of Chicago Medical Center and chief operating officer of the 1,286-bed University of Chicago Medicine health system, Sharon O’Keefe oversees a clinical enterprise with annual operating revenue of $2.21 billion. In the past 18 months, UChicago Medicine opened an expanded adult emergency department—a $39 million investment—and an adult trauma center. Since 2011, the system has generated annual growth of nearly 5 percent in revenue and 4 percent in patient admissions. O’Keefe previously was president of Loyola University Medical Center and executive vice president and chief operating officer at Boston’s Beth Israel Deaconess Medical Center. She serves on the Illinois Hospital Association finance and audit committee and is on the American Heart Association’s Midwest affiliate board.
Rubio compares the founding of the UFC to landing a man on the moon
US Secretary of State Marco Rubio extolled the virtues of the Ultimate Fighting Championship as being intrinsically American, likening its creation to putting the first man on the moon.
Who evaluates the evaluators? The data science behind agent evals
Learn how Copilot Studio approaches AI agent evaluation with generated data, grader validation, and scalable testing that improve agent quality.
AI-Generated Microdramas Are Real — and Thriving Under Our Noses
Vertical-first platforms are proving that human-assisted AI production is a commercially viable engine for mobile entertainment
AI-Generated Microdramas Are Real — and Thriving Under Our Noses
Vertical-first platforms are proving that human-assisted AI production is a commercially viable engine for mobile entertainment
‘Residual algae’ coats part of newly opened Reflecting Pool
The Trump administration has spent days heavily promoting the finished renovations at the Lincoln Memorial Reflecting Pool. But a day after the pool was refilled with water, algae was already coating it.
Large language model helps radiology department boost patients’ report comprehension
Emory University has utilized OpenAI’s GPT-5 to create LLM-produced radiology report summaries, clickable terms with embedded educational content, and AI-generated videos.
Oklahoma Ethics Commission, political leaders weigh future of AI-generated ads
In response to concerns from candidates, elected officials and the public, Oklahoma's Ethics Commission began exploring the regulation of AI-generated campaign ads at a special meeting Friday.
Oklahoma Ethics Commission, political leaders weigh future of AI-generated ads
In response to concerns from candidates, elected officials and the public, Oklahoma’s Ethics Commission began exploring the regulation of AI-generated campaign ads at a special meeting Friday.
Apple Brings AI Tab Organization and AI-Generated Extensions to Safari
Apple today unveiled a raft of Safari upgrades powered by Apple Intelligence, including automatic tab organization, AI-generated custom extensions, and new privacy-first browsing tools. The centerpiece feature is automatic tab organization, which uses Apple Intelligence to group a user's open tabs into relevant topics without any manual intervention. If someone is planning a weekend trip, for example, Safari can pull all of their travel-related tabs into a single topic.
GBTA: U.S. business travel spending hits record $538.5B in 2024
Business travel spending in the U.S. | The report—based on 2024 data—found that business travel accounted for 2.1 percent of total U.S. GDP and generated $148.6 billion in federal, state and local tax revenue.
South Korea's Lee says success of business should be shared, plans surplus tax revenue use
South Korean President Lee Jae Myung said on Monday the gains of business success should be shared throughout society and the government will devise a plan to effectively use the surplus tax revenues generated from the country's semiconductor sector.
Is Macau Outperformance And Community Investment Altering The Investment Case For Melco Resorts & Entertainment (MLCO)?
In the first quarter of 2026, Melco Resorts & Entertainment’s Macau properties generated 87% of group gross gaming revenue and 75% of EBITDA, with both metrics expanding year-on-year and quarter-on-quarter alongside a 1.3 percentage point gain in Macau gross gaming revenue market share. This outperformance in Macau, coupled with Melco’s ongoing support for inclusion-focused events such as the 2026 Inclusion Conference & Festival and the Macau Golf Masters, highlights how operational strength...
Rep. Mace: If price of an endorsement was ‘to not vote to release the Epstein files, that is a price I am unwilling to pay.’
GOP Congressman on President’s ‘anti-weaponization’ fund: ‘The votes are not there… to give a dime to this fund’
Senator Warner: Trump threw ‘live hand grenade’ into FISA negotiations with Pulte appointment
Hideo Kojima Says He's No Longer Interested In AI
The Death Stranding 2 directly recently appeared in an AI-generated promo for a new art exhibit
Belmont Stakes Day Generates More Than $116 Million In Handle
Saturday's blockbuster Belmont Stakes Day program, highlighted by Golden Tempo’s victory in the 158th running of the $2-million Belmont Stakes (G1) presented by NYRA Bets, generated all-sources handle of $116,077,378 and paid attendance of 46,128. On-track handle for the 14-race Belmont Stakes Day ...
AI-designed universal coronavirus vaccine passes first human trial
Scientists have successfully tested an AI-designed universal coronavirus vaccine in humans for the first time, finding it to be safe and well tolerated. The vaccine generated immune responses against multiple coronaviruses, including SARS-CoV-2, SARS, and related bat viruses with pandemic potential. By targeting features shared across an entire virus family, it aims to provide protection even as viruses evolve.
Google Employees Internally Share Memes About How Its AI Sucks
Google’s CEO says 75% of the company’s code is AI-generated. The people who write that code say the AI they’re using is overhyped.
Amazon’s search bar will invent AI-generated products you can’t buy
You can search for products that look like the fake images.
Amazon will show AI product images when you search for some reason
Amazon will use visual search and AI to show AI generated product images that match your search queries. The retailer says it will help guide users to products.
May's top PlayStation games by copies sold
Yesterday’s State of Play gave us an idea of where PlayStation’s heading next. But we’ve had our May estimates for a couple of days now (we always update our data daily for clients), so it’s time to look at what performed best on PlayStation last month. We’ve got a new IP at the top, two evergreens doing their evergreen thing, FC26 smashing it ahead of the World Cup Plus pivot, and a quiet but promising result for Lego Batman. Let’s have a look at the state of Play…Station’s top games for May. 007 takes #001 007 First Light sold 1M copies on PS5 in May, easily making it the month’s top PS5 game by copies sold. Over 80% of those May copies were digital, which is broadly in line with where PlayStation’s digital share has settled for new releases this year. To date, 007 First Light has sold through 2.2M copies across platforms (so no unsold retail copies in that figure). The platform split is 55.1% PS5, 33.1% Steam, and 11.8% Xbox (console, Windows, and cloud combined). In gross revenue terms, 007 First Light has generated $150M. Owing to regional pricing and audience composition differences, the consoles make up a higher share of revenue than they do copies. Of the $150M, 60.5% came via PlayStation, 27.6% via Steam, and 12.9% via Xbox. Part of this is because over two-thirds of 007 First Light‘s PlayStation audience is in North America (43.4%) or Western Europe (23.2%), where local currency means the game generates more revenue per player. On Steam, under half of First Light‘s audience is from those same regions (31.8% North America, 15.1% Western Europe). As we covered in last week’s 007 Steam piece, the Steam version is pulling in higher-than-expected numbers in China, which now accounts for 17.3% of First Light‘s Steam audience. 007 is the equivalent of $44 USD in China, which is roughly 37% cheaper than the US price and about 44% cheaper than Western Europe. Subscribe for free to get the most accurate games estimates in your inbox twice a week 🫶 Subscribe The crossover data backs up what we’ve seen all year about launch-window cohorts. 11% of PS5 players who played 007 First Light in May also played Lego Batman: Legacy of the Dark Knight, which launched just a few days before. Last month was a great month for Denmark! IO Interactive is Copenhagen-based, and Lego Group is headquartered in Billund (TT Games is UK-based but produces work under Lego Group licence and direction). Speaking of which… A very blocky #2 and #3 Minecraft sold another 788K copies on PlayStation consoles last month. Business as usual, since Minecraft hasn’t sold fewer than 760K copies in a single month all year. With over 350M copies sold across all platforms, Minecraft is the best-selling game in history and one of the strongest brands in the world. Every month, a new cohort of children reaches Minecraft age, which guarantees a constant volume of new sales regardless of what the broader market is up to. The demographic refresh rate is truly impressive, with the audience renewing itself faster than it’s churning. Lego Batman: Legacy of the Dark Knight shifted 757K copies on PS5 last month, bringing its lifetime total on the platform to over 800K. Across all platforms, Legacy of the Dark Knight has now passed 1.5M sold through, so PlayStation accounts for over half of the game’s players. The May crossover data for Legacy of the Dark Knight on PS5 is also useful. 27% of those players also played Fortnite, 16% Roblox, 16% FC 26, and 14% NBA 2K. That’s the household-and-family cohort showing up, plus the launch-window cohort of core gamers who buy practically everything. FC 26 gets players through the door ahead of the World Cup FC 26 sold 411K copies on PlayStation last month (90% via PS5), the fewest copies FC 26 has sold all year and down heavily from April’s 700K. Part of this dropoff is because FC 26 has been available as a PlayStation Plus monthly game since 6 May, cannibalising premium sales. Subscribe for free to get the most accurate games estimates in your inbox twice a week 🫶 Subscribe The strategic logic is straightforward for EA, which is sacrificing premium unit sales in May to build up the player base ahead of the FIFA World Cup, which kicks off on 11 June. Obviously, a bigger player pool going into the tournament means a bigger pool of potential Ultimate Team spenders during the period when football attention is at its peak. The early returns are around what you’d expect, with 4.4M new players accessing FC 26 via PS Plus last month – a substantial new spender pool. Anecdotally, a few of my mates who were ‘’skipping FIFA and Ultimate Team this year’’, were drawn back in via PS Plus. Lo and behold, one of them is buying packs like it’s going out of fashion. Whether this is all a smart trade for EA depends entirely on the Ultimate Team conversion rate over the next six weeks. Either way, the short-term engagement impact on the game as a whole is evident. FC 26‘s MAUs hit a record 24M on PlayStation in May, up 30% from the previous record set in April. GTA V does what GTA V always does Rounding out the top five is another evergreen title. Grand Theft Auto V shifted another 387K copies on PlayStation last month. No matter what else is happening in the industry, GTA V keeps pulling players in. It’s sold another 1.8M copies on PS5 in the first half of this year alone, helping the franchise pass the 230M-sold milestone across all platforms. Subscribe for free to get the most accurate games estimates in your inbox twice a week 🫶 Subscribe I have a theory that Minecraft and GTA V are doing the same thing at different demographic levels. Both are functioning as generational gateway games that the audience ages into faster than it ages out of. Minecraft captures kids around age 6-10, GTA V captures much of the same audience around age 12-15 (unofficially, of course). The crossover data suggests this: 40% of GTA V‘s monthly PlayStation players typically play Fortnite in any given month, while 30% play Roblox. Household accounts aside, that’s not the original GTA V audience from 2013. Of course, the under-12 audience would love to get their hands on GTA, too. It’s always been the way of things, and some parents are happy to oblige. Mine did too back in the day, and I turned out just fine. Right? Right!? Want to get your hands on our data for yourself – for free? We’re offering a free trial of our platform for games companies. Send us a message here, or reply to this email, and we’ll set you up. The last word Reply to this email – or reach out here – if you have any feedback for the newsletter – or want to request a game for us to cover. [Alinea Analytics boasts the most accurate PC and console estimates in the business. Game makers use our platform to understand their audience, keep an eye on the competition, monitor sales trends, and spot new opportunities. We equip game studios and financial institutions with accurate data and the confidence to make smarter, data-driven decisions. Want to talk about all things games market data? We’d love to chat!]
France rated second favourites for World Cup by Opta supercomputer
France have been identified as the second favourites to win the 2026 FIFA World Cup according to predictions generated by Opta’s supercomputer ahead of the tournament.With just over a week remaining...
Microchip Provides Data Center Solutions Business Unit Revenue Information
Our Data Center Solutions Business Unit generated $302.7 million in revenue in calendar year 2025, with approximately 65% growth expected in…...
‘Very close’ – Real Madrid president drops major Vinicius contract update
Real Madrid president Florentino Perez has addressed two topics that have generated significant discussion around the club in recent weeks, offering clarity on both Vinicius Jr’s future and Anas Lag...
Gravity Waves From Super Typhoon Sinlaku
Satellites observed striking upper-atmosphere phenomena generated by an intensifying tropical cyclone.
Are these AI-generated ads slamming Jennifer Jenkins and Jared Moskowitz the future of campaigning?
The Republican Party of Florida spent about 2 days to make each of these ads. Officials haven't spent anything to target voters — yet.
GOP strategist: ‘There are 8 Senators in the Republican Conference… who are pretty put out with the White House’
Interior Secretary Burgum on artists bailing on 250th concerts: ‘Some musicians seem to have segmented their audiences.’
From Backrooms to Paul McCartney: your complete entertainment guide to the week ahead
A horror film takes on the internet craze for user-generated paranormal tales, and Macca returns with his most affecting songs in years
Hideo Kojima Collaborates With Prada On AI Slop Short Film
The mind behind Metal Gear and Death Stranding ‘stars’ in a generated ad for the fashion company’s upcoming New York event
Fact check: Female politicians hurt by sexualized deepfakes
Female politicians around the world are being targeted by AI-generated sexual content, denting their confidence and reputations.
Across the globe, female politicians are increasingly being targeted...
Across the globe, female politicians are increasingly being targeted with sexualized AI-generated content. For women in politics, sexualized deepfakes have become a tool for humiliation,...
AI-generated images are making it impossible to distinguish truth from fiction. We need laws and AI watermarks to protect our shared reality.
Generative AI is destroying the baseline assumption that photographs bear some causal connection to reality. That's bad news for democracy.
Spotify Introduces AI-Generated Personal Podcasts
Per the new feature, Spotify will create a audio based on prompts such as "Share my daily city updates, and tell me about local concerts from artists I love."
He made up a song about traveling to Puerto Rico. Try getting 'first time in San Juan, mi hijo' out of your head.
Comedian and Pittsburgh Pirates fan Bill Stiteler is using AI-generated music, humor and lesser-known destinations to carve out a new lane in travel content.
A key science publishing platform is cracking down on AI slop
The pre-print website arXiv has announced that researchers who put their names to papers which included errors clearly generated by artificial intelligence (AI) will face a year-long ban and ongoing restrictions.
LA mayor's race: AI videos supporting Spencer Pratt shake up political playbook
AI-generated videos depicting L.A. mayoral candidate Spencer Pratt as a superhero and his rival Karen Bass as a villain are gaining traction online.
Amazon Alexa Plus Now Produces AI-Generated Podcast Episodes
The podcast industry suddenly has a big new player: Amazon's Alexa+ AI-powered voice assistant, which can now create extended 'podcasts' on any topic.
Final Fantasy creator Hironobu Sakaguchi praises AI-generated FF6 remake teaser, is promptly told "please stop" by SaGa's Akitoshi Kawazu
Hironobu Sakaguchi, the father of Final Fantasy, praised an AI-generated teaser for a hypothetical FF6 remake, but SaGa creator Akitoshi Kawazu disagrees.
Quantum ghost imaging works using only sunlight in stunning new experiment
Scientists have achieved something that once sounded almost impossible: using ordinary sunlight to create quantum-linked photon pairs, a phenomenon normally dependent on precise laboratory lasers. By building a sun-tracking system that funnels sunlight through optical fiber into a special crystal, researchers generated strongly correlated photons capable of performing “ghost imaging,” where images are reconstructed indirectly through quantum correlations. Remarkably, the sunlight-powered setup produced image quality close to that of a traditional laser system, even recreating detailed images like a “ghost face.”
‘Never-ending’ AI slop strains corporate hacking reward schemes
‘Bug bounty’ programmes have seen a jump in spurious AI-generated submissions
AI research papers are getting better, and it’s a big problem for scientists
Journal editors and peer reviewers are being flooded with AI-generated papers that are almost impossible to detect.
AI-generated pro-Spencer Pratt mayoral campaign videos point to a new political reality
The reality TV alum’s bid for higher office gained viral traction after videos, which Pratt said were “fan-made,” circulated across social media.
Deepfake “doctors” are a problem—here are 7 keys to stopping them
There’s a need for clear, enforceable protections against unauthorized AI generated deepfakes that threaten patient safety. Learn more with the AMA.
OpenClaw and Claude can put your AI-generated podcasts in Spotify
Your own personal AI podcast feed.
Sphere Entertainment generated $386.4M in Q1 revenues, up 38% YoY – driven by The Wizard of Oz and concert
‘Today’s results demonstrate our continued success proving out Sphere’s business model,’ said Executive Chairman and CEO James L.
AI political ad stirs controversy ahead of California debates
An AI-generated political ad depicting reality star and L.A. mayoral candidate Spencer Pratt is being celebrated by some, but also raises ethical questions. All of it as candidates prepare for key California debates just weeks before the primary. NBC News' Dana Griffin reports
Astrocade: $56 Million Raised To Build AI-Powered Interactive Entertainment Platform
Astrocade announced $56 million in new funding to expand its AI-powered interactive entertainment platform that enables users to create and play games generated with artificial intelligence. The funding included a Series B round led by Sequoia Capital and a Series A round led by Sea, with participation from Google’s AI Futures Fund, NVIDIA, LG Technology Ventures, Dentsu Ventures, Conviction Embed, Chaac Ventures, Rogue VC, and additional investors.
A Landslide in Alaska Set Off a Tsunami. There May Be More to Come.
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‘The reality, for better or worse’: Columbia comp sci students and faculty grapple with AI’s disruption of the field
‘The reality, for better or worse’: Columbia comp sci students and faculty grapple with AI’s disruption of the field ‘The reality, for better or worse’: Columbia comp sci students and faculty grapple with AI’s disruption of the field A field that once seemed like a direct path to stable, lucrative work is becoming less certain under AI, students and faculty told Spectator. By Ria Vasishtha and Arjun Menon May 3, 2026 Shanying Liu / Deputy Illustrations Editor Asia Genawi, SEAS ’29, first encountered artificial intelligence during her sophomore year at her high school in Indiana. Back in 2023, policies on AI varied widely—even within the same district—and some schools had no guidance at all. As Genawi began to see the effects of AI trickle into her classroom, she turned to guidance from her home state’s Department of Education, which she said she found “outdated and inaccessible.” Genawi spent the rest of her high school career dedicated to the issue, including writing a 15-page memo exploring varying AI policies across Indiana schools, which she sent to every Indiana state senator and representative whose contact information she was able to find. She later helped draft a bill that would have required public high schools to establish and share their own AI policies with students in an accessible format. But with so many other bills already awaiting referral, hers never made it to committee. When Genawi arrived at Columbia to study computer science, she found that the gaps she had spent years trying to address in Indiana had followed her there. Many students and professors were also grappling with what AI meant for the field. Across Columbia’s undergraduate schools, computer science has become the most popular major—accounting for around 11 percent of degrees awarded in Columbia College, 32 percent in the School of Engineering and Applied Science, and 12 percent in the School of General Studies in 2024. While the number of computer science majors in SEAS grew from 166 to 173 during the 2024-25 academic year, the total number across the three schools fell around 4.5 percent from 393 to 375, driven by declines at Columbia College and General Studies. At Barnard, it has grown to become the second most popular major as of 2025, up from third the year prior. The number of degrees awarded have grown fivefold since 2016. Faculty members and students in the department told Spectator that the surge in the major’s popularity has been driven in large part by its apparent promise of a secure, well-paid career path. However, they noted that the recent rise of generative AI has compromised the sense of stability that once defined the field, even as interest in technical skills among students persists. According to data from the Federal Reserve Bank of New York in 2024, out of 74 majors tracked, computer science had the fifth highest unemployment rate among majors at 7 percent, while computer engineering had the second highest at 7.8 percent. “Anecdotally, people are moving away from CS as a major,” Daniel Bauer, a senior lecturer in the computer science department, said. “They’re still taking some of our classes, right, because they think they need that, but they’re instead majoring in other things.” Bauer described a field that had shifted from what he called a “nerdy outlier discipline” to one that “everyone needs,” a sign that technical skills have become a baseline expectation across industries with the emergence of AI. “A lot of people thought, ‘Oh, it’s a guaranteed path to a stable income. You get a six-figure job right out of your undergrad,’” Bauer said. Now, companies may see AI as a way to reduce demand for entry-level programmers, especially in what he calls “code monkey jobs,” roles where a large number of employees are “just writing out code nine-to-five.” Chris Murphy, a senior lecturer in the computer science department, described the current moment as the convergence of two forces: the downturn of the job market and generative AI coming onto the scene. “Things kind of started to really pick up in 2014, 16,” he said, recalling the years after the weaker 2010 market. Murphy added that this was also a period where “students were getting more experience outside of class than they were inside of class” through internships, jobs, and side projects. Murphy suggested that the earlier momentum helped make computer science feel like both an academic program and a reliable pathway into work. That feeling is harder to sustain now as the industry reconfigures, which is a shift that students are seeing firsthand. Rebecca Yu, SEAS ’27, said that during a recent internship in Big Tech, she saw that “every single tech company was racing to integrate” large language models. She added that her manager said her intern class was the first to complete their assigned projects, which she attributed to the increased efficiency that comes with AI. Frank Liu, SEAS ’29, said that with AI lowering the barrier to coding, companies now expect everyone to write code. “A lot of companies outright say if you’re not using coding in your job, you might get fired for not being productive enough,” Liu said. Yu similarly expressed that students increasingly have to accept AI being a part of industry workflow, adding that many also “make use of it to maximize their productivity.” Richard Li, CC ’28, described a “franticness” among his peers as the pace of change accelerates. He explained how “some new tool” is released regularly, noting that tools rise and fall in prominence within weeks. He has come to believe that he doesn’t need to “match that speed all the time” and keep up with every development. Li has learned that AI tools allow him to “take a breath” and “get back into the loop much easier than before” when he needs to. While some companies specifically target Columbia when hiring, sending representatives to campus career fairs and recruiting large numbers from Columbia, a computer science degree cannot be treated as a static credential, Yu described. “You can’t just get your degree and stop learning after that. You have to always be learning,” Yu said. “That is something you basically have to expect for your job.” AI has not only affected students’ decisions to major in computer science, but also reshaped how the subject is taught. Across departments, faculty members no longer treat work done outside the classroom as a reliable measure of understanding, shifting instead toward in-person exams, quizzes, and attendance checks. While homework once made up as much as 60 to 70 percent of a student’s grade in computer science classes, Murphy said that breakdown has since flipped, with exams and quizzes now accounting for the majority. “The assumption—especially among pessimists—is that they’re using it to do their homework,” Murphy said. “They take the homework assignment. They put it into generative AI. Out comes the solution. Submit solution. The end.” Murphy said that faculty members ranged in their responses from fully prohibiting AI use to actively teaching students how to effectively work with AI. He said he shifted his approach this year after his teaching assistants called his belief that students weren’t using the technology “naïve,” and now permits students to use AI on assignments. His surveys of students in his introductory classes have told a more complicated story than the one so-called pessimists offer: Around 60 to 70 percent of students who reported using AI said they used it to have concepts explained to them, to clarify assignment instructions, to generate test cases, or to create practice questions. “Those are all ways that you might have had a tutor in the past to do that, and now you have this AI essentially as your tutor,” he said. Bauer has taken a different approach, teaching students how to use AI productively without sacrificing the core principles of the discipline. “People who are trained to actually use AI tools productively, while being in charge of designing the overall project, will be very much in demand in the next couple of years,” he said. Over the past year, a working group of computer science faculty has been redesigning the introductory and intermediate programming sequence to integrate generative AI as both a subject and a tool, representatives from SEAS wrote in a statement to Spectator. The effort is “coordinated” across the department, “not course-by-course,” with a systematic assessment of how AI integration is affecting student outcomes underway to shape the next round of changes. The goal, the department explained, is for students to be able to “read, verify, and reason about code, whether they or a model wrote it.” Tony Dear, senior lecturer in the computer science department, is piloting individualized AI feedback in a discrete mathematics course, while a machine learning course is also testing a Socratic AI dialogue system designed to “guide inquiry rather than supply answers,” the statement reads. Beyond individual courses, SEAS funded seven cross-departmental faculty projects in generative AI this past academic year, spanning biomedical engineering, chemical engineering, industrial engineering, and computer science, according to the statement. This phenomenon extends beyond the computer science department. SEAS’ new AI minor, which it announced in November 2025, reflects the University’s attempt to adapt. The minor is specifically designed for noncomputer science majors and aims to provide “essential AI knowledge” while emphasizing practical and responsible use across disciplines, according to the SEAS website. At the center of the minor is AI in Context, a course taught by a team of faculty from the departments of computer science, applied mathematics, philosophy, music, literature, and the Writing Center, the representatives told Spectator. Bauer described it as targeted at students who want to bring AI into fields like economics or biology, rather than as a path into software engineering itself. At the graduate level, SEAS announced a new Master of Science in artificial intelligence in February, with the inaugural cohort starting in the fall. While recognizing how AI has helped them navigate coursework, students also described its rise as isolating, even among members of the Application Development Initiative, one of Columbia’s largest computer science clubs. “As people start to ask AI for questions that they would normally ask students and members, it starts to isolate people” Li said. Alexa Kafka, BC ’27, echoed Li’s sentiment, pointing out that computer science has always been a collaborative discipline with code reviews and pull requests, even as AI makes independent work easier. Despite this, Kafka noted that she hasn’t been to office hours “in at least a year.” Bauer added that faculty are exploring long-term solutions to the assessment problem. “One of the things that we’re trying to do at the department or school level is to maybe move towards computerized testing facilities,” Bauer said, referring to ideas in the department to revitalize computer labs as an alternative to pen-and-paper exams. “We have to accept that this is the reality, for better or worse.” But more exams, students say, does not mean better learning, nor does it reflect how computer science is actually done. “Code is so variable and can be approached in so many directions, there’s never just going to be one correct answer. There can be multiple optimal solutions,” Kafka said. Students also expressed concern that the shift toward exam-heavy grading pulls focus away from the applied, project-based work that better reflects both discipline and industry expectations. ADI has tried to respond more quickly than the curriculum can. Through a vibe coding workshop this past semester, club members said they wanted to help students understand not just that AI exists, but how to use it deliberately. “Vibe coding” refers to the practice of prompting AI to write code for a task or project, and has become widespread enough that ADI felt the gap in formal instruction was worth addressing, according to Sophia Huang, BC ’29. The workshop introduced students to the concept of context engineering, which Shaina Sahu, SEAS ’27, described as not just writing a prompt, but optimizing “the rest of the relevant information that you would feed into the model.” Without that, students said that AI-generated code can fail at scale or introduce difficult-to-detect bugs. Genawi said the shift toward AI has changed what it means to be good at computer science. “I think the shift has kind of gone towards what can you create and what can you do, instead of, what do you know,” she said. Indeed, during ADI DevFest, its annual hackathon, Li said more teams are trying to complete their projects than in years past. While sign-ups have historically outpaced submissions, Li said this is beginning to change because teams “have a tool that completes the vision for them.” While many students see AI as an equalizer that lowers the barrier to entry for coding and technical work, Murphy said it also creates new equity concerns inside the classroom around who can afford stronger tools and who already knows how to use them. “The equity issues I worry about are students who have access to paid versions of things versus free versions of things,” he said. Although popular AI models like ChatGPT and Claude have free versions available, both have paid models that can reach over $100 per month, which output different qualities of code. Murphy also pointed to differences in prior exposure to AI literacy itself. “Students who go to high schools or K-12 education, where they’re taught AI literacy, prompt engineering, context engineering, they understand how to do this, as opposed to students who go to schools who don’t teach that,” he said. “Then they come in, and then they’re somehow expected to know how to use these tools.” For Genawi, those disparities begin long before students arrive on campus. “It’s very interesting to consider how lucky you were geographically,” she said. “To be born where you were is influencing your ability to get access to these spaces.” Students like Yu, though broadly apprehensive about the future of computer science, are not without hope. “I’m optimistic, because I think if you’re truly passionate about CS, there will definitely be a place in the field to do something you want to do,” she said. Senior Staff Writer Ria Vasishtha can be contacted at ria.vasishtha@columbiaspectator.com. Follow Spectator on X @ColumbiaSpec. Staff Writer Arjun Menon can be contacted at arjun.menon@columbiaspectator.com. Follow Spectator on X @ColumbiaSpec. Want to keep up with breaking news? Subscribe to our email newsletter and like Spectator on Facebook. Produced with Spectate by Emily Ta
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Punk Politics/Camp Costume is a fashion exhibition curated by (some of my) brilliant Parsons students!
I have the most amazing students. I teach Fashion Journalism at Parsons, as part of its MA Fashion Studies degree, though I have students of all different disciplines throughout the New School in my class — from fine-art photographers to investigative journalists to textile designers. And I learn about all sorts of fascinating things from them, like that designers are adding faux sweat stains to their garments now (part of a trend piece about “anatomy core”) and that real “French girl style” is actually about being “cunti cunta” (aka loud, rude, too much, liberated). So when I found out that some of my students were curating a fashion exhibition opening tonight(!!!), I just knew that it would be brilliant too. Wearable Art is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber. Subscribe It’s called Punk Politics/Camp Costuming1, and it’s up through May 10 at La Sudestada, the wonderful gallery and concept store in Greenpoint, Brooklyn. I asked the exhibit’s lead curator, Ella Birney (a talented costume and knitwear designer from Belfast who also happens to be in my class), all about it. This conversation has been edited for length and clarity. Tell me about the idea of this exhibition and how it came about. Ella Birney: For our Fashion Curation class, we had to pitch [exhibition] proposals to our professor, Jessica [Glasscock], and I really wanted to continue on the themes that I was exploring in my BA when I was studying in London a couple of years ago. My BA was very punk-inspired and very political. Everything I do, as you know from my writing, always has a slight Irish, political twist to it2. So in my BA project, it was looking at knitwear as a conveyor for exploring political identity in somewhere like Ireland, where identity is such a point of contention. And looking at the images that I generated from that project, there was something so camp about the whole thing. Like, it’s so playful and in bad taste to do a political message — like a knitted Union Jack — out of mohair. There’s something very camp about that. So that’s where it kind of became punk politics/camp costuming — looking at how from the 1970s to now there’s been protest through costume and clothing. What was your BA in? It was fashion textiles, knitwear. Very craft heavy, which — craft is never taken seriously either. That’s also a kind of spin [on the punk/camp thing]. The Union Jack knit that you made is included in the show — what is camp about knitting a Union Jack out of mohair? The whole ethos of camp is kind of bad taste, doing things that are tongue in cheek and a bit wink, wink, nudge, nudge. Like, this is a bit silly. Everything I do is like, this is a bit silly. Like, being from the North of Ireland, everything you do is political. So it’s like, everything is going to be looked at in a certain lens anyway, so we may as well lean into it. So the Union Jack was because I come from a mixed marriage — Protestant-Catholic. And in the North of Ireland, that’s still a big deal. And even though I’m a Catholic and brought up in a very like Catholic Nationalist family, there [were] Union Jacks [the symbol of the United Kingdom] on my street. So I was like, then I’m gonna make your Union Jack out of knitwear. And then that kind of all linked back to the punk movement that Vivian Westwood forefronted in the late 70s, [with her stores] Let It Rock and Seditionaries. How did you source your items? Once we decided on this exhibition idea, everyone in the class was put to [think about] what do you think can fit into punk politics/camp costuming and finding designers that fit that brief. Me and my co-curators, Dulcinea Flores and Allison Gramando, made a brief to send out — with a mood board and color stories, stuff like that — and then everyone kind of got to work emailing people. We reached out to other Parsons grads. Even through Instagram stories we’ve been able to reach so many people who were like, Yeah, of course, I’ll write something for this, or Please — let me submit stuff. It actually was quite easy sourcing things. … The Parsons thing gets you quite far. What were some great pieces you got? There’s a Brooklyn-based, nonbinary artist called Buzz Slutsky. I can’t even remember how I found them, but I came across this crazy, shoe thing — they had made all these different shoes out of papier-mâché, and the story behind them is so fantastic, so interesting. They were just so obliging, like, Of course, you can have these for a few weeks. I was really happy about that. And then we have art from a collective here called Art Comes First. And they lent loads of really amazing pieces that just tied everything together. You have your Union Jack knit in the show too. Any other pieces that you made? There’s three of my BA mohair knits. There’s the Union Jack. There’s a mohair with the word “No” — which is based on an old political campaign in Ireland that was “Ulster says no to sodomy.” And then there’s another one that is red, white and blue, like the Union Jack, but has the word “Catholic” on it and lots of holy medals. I’m so happy I got to include those. How many pieces are in the show? Between 49 and 52, something like that. A load of clothing and accessories, shoes. There’s a Brooklyn-based Irish photographer who’s given us photos. There’s also a shopping cart that is an art piece by Art Comes First that has gold knuckle dusters as the handles. There’s also lots of T-shirts, original pins from the 70s and 80s that were from people’s dads. I also brought my record player, and all of [co-curator] Allison’s dad’s original albums so everyone could play records. Oh my gosh! Yeah, it’s cool. Anything else you would like to add? If we get to do an exhibition, why would we not make it political in this day and age? I hope that people come. There’s a lot of history, because it starts back in the 70s. It’s not like chronological or anything, but there are historical objects. I hope people come out of it thinking, out of all the really horrendous decades of the 70s and 80s and 90s, all these amazing subcultures happened. There are horrible political times, but there’s art that comes out of it that lasts. Punk Politics/Camp Costume is on view May 1-10 at La Sudestada, 67 West St. Suite 513, Greenpoint, Brooklyn. RSVP for the opening Friday May 1 6pm-8pm here. There’s also a button-making and patch-making workshop and artist talk May 9. Follow the show’s Instagram page @punkxcamp.parsons. Special shout out to all the students who put on this show: Ella Birney (lead curator), Dulcinea Flores (curator), Allison Gramando (curator), Pierre Sanon (lead exhibition designer), Eliana Daneshvari (exhibition designer), Reilly Lowell (editor), Jess Gayo (researcher/writer), Joyce Gayo (researcher/writer), Maria Magdalena Ugarte Montero (researcher/writer), Cassidy Colarik (exhibition press officer), Shelby Shovein (educator), Sarah Mahnke-Baum (educator), Trinidy Coleman (graphic designer), and Leonie Soravia (project manager). Jessica Glasscock was the faculty advisor. 1 The website is definitely worth checking out. 2 This is true!
Ecovyst Announces Agreement to Acquire Calabrian Sulfur Dioxide & Sulfur Derivatives Business
/PRNewswire/ -- Ecovyst Inc. (NYSE: ECVT), a leading provider of virgin sulfuric acid and regenerated sulfuric acid products and services ("Ecovyst"),...
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