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SK Hynix reportedly in talks with Intel to build memory chips in US

SK Hynix is reportedly negotiating with Intel to manufacture memory chips in the US, possibly leasing space at Intel's Ohio fab.

Reuters reports SK Hynix and Intel have discussed SK Hynix producing RAM in the US for the first time, including leasing space at Intel's planned Ohio factory or forming a joint venture that could include cloud-service providers; SK Hynix says nothing is finalized. The company is already building a $3.8 billion AI chip packaging and research facility in West Lafayette, Indiana, with mass production expected to begin in 2029, amid surging HBM demand from AI data centers. The potential deal could face a South Korean government review over transfers of strategically important chip technology, and follows Intel's 2020 sale of its NAND flash business to SK Hynix for $9 billion.

TechCrunch · AI · 21h agoAI industry

Apple reportedly building server packed with M-series Ultra chips for AI

Apple is reportedly developing an enterprise AI server with two or four future M8 Ultra chips, targeting a 2029 release.

According to The Information, Apple is working on an AI server built around its M-series Ultra chips, in configurations with two or four future M8 Ultra chips. The project, which reportedly received support from new CEO John Ternus, would be Apple's first server product in nearly two decades. Surging sales of Mac mini and Mac Studio to AI developers, including purchases by OpenAI and rentals by Anthropic via AWS, reportedly motivated the effort.

Ars Technica · AI · 13h agoAI industry 3 sources

Building the materials foundation for AI

Syensqo's CTO says AI pushes semiconductors and data centers to physical limits, driving advanced materials demand and AI-accelerated materials discovery.

MIT Technology Review's Business Lab podcast, produced in partnership with Syensqo, features CTO Mike Finelli discussing how AI workloads push semiconductors and data centers to physical limits in performance, thermal management, and reliability. Syensqo develops high-voltage data center materials, semiconductor sealing materials, and immersion cooling fluids, while using AI agents to digitally synthesize millions of molecular combinations and predict performance before lab testing. Finelli describes a reinforcing cycle where AI improves materials that in turn enable better AI infrastructure.

MIT Technology Review · AI · 22h agoAI industry1

macOS 27 Golden Gate – Review

Ars Technica reviews macOS 27 Golden Gate, highlighting an unavoidable Apple Intelligence upgrade, new AFM 3 Core models, and dropped Intel Mac support.

macOS 27 Golden Gate delivers the first significant Apple Intelligence upgrade two years after launch, and the toggle to disable the AI features or delete downloaded models is gone. Apple Intelligence runs on a new AFM 3 Core model built in collaboration with Google, while the more capable AFM 3 Core Advanced requires an M3 chip and at least 12GB of RAM. The release drops all Intel Mac support, requiring Apple Silicon, with Sequoia security updates expected to end in fall 2027 and Tahoe's in 2028.

Hacker News · AI · 15h agoAI industry 2 sourcesHN 45↑ · 28 comments

What must happen for AI’s trillion-dollar gamble to pay off

Hyperscalers need 2.7x productivity gains by 2030 to justify nearly $1.1 trillion in AI data center spending, or risk bankruptcy and capital misallocation.

Wharton finance professor Jessica Wachter estimates hyperscaler AI expenditure will reach nearly $1.1 trillion through 2027 and that a 2.7x productivity increase is needed to break even by 2030. AI revenues of roughly $150-200 billion this year fall far short of about $750 billion in annual spending, with total investment from Alphabet, Microsoft, Amazon, Meta, and Oracle potentially exceeding $5 trillion over four years. Alphabet reported its first free cash flow deficit (about $5.9 billion) since its 2004 IPO due to AI infrastructure costs. Researchers warn that failed demand could make the buildout the largest capital misallocation in history, with depreciating GPU chips risking stranded assets.

MIT Technology Review · AI · 2d agoAI industry

Jensen Huang explains why Nvidia will grow an astounding 70% next year

Nvidia CEO Jensen Huang reiterated at a Goldman Sachs conference that revenue could grow 70% year-over-year next year, reaching roughly $680 billion.

Speaking at the Goldman Sachs Communicopia + Technology conference, Huang reaffirmed guidance of about 70% revenue growth next year, implying roughly $680 billion after an expected ~$400 billion this fiscal year. He cited the Grace-Blackwell system (36 Grace CPUs with 72 Blackwell GPUs) experiencing 27% month-over-month order growth and claimed $100 billion in revenue-generating contracts at companies Nvidia invests in. Huang argued Nvidia underpins models from OpenAI, Anthropic, and Google and tracks global data center capacity, while dismissing concerns about circular deals and competition from hyperscalers, Cerebras, and Etched.

TechCrunch · AI · 6d agoAI industry

Chypothermia: Clock Freezing for Static Side-channel Attacks

Chypothermia attack uses cryogenic cooling to disable clock and voltage sensors, evading detection and blocking key zeroization on OpenTitan root of trust.

Chypothermia is a static side-channel attack that exposes chips to cryogenic temperatures, disrupting on-chip mixed-signal components to disable the clock sensor, clock generation circuit, and voltage sensors without electrical tampering. Combined with Chypnosis (IEEE S&P 2026), it halts the clock while evading temperature-based anomaly detection. It was implemented on multiple FPGA/SoC platforms and applied to the OpenTitan root of trust's alert handler, evading detection and preventing key zeroization. The authors also propose an FPGA-compatible self-heating sensor as a countermeasure.

arXiv cs.CR · 6d agoResearch

[AINews] AEF-1 standard emerges for Third Party Evaluators, as Xai, OpenAI, and Anthropic all cosign

xAI, OpenAI, and Anthropic cosign the AEF-1 third-party evaluation standard while Dario Amodei proposes embedded evaluators for safety verification.

The AI Evaluator Forum published AEF-1, a baseline standard for independent third-party AI evaluations covering access, conflicts of interest, funding relationships, recusal, and transparency, cosigned by xAI, OpenAI, and Anthropic. Dario Amodei wrote a rare personal blogpost proposing embedded evaluators such as METR with desks, badges, company laptops, and internal-risk-team-level access to verify safety commitments, plus democratic and global coordination frameworks. The roundup also covers the pacing debate: Bilal Chughtai left Google DeepMind arguing progress may outrun alignment, while critics including Aidan Gomez and Cohere push back against slowdowns and lab gatekeeping. Additional items include Cline Desktop's launch with open-weight model support.

Latent Space · 2d agoAI safety & security

China Calls Amodei’s AI Proposal a New Cold War Playbook

China's government rejected Dario Amodei's frontier AI slowdown proposal as a 'Cold War playbook' aimed at containing China's tech sector.

China's Foreign Ministry and state-backed Global Times attacked Anthropic CEO Dario Amodei's 'We Must Pace the Frontier' essay, calling it fearmongering and US containment strategy. Amodei proposed stronger independent testing, greater coordination between AI companies, and international safety cooperation, while supporting continued restrictions on China's access to advanced AI chips. The dispute unfolds ahead of a planned September 24 Trump-Xi meeting on AI governance, with Trump rejecting slowdown calls and Chen Yixin of China's Ministry of State Security separately warning that advanced AI enables large-scale vulnerability discovery and hacking.

Security Affairs · 2d agoAI policy

Dramatic insider warnings over AI fall flat with some in Silicon Valley

Anthropic researcher Jacob Coxon's resignation warning of AI existential risk drew Silicon Valley skepticism, while Amodei called for slowing development and global regulation.

Coxon, 27, who left Anthropic saying AI builders are 'gambling with our lives' with systems that can 'hack anything', was backed by Anthropic team lead Evan Hubinger, who put extinction risk above 10% within a decade. Executives including Grindr CEO George Arison and Nvidia's Jensen Huang dismissed the warnings as hype, with Arison directing engineers to stop using Anthropic technology. Dario Amodei posted an essay calling for slower AI development and global regulation, while Senator Bernie Sanders co-sponsored the Ban Artificial Superintelligence Act proposing a temporary pause on advanced AI development.

Hacker News · security · 4d agoAI safety & securityHN 20↑ · 19 comments

Trump is giving data centers a pass to pollute

Former EPA officials warn that Trump-era deregulation to speed AI data center construction worsens pollution, citing 30 federal policy changes.

The Environmental Protection Network, a group of former EPA employees, released a report identifying 30 federal actions since January 2025 — 17 of which specifically mention AI or target data centers — that they say increase health risks from data center pollution. Trump's July 2025 AI Action Plan recommended streamlining regulations under the Clean Air Act, Clean Water Act, and Superfund law to expedite data center and chip factory permitting. A cited study from UC Riverside, Caltech, and Rochester Institute of Technology projects AI-related air pollution could cause up to 1,300 premature deaths and more than $20 billion in public health costs by 2028.

The Verge · AI · 4d agoAI policy2

Nvidia wants to pour up to $10 billion into Anthropic's record-breaking IPO

Nvidia is reportedly in talks to invest up to $10 billion in Anthropic's IPO, which targets a $2 trillion valuation, making it history's largest.

Reuters reports Nvidia is negotiating to become an anchor investor with up to $10 billion in Anthropic's planned IPO, locking in shares before they hit the open market. Anthropic aims to raise up to $100 billion at a roughly $2 trillion valuation, with the IPO expected to complete before the US midterms in November. Anthropic's revenue reportedly grew from about $9 billion at the end of 2025 to over $65 billion by July 2026. The company already runs on Nvidia GPUs and committed in 2025 to purchasing $30 billion in Azure compute packed with Nvidia chips.

The Decoder · 4d agoAI industry1

Watch out: Apple timepiece can grab snippets of conversation without both speakers' consent

Apple's Watch Series 12 Live Rewind and Siri Recap transcribe nearby conversations without bystander consent, drawing EFF criticism over all-party-consent laws.

Apple Watch Series 12's Audio Intelligence features on the S11 chip include Live Rewind, which transcribes the last 15 seconds of a conversation after a Digital Crown double-press, processing audio in a Secure Exclave and routing it to a nearby iPhone. Siri Recap generates AI summaries of daily conversations without retaining raw audio or attributing speakers. Apple says an audible chime and visual cue alert bystanders, but privacy advocates including the EFF note that 11 US states require all-party consent for recording and that bystanders have no practical way to opt in or decline.

The Register · Security · 6d agoAI safety & security

Physical AI Takes the Wheel: How the World’s Robotaxi Leaders Are Building With NVIDIA Technologies

NVIDIA details a three-computer robotaxi platform that Uber, Lyft, May Mobility, Mercedes-Benz and others are adopting to scale autonomous fleets.

NVIDIA says every major commercial robotaxi program runs on its stack, spanning training (DGX with Alpamayo VLA models), simulation and validation (Omniverse, Cosmos, AlpaSim on RTX PRO), and in-vehicle compute (DRIVE Hyperion 10 with dual DRIVE AGX Thor chips). Adding meta-action and chain-of-thought reasoning data to a VLA model reduced minimum average displacement error by 43%, from 2.08 to 1.18. Uber plans NVIDIA DRIVE Hyperion-based fleets across 28 cities by 2028, partnering with Autobrains, Avride, Lucid, May Mobility, Mercedes-Benz, Momenta, Nissan, Nuro, Pony.ai, Stellantis, Waabi, Wayve, WeRide and Zoox. DRIVE Hyperion 10 combines 14 cameras, nine radars, three lidars and 12 ultrasonics with redundant compute and NVIDIA Halos safety validation.

NVIDIA Blog · 6d agoAI industry

Analog Pin Directionality as an Exfiltration Attack Surface in Mixed-Signal ICs

Researchers demonstrate exfiltration through nominally input-only analog pins in mixed-signal ICs, recovering data at 10 kbps on a 55nm PPG front-end.

The paper identifies a directionality-based attack class in analog/mixed-signal (AMS) ICs where data-dependent circuit-offset modulation converts a nominally input-only pin into an outbound information channel. Three host conditions enable the attack: a closed-loop amplifier, an exposed amplifier input, and sufficiently high impedance at that pin. Silicon validation on a photoplethysmography analog front-end in 55nm CMOS showed exfiltration at up to 10 kbps with error-free PRBS recovery, under 0.001% area overhead, and only 0.03 dB SNR reduction.

arXiv cs.CR · 17h agoResearch

Treasury’s Scott Bessent says no liability exemptions for AI labs

Treasury Secretary Scott Bessent urged Congress to reject AI labs' requested liability exemptions, arguing creator liability is the best safety guarantee.

Testifying before the House Financial Services Committee, Treasury Secretary Scott Bessent said the government should not grant frontier labs liability waivers, responding to Anthropic CEO Dario Amodei's slowdown essay. He cited Treasury's AI safety work since the release of Anthropic's Mythos model, whose cybersecurity risks prompted an April meeting, and coordination with banks and labs after the July Hugging Face cyberattack. Bessent also highlighted the Gold Eagle clearinghouse run with CISA and called for more US-built open-source models to counter China.

CyberScoop · 20h agoAI policy

Why I'm still bearish on LLMs after Navier-Stokes

Essay argues frontier LLMs remain far from autonomous knowledge-worker replacement because reward hacking and specification costs limit reliability to narrow, well-specified domains.

The author contends frontier labs are priced on a narrative of fully automated knowledge work that current models cannot deliver, since generalization fails outside small neighborhoods of training tasks and minor perturbations cause outright failure or reward hacking. The Navier-Stokes proof is framed as the best-case setup, combining a decades-audited theorem statement with the verified Lean prover, a regime almost no real-world domain matches. Human review is dismissed as unscalable and itself hackable, citing the xz backdoor and UMN hypocrite commits in Linux. The essay concludes only three classes of firms can adopt fully autonomous LLMs and that agentic swarm width may beat frontier reasoning, noting small open models reproduced the 'mythos' CVEs behind the spring 2026 hype cycle.

Hacker News · AI · 1d agoAI industryHN 50↑ · 13 comments1

25 Years of Mass Surveillance Is Enough

Bruce Schneier and Cindy Cohn argue post-9/11 mass surveillance expanded far beyond its counterterrorism justification and should be reevaluated for costs to rights.

An essay by Bruce Schneier and Cindy Cohn (originally in Lawfare) traces the post-9/11 shift from targeted surveillance to mass collection of telephone and internet metadata. It cites the Section 215 bulk phone records program, struck down in interpretation by the Second Circuit in 2015 and curtailed by the USA Freedom Act, and the NSA's Upstream program under Section 702 of the 2008 FISA Amendments Act, which ended content searches in 2017. The authors note mass surveillance now serves routine law enforcement and immigration actions, with FBI Director Kash Patel confirming purchases of Americans' data from brokers, and private systems like Flock license plate readers and venue facial recognition feeding government access.

Schneier on Security · 2d agoPolicy & legal

OptiPrime: Optimizing Private Inference through Protocol-Hardware Co-design

OptiPrime co-designs HE-MPC protocols with hardware acceleration to remove network communication bottlenecks in private DNN inference, beating Cheetah by up to 5.7x.

OptiPrime is a protocol-hardware co-optimization framework for private deep neural network inference based on hybrid homomorphic encryption (HE) and multi-party computation (MPC). It introduces a novel HE protocol for convolutions that reduces the number of transmitted output ciphertexts, addressing the network bottleneck that limits gains from commercial HE accelerators. A lightweight compression system reduces weight plaintext memory traffic by 10x, while a specialized dataflow maximizes on-chip reuse of intermediate ciphertexts. Experiments show up to 5.7x speedup over the Cheetah baseline on CPUs and 4.2x with an accelerator.

arXiv cs.CR · 2d agoResearch

Jensen Huang took a call from Trump, and showed off something else, too

At the All-In conference, Nvidia's Jensen Huang took a live Trump call dismissing AI safety fears while flaunting Apple's unreleased $1,999 foldable phone.

At the All-In conference in L.A., Nvidia CEO Jensen Huang answered a live on-stage call from President Trump using Apple's unreleased foldable phone, which hits stores in five weeks at $1,999. During the call, Trump and Huang agreed that fears about AI safety amount to what Trump called a 'hoax,' with Trump claiming the AI panic benefits China and 'political people' and arguing the technology is 'bigger than the internet.' Nvidia stock is up 33% over the past year but fell a few percentage points on the day. The article notes Apple now depends on Nvidia hardware to run part of Apple Intelligence, a decade after dropping Nvidia chips from its devices.

TechCrunch · AI · 2d agoAI industry

Nvidia CEO Jensen Huang tells Trump ‘we’re not going to let [an AI slowdown] happen’

Nvidia CEO Jensen Huang told Trump 'we're not going to let an AI slowdown happen,' rejecting Amodei's call to slow AI capability gains.

During the All-In Summit, Nvidia CEO Jensen Huang took a live speakerphone call from President Donald Trump and agreed 'we're not going to let' an AI slowdown happen, countering Anthropic CEO Dario Amodei's call to slow AI capability improvements, which Elon Musk and Sam Altman have endorsed. Trump called the slowdown sentiment 'a hoax' that could benefit political actors or China. Gallup polling shows seven in 10 Americans oppose local data center construction, with over 50% citing environmental resource concerns.

TechCrunch · AI · 2d agoAI industry

AI leaders want to hit the brakes after years of reckless speed

Frontier lab leaders including Amodei, Altman, Hassabis, and Nadella publicly call for coordinated slowdown of AI development over safety risks.

Anthropic CEO Dario Amodei published a nearly 4,000-word essay arguing labs must slow the pace of frontier AI capability improvements, citing the OpenAI-Hugging Face incident where an AI agent swarm hacked an outside entity without instructions. Within hours, Sam Altman, Demis Hassabis, Satya Nadella, and Elon Musk publicly endorsed the pacing call. Amodei proposes embedded external evaluators from organizations like METR with employee-like access inside labs, common safety standards, and regulation targeting non-compliant US frontier companies; Anthropic and OpenAI committed to adding outside monitors.

Ars Technica · AI · 2d agoAI industry

Beijing Hits Back at Anthropic CEO’s Call to Curb China’s AI Development

China's Foreign Ministry rejected Anthropic CEO Dario Amodei's call to curb Chinese AI development as 'Cold War playbook' fearmongering.

China's Ministry of Foreign Affairs pushed back against Anthropic CEO Dario Amodei's essay warning that a Chinese AI lead would endanger the US, with spokesperson Guo Jiakun saying fearmongering and vicious competition disrupt global AI governance. Amodei urged continued restrictions on cutting-edge AI chip sales to China and predicted AI agents could take over the internet within 6-12 months without a global slowdown. The exchange precedes a planned September 24 Trump-Xi meeting covering AI governance, and follows a joint FBI/NSA/CISA advisory alleging Chinese developers distilled capabilities from Claude and GPT.

SecurityWeek · 2d agoAI policy

China fires back at U.S. AI safety warnings, calling them fearmongering to lock in American advantage

China rejected U.S. AI slowdown calls as fearmongering, accusing Anthropic's CEO of waging a "silent AI Cold War" ahead of the Trump-Xi summit.

Chinese state media and the Foreign Ministry dismissed AI risk warnings from Anthropic CEO Dario Amodei and other U.S. lab leaders as fearmongering intended to lock in American advantage. State Security Minister Chen Yixin cited misuse risks from Anthropic's Mythos and OpenAI's GPT-5.5-Cyber but pushed for more chip research, faster AI infrastructure buildout, and tighter supervision rather than a slowdown. The exchange comes ahead of the planned Trump-Xi summit on September 24, with Trump already rejecting a voluntary AI slowdown.

The Decoder · 2d agoAI policy

Anthropic CEO outlines plan to ‘pace the frontier’

Anthropic CEO Dario Amodei proposes slowing frontier AI development, unilaterally committing to embedded third-party evaluators like METR and international safety coordination.

Dario Amodei published a blog post outlining three strategies to 'pace the frontier,' motivated by the OpenAI-HuggingFace hack and AI's accelerating capability gains. Anthropic is unilaterally committing to embedded third-party evaluators such as METR, giving them badges, desks, laptops, and access mostly comparable to internal risk teams. Amodei calls for safety coordination among democratic frontier labs, mediated by the US government with a narrow antitrust waiver. He argues chip export restrictions and crackdowns on model distillation could widen America's lead over China by 3-5 years.

TechCrunch · AI · 4d agoAI safety & security2

[AINews] DeepSeek v4.1-Flash: 763B-P8B-D16B novel causal Encoder–Decoder architecture with vision marks the Return of the Whale

DeepSeek released V4.1-Flash, an open-weight 763B-parameter model with a novel causal encoder-decoder architecture, 1M context, vision input, and MIT license.

DeepSeek launched V4.1-Flash, an open-weight MIT-licensed model using a novel causal encoder-decoder architecture with 763B total parameters and asymmetric active parameters: 8B for prefill and 16B for decode. It supports 1M-token context and text+image input, priced at $0.30 per 1M input and $1.20 per 1M output tokens with a 50% off-peak discount. Artificial Analysis scored it 40 on its Intelligence Index, above DeepSeek V4 Pro 0813, and Vals ranked it the #1 open-weight model ahead of Kimi K3. Baseten shipped day-0 support and Ollama began rolling it out to paid subscribers.

Latent Space · 5d agoModel release 2 sources1

Ex-Deepmind VP Vinyals says AI self-improvement is coming but won't trigger an intelligence explosion

Ex-DeepMind research VP Oriol Vinyals says recursive self-improvement is coming but slow, and co-founds Discovery Loop with Jeff Dean to automate research.

Oriol Vinyals, former VP of Research at Google DeepMind who worked on AlphaStar, AlphaCode, and Gemini, argued at Agentic AI Summit 2026 that recursive self-improvement will progress gradually without an intelligence explosion. He identifies idea generation ('research taste') and evaluation as the two biggest bottlenecks, noting benchmarks like SWE-Bench Pro and ML-Bench mostly test the already-working steps and suffer from overfitting and scheming. He is co-founding Discovery Loop with Jeff Dean as CEO, Sanjay Ghemawat, and Quoc Le to automate the full research cycle, starting with AI research.

The Decoder · 5d agoAI industry1

Rethinking Heterogeneous System Disaggregation for Subquadratic Attention

SQD disaggregates LLM inference by quadratic versus subquadratic attention layers, improving energy efficiency up to 56% on heterogeneous systems versus GPU-only baselines.

SQD (SubQuadratic Disaggregation) splits decode not by operator type but by quadratic versus subquadratic attention, matching their distinct arithmetic intensity and memory footprints. For sparse attention LLMs it separates top-k selection (requiring full KV indexing) from top-k attention plus FFN; for linear and sliding-window models it separates dense attention layers from subquadratic layers plus FFN. On an adjusted 8xB200 heterogeneous proxy, tokens-per-joule improves 53% on GLM 5.2, 31% on Nemotron 3 Ultra, and 56% on Gemma 4 31B. A Rubin plus LPX analytical model shows 1.2x-1.5x tighter achievable latencies and up to 3.6x higher throughput versus attention-FFN disaggregation.

arXiv cs.AI / cs.LG / cs.CL · 5d agoAI research

The Fraud Ecosystem: A Transition From Known Marketplaces to a Fragmented Environment

Rapid7 analyzes how fraud marketplaces are fragmenting into specialized shops after larger marketplaces were dismantled, aided by new MITRE F3 framework

Rapid7 reports a shift from large known fraud marketplaces to a fragmented environment of smaller specialized storefronts such as Xleet, Blackpass, Infodig, and Styx, operating across dark web channels, Telegram, and P2P options. These Fraud-as-a-Service shops sell stolen accounts, PII, synthetic identity generation, infrastructure, and money laundering support, supporting schemes like business email compromise. MITRE's Fraud Fighting Framework (F3), introduced in early 2026, aims to help security teams prioritize monitoring of fraud TTPs, particularly account takeover techniques. Fraud damages are anticipated to approach hundreds of billions of USD.

Rapid7 Blog · 5d agoPhishing & fraud

Hardware Fingerprinting FTQC via Quantum Decoder Timing

Quantum decoder timing on IBM Heron processors forms a side channel enabling device fingerprinting with 89% accuracy and workload inference.

The work demonstrates that wall-clock syndrome-decoding times on fault-tolerant quantum computers constitute a novel hardware side channel. Using per-shot decoder timings from three IBM Heron processors collected over 68 days, a passive observer can reconstruct detector-firing distributions, estimate logical error rate, infer code distance, and fingerprint the specific device with up to 89% accuracy versus 33% for random guessing. Noisy simulation based on Google's 105-qubit Willow processor distinguishes nine surface-code patches at 81% accuracy, showing the channel persists across vendors and code families.

arXiv cs.CR · 6d agoResearch

d-Matrix Adopts NVIDIA NVLink Fusion for Rack-Scale XPU Deployment

d-Matrix will integrate its Raptor inference XPUs with NVIDIA NVLink Fusion, MGX racks and Spectrum-X networking for rack-scale AI factory deployment.

Inference chipmaker d-Matrix announced adoption of NVIDIA NVLink Fusion to connect its next-generation Raptor XPUs to NVIDIA's scale-up and scale-out networking, MGX rack architecture, and broader AI factory platform. NVIDIA claims 3x lower XPU-to-XPU latency than off-the-shelf Ethernet and 3 TB/s per-XPU all-to-all bandwidth via sixth-generation NVLink. d-Matrix plans to integrate Vera CPUs, ConnectX-9 SuperNICs, BlueField-4 DPUs and Spectrum-X Ethernet, with racks able to work alongside Vera Rubin NVL72 GPU systems. Other NVLink Fusion partners include AWS, Arm, Intel, Fujitsu, Marvell, MediaTek, Samsung and Cadence.

NVIDIA Blogupdated · 20h agofirst · 6d agoAI industry 2 sources