Every week, I organize 400 to 700 links into roughly 60 categories as part of my ongoing effort to learn about AI. This is my personal notebook, which I enjoy sharing with friends… a hobby and a labor of love, rather than a commercial publication or product.
If you arrived here through a search or shared link, this page collects the links I found for Chips and Hardware for the week ending August 28, 2026.
As part of my learning process, I like to automate the category covers. It gives me a chance to learn Python and APIs.
This week’s cover prompt was written using Claude Opus 4.7, and the image was generated using Nano Banana 2.1.
Category Cover Image Prompt: A mid-1980s murder-mystery comedy movie poster in dense pen-and-ink engraving on pure black, a wide three-story gothic Victorian mansion with twin turrets, windows glowing warm amber showing costumed suspects (a bunny-suited fab engineer holding a shimmering silicon wafer, a monocled tycoon cradling a giant GPU, a technician posing with a glowing lithography lens) alongside windows crowded with chip dies, tweezers, and stacked server accelerators, plus one window with a magnified glowing die floorplan on fogged glass; the open central door reveals a slim upright silver-haired butler with pencil mustache in black tailcoat holding a silver tray with an envelope sealed by a tiny microchip wax emblem; fat rounded white sans-serif title Chips arcing above the roofline, campy spooky theatrical.
This Week in Chips and Hardware News
Summary by Claude Sonnet 5.5 based on this week’s links:
- Nvidia's quarter and Vera Rubin ramp: Nvidia's reported Q2 revenue hit $96.2 billion, up 106% year over year, with data center at $89.0 billion. Vera Rubin NVL72 racks are in production, and Nvidia says early agentic-workload tests show up to 30x more throughput per megawatt than GB300 NVL72.
- Labs building their own silicon: OpenAI shared first benchmark results for Jalapeño, its custom inference chip, claiming higher peak throughput per kilowatt and lower latency than the commercial systems it compared against. Anthropic reportedly hired Google TPU veteran Amir Salek for its own chip effort.
- A frontier-scale model on Chinese chips: Z.ai revealed GLM-5.3-Flash, a 320B-A18B MIT-licensed model that ran entirely on Chinese AI chips during its Ox Alpha preview. SemiAnalysis said it served 100T tokens per day that way, which commentators found striking.
This summary was generated by Claude Sonnet 5.5 to help you explore the links below. Rest assured, I select, organize, and check the links by hand in Google Sheets, and write the introduction and personal commentary in The Main Newsletters myself each week as a labor of love.
This week's links related to Chips and Hardware
Meet Portable Computer, Perplexity’s new local-first agent stack on NVIDIA DGX Spark. When running locally, Portable Computer offers one-click local inference setup and an optimized agentic experience for DGX Spark. Learn more and get started today:
https://x.com/nvidia/status/2092269109086126575
Perplexity partners with Nvidia to launch Portable Computer, a fully local AI agent with zero token costs | VentureBeat
https://venturebeat.com/infrastructure/perplexity-partners-with-nvidia-to-launch-portable-computer-a-fully-local-ai-agent-with-zero-token-costs
The first CPU built for agents is going to work at scale. @SpaceX is deploying NVIDIA Vera to accelerate the orchestration, code execution, and data processing that powers its next generation of agentic AI … keeping GPUs fed and agents acting fast. From gigawatt AI factories”
https://x.com/nvidia/status/2091920680317046847
Our general-purpose coding agent just scored 100% on the ARC-AGI-3 interactive reasoning benchmark. NVIDIA AVO completed all 183 levels across all 25 public environments, figuring out what to do with no instructions, explicit rules, or stated goals.”
https://x.com/NVIDIAAI/status/2090786258981466231
OpenAI decided to keep the chip team small and use AI for a an improvement loop Early stages of Hardware in the loop RSI?”
https://x.com/beffjezos/status/2092418951586390137
Anthropic hires Google TPU veteran Amir Salek for its own chip push
https://runtimewire.com/article/anthropic-hires-google-tpu-veteran-amir-salek-chip-team
OpenAI: “Today, we shared the first measured performance results from Jalapeño, OpenAI’s first custom inference chip. On InferenceX, a public benchmark using GPT‑OSS 120B, Jalapeño delivered more peak throughput per kilowatt and lower token latency than the commercial systems in”
https://x.com/firstadopter/status/2092266927377039838
Today Hark is announcing a multi-year partnership with NVIDIA with gigawatt-scale compute capacity on next-generation Vera Rubin platforms Hark is building multimodal systems that remember who you are and what you plan to do. Our work with NVIDIA will support frontier model”
https://x.com/adcock_brett/status/2092989234189869211
Nvidia Agrees to Buy Open Source AI Platform Hugging Face For $12.9 Billion … The Information
https://www.theinformation.com/articles/nvidia-agrees-buy-open-source-model-repository-hugging-face-12-9-billion
Nvidia Is Spending $6 Billion to Build a Powerful U.S. Alternative to Chinese AI – WSJ
https://www.wsj.com/tech/ai/nvidia-is-spending-6-billion-to-build-a-powerful-u-s-alternative-to-chinese-ai-c51c38cc
Nvidia just doubled an already enormous business: Q2 revenue reached $96.2 billion, up 106% YoY and 18% QoQ. -Data Center: $89.0B, +117% YoY, +18% QoQ -GAAP net income: $59.7B, +126% YoY -Operating income: $63.7B, +124% YoY -GAAP EPS: $2.46, +128% YoY -Gross margin: 75%, up 2.6″
https://x.com/kimmonismus/status/2092737142787084468
NVIDIA’s $108b Quarter | Tomasz Tunguz
https://tomtunguz.com/nvidia-q2-fy27-earnings
Nvidia Discusses Perplexity Investment at $30 Billion-Plus Valuation … The Information
https://www.theinformation.com/articles/nvidia-discusses-perplexity-investment-30-billion-plus-valuation-considered-tech-licensing-deal
Ox being a “flash” model is insane. Serving all the traffic on Chinese chips is even more insane.”
https://x.com/theo/status/2092708047445795186
Introducing GLM-5.3-Flash – Leading capabilities at a highly competitive price – Natively multimodal with a 1M-token context window – A 320B-A18B model released under the MIT License – Previously previewed as Ox Alpha, running entirely on Chinese AI chips Blog:”
https://x.com/Zai_org/status/2092616204787626030
Ox Alpha has been unveiled as GLM-5.3-Flash, but what’s shocking is that the 100T tokens per day is served on Chinese chip. (1/3)🧵”
https://x.com/SemiAnalysis_/status/2092623833630998556
The sense of touch is the most criminally under-explored modality in robotics. Imagine doing sleight of hand wearing thick oven mitts. That’s exactly how a robot feels today if it were alive. A magnetic piece snapping into place, a paper cup peeling out of a stack, a USB”
https://x.com/DrJimFan/status/2090832821036470626
SpaceX, in partnership with Nvidia, has designed a space-optimized Vera Rubin NVL72 system for launch to orbit in Q4 next year, with significant scale in 2028″
https://x.com/elonmusk/status/2091939113008238838?s=20
we made a chip and it is fast”
https://x.com/sama/status/2092339694210040187
Since announcing Jalapeño, our first custom inference chip, we’ve been testing it and the system around it. The results show a major advance: more intelligence from every watt and faster responses, delivering both higher throughput and lower latency in one architecture without”
https://x.com/OpenAI/status/2092300846675505602
Welcome 🚀Carnice-V3-27b! 🚀 → Carnice is a 27 billion parameter model capable of beating models 10x the size in Hermes-agent, fully open-source and built on top of Qwen3.8-27B →Build to fit on Consumer GPU on a 3090+ to run locally🔥 →A full merged BF16 Qwen3.8-27B”
https://x.com/kaiostephens/status/2091710751509475543
NVIDIA Vera is heading to @awscloud. NVIDIA’s Ian Buck hand-delivered AWS’s first Vera CPU Server and Vera Rubin GPU to Willem Visser and Supreeth Sheshadri at the AWS HQ in Seattle. Vera is purpose-built for agentic AI: more tokens per dollar, faster results for users, and”
https://x.com/nvidia/status/2092960847408583120
Very interesting new paper from NVIDIA. (bookmark it) It takes a closer look at evaluating agent skills. Enterprise teams are starting to leverage shared skill libraries, and the review gate is typically a scanner that checks structure, style, and security. NVIDIA measured”
https://x.com/omarsar0/status/2091869893339812222
Congratulations to @SemiAnalysis_ on the release of AgentX 1.0 🎊, an open-source multi-turn agentic coding benchmark collected from ~$3M of real traces, running on 1000+ chips and ~2MW of continuously operated compute. We are excited to see @vllm_project’s competitive”
https://x.com/vllm_project/status/2092040745842774377
📢 First ever on-silicon NVIDIA Vera Rubin performance measured on how agents actually run. ⚡ Up to 30x more throughput per megawatt and up to 35x lower token cost than GB300 NVL72. Agentic sessions are nothing like chat or summarization workloads. Context grows across”
https://x.com/nvidia/status/2091904062077694153
From the show floor to the AI factory: Hot Chips 2026 was all about extreme co-design to accelerate agentic workloads … the most complex workload in history. Vera CPU, Vera Rubin, Groq 3 LPX, Spectrum-X Multiplane, BlueField-4 Scale-In networking. One full AI stack platform”
https://x.com/nvidia/status/2092390101959479713
GitHub – karpathy/autoresearch: AI agents running research on single-GPU nanochat training automatically · GitHub
https://github.com/karpathy/autoresearch
This is very nice work from NVIDIA. Like all high-performing approaches on ARC-AGI-3, it uses deep learning-guided on-the-fly synthesis of symbolic world models, i.e. navigating the world by generating programs to represent what you know. To be clear, like with several other”
https://x.com/fchollet/status/2090838046937645398
Could AI investment start a global sovereign debt crisis? If you look at the SpaceX-Google deal, it is already the case that the entire capex for the data center can be paid off by leasing it out for roughly 1 year. As we get closer to AGI, the returns on compute will be”
https://x.com/dwarkesh_sp/status/2092387983345516960
OpenAI and Anthropic can take compute which costs them $15b a GW, and turn it into $50b+ of revenue. In order to get the credit to build their datacenters, most neoclouds have already signed long term contracts to supply compute at these $15b/GW rates. However, Meta and SpaceX,”
https://x.com/dwarkesh_sp/status/2092681058118521169
Dylan argues that even if AI progress continues at apace and generates lots of revenue, the semiconductor industry will not be able to keep up with the labs’ current 3xing+ of compute (in watts) year over year. By the end of the decade, you end up bottlenecked on wafer fab”
https://x.com/dwarkesh_sp/status/2092990531345228024
Nvidia Climbing the Wall of Worries
https://www.mbi-deepdives.com/nvdafy2q27/
OpenAI Data Center Executive Chris Malone Departs the AI Startup – Bloomberg
https://www.bloomberg.com/news/articles/2026-08-25/openai-data-center-executive-chris-malone-departs-the-ai-startup
My AI broadly agrees with Arvind’s AI: state-level data center bans have very little impact overall on AI progress. If your concern is AI development, concentration of power, future use, or anything else other than “is a datacenter near me,” this is not a substitute for policy.”
https://x.com/emollick/status/2091973930810548261
Taiwanese prosecutors charge 9 for illegal exporting of AI servers to China | AP News
https://apnews.com/article/taiwan-china-us-nvidia-ai-server-chip-illegal-export-511e9ae69d517c49f19512d45b1a8b0c
Inference on steroid: NVIDIA’s Groq 3 LPX is now in full production, adding a dedicated token-generation accelerator to the Vera Rubin platform. NVIDIA says it reached 3,400 output tokens per second running Gemma 4 31B with a 100,000-token context in Artificial Analysis”
https://x.com/kimmonismus/status/2091926070085759448
[2406.11704] Nemotron-4 340B Technical Report
https://arxiv.org/abs/2406.11704
China still continues to produce only sub-10% of incremental world compute. But their domestic production will have a big ramp up starting 2028. We talk about what implications this has for the discussion I had with Jensen:”
https://x.com/dwarkesh_sp/status/2092718735576732102
Seeing the size, price, design of GLM 5.3 Flash, it’s natural to say it has comparable inference economics to V4-Flash (diff compute:mem balance though). So 10K t/s/NPU is realistic. 864M/day. 100T/day is just… 116K chips. 100K+… would take all their compute, but doable.”
https://x.com/teortaxesTex/status/2092778623451234734
NVIDIA Vera Rubin is ramping into full production. Congrats to the teams at @Microsoft who made this exciting milestone happen.”
https://x.com/nvidia/status/2090944279103635481
NVIDIA Vera Rubin NVL72 production racks are here. The compute tray is engineered for fast compute, assembly, and serviceability. Manufacturing is 100% automated, and every tray goes together in one minute. Congratulations to @Microsoft on the first operational Vera Rubin NVL72″
https://x.com/nvidia/status/2092337107108770116
Congratulations to Josh Parker, NVIDIA’s Head of Sustainability, on being named to @TIME’s 2026 #TIME100AI list. Learn more:
https://x.com/nvidia/status/2093036251603734919
Hot Chips 2026: CUDA Targets RISC-V – by Chester Lam
https://chipsandcheese.com/p/hot-chips-2026-cuda-targets-risc
NVIDIA Enters Full Production of Groq 3 LPX AI Inference Accelerator Chips, Supercharging Vera Rubin With The Fastest Token Generation Speeds Ever Recorded
https://wccftech.com/nvidia-groq-3-lpx-ai-inference-accelerator-full-production-supercharging-vera-rubin/
NVIDIA is building more than faster GPUs. We’re building the software and algorithms that help redefine what accelerated computing can do. CUDA-X provides the specialized software acceleration industries need to build what’s next. Watch how CUDA-X libraries turn GPU compute into”
https://x.com/nvidia/status/2091973784647451096
We are thrilled to announce that Groq will be among the first adopters of NVIDIA Groq 3 LPX, deploying it alongside NVIDIA Vera Rubin NVL72 in our purpose-built AI inference Cloud. Groq is working with Dell Technologies to deploy NVIDIA Groq 3 LPX. When Groq brings NVIDIA Groq 3″
https://x.com/GroqLLC/status/2091908837305663688
Import AI 470: No rights for machines; automating environment generation with SPADE; and building better GPU kernels with Hawkeye
https://importai.substack.com/p/import-ai-470-no-rights-for-machines
Who Eats Memory Costs? – StreetSignal
https://streetsignal.substack.com/p/who-eats-memory-costs-2a1
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