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  • Etched re-doubles valuation 💰, Google collabs with AMD on TPU 🤝, Cerebras takes on Nvidia ⚔️

    From TLDR Hardware@VERT to All on Wed Aug 19 13:41:39 2026
    Etched raised $700 million at a $21 billion valuation, led by Jane
    Street, just a month after closing a $10.3 billion round and eight
    months removed ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌  ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ 


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    TLDR

    TLDR HARDWARE 2026-08-19

    📱

    HEADLINES AND LAUNCHES

    ETCHED DOUBLES VALUATION AGAIN TO $21B, JANE STREET PUTS FIRST RACK
    INTO PRODUCTION (3 MINUTE READ) [4]

    Etched raised $700 million at a $21 billion valuation, led by Jane
    Street, just a month after closing a $10.3 billion round and eight
    months removed from a $5 billion valuation in December. The jump is
    backed by real deployment: Jane Street tested and bought Etched's
    hardware before investing, and has now put its first “frontier
    inference cluster” rack into production in its own data center.
    Etched's pitch centers on two custom-built components for AI
    inference, a low-voltage prefill chip and a new memory/interconnect
    design for the decode stage, and the company has walked back its
    original plan to etch specific models into silicon in favor of systems
    that run any frontier model.

    GOOGLE REPORTEDLY TAPS AMD TO DESIGN NEXT-GENERATION TPU (3 MINUTE
    READ) [5]

    Google is reportedly collaborating with AMD to develop a
    10th-generation TPU variant featuring on-package CPU cores and
    advanced 3D packaging. While Google maintains its long-standing
    partnership with Broadcom for conventional AI accelerators, this
    hybrid design is expected to leverage AMD's x86 CPU IP and SoIC
    packaging expertise to integrate general-purpose compute directly
    alongside TPU matrix engines. The architectural shift targets complex reinforcement learning, reasoning, and agentic workloads that demand low-latency execution and higher CPU-to-accelerator compute ratios
    than standard LLM pipelines.

    🔨

    ENGINEERING AND APPLICATIONS

    CEREBRAS SAYS ITS NEW COMPUTER BOOSTS AI SPEED ADVANTAGE OVER NVIDIA
    (3 MINUTE READ) [6]

    Cerebras Systems has announced its next-generation wafer-scale AI supercomputing system, claiming substantial speed and throughput
    advantages over Nvidia's flagship accelerators. Built around its
    massive single-wafer processor architecture, the new machine
    eliminates inter-chip interconnect bottlenecks to deliver ultra-low
    latency and higher tokens-per-second performance for large language
    models. The rollout sharpens competition in datacenter AI
    infrastructure as Cerebras pitches its specialized wafer-scale silicon
    as a higher-performance, power-efficient alternative to traditional
    multi-GPU clusters for frontier model training and real-time
    inference.

    NVIDIA PLANS TO USE TSMC 1.6NM PROCESS FOR FEYNMAN IN H2 2028 (3
    MINUTE READ) [7]

    Nvidia has reserved advanced production capacity on TSMC's 1.6nm
    (A16) manufacturing node for its next-generation "Feynman"
    architecture, slated for production in the second half of 2028.
    Incorporating nanosheet transistors alongside backside power delivery
    networks, TSMC's A16 process offers substantial improvements in logic
    density, power efficiency, and signal routing. By securing early
    foundry capacity, Nvidia locked in its long-term hardware roadmap.

    🧠

    RESEARCH AND PROTOTYPES

    DATA CENTERS BUILT IN WEEKS (SPONSOR) [8]

    Runware is building its own infrastructure to make AI compute cheaper
    and more abundant. Sonic Inference Pods pack up to 1200 GPUs into
    modular 1MW data centers, deployed in weeks rather than years and
    purpose-built to squeeze more performance from every GPU. Run any AI
    workload on them through Runware Serverless [8].

    FLUID-SIDE OBSERVABILITY EXPANDS AI HARDWARE RELIABILITY (4 MINUTE
    READ) [9]

    As liquid cooling becomes standard for high-power AI accelerators,
    heat now travels through a whole chain - cold plate, manifold, hoses, distribution unit, and facility heat rejection - rather than staying
    inside the server, meaning problems anywhere along that path can
    quietly eat into a chip's thermal margin before temperature alarms
    ever trigger. Component temperature alone only confirms a chip is
    currently within limits - it doesn't reveal how hard the control
    system is working to hold that temperature or how much margin is left,
    since pumps and valves are designed to compensate for developing
    issues invisibly.

    800VDC PUSHES AI POWER DESIGN FROM GRID TO GATE (4 MINUTE READ) [10]

    This article details how AI datacenters are evaluating the transition
    to 800VDC architectures of power distribution. Moving away from
    current 48V distribution streamlines the conversion path from
    medium-voltage grid AC to sub-1V silicon, cutting conversion heat
    losses and reducing heavy copper cabling requirements. Realizing this grid-to-gate efficiency relies on silicon carbide (SiC) and gallium
    nitride (GaN) power semiconductors, solid-state transformers, and
    upgraded DC-rated switchgear to manage high-voltage safety and rapid
    load switching across AI clusters. While these technologies are
    rapidly maturing, it still may take years to change datacenter designs
    that form the bedrock of all computing stacks.

    🎁

    MISCELLANEOUS

    CHINA'S AI HARDWARE EXPORTS OFFER A WAY OUT OF WALL STREET'S CIRCULAR
    AI TRADE (4 MINUTE READ) [11]

    US AI investment has become dangerously circular. Suppliers are
    financing customers who spend that capital back on the suppliers' own
    hardware, making it hard to separate real end-user demand from
    financial engineering. China's push into overseas industrial AI
    hardware, robotics, data-center equipment, and automated production
    systems has a cleaner signal, since a robot shipped abroad and
    installed on a factory floor can be checked against customs data and
    production volumes rather than internal financing loops.

    THE US-CHINA TECH WAR IS COMING FOR AI'S PLUMBING (3 MINUTE READ)
    [12]

    The reported FCC ban on Chinese optical transceivers shows that the
    US-China tech war is expanding past chips and into the smallest links
    of AI's physical plumbing. Washington's concern centers on data theft,
    service disruption, and long-term dependence, since these modules sit physically embedded throughout the network and could theoretically
    carry malware. A sudden ban risks backfiring, as US suppliers can't
    match Chinese scale, leading hyperscalers like Amazon and Microsoft to
    face real supply disruption if forced to substitute quickly.

    ⚡

    QUICK LINKS

    GROQ VALUED AT $3.5 BILLION IN FUNDING ROUND AFTER NVIDIA DEAL (3
    MINUTE READ) [13]

    AI chip startup Groq has reached a $3.5 billion valuation in a new
    funding round following its IP acquisition by Nvidia.

    SELF-DRIVING TRUCKS ARE OFFICIALLY TESTING ON CALIFORNIA HIGHWAYS (3
    MINUTE READ) [14]

    Autonomous trucking company Kodiak Robotics has officially commenced
    road testing on public California highways following state regulatory clearance.

    NOKIA QUITS R&D IN CHINA AND CUTS 1,600 JOBS (3 MINUTE READ) [15]

    Nokia is shutting down its research and development operations in
    China and cutting approximately 1,600 jobs as part of a broader
    corporate restructuring and cost-reduction program.

    ETCHED IS SCOOPING UP NVIDIA TALENT (3 MINUTE READ) [16]

    Etched, a high-flying AI chip startup, is aggressively poaching
    senior hardware engineers and system architects directly from Nvidia.

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    Thanks for reading,
    Kshitij Sudan [21] & Adi Nikumbh [22]

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    [4] https://links.tldrnewsletter.com/3j7xIa
    [5] https://www.tomshardware.com/tech-industry/artificial-intelligence/google-reportedly-taps-amd-to-design-next-generation-tpu-hybrid-ai-asic-could-integrate-on-package-cpu-cores-for-reinforcement-learning?utm_source=tldrhardware
    [6] https://links.tldrnewsletter.com/b7bpPO
    [7] https://www.electronicsweekly.com/news/business/nvidia-books-tsmc-1-6nm-process-for-feynman-in-h2-2028-2026-08/?utm_source=tldrhardware
    [8] https://runware.ai/sonic-inference-pod?utm_source=tldr-tech&utm_medium=paid-newsletter&utm_campaign=2026-08-20206-08-sonic_pods_launch&utm_content=2026-08-14_sonic-pods-hardware-nl-secondary-1
    [9] https://www.eetimes.com/fluid-side-observability-expands-ai-hardware-reliability/?utm_source=tldrhardware
    [10] https://semiengineering.com/800vdc-pushes-ai-power-design-from-grid-to-gate/?utm_source=tldrhardware
    [11] https://www.investing.com/analysis/chinas-ai-hardware-boom-offers-an-escape-from-wall-streets-circular-trade-200685935?utm_source=tldrhardware
    [12] https://www.scmp.com/opinion/world-opinion/article/3363884/us-china-tech-war-coming-ais-plumbing?utm_source=tldrhardware
    [13] https://links.tldrnewsletter.com/h6DZxT
    [14] https://techcrunch.com/2026/08/14/self-driving-trucks-are-officially-testing-on-california-highways/?utm_source=tldrhardware
    [15] https://www.lightreading.com/business-transformation/nokia-quits-r-d-in-china-and-cuts-1-600-jobs?utm_source=tldrhardware
    [16] https://links.tldrnewsletter.com/eqdF8C
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    [19] https://jobs.ashbyhq.com/tldr.tech/c227b917-a6a4-40ce-8950-d3e165357871 [20] https://www.linkedin.com/feed/update/urn:li:activity:7401699691039830016/ [21] https://www.linkedin.com/in/kshitij-sudan/
    [22] https://www.linkedin.com/in/adinikumbh
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    [24] https://a.tldrnewsletter.com/unsubscribe?ep=1&l=516aef72-d5bc-11ee-9229-6b70acf0ae94&lc=48ce571c-d4e0-11f0-8279-1f6dc2dca83a&p=3b7df81e-9b97-11f1-a84e-898ce6402c70&pt=campaign&pv=4&spa=1787144422&t=1787146898&s=86ad2bd888b328fe9abe6d48cbf4003c4d8ab28a469a82f6eda04ef3966ac527

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