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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