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Cohere Completes First Close of Series E, Targeting Up to C$7 Billion in Funding at a C$35.7 Billion Valuation

On October 29, 2026, Cohere announced the first close of its Series E financing, targeting up to C$7 billion in funding at a corresponding valuation of C$35.7 billion, led by a company under Schwarz Group, with Bell Ventures, Bullhound Capital, and the Government of Canada joining as new investors. Cohere said this is the largest private financing for a Canadian tech company, and the funds will be used to advance its model and product roadmap, verticalized AI solutions for regulated industries, and long-term compute infrastructure. The company also disclosed that as of Q3 2026, its annual recurring revenue grew 165% year-over-year, with global customers increasing to 300.

Nvidia Invests $3 Billion in Meta's Muse Agent and Reaches Partnership

Nvidia has invested $3 billion in Meta's Muse agent and the Muse series models, and the two sides announced that the Muse models (Wonder and Wonder Full) and the agent will run on Nvidia infrastructure. Meta plans to expand its deployment of Nvidia hardware, including using Vera Rubin and Vera CPU for next-generation AI agents, and the two sides are also exploring using Nvidia's OpenShell reference architecture for agent security. Meta's consumer-grade Muse agent has reached 10.9 million downloads and 2.5 million daily active users since its launch on September 8, but it has not yet become a profit engine.

AI Drives a Wave of Formal Verification Startups as &Truth Raises $70 Million

WIRED reports that generative AI is pushing formal verification toward commercialization. &Truth has raised $70 million and launched publicly, while Harmonic has raised a cumulative $295 million, and its math AI agent Aristotle supports verification of C code and Verilog hardware designs. Stanford researcher Chuyue Sun used AI tools to complete an engineering project in less than half a day at a cost of under $500, whereas three experts working by hand took five months to complete the same work. The report also notes that the technology is still at the prototype stage, that customers' willingness to pay and adoption methods remain unclear, and that Antithesis's Will Wilson calls formal verification a "trap" that can only provide partial guarantees.

Iluvatar CoreX Tianyao 300 Benchmarked Against H200: Training Throughput Reaches 1.33x That of H100

Iluvatar CoreX held its first live demonstration of the Tianyao 300 at a media open day on October 28, claiming that in comparative tests on large language models such as GLM-5.3 as well as text-to-image and text-to-video scenarios, it outperformed the H200 overall. On the training side, in an 8-GPU full-system FP8-precision demonstration based on Qwen3-32B, the Tianyao 300 achieved per-GPU effective throughput 1.33 times that of the H100. The Tianyao 300 was unveiled at this year's World Artificial Intelligence Conference in July, features 144GB of memory, and its IXL144 supernode integrates 144 GPUs with roughly 10.1TB of memory in a single standard rack, reducing the cost per million effective tokens by about 40% compared with mainstream international solutions.

Microsoft's AI infrastructure spending is $6.5 billion less than expected due to delayed data center deliveries

Microsoft's capital expenditure (including finance leases) for the September quarter was $45.2 billion, $6.5 billion less than analysts' expected $51.7 billion, but still up about 30% year-over-year. CFO Amy Hood attributed the shortfall to delays in third-party data center capacity deliveries, with the related facilities expected to come online in the second half of Microsoft's fiscal year, while also lowering its calendar 2026 spending forecast from $175 billion to $170 billion. Microsoft added 24 data centers in the quarter and has signed contracts worth more than $80 billion with CoreWeave, Nebius, and Nscale since 2023; Azure revenue grew 48% to $33.2 billion.

Google TPUs will run on a hyperscale cloud outside Google for the first time, with Oracle deploying starting in 2027

Google's TPUs will run on a hyperscale cloud outside Google for the first time, with Oracle deploying capacity starting in calendar year 2027 and gradually expanding over several years. Oracle provides power, cooling, and data center networking; its Acceleron network connects TPU clusters to Oracle's databases and storage, letting enterprises fine-tune and deploy models next to their data without cross-cloud transfers. Google says the eighth-generation TPU delivers up to 12.6 PFLOPS of FP4 compute per chip, achieves over 97% effective cluster uptime during large-scale training, and improves performance per dollar by up to 80% for low-latency serving; its open-source TorchTPU stack lets existing PyTorch code and tools such as vLLM and SGLang run on TPUs without rewriting models.

Anthropic Publishes Early Progress of Claude in Drug Discovery

On October 27, 2026, Anthropic released a life sciences progress update, disclosing early results from collaborations with six institutions—BigHat Biosciences, Bristol Myers Squibb, Divergence Labs, Enveda, Generate Biomedicines, and The Column Group—as well as its first in-house drug program. Six scientists at Generate used Claude Code to build an agent system and selected candidates from 186 CAR T cell therapy signaling domain redesigns; one design was about 70% shorter than the standard version, and in laboratory tests the number of cell surface receptors was about 10 times the original. Divergence Labs said Claude generated about 35,000 antibody designs under about 2,750 hours of H100 compute, and 20 of the 91 tested disruptor designs measurably stripped already-bound IgE. Enveda used Claude to review 1,061 pages of production batch records, reducing review time from 25.9 hours to 2.8 hours, and said drafting Module 2 of an investigational new drug application was shortened from about three months to four hours. Anthropic emphasized that these results are still early, mostly preclinical, and safety and efficacy have not yet been validated in patients.

Oracle Cloud announces the introduction of Google TPU, with services to begin in 2027

At the Oracle AI World 2026 keynote, Oracle announced that it will bring Google's self-developed AI chip, Google TPU, into Oracle Cloud Infrastructure, and plans to begin offering Google TPU services in 2027. Oracle said it will provide supporting infrastructure such as power, cooling, and intra-data-center networking for large-scale deployments. The article also mentioned that Google Cloud last week open-sourced TorchTPU, which enables native PyTorch support for TPU.

PyTorch Conference 2026 held in San Jose, announces progress on TorchTPU and TorchNeuron

PyTorch Conference North America 2026 was held on October 20–21 in San Jose, attracting more than 3,500 attendees and focusing on accelerating open intelligence and projects including PyTorch, vLLM, DeepSpeed, Ray, Helion, and Safetensors. The event announced TorchTPU, a native PyTorch TPU backend developed in collaboration between Google and Meta, as well as TorchNeuron, a native backend for AWS Trainium, which entered public testing under Apache 2.0 on October 20. Shopify shared a case study of building a continuous learning loop with PyTorch and vLLM, saying it compresses production failures into model weights every day and has reduced serving costs by 96%.

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China's Ministry of Commerce plans to include AI models in the export control catalog

China's Ministry of Commerce and Ministry of Science and Technology issued Announcement No. 48 of 2026 on October 16, proposing to add 40 items to the Catalogue of Technologies Prohibited or Restricted from Export in China, of which 14 are prohibited from export and 26 are restricted from export, and to implement pre-export registration for all newly added technologies effective immediately. The draft sets three thresholds for frontier models: ≥10^26 FLOP, ≥2T parameters, or reaching a globally leading level, and also covers AI chip design, memory chips, ten-thousand-card-level clusters, agents, AIGC detection tools, training data, and cyber offense and defense capabilities; scenarios such as open source, self-built overseas data centers, and overseas tape-out may use the report-and-export channel. The public comment period runs until November 15.

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OpenAI plans to raise $30 billion at a $1.4 trillion valuation, ahead of Anthropic's IPO

According to Reuters, OpenAI is accelerating a $30 billion fundraising at a valuation that could exceed $1.4 trillion, with existing investors including SoftBank and MGX in talks to participate. OpenAI told investors its annualized revenue has reached $50 billion and is expected to rise to $70 billion by the end of 2026; its previous valuation was $852 billion in March 2026. The report also mentions that Anthropic is expected to IPO in mid-November at a valuation of up to $2 trillion, with third-quarter 2026 revenue of $16.8 billion and first-half compute and infrastructure spending of nearly $9 billion.

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Arda Industries raises $232 million to make production lines easier to adjust with AI

Arda Industries officially launched with $232 million in funding, led by Accel, Altimeter, Founders Fund and Khosla Ventures, with participation from XYZ Venture Capital, 8VC, SVAngel and Felicis. The company's co-founder and CEO is Bob McGrew, former Chief Research Officer at OpenAI. Its platform lets users upload product blueprints and then automatically plan production lines, determine which robots to use and generate visual work instructions. Its current customers are concentrated in defense and data center electronics; Anduril uses it to optimize production lines. The company's long-term plan is to enter the consumer electronics market and develop AI agents that can adapt to new equipment within days.

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