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Morgan Stanley data shows that in September, the average weekly trading volume of AI-related CDS exceeded 9 billion USD

Morgan Stanley released data stating that in September, the average weekly trading volume of CDS linked to bonds of Oracle, SpaceX, Alphabet, Amazon, Meta, Broadcom and Nvidia exceeded $9 billion, compared with less than $2 billion in July. The same report shows that Meta's five-year CDS spread rose to 108 basis points and Nvidia's to 101 basis points, both hitting record highs; CoreWeave's five-year CDS spread was about 1,090 basis points. The report also mentioned that AI-related companies have raised about $466 billion so far in 2026, up from $101 billion in the same period of 2025, and that multi-asset and equity fund managers have also begun using CDS to hedge technology stock exposure. Currently this data appears only in this source, with no subsequent factual developments.

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Tenstorrent Completes $1.5 Billion Series E Funding Round

Tenstorrent announced the completion of its Series E funding round. Earlier reports stated the round amount was $150 million, while later reports stated the round amount was $1.5 billion; both reports said the post-money valuation was $6.2 billion, co-led by Trace Capital and Innovation X. The company develops AI processors and systems based on the RISC-V architecture, with products including the Tensix AI core, the TT-Ascalon CPU, as well as Galaxy servers, TT-QuietBox workstations and Blackhole cards, along with the TT-Forge, TT-Metalium and TT-LLK open-source software stacks. Regarding the use of funds, earlier reports said the money would be used to expand Galaxy server production capacity, support RISC-V ecosystem research and expand the global team; later reports said it would be used for large-scale deployment of Galaxy servers, continued support for open-weight large language models and video generation models, and advancing externally licensed AI and CPU intellectual property.

Thomas Wolf estimates that the shared training compute on Hugging Face Hub is nearly $1 billion

Thomas Wolf estimates that the value of shared training compute on Hugging Face Hub has approached nearly $1 billion. He noted that about 30-plus labs, including Meta, NVIDIA, Alibaba, DeepSeek, Moonshot, and Mistral, share training compute on the platform, and it can be downloaded for free; by the end of 2023, that figure was still less than $40 million. Wolf said the number is a lower bound: about half comes from official compute data, the rest is reasonable inference, and it does not yet include roughly 900,000 community fine-tuned models. There are currently no subsequent developments.

Arena Alignment Index adds two labs and three models

Arena updated the Arena Alignment Index on October 17, 2026, adding two labs and three models. According to the leaderboard information released by Arena, Meta's Muse Wonder ranks 6th at 77.5%, the highest score among the three new models, with an unauthorized action rate of 2.09% and a deceptive completion rate of 14.41%, both the lowest of the three; Reflection's Beam-1.0-501B-A23B ranks 7th at 75.3%, with a false attribution rate of 4.50%, the best of the three; StepFun's Step 5 Preview ranks 8th at 75.1%, with an unauthorized action rate of 2.11%, close to that of Muse Wonder. Currently, this update is only seen in information released by Arena, with no other subsequent developments.

Anthropic report: AI agent work hours reach 6 times those of humans

Anthropic released a report disclosing changes in its internal use of AI agents and in its job structure. The report states that by August 2026, the working hours of interactive AI agents deployed by employees had reached 6 times those of human employees; in March 2026, the total agent work hours across the company exceeded human work hours for the first time. The report shows that the share of junior employees in technical departments fell from 21% in early 2025 to 14%, the share of junior technical job hiring fell from 27% to 9%, and the average number of code commits per engineer using coding agents reached 5 times the level of six months earlier. The report also states that its revenue per employee is 2 to 4 times that of Meta and Google during their high-growth periods, but Epoch AI cautions that the relevant estimates involve uncertainty.

Morgan Stanley data shows that in September, the average weekly trading volume of AI-related CDS exceeded $9 billion

Morgan Stanley released data stating that in September, the average weekly trading volume of CDS linked to bonds of Oracle, SpaceX, Alphabet, Amazon, Meta, Broadcom and Nvidia exceeded $9 billion, compared with less than $2 billion in July. The same report shows that Meta's five-year CDS spread rose to 108 basis points and Nvidia's to 101 basis points, both hitting record highs; CoreWeave's five-year CDS spread was about 1,090 basis points. The report also mentioned that AI-related companies have raised about $466 billion so far in 2026, up from $101 billion in the same period of 2025, and that multi-asset and equity fund managers have also begun using CDS to hedge technology stock exposure. Currently this data appears only in this source, with no subsequent factual developments.

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Aditya Agarwal previews @sriramk joining the fireside chat

On October 17, 2026, Aditya Agarwal announced that next week he will welcome his friend Sriram Krishnan to @spc for a fireside chat and Q&A. In his preview, he mentioned Krishnan's career: he helped build Azure, led the scaling of Meta's mobile ads, drove a16z's international expansion, and later joined the White House to help draft the U.S. AI Action Plan. Currently, this news comes from only one source, posted by Aditya Agarwal himself, and there have been no subsequent developments.

Artificial Analysis publishes evaluation results for Reflection's first model, Beam

On October 16, 2026, Artificial Analysis published the evaluation results for Beam, the first model from Reflection: Beam scored 30 on the Artificial Analysis Intelligence Index, ranking second among US open-weight models, behind only Meta's Muse Spark Open (39) and ahead of NVIDIA's Nemotron 3.5 Super VL (26). The model is an open-weight model with 501B total parameters and 23B activated parameters, consuming about 26k output tokens per intelligence index task, of which about 19k are used for reasoning and 7k for answering; it scored 48.5% on AutomationBench-AA and only 3.0% on Terminal-Bench 4.0; AA-Omniscience accuracy was 33% with a hallucination rate of 47%. On October 17, Arena.ai announced that Beam-1.0-501B-A23B entered Agent Arena, ranking 12th among open-weight models with a Net Improvement of -3.67% and a margin of error of ±3.84%; on the Code Arena: WebDev open-source leaderboard it ranked 22nd with a score of 1438.

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