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Sierra announces ARR surpassing $400 million
On October 30, 2026, Sierra announced on its official blog that the company's annualized revenue (ARR) had surpassed $400 million. Sierra said that in the third quarter alone it added more than $150 million in ARR, exceeding its ARR for the entire previous year. The company also said it took six months for ARR to grow from $100 million to $200 million, and only five months to grow from $200 million to $400 million, and that it currently serves nearly 50% of Fortune 50 companies. In the same blog post, Sierra mentioned that a large U.S. retailer with revenue exceeding $40 billion used Ghostwriter to go from first meeting to agent launch in 27 days, and said it is working with more than 50 companies including Meta, Shopify, Stripe, and Walmart to advance Poppy, an open standard for personal agent interaction.
w from $100 million to $200 million, and only five months to grow from $200 million to $400 million, and that it currently serves nearly 50% of Fortune 50 companies. In the same blog post, Sierra mentioned that a large U.S. retailer with revenue exceeding $40 billion used Ghostwriter to go from first meeting to agent launch in 27 days, and said it is working with more than 50 companies including Meta, Shopify, Stripe, and Walmart to advance Poppy, an open standard for personal agent interaction.
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Warp Sciences raises $215 million to build AI chemistry research lab
Warp Sciences has completed a $215 million financing round to build a chemistry research facility in the United States, using AI and robotics to assist pharmaceutical and biotechnology companies in developing drugs. The company was founded by Kevin Weil, former head of OpenAI's science initiatives, about six months after he left OpenAI; its co-founders include former White House chief data scientist DJ Patil and former Meta executive Mano Paluri. The company operates as a chemistry contract research organization (CRO), initially focusing on lead compound optimization through analog synthesis. Experimental data will be used to train its AI models, while chemists wear cameras and sensor-equipped gloves to demonstrate actions for robots to learn experimental procedures. The round was led by Lightspeed Venture Partners, with participation from Premji Invest, Mayfield, IVP, Lux, Conviction, Menlo Ventures, 01 Advisors and others; angel investors include Brian Armstrong, Ion Stoica and Dylan Field. No further developments have been disclosed at this time.
Kevin Weil, former head of OpenAI's science initiatives, about six months after he left OpenAI; its co-founders include former White House chief data scientist DJ Patil and former Meta executive Mano Paluri. The company operates as a chemistry contract research organization (CRO), initially focusing on lead compound optimization through analog synthesis. Experimental data will be used to train its AI models, while chemists wear cameras and sensor-equipped gloves to demonstrate actions for robots
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Sensor Tower data shows Muse reached 10.2 million downloads in the US
Sensor Tower data shows that Meta's AI assistant Muse reached 10.2 million downloads in the US within 40 days of launch, with cumulative global downloads of 10.9 million, making it only the 12th app to reach this milestone. The same report also noted that Meta allocated 39% of its total advertising budget in October to promoting Muse, up from 23% the previous month; Muse's 7-day retention rate in the US was 30% and its 14-day retention rate was 23%, higher than the averages of 19% and 16% for competitors such as ChatGPT, Claude, and Grok. There are currently no new follow-up developments on this event.
Sensor Tower data shows that Meta's AI assistant Muse reached 10.2 million downloads in the US within 40 days of launch, with cumulative global downloads of 10.9 million, making it only the 12th app to reach this milestone. The same report also noted that Meta allocated 39% of its total advertising budget in October to promoting Muse, up from 23% the previous month; Muse's 7-day retention rate in the US was 30% and its 14-day retention rate was 23%, higher than the averages of 19% and 16% for co
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Sensor Tower data shows Muse reached 10.2 million downloads in the US
Sensor Tower data shows that Meta's AI assistant Muse reached 10.2 million downloads in the US. Reports say that within 40 days of launch, Muse hit 10.2 million US downloads and 10.9 million worldwide, becoming only the 12th app to reach this milestone. The reports also note that Meta allocated 39% of its advertising budget in October to promoting Muse; its US 7-day retention rate was 30% and its 14-day retention rate was 23%, above the competitor average of 19% and 16%. On October 16, Muse's daily active users reached 2.5 million for the first time. The app is currently available only in the US and Canada.
Sensor Tower data shows that Meta's AI assistant Muse reached 10.2 million downloads in the US. Reports say that within 40 days of launch, Muse hit 10.2 million US downloads and 10.9 million worldwide, becoming only the 12th app to reach this milestone. The reports also note that Meta allocated 39% of its advertising budget in October to promoting Muse; its US 7-day retention rate was 30% and its 14-day retention rate was 23%, above the competitor average of 19% and 16%. On October 16, Muse's da
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Matt Turck announced that he is leading Daytona's Series B funding round
Matt Turck announced that he is leading Daytona's Series B funding round. According to Fortune Tech, Daytona, which provides cloud sandboxes for AI agents, has completed a $60 million Series B funding round at a valuation of $1 billion, led by FirstMark, bringing its total funding to approximately $91 million. Matt Turck said that FirstMark led the Series A round earlier this year and is now leading the Series B round as well. The report also said that Daytona's customers include Anthropic, OpenAI, Nvidia, Cursor, Cognition, Meta, and Cohere; CEO Burazin said the company's revenue run rate grew 25-fold between January and September, and said it can provision a new sandbox for an agent within 60 milliseconds.
tion of $1 billion, led by FirstMark, bringing its total funding to approximately $91 million. Matt Turck said that FirstMark led the Series A round earlier this year and is now leading the Series B round as well. The report also said that Daytona's customers include Anthropic, OpenAI, Nvidia, Cursor, Cognition, Meta, and Cohere; CEO Burazin said the company's revenue run rate grew 25-fold between January and September, and said it can provision a new sandbox for an agent within 60 milliseconds.
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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.
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
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Google open-sources TorchTPU native PyTorch stack
Google collaborated with Meta's PyTorch team to launch the open-source project TorchTPU, providing a native PyTorch backend for Google TPU; migration only requires changing model.to("cuda") to model.to("tpu"). The project supports both eager and torch.compile modes, adds a new DeferAndFuse eager mode, covers about 450 Aten operators, and has been verified to run out of the box on 4,917 Hugging Face models, with a Tier 1 pass rate of 98% and Tier 2 numerical consistency relative to GPU of 97%. The official statement says it has been used in the inference and training production workloads of some Google Cloud major customers, and is integrated with vLLM, SGLang, TorchTitan, Ray, and TorchRec. Subsequent reports said that at PyTorch Conference North America 2026, Google open-sourced TorchTPU, whose runtime no longer depends on JAX, and existing workloads can be migrated with only minor code changes; PyTorch noted that TorchTPU's default Skinny Collectives scheme suffers roughly 30–40% end-to-end performance loss under distributed workloads compared with optimized schemes, and achieving peak performance still requires Pallas kernels and vLLM-T
Google collaborated with Meta's PyTorch team to launch the open-source project TorchTPU, providing a native PyTorch backend for Google TPU; migration only requires changing model.to("cuda") to model.to("tpu"). The project supports both eager and torch.compile modes, adds a new DeferAndFuse eager mode, covers about 450 Aten operators, and has been verified to run out of the box on 4,917 Hugging Face models, with a Tier 1 pass rate of 98% and Tier 2 numerical consistency relative to GPU of 97%. Th
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MiniMax thanks for bringing H3 to TPU and looks forward to open-source work on efficient video inference
MiniMax responded to SGLang including MiniMax H3 in the TPU support list of SGLang-TorchTPU, expressing thanks and saying it looks forward to more open-source work around efficient video inference. SGLang said that SGLang-TorchTPU was jointly built by SGLang, the Google TPU team, and the Meta PyTorch team, has been used for Meta's production inference, and supports models including Muse Spark Open, GLM-5.3 Flash, Kimi K3, Ling 3.1 Flash, and MiniMax H3. There are currently no facts about subsequent developments.
to SGLang including MiniMax H3 in the TPU support list of SGLang-TorchTPU, expressing thanks and saying it looks forward to more open-source work around efficient video inference. SGLang said that SGLang-TorchTPU was jointly built by SGLang, the Google TPU team, and the Meta PyTorch team, has been used for Meta's production inference, and supports models including Muse Spark Open, GLM-5.3 Flash, Kimi K3, Ling 3.1 Flash, and MiniMax H3. There are currently no facts about subsequent developments.
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Trump demands data centers generate their own power and pay dividends to communities
On October 21, 2026, Trump posted on Truth Social stating that large new data centers must generate their own power and pay cash "dividends" to their host communities. Related reports noted that the closest existing commitment is the Ratepayer Protection Pledge signed in March of that year by Amazon, Google, Meta, Microsoft, OpenAI, Oracle, and xAI, under which signatories pledged to build or purchase generating capacity and bear infrastructure upgrade costs, though experts believe the pledge may not be enforceable at the federal level. Trump said the dividend proposal goes further than that pledge. Reports on October 22 further stated that Trump also demanded that data centers supply surplus power to local communities free of charge or sell it to them, and noted that communities across the United States have continued to protest AI data center projects over rising electricity prices, noise, water shortages, and other issues. There are currently no facts on subsequent developments.
dividends" to their host communities. Related reports noted that the closest existing commitment is the Ratepayer Protection Pledge signed in March of that year by Amazon, Google, Meta, Microsoft, OpenAI, Oracle, and xAI, under which signatories pledged to build or purchase generating capacity and bear infrastructure upgrade costs, though experts believe the pledge may not be enforceable at the federal level. Trump said the dividend proposal goes further than that pledge. Reports on October 22 f
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Sensor Tower reports Muse's U.S. downloads reached 10.2 million
Sensor Tower released data showing that Meta's AI app Muse reached 10.2 million downloads in the United States. According to a TechCrunch AI report on October 21, 2026, Muse has accumulated 10.9 million downloads since its launch in September, of which 10.2 million were in the U.S. market. The same report, citing Sensor Tower data, said that Muse's 7-day retention rate in the U.S. was 30% and its 14-day retention rate was 23%, higher than the average levels of 19% and 16% for ChatGPT, Claude and Grok; on October 16, its daily active users reached 2.5 million for the first time, up 15% month over month. The report also said that Meta spent 39% of its advertising budget in October on promoting Muse, up from 23% the previous month. There are currently no subsequent developments in this matter.
Sensor Tower released data showing that Meta's AI app Muse reached 10.2 million downloads in the United States. According to a TechCrunch AI report on October 21, 2026, Muse has accumulated 10.9 million downloads since its launch in September, of which 10.2 million were in the U.S. market. The same report, citing Sensor Tower data, said that Muse's 7-day retention rate in the U.S. was 30% and its 14-day retention rate was 23%, higher than the average levels of 19% and 16% for ChatGPT, Claude and
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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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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.
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 hav
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