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Artificial Analysis publishes AA-AgentPerf results for Muse Spark Open

Artificial Analysis on October 24, 2026 published on AA-AgentPerf preliminary test results for Meta's newly open-weight model Muse Spark Open. The model is a 816B-parameter, 42B-active MoE, scoring 39 on the Artificial Analysis Intelligence Index. Tests show that NVIDIA B300 and GB300 each reach about 150M tokens/s per megawatt of power under throughput-first configurations; GB300 reaches about 108M and B300 about 92M at 100 tok/s output speed; AMD MI355X reaches 70M tokens/s per megawatt at 65 tok/s. Of the model's 62 layers, 46 use 2,048-token sliding window attention, reducing KV cache requirements at 1M context by about 75% versus full attention. Meta released an NVFP4 checkpoint, and AMD released an MXFP4 checkpoint. There are currently no subsequent development facts.

1Password launches password login feature for AI agents

On October 22, 2026, 1Password launched 1Password for Agents, allowing AI agents to complete logins without viewing passwords. According to 9to5Google, when an agent reaches a login form, it authenticates to 1Password using a digital key; after the user confirms the required credentials and their purpose, 1Password fills them directly into the form. The credentials are not handed to the agent and are removed once login succeeds, so the agent cannot read or reuse them. The integration currently supports only Meta's Muse and Grok Bot, with OpenAI Dots and Anthropic Claude Duet to follow. Another report says the first integrations are Meta's Muse and SpaceXSI's Grok Bot, to be deployed within the next few days; partners including Anthropic's Claude Duet, OpenAI's ChatGPT Work and dots, and Perplexity have not yet given a timeline. The service is included in personal and family subscriptions at no extra charge and currently supports only accounts hosted on 1Password.com; 1Password.eu and 1Password.ca accounts are not yet supported.

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

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.

The author judges that Apple Glasses will only be sold to people who already wear glasses

On October 24, 2026, 9to5Mac author Ben Lovejoy offered a judgment, arguing that Apple Glasses will only sell to people who already have a habit of wearing glasses. Based on his experience with the Ray-Ban Meta and Even Realities G2 smart glasses, he pointed out that Apple Glasses have limited appeal for people who do not wear glasses. According to his description, the first generation is expected to be released next year, with no display and only audio output, and the camera used only for Visual Intelligence; the second generation will have a display, with navigation and translation being the most practical scenarios, but the frequency of demand is not high. On this basis, he judges that people who wear glasses and have a sufficient budget may want the second generation, while those who do not wear glasses will be hard to persuade. At present, this judgment remains the author's personal opinion, and there are no subsequent factual developments.

Carl's AI Watts shares Personal Agent entry rankings

On October 23, 2026, Carl's AI Watts published an article ranking 13 Personal Agents by the number of apps they can connect to. According to the article, meta muse tops the list with 54, chatgpt dots has 50, gemini spark has 35, today and poke each have 30, grok bot has 20, manus cue has 15, Instinct has 12, and hark, Lingguang 2.0, Qwen Go, Hermes, and OpenClaw each have about 10. The article also notes that Hark is free with no feature limits, muse is only available in the US and Canada, and Qwen Go, Lingguang 2.0, cue, and Instinct still require invitation-only beta access. This ranking is currently only seen in this source, with no subsequent developments yet.

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.

OpenClaw says cybersecurity is developing faster than AI this week

On October 23, 2026, OpenClaw reposted and commented on the "personal AI agents" weekly roundup compiled by McBain, and offered this judgment: the only industry changing faster than AI this week is cybersecurity. The weekly roundup covers Anthropic, OpenAI, Meta, OpenClaw, Perplexity, and others. OpenClaw's comment made the above comparison in a teasing tone; there is currently no further follow-up development or independent source cross-verification.

Google paper shows that task-specialized harnesses can improve agent scores

Google published a paper proposing OO-Harness, a method for evolving task-specific agent harnesses by task type. The method evolves harnesses along code-class lines: each specialized harness inherits from a parent class and changes only the parts that its task cluster needs adjusted; a router then selects a specialized harness or keeps the base result based on the base run's results. The paper reports that on AutomationBench business workflows, the method scored 77.41%, versus 61.62% for the base harness and 63.92% for the global method Meta-Harness; on unfamiliar applications, it kept the base harness and maintained a 59.18% pass rate, while Meta-Harness's global harness dropped to 44.90%. The authors recommend using the base harness as a fallback for mixed workloads and routing to a specialized harness only when a run exposes a known problem.

Artificial Analysis publishes AA-PersonalityBench sycophancy rankings

Artificial Analysis has published the AA-PersonalityBench sycophancy trait rankings. The benchmark scores models on their sycophantic personality traits, and the results show that the three oldest models — GPT-4o, Llama 4 Maverick, and GPT-3.5 Turbo — rank highest, while Grok 4.7, Claude Fable 5.1, and Inkling rank lowest. By vendor, all five Meta models tested scored above 65, with Llama 4 Maverick at 97, Muse Spark 1.3 at 87, Muse Glimmer at 79, Muse Spark Open at 76, and Muse Wonder at 65; the Claude series all scored 55 or below; Grok 4.7 was the lowest overall. Currently, these rankings are published by Artificial Analysis as a single source, with no subsequent updates yet.

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.

Arena.ai announces that Muse Wonder Full (Max) ranks 7th on the Agent Arena

Arena.ai announces that Meta's Muse Wonder Full (Max) ranks 7th on the Agent Arena. The result covers over 6.5K real agent sessions, with a net improvement of +11.3%, helping Meta rise to 4th among labs. The same source also shows that this model is 7.5 percentage points higher than Muse Wonder (Max) and 7.8 percentage points higher than Muse Spark 1.3 (Max); its category rankings are 5th in Chat, 6th in Code, and 7th in Work. At the signal level, it ranks 6th in Praise vs. Complaint (+21.9%), 6th in Confirmed Success (+13.4%), 7th in Steerability (+11.2%), and 16th in Bash Reliability (+7.7%), with no issues in Tool Hallucination. Currently, this is the only published result, with no further developments yet.

RadixArk SGLang team open-sources SGLang-TorchTPU

The RadixArk SGLang team has open-sourced SGLang-TorchTPU. According to information published on the LMSYS Blog on October 20, 2026, the team, together with Google and Meta, launched this PyTorch-based native backend, bringing SGLang's full serving stack to Google Cloud TPU, and it has already been used in Meta's large-scale production environment. Initial support covers models including Muse Spark Open, GLM-5.3, Kimi K3, DeepSeek V4, Qwen3.8, and Gemma 4, spanning features such as speculative decoding, KV cache offloading, PD disaggregation, and FP8 KV cache. The team also used TorchTitan and Miles to complete GRPO training of Qwen3-4B on a single 4-chip TPU v7x, with the reward curve consistent with a 6-card H200 baseline within the range of random fluctuation. There are currently no subsequent development facts.

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.

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.

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.

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EssilorLuxottica reports third-quarter revenue of €7.486 billion

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