Alexandr Wang Says Muse Wonder Outperformed Astra in Physics Testing
“[Muse Wonder] definitely mogged Astra in my hardcore physics testing.” — the new beff times
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Alexandr Wang · X18 Alexandr Wang · XPicks82 Meta releases Muse Wonder and Muse Wonder Full with higher benchmark scores
Meta has released Muse Wonder and Muse Wonder Full, according to Artificial Analysis in the post quoted by Alexandr Wang. At max reasoning effort, they score 52 and 56 on the Artificial Analysis Intelligence Index v4.3, compared with Muse Spark 1.3’s 48, following a release gap of 6 weeks. Muse Wonder is available through Meta’s first-party API and Muse Code, while Muse Wonder Full is limited to Muse Code users; both have 1M-token context windows.
Why it matters: Artificial Analysis’s comparison highlights a tradeoff between Muse Wonder’s improved benchmark performance and its higher cost per task relative to Muse Spark 1.3 despite lower output token usage.
Alexandr Wang · X31 Alexandr Wang Says Muse Wonder Is State of the Art for Personal Agents
Alexandr Wang says Muse Wonder is state of the art for personal agents. He says Meta developed the Personal Superintelligence Index (PSI) internally to measure what makes a model useful for personal agents, beyond external benchmarks, and that the model performs well in areas including Active Memory and Active Focus.
TechCrunch · AI65 WindBorne wins US Air Force balloon data contract worth up to $49 million
The U.S. Air Force awarded WindBorne Systems a contract worth up to $49 million for atmospheric data collected by its autonomous weather balloons, with $1.7 million ordered so far. The Air Force pays as needed and can request data for specific regions and times. WindBorne operates about 700 balloons globally and also feeds their readings into its AI weather forecasting model; executives say the contract can support fleet expansion and hardware research and development.
TechCrunch · AIPicks83 Meta releases frontier models Muse Wonder and Muse Wonder Full
Meta’s Superintelligence Lab released Muse Wonder and Muse Wonder Full on Monday, larger models described as more capable than Muse Spark. Meta reports benchmark scores comparable to Fable 5.1 and GPT-6 Astra and emphasizes information retention through “active memory.” Wonder costs $4.00 per million input tokens and $20.00 per million output tokens through the Meta Model API; Wonder Full is available only to Muse Code subscribers. Both models will power the Muse agent.
Why it matters: The split between API access for Wonder and subscriber access for Wonder Full gives developers a concrete basis for comparing integration options within Meta’s new model lineup.
雷锋网46 OnePlus 16 Launches in China With 185Hz Display and 9,000mAh Battery
OnePlus launched the OnePlus 16 on October 12, with preorders open ahead of its October 13 sale in China. The phone features a 185Hz fourth-generation Oriental Screen, a 9,000mAh battery, and support for native 185FPS gaming; its China subsidy price starts at 5,199 yuan. The article also lists four storage configurations, with launch prices from 5,699 yuan to 8,199 yuan.
Nathan Lambert · X64 Meta introduces Muse Wonder frontier models for personal and professional agentic work
Nathan Lambert writes, “Looks like Meta is back at the frontier 🫡” He quotes @finkd introducing Muse Wonder, Meta’s new family of frontier models, with claimed state-of-the-art performance for personal and professional agentic work.
Nathan Lambert · X19 If you announce a model's benchmarks without releasing it (weights, product, api, etc "later"), feels like almost a sure thing that someone releases a better model in your category before you get it out.
If you announce a model's benchmarks without releasing it (weights, product, api, etc "later"), feels like almost a sure thing that someone releases a better model in your category before you get it out.
宝玉 · XSame news82 Meta launches Muse Wonder with developer access and conflicting consumer availability statements
Meta released Muse Wonder and Muse Wonder Full on October 12, according to Baoyu’s account of the announcement. Developers can access Muse Wonder through Meta Model API or Muse Code, while Full is available to Muse Code subscribers; Meta’s blog and Zuckerberg’s X post differ on consumer availability. The models support a 1 million Token context window and multimodal input with text output, while Meta’s reported benchmarks show strengths in sustained agentic and coding tasks alongside weaker results elsewhere.
The same story is shown in the picks as 《Meta releases frontier models Muse Wonder and Muse Wonder Full》
Artificial Analysis · XSame news81 Meta releases Muse Wonder and Muse Wonder Full with higher Artificial Analysis scores
Meta has released Muse Wonder and Muse Wonder Full, which Artificial Analysis reports score 52 and 56 on its Intelligence Index v4.3 at max reasoning effort, versus 48 for Muse Spark 1.3 (max). Muse Wonder Full improves across all ten evaluations, with the largest gains in agentic evaluations. Muse Wonder is available through Meta’s first-party API and Muse Code at launch, while Muse Wonder Full is limited to Muse Code users; Muse Wonder costs $4.52 per Intelligence Index task.
The same story is shown in the picks as 《Meta releases Muse Wonder and Muse Wonder Full with higher benchmark scores》
Alexandr Wang · X0 somehow the corposlops refused to use my video
somehow the corposlops refused to use my video
Alexandr Wang · X43 Alexandr Wang Reacts to @charlieholtz’s Post About Wonder
@charlieholtz says Meta is at the frontier and calls Wonder “really really good,” citing a security vulnerability it found, its design and visualizations, and features in its CLI. Alexandr Wang reacts: “what a wonder full world 🍉”
Alexandr Wang · X21 MUSE WONDER 🍉 this model was developed to power personal agents. three highlights: - ACTIVE MEMORY: best memory across days/weeks/months - ACTIVE FOCUS: gets your tasks done - DOMAIN EXPERTISE: sota in finance & legal, strong in health
MUSE WONDER 🍉 this model was developed to power personal agents. three highlights: - ACTIVE MEMORY: best memory across days/weeks/months - ACTIVE FOCUS: gets your tasks done - DOMAIN EXPERTISE: sota in finance & legal, strong in health
AI at Meta · X3 From rebuilding our foundation to pushing the frontier in 14 months 🚀
From rebuilding our foundation to pushing the frontier in 14 months 🚀
The Verge · AI65 Meta launches Muse Wonder and Muse Wonder Full AI models
Meta launched Muse Wonder and Muse Wonder Full, available to Muse Code subscribers starting today; Wonder is also accessible through the Meta Model API. Meta claims internal benchmark testing shows the models can rival OpenAI’s GPT-6 Astra and Anthropic’s Claude Opus 5.5 and Claude Fable 5.1. The company plans to power its Muse AI agent with Wonder, starting with subscribers, but has provided no timeline.
OpenAI Developers · X17 Already showing people what they can build with Codex? Applications to become a Codex Ambassador are open again. We support you in hosting meetups and sharing what you’ve learned: https://developers.openai.com/community/codex-ambassadors
Already showing people what they can build with Codex? Applications to become a Codex Ambassador are open again. We support you in hosting meetups and sharing what you’ve learned: https://developers.openai.com/community/codex-ambassadors
Alexandr Wang · X27 introducing muse wonder our new frontier model. state-of-the-art at personal agents and professional agents. our largest and most capable model yet—rivals the big bois
introducing muse wonder our new frontier model. state-of-the-art at personal agents and professional agents. our largest and most capable model yet—rivals the big bois
Alexandr Wang · X28 MUSE WONDER this is the culmination of over a year of research and infrastructure work in msl since we originally shipped muse spark in april, we have continued to scale our models across pre-training and RL, now reaching the frontier 🏆 see our model's improvements on the artificial analysis index:
MUSE WONDER this is the culmination of over a year of research and infrastructure work in msl since we originally shipped muse spark in april, we have continued to scale our models across pre-training and RL, now reaching the frontier 🏆 see our model's improvements on the artificial analysis index:
Alexandr Wang · X19 MUSE WONDER 🍉 muse wonder is the best model in the world for personal agents and professional agents. we evaluated our model against the best models in the world across agentic and coding tasks, and we think you all will like it.
MUSE WONDER 🍉 muse wonder is the best model in the world for personal agents and professional agents. we evaluated our model against the best models in the world across agentic and coding tasks, and we think you all will like it.
AI at Meta · XSame news70 Meta introduces Muse Wonder and Muse Wonder Full for agentic tasks
Meta introduces Muse Wonder and Muse Wonder Full, describing them as its most capable models yet and frontier models built for personal and professional agentic tasks. Muse Wonder is available today via the Meta Model API and Muse Code. Muse Wonder Full is available today for Muse Code subscribers. Muse Wonder will also soon power experiences in Meta’s personal agent product, Muse, rolling out first to subscribers.
The same story is shown in the picks as 《Meta releases frontier models Muse Wonder and Muse Wonder Full》
Mistral AI · X37 Le Chonk cooked on visual grounding. Pinpoints exactly where things are in an image. 42% on Dense 200, ahead of even frontier closed models..
Le Chonk cooked on visual grounding. Pinpoints exactly where things are in an image. 42% on Dense 200, ahead of even frontier closed models..
雷锋网26 IEIC International Embodied Intelligence Skills Competition to Test Robots on Real-World Jobs
The 2026 IEIC International Embodied Intelligence Skills Competition will test robots on real workplace tasks in Shanghai from October 23 to 25. It will feature nine tracks and 23 events, using a shared four-part, 100-point evaluation framework covering task execution, embodied data collection and feedback, autonomy, and innovation. Registration is ongoing, and winning teams may receive investment interest worth tens of millions of yuan and professional fundraising guidance.
Z.ai 智谱 · X51 Z.ai introduces GLM-Legal, built on GLM-5.3-Flash
Introducing GLM-Legal Built on GLM-5.3-Flash, GLM-Legal matches frontier models on mainstream legal benchmarks, according to Z.ai. Designed for real legal workflows: contract review, evidence analysis, compliance, and more. Tech Blog: http://z.ai/blog/glm-legal Apply for API Access: http://z.ai/consultation/legal Try AutoClaw: http://autoclaw.z.ai
Ethan Mollick · X37 If you haven’t made sure to turn on two-factor authentication on all accounts, have passwords with family in case you get voice calls asking for money, etc, now would be a good time. AI gains mean the costs of mass targeting individuals with sophisticated attacks are dropping.
If you haven’t made sure to turn on two-factor authentication on all accounts, have passwords with family in case you get voice calls asking for money, etc, now would be a good time. AI gains mean the costs of mass targeting individuals with sophisticated attacks are dropping.
Microsoft ResearchPicks65 Simulating student learning for better AI tutoring
Microsoft Research introduces StudentSim, a research system that trains personalized student simulators from publicly available, de-identified learner records to evaluate and improve AI tutors. StudentSimEval measures behavioral fidelity and guidance responsiveness across chess, second-language English writing, and mathematics, where StudentSim outperforms leading baselines. In a chess tutor study, training with StudentSim feedback achieves 90.5% accuracy versus 75.7% without reinforcement learning and 71.6% with GPT-5.4 feedback; real learner studies remain essential, and the paper and code are publicly available.
Why it matters: Evaluating both a simulated learner’s starting ability and response to guidance offers a concrete method for assessing tutor feedback beyond the correctness of an explanation.
AWS Machine Learning BlogPicks66 Run multi-node inference workloads using Ray LLM Deep Learning Containers
AWS shows how to deploy Qwen3.5-9B across two GPU nodes on Amazon EKS using Ray LLM Deep Learning Containers, with separate prefill and decode deployments behind one OpenAI-compatible endpoint. The walkthrough configures the application in YAML and uses NIXL over EFA to transfer the KV cache between nodes. It covers cluster provisioning, model invocation, transport verification, and resource cleanup.
Why it matters: The guide provides a transferable deployment pattern for separating prefill and decode, including how to verify the transport backend and avoid a silent fallback to TCP-speed communication.
AWS Machine Learning BlogPicks61 Deploy decision models with llama.cpp on Amazon SageMaker AI
AWS explains how to deploy GGUF models with its llama.cpp Deep Learning Container on Amazon SageMaker AI, then add a SemIf adapter that returns probabilities over declared options without generating answer tokens. The guide includes CPU and GPU deployment code. Across 231 JevBench tasks using Qwen3.5-4B Q4_K_M, the GPU configuration delivered 4.9 times faster p50 and 32.2 times faster p95 latency than the CPU configuration, with similar accuracy.
Why it matters: The deployment pattern shows how applications can score predefined choices without parsing generated prose, while keeping authorization, thresholds, and fallback rules under application control.
The Decoder72 Clearing chat history helps AI agents find better solutions
A Microsoft Research study reports that Fork-and-Flush helps long-running AI research agents explore better solutions by creating parallel branches that retain workspace files but discard chat history. Across 13 tasks with the same compute budget, it achieved a min-max-normalized average score of 0.78, versus 0.47 for single runs and 0.54 for best-of-4. The researchers found that accumulated context can trap agents in similar approaches, even when conversation histories are periodically compressed.
TechCrunch · AI49 Microsoft’s Brad Smith says the U.K. is best placed to lead AI regulation
Microsoft President Brad Smith called for urgent global AI safety rules, arguing that the U.K. is better positioned to lead than the U.S. or European Union. He said voluntary self-regulation lets responsible companies comply while leaving less responsible ones a concern. Smith supports legal breach reporting for rogue AI agents and spoke positively about outside evaluations before release and kill switches to pause or slow AI systems.
Clément Delangue · X16 Clément Delangue urges researchers to share their RL environments openly
If you’re a researcher, please consider sharing your RL environments openly! Something you built for one experiment could help the entire field move forward. I know we’re in dark days for sharing from frontier labs in the US, but I believe this can have a huge impact on the field and the world!
Clément Delangue · X22 Clément Delangue Reacts to a Microduck Testing Video
@antoinepirrone posted 3 minutes of uncut Microduck testing on carpet. Clément Delangue reacts: 😂 faceplant at 0:50 https://twitter.com/antoinepirrone/status/2109667437503193163
Aravind Srinivas · X40 Aravind Srinivas Thanks @MollySOShea for the Conversation
@MollySOShea says she spoke with Perplexity Founder and CEO Aravind Srinivas about why AI-native SMBs could drive the next American millionaire economic boom. Was a fun chat! Thanks for having me @MollySOShea! https://twitter.com/mollysoshea/status/2109645765958132083
NVIDIA BlogPicks79 NVIDIA Opens Vera Rubin Rack Designs and Expands AI Factory Infrastructure at OCP
NVIDIA contributed Vera Rubin rack and compute tray designs to OCP through its open MGX architecture and launched open source components for DSX AI Factory. MGX 1.2 supports rack deployments up to 250kW and adds standardized power, cooling and interconnect interfaces. NVIDIA and partners also announced facility and grid resilience specifications, Meta’s adoption of Spectrum-6 switches, plans for USFP optical modules with Cisco, and Falcon Transport support on future ConnectX-10 SuperNICs and BlueField DPUs with Google.
Why it matters: The specifications show how shared rack, cooling, power and software interfaces can give infrastructure builders a common implementation target as AI factories scale to higher power densities.
TechCrunch · AI52 Blueprints AI says it can generate permit-ready architectural blueprints in minutes
Blueprints AI says its software generates code-compliant, permit-ready architectural construction blueprints in minutes and will make its second-generation version publicly available this week. Version 2 accepts project descriptions or sketches and produces architecture, structural, mechanical, electrical, plumbing, and interior design blueprints, with design changes updating the entire project and being checked against local building codes. The co-founders say licensed professionals still review and seal documents before permit submission.
The Decoder75 Microsoft plans to scale its own Maia AI chips to gigawatt levels by 2027
Microsoft plans to deploy Azure Maia AI chips at multi-gigawatt scale starting in 2027, making them its main inference system across its products, executive Scott Guthrie writes. Maia 200 already runs Microsoft Copilot in the US, Europe, and Australia, with GitHub Copilot and Foundry following by year's end. Maia 300 ships in 2027 for long inputs, fast chats, and agentic tasks; Microsoft claims 40 percent more tokens per megawatt than leading GPU systems and up to seven times the tokens per 96-chip rack compared with a Maia 200 rack.
Alexandr Wang · X0 vibes kinda good 🍉
vibes kinda good 🍉
Mustafa Suleyman · X73 Microsoft introduces Maia 300 with 40% more tokens per watt
Mustafa Suleyman calls Microsoft’s new silicon 🔥 and highlights “40% more tokens per watt!” In the quoted announcement, Satya Nadella says Maia 300 delivers 40% more tokens per watt than leading GPU-based systems, with multi-gigawatt Maia deployments planned starting next calendar year as the primary inference system for Microsoft’s products and services. He says Maia 200 is already being deployed across the US, Europe, and Australia, delivering up to 1.7x more tokens per watt across Teams and Copilot experiences. https://twitter.com/satyanadella/status/2109631106404487523
TechCrunch · AI4 TechCrunch Disrupt 2026 Starts Tomorrow, Offering Ticket Savings of Up to $100
TechCrunch says Disrupt 2026 starts October 13 at 8 a.m. PT at San Francisco’s Moscone West and runs through October 15. Attendees can save up to $100 on a pass, get 50% off a second pass of the same ticket type, or buy a $75 Expo+ Pass if they’ve been laid off.
Josh Woodward · X48 Josh Woodward shares praise for Lenny ahead of their interview
I’ve learned from Lenny for years, but we had never met. What you see is what you get with him: he’s kind, prepared, and deeply curious. Great interviewers do their homework, and you can tell he’s in that league: he took our conversation to places that I’ve never talked about in public. Enjoy the first 60 minutes of us getting to chat together. Thank you @lennysan !
Ars Technica · AI60 Amazon has over 1 million robot workers. What’s next for human employees?
Amazon operates more than 1 million warehouse robots and plans to expand its fleet, while employing more than 1.5 million full-time and part-time human workers according to its 2025 annual report. Executives say robots reduce physically demanding tasks and injury risks, but labor advocates and researchers raise concerns about AI-driven automation. George Mason University professor Brad Greenwood says collaborative robots change workplace dynamics by working near people and potentially dictating their pace.