$META Connect 2026 keynote is today at 7 PM ET, with Mark Zuckerberg presenting. What to watch for: • Next-gen glasses, incl. possible camera-free models • Project Phoenix mixed-reality headset • New Muse AI updates + deeper wearable integration • HorizonOS / avatar updates • More details on Meta’s broader AI strategy

Meet E-Commerce Bench, a new benchmark for long-horizon autonomous business operations. 🚀 Agents start with ¥100,000 to run online stores for 365 days, handling sourcing, negotiation, pricing, promotions, inventory and cash flow, in a market driven by real e-commerce data. What's inside: 👀 - Real economics: 6886 products, 576 suppliers (152 fraudsters), 600-minute workdays, storage fees, returns and reputation. - Long-horizon learning: almost no model learns to buy cheaper or improve its strategies over a full year of operation. - Seven-axis evaluation: beyond year-end assets, we score six more dimensions, revealing that no single model dominates across the board. Learn more about E-Commerce Bench: 👇 - Blog: - Paper: - Project:  - Code: 

NEW SKILL: This team take humanoid parkour to the next level! This project involves @zhenkirito123, @Yuanhang__Zhang, @pabbeel, @carlo_sferrazza, @GuanyaShi, and others. Called Perceptive Humanoid Parkour (PHP), it lets a Unitree G1 humanoid (29 DoF, 1.3 m) run long-horizon, vision-based parkour and decide on its own whether to step over, climb onto, vault, or roll off obstacles, using only onboard depth sensing (a 30 Hz camera) plus a discrete 2D velocity command from the operator. It builds the motions by motion matching, a nearest-neighbor search in a 27-dimensional feature space (imported from the video-game industry) that stitches retargeted atomic human clips into long-horizon kinematic trajectories through a shared Locomotion to Skill to Locomotion manifold. It then trains per-motion RL tracking experts (with a privileged height scan) and distills them into one depth-based multi-skill student via DAgger combined with RL. It replaces hand-scripted skill sequencing and operator-triggered skill selection. The onboard depth-only student holds 0.95 to 1.00 success across obstacle heights in simulation, while a naive end-to-end depth policy collapses from 0.95 to 0.07/0.08 at 58 and 76 cm. The upside comes from distilling privileged-height-scan experts and from motion-matching composition, not from training onboard from scratch. The operator sends only a coarse 2D velocity (W/A/D keys), and the robot itself picks which skill to run from the depth image. The training data contains only single-obstacle traversals, so the ability to chain skills across a multi-obstacle course is generalization the policy was never explicitly taught. Transitions are constructed in kinematics, not rediscovered by learning. Every skill enters and exits through a shared locomotion manifold, so no hand-captured skill-to-skill transition clip is needed. Motion matching densifies a sparse library into smooth long-horizon trajectories before any RL. The entire parkour library is only about 66 seconds of mocap, and each skill is just a few seconds. Ablating approach-distance variety ("Extreme Distances") drops the 76 and 94 cm climbs to 0.62 and 0.64, and "Half Density" drops the 76 cm climb to 0.32. Motion matching's job is to manufacture stride-phase and approach variety out of seconds of data. It clears a 1.25 m wall (96 percent of its 1.3 m height) in 3.63 s, and a cat-vault peaks at 3.41 m/s clearing a 0.4 m by 0.5 m obstacle in 0.8 s. A single 30 Hz depth stream drives both traversal and runtime re-planning, shown by displacing obstacles about 0.5 m mid-run.

Anthropic Head of Economics @PeterMcCrory reveals the 3 AI singularities his team is racing to understand: "I like to think about three different singularities that might be on the horizon and trying to understand the economic forces that relate to them." "One is the software singularity, and trying to understand the economics of recursive self-improvement is a really important research question." "The second is the labor market impact of the technology, how quickly the productivity benefits materialize, and whether we're on the cusp of an economic singularity." "The third is the possibility of a Coasean singularity. Increasingly, people are relying on AI systems to take economic actions on their behalf. If that produces a collapse in transaction costs, that might reshape how systems of economic exchange are organized. We did a really cool pilot experiment last year called Project DEAL to explore some of those ideas." @AnthropicAI

Most people in crypto know me as a kind of economics-special situations-accounting type person, but I used to be an archaeologist. I recently had a new archaeologist (kid of a client of a friend) ask me for advice as they start their first private sector archaeology project. One of the defining features of private contracting in archaeology is that work is measured in weeks or months, not years. So you need to constantly be prospecting for work. I explained to this kid that, as the end of a project is on the horizon, you need to email 5+ clients per day, and after 48 hours pick up the phone and call. It’s harder to say no to someone on the phone. I’m not sure why. But my point was that even in bad weather, in the winter (frozen ground is bad for archaeological work), in a recession, someone has work somewhere. But the kid’s takeaway was about phone calls. Do people below a certain age not do regular phone calls? I don’t know. Maybe it’s this one 22 year old. But I feel like I’ve run into it before. But it struck me as a possible generational divide. In crypto, we generally do video calls (often with the camera off). So doing even less seemed less scary to me? Anyone out there have thoughts or data l on whether this is an anecdotal story or part of a larger trend of avoiding phone calls?

SOMEONE VIBE CODED A RACING GAME WITH FORZA LEVEL GRAPHICS THAT RUNS ENTIRELY IN YOUR BROWSER he wanted to see if he could make something that looks like forza horizon or need for speed, but runs in a browser tab and doesnt need a fancy gpu, because he doesnt even have one so he just started experimenting with claude and kept pushing > he grabbed 3d models for the cars, guardrails and streetlights off sites like sketchfab, then had claude compress them to cut the computational load > textures and skies came from polyhaven, also compressed and optimized so it stays light > physics run on rapier, so the car actually handles instead of just sliding around > he started on sonnet, then switched to opus 4.8 once the project got complex enough > and he built the whole thing on the 20 dollar claude pro plan a year ago this was a full studio with a render pipeline and a team. now its one guy, a browser, and claude

SpaceX 15-Year Investment @elonmusk My evaluation of a long-term bullish investment for SpaceX based on a 15-year investment horizon. The evaluation assumes SpaceX evolves beyond aerospace into a global infrastructure platform spanning communications, defense, transportation, AI infrastructure, and the emerging space economy. Key Value Drivers - Starlink broadband growth
- Direct-to-cell mobile connectivity
- Government and defense contracts
- Starship and launch-cost reduction
- Orbital infrastructure
- Lunar and Mars logistics
- Future industries enabled by low-cost access to space An extremely important development is the impact of large AI infrastructure contracts on the valuation of SpaceX. A key component of the bullish investment thesis is that the market may be underestimating the value of recurring AI compute revenue when compared with traditional launch and satellite communications businesses. Google AI Infrastructure Contract Recent reports indicate that Google entered into a computing capacity agreement with SpaceX valued at approximately $920 million per month. If maintained over the reported contract period, the agreement represents nearly $30 billion of contracted revenue. Anthropic Contract In addition to Google, reports indicate that Anthropic entered into a compute-capacity agreement valued at approximately $1.25 billion per month. Together, the Google and Anthropic contracts imply annualized revenue of approximately $26 billion. Why This Matters Many investors continue to value SpaceX primarily as a launch company and satellite communications provider. However, these AI-related contracts suggest the emergence of a third major business segment: AI infrastructure and compute services. Potential Strategic Position If SpaceX successfully integrates launch services, Starlink communications, AI infrastructure, and future orbital computing capabilities, the company could evolve into a hybrid of a cloud infrastructure provider, global telecommunications company, defense contractor, and transportation platform. Investment Implications Recurring infrastructure revenue generally receives higher valuation multiples than project-based revenue streams. Consequently, sustained growth in AI infrastructure revenue could materially alter the market’s perception of SpaceX and support valuation frameworks significantly above those used for traditional aerospace companies. Bull Case SpaceX becomes the dominant communications and transportation infrastructure provider for Earth and near-Earth economic activity. Starlink achieves global scale, Starship reaches full operational capability, and multiple new industries emerge around orbital infrastructure. Base Case SpaceX remains the global leader in launch services and satellite communications while generating strong growth from Starlink and defense-related revenue streams. Bear Case Growth continues but at a slower pace due to regulatory, competitive, technical, or capital allocation challenges. Comparison with Historic Winners Historically, Amazon, NVIDIA, Apple, Microsoft, and Tesla created extraordinary shareholder wealth by becoming platform companies rather than remaining confined to their original industries. The bullish SpaceX thesis assumes a similar transition. Key Risks The principal risks include execution risk, regulatory risk, geopolitical factors, competition, slower-than-expected adoption of space-based industries, and the possibility that SpaceX enables large industries without capturing most of the resulting value. Conclusion The bullish investment thesis is that SpaceX is transitioning from a launch and communications company into a foundational infrastructure platform serving communications, AI, defense, and future space-based industries. If successful, this transition could support valuation outcomes substantially above conventional aerospace benchmarks A bet on technological progress, and the emergence of a large space-based economy

🇺🇸 Jensen Huang said data centers should look better, and that the industry already knows how... Many local fights start when a blank warehouse, a new substation, and a fence show up on the edge of town, and the council kills the project. The same week, designers point to mines, bunkers, and waste heat that warms homes and greenhouses. A plant that fits the street gets through, while a box that eats the horizon stalls. Better design and reused heat are also how the next wave gets built in places already angry about the last one. Writer: Lucas

🚨 Claude Fable 5.1 and Mythos 5.1 are now available in the API. Just found the details in Anthropic's official docs. This looks like a serious upgrade for long-running agentic work. - 1M token context + 128K max output - Stronger agentic coding, research, documents, spreadsheets and slides - Better computer use and long-horizon tasks - Adaptive thinking with adjustable effort - 75% cheaper cache reads than Fable 5 - $10/M input tokens - $50/M output tokens - $0.25/M cached input tokens - Fable 5.1 is available to all API customers - Mythos 5.1 is currently limited to Project Glasswing participants

😃Meet Qwen3.8-Max On Qwen Cloud — our most capable model to date. Next week, the open weights of Qwen3.8-Max will be released, and Qwen3.8-27B is also going open-weights to meet you all! 👏Qwen3.8-Max, a new bar for coding and cowork at 2.4T parameters: - Autonomous coding: 10+ days of self-evolving development, from empty folder to production without hand-holding, complete project trace in the GitHub： - Real work, real results: Production-quality deliverables across hundreds of professions. - Long-horizon mastery: System-level autonomous planning with closed-loop adaptive learning, driving 500+ turns of chip design optimization and 365 days of e-commerce strategy. - Native multimodal intelligence: Vision isn't just input — it's a continuous feedback loop for planning, execution, and self-correction. 💰Pricing: Input: $2.0 / M tokens Output: $6.0 / M tokens Implicit Caching: $0.25 / M tokens Start building with Qwen3.8-Max!🚀 👇Try Qwen3.8-Max and get your API KEY on Qwen Cloud