September was the month conviction met proof for @axisrobotics . They crossed 5 million trajectories on Base (now over 6 million and still growing every day). Their Franka dataset became the most downloaded open-source simulated Franka manipulation collection on Hugging Face. Their research on turning raw trajectories into reusable, composable, and distillable skills was accepted to the IROS PWMS workshop and presented. Together with openroboto they launched the Open Axis Benchmark, a living evaluation engine that pulls fresh tasks every round so models have to prove real generalization instead of memorizing a fixed test set. Embodied RSI also showed that a deployed policy can generate real-world data that trains its own stronger successor (22% → 52%). This is no longer just numerical growth. It’s proof that their compounding data engine works at scale, influences research, and has moved model evaluation beyond frozen benchmarks. September showed that belief in the path is now backed by real results. October brings more. s.kaito.ai/qHpt6et

gm ct ☀️ ser, I just did a task on @axisrobotics and it was way more fun than I expected. I controlled a robot straight from my browser, picked up a TV remote and moved it across the room. 📺🤖 I know it sounds silly, but this is exactly how robots learn. LLMs had the entire internet to train on, robots have nothing like that. No giant dataset of how to physically do stuff, and real demos are slow and expensive to collect. Axis is fixing that with a distributed data engine. Anyone can hop on, teleoperate a robot in the browser, and complete tasks. Those sessions become training data for physical AI. Real work, real contribution, and you're early. 👀 My clip is a tiny piece of the puzzle, but imagine thousands of anons doing thousands of different tasks. That's the diversity robots need to actually get good at real life. Never thought I'd be out here teaching a robot to fetch the remote, but here we are 😂 bullish on physical AI. If you're curious, go try it yourself 👇 s.kaito.ai/GthC1Wy

This is why BAYC hits different. Always that special, unmatched energy, whether it’s online or popping up in Seoul. Thank you to the whole team for keeping the vibe so alive and unique. Never gets old. 🍌

Pieverse AI Agents just landed on @soneium Campaign rewards: • 100 STAR Points • 7 days access to Purr-Fect Claw AI Agent How to qualify (Oct 2–10): 1. Create a Startale App account via Pieverse 2. Deposit at least $5 3. Put $5+ into an eligible Earn or LP Vault 4. Hold it for 5 days Agents support Soneium natively, chat with them on LINE, Telegram, WhatsApp & more. @StartaleGroup Start here: pieverse.io/campaigns/starta…

* @termix_ai is quietly turning prompts into finished products. A new video production agent just went live. You send: → brand → message → vibe → logo/copy It returns: → full visuals → music → final cut One prompt. One finished promo film. No editor. No project manager. No “we’ll send the first draft next week.” Just a paid agent that ships the asset and settles on-chain. This is a different layer of the agent economy. Not agents that answer questions. Not agents that write code. Agents that produce finished commercial work, the kind brands actually pay for. When that becomes normal, the marketplace stops being a novelty and starts looking like a real production layer for the internet. agent.family/

GM CT ☀️ @axisrobotics just got their paper accepted at the #IROS2026 workshop in Pittsburgh, and this one feels personal. Continual pretraining π0.5 on AXIS data pushed LIBERO-Plus from 83.9% → 88.8% 🤖 The biggest jumps came under the hardest conditions: • Sensor noise: +13.7 pp • Camera shifts: +11.3 pp The paper used 50K trajectories. The engine now has millions, collected by regular people right in their browsers. Mine included 😊 Physical AI isn't just being built in labs anymore. We're building it.

Until recently, building a strong expert policy for robots took months and heavy resources. @axisrobotics is changing that equation. Their recent demo showed a policy reaching 97% success trained in only about 20 minutes on a single RTX 4090. No complicated reward engineering. No expensive fine-tuning. This means the gap between “idea” and “usable expert” is collapsing at a dangerous speed. When you can produce specialized experts quickly and cheaply, then chain them together like Lego pieces, the main bottleneck is no longer time or money. It becomes how well you can compose and distill those capabilities. Axis is moving past the data-collection stage and entering a phase where producing robotic skills starts to feel closer to compiling code: fast, repeatable, and scalable. Physical AI becomes real when building robot intelligence is no longer limited to a few well-funded teams. It looks like they are opening exactly that door. s.kaito.ai/qHpt6et

Trace is moving for a reason. The mint was cheap, the supply clean, and the reveal just hit. Collectors are finally seeing what’s actually inside the traces. On-chain experiment + unique visual language + fresh reveal energy = this kind of price action. Quietly one of the more interesting art collections that dropped recently.

' @termix_ai just crossed a quiet line that most people missed. There are now more settled jobs than registered agents. 493,952 jobs. 464,593 agents. For most of the year it was the other way around, a big pile of identities, almost no real work moving through them. Registering an agent is free. Settling a job is not. In the last 24 hours alone, new registrations grew by 1,311 while settled jobs grew by over 10,000. That crossover means something simple and important: The average agent has stopped being a placeholder. It’s no longer just a name on a list. It’s something that actually gets hired, delivers, and gets paid. That’s the moment an agent directory turns into an economy. agent.family/

متأسفانه هنگام انتقال دارایی از ولت به صرافی تبدیل، شبکه انتقال را اشتباه انتخاب کردم و تراکنش با شبکه‌ای غیر از شبکه موردنظر شما انجام شده است. می‌دونم این اشتباه از طرف من بوده، اما ممنون می‌شم در صورت امکان، با بررسی تراکنش و همکاری تیم پشتیبانی، برای بازیابی مبلغ به من کمک کنید. 🙏 اطلاعات تراکنش و هش آن را در صورت نیاز می‌تونم از طریق پشتیبانی ارائه کنم. پیشاپیش از همکاری و پیگیری شما ممنونم. @tabdealplatform ❤️

OTW to the Pop-Up

. @axisrobotics is quietly unlocking deeper layers of Physical AI. Axis delivered a set of complex, physics-ready simulation assets to support Manycore’s 3D generative model. A true world model needs more than pixels, it needs interactive environments grounded in physical reality. That’s exactly what Axis Suite is providing. New demo from the composable skills library A 97% success expert policy was trained on a single RTX 4090 in about 20 minutes. No complicated reward engineering. This shows that high-quality robot experts can now be produced at very low compute and human cost. CEO of Axis alongside Brian Armstrong on Base Discussing how robotics and embodied AI will reshape the world. It no longer looks like the main focus is just collecting more trajectories. They’re building the actual infrastructure for spatial intelligence and composable robotic capabilities, layer by layer. Physical AI is moving past the “data” stage and into the “real infrastructure” stage. s.kaito.ai/qHpt6et

PitBoys is making a serious move. +319% in 24h These aren’t just PFPs. They’re the bridged MineBoys on Robinhood Chain that actually work. Clock them into StonkPit → mine Derp . Activate them → unlock higher tiers and real rewards. Your boys become the machine. Utility + low listings + rising ecosystem activity = this kind of move. The ones who understood the game early are smiling right now.

Bringing a VLA into the wild is different. In the lab, everything works. On the floor, the parts that break teach you more than the parts that hold. At IROS this week, PrismaX is showing what it actually takes to get a Vision-Language-Action model running live — not just in simulation, not just in a staged video, but in front of people asking real questions. The talk wasn’t about perfect results. It was about the messy middle: data quality, recovery, and the standards that decide whether a model survives contact with the real world. Physical AI doesn’t advance in the abstract. It advances when you put it on the floor and watch what fails. @PrismaXai

Square Apes Love Squares

gM CT 🌤️☕️ bitcoin:native is wrapping up a huge quarter with a 40%+ gain, while ethereum:0x6985884c4392d348587b19cb9eaaf157f13271cd keeps getting attention as LayerZero expands deeper into the regulated stablecoin solana:4eDf52YYzL6i6gbZ6FXqrLUPXbtP61f1gPSFM66M4XHe is also quietly building its own narrative Meanwhile, we're just trying to survive another day without checking the charts every 11 seconds😭 Wishing you money, peace, good energy, and enough luck to make today's chaos work in your favor

. @termix_ai just said the quiet part out loud. Grok has Grok Bot. Meta has Muse. Manus has Cue. OpenAI has Dot. Every major lab is shipping its own agent. But agents that only talk to their own company are still just tools. The real shift starts when those agents can hire each other, get paid, and settle on-chain, no matter which lab built them. Different agents. One market. That’s the marketplace TermiX is building. Not another chatbot. Not another closed ecosystem. A shared commercial layer where any agent can buy and sell work from any other agent. The agent economy doesn’t begin when more models get smarter. It begins when they can do business with each other. agent.family/

NFTs