mberk 🦾 @mberketh

At Axis Robotics, our vision is to build a compounding data engine—one that connects large-scale pretraining data, corrective post-training data, model deployment, and failure feedback in a continuously improving loop. Over the next 6–12 months, we will advance this vision across three connected fronts. On the product side, we plan to scale our egocentric data pipeline in September, with tens of thousands of hours already collected and product requirements being shaped with frontier labs. In October, we will expand our simulation data across more robot embodiments and atomic capabilities. By year-end, we plan to release a large-scale post-training dataset built through human-gated DAgger (HG-DAgger), where the policy acts autonomously and contributors intervene only when it needs correction. On the network side, we will expand our contributor ecosystem into Latin America and Eastern Europe, strengthen our 100K+ contributor network and grow toward 10K DAU. This expansion is designed to support the production of more than 500 hours of egocentric data and 50 hours of simulation data per day while building capacity for corrective post-training data. On the commercialization side, we plan to complete two to three new paid pilots by year-end and work toward becoming a preferred vendor for foundation model companies in Q1 next year. The longer-term goal is to embed the data engine directly into the training and deployment workflows of robot hardware companies, model developers, and industrial operators. These are not separate tracks. They reinforce the same flywheel: broader data coverage produces stronger models; stronger models reach new states; and new failures reveal what data should be collected next. That is the future we are building toward: Scale to produce data continuously. Diversity to reflect the complexity of the physical world. A closed loop to turn deployment feedback and failures into the next round of model improvement. Our north star is not simply more data. It is faster model evolution.

Axis Robotics @axisrobotics

3 weeks ago

We’re thrilled to announce a $12M Seed round, led by @hack_vc, with participation from @NomadCapital_io , @PiCoreTeam Ventures , @10kventure and top angel investors. Physical AI has a data problem. Models need more than static datasets—they need diverse data that evolves with

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Brian Armstrong/ Jesse/ Base anytime they accidentally attract users to Base:

Base Batches 003 Robotics Track by @virtuals_io has officially concluded at @ns. After 8 weeks of pushing robotics onchain, here are the winners: 🏆 Champion — @opengotchi 🥈 1st Runner-Up — @shadowcleague 🥉 2nd Runner-Up — @Vader_AI_ The future of robotics is on @base.

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Everyone missed what @Vader_AI_ was actually building... They weren't building a data collection app. They were building the physical AI infrastructure stack for the humanoid era. Built on @virtuals_io Most people saw the glasses phase and stopped there. Wear a headset. Complete structured daily tasks on camera. Earn $VADER. That was the surface layer. What was actually happening: Vader was collecting egocentric video data from human participants at scale. First-person footage of real physical actions in real environments. The exact perspective from which robotic systems must eventually operate. You weren't just doing tasks for tokens... You were building the training dataset for the next generation of humanoid robots. Now that data layer is plugged into a full three-layer physical AI infrastructure protocol. ➜ Layer 1 collects three modalities of physical AI training data ⇁ EgoPlay: egocentric video from participants completing structured daily tasks ⇁ SimPlay: synthetic data generated in physics-based simulation environments (MuJoCo) ⇁ Remote Teleops: high-fidelity manipulation data recorded via robotic arm control ➜ Layer 2 turns that data into trained models ⇁ World Action Models (WAMs) learn general representations of physical action ⇁ Vision Language Action Models (VLAs) bridge visual input with language-conditioned outputs ⇁Task-Specific Policy networks trained for defined manipulation or locomotion tasks ➜ Layer 3 closes the loop on real hardware ⇁ Partners validate trained models on Unitree G1 humanoids in controlled lab environments ⇁ No hardware ownership required ⇁ Access is gated by staking $VADER End-to-end. Raw data to trained model to hardware validation. One protocol. Season 2 is live right now. 200K $VADER pool. Snapshot May 4. Distribution May 11. Data contributed today feeds partners who stake $VADER to access it. Those partners train robotics models and validate them on deployed physical hardware. The protocol grows as participation grows. Think about what early contributors actually built. A dataset of grounded, real-world human action data that doesn't exist outside closed institutional research labs. The exact type of data robotics teams worldwide need to train competitive physical AI systems. You were the training signal. The humanoids are the output. If humanoid deployment is the next compute race, who else is building a protocol that lets everyday participants own a piece of that pipeline from day one? The glasses were just the start...

Just keep building.

jesse.base.eth @jessepollak

10 months ago

Just keep building.

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@Pirat_Nation Rip Kaito, Wallchain, Cookie, Galxe, Layer 3 users

Bir anda bu kadar tokenizasyon haberi gelmesinin arkasında birçok sebep yatıyor olabilir. Bunları düşünürken tokenizasyonun projelere doğrudan maddi katkı sağladığını ama komünite açısından ciddi riskler barındırdığını unutmamak lazım: -Halihazırda FED faizlerinin düşmeye devam etmesi ve son çeyrek için de oluşan düşüş beklentisi, kısaca “iyi bir market ortamında likiditeyi yakalama” isteği -ABD tarafındaki yeni düzenlemeler doğrudan tokenizasyonu ilgilendirmesiyle şimdiden hazırlanma veya inside bilgiyle şartlar zorlaşmadan/yasaklar gelmeden hareket etme - Narrative/airdrop marketing etkisi ile “mindshare” kaptırmadan direkt rakiplerin de marketing gücünden de faydalanmak -Linea’nın gelişi, ardından M*tamask, Rabby ve özellikle komünite gücü ile maddi olarak rahat olan Base’in böyle bir karar alması işlerin kurumsal taraftan gelmiş bir haberle hızlandığını gösteriyor olabilir. Ya da belki de sadece basit bir “builder’a para dağıtma dropu” 🤷 Yada kesin onların bir bildiği vardır biz de çıkalım düşüncesi… özetle; hareketli bir 3 ay bizi bekliyor ama bence $eth ve altlar için iyi bir çeyrek görebiliriz 👍🙏

Introducing EgoPlay 👓 A gamified platform where users complete daily tasks with smart glasses to earn Vader Points. Now in Closed Beta! 🧵

1/ We’re excited to share that Monitize AI raised $1.1M in funding to accelerate our mission: powering Physical AI.

NOT BABY JOKIC. CALL HIM DADDY ŞENGÜN. #EuroBasket

Always building on $BOB 🟠 Welcome to the future of BTCFi 🟠 Spark $SPK- ✅ Build-on-Bitcoin $BoB- 👀 soon..

mberk 🦾 @mberketh

2 years ago

Herkese iyi haftalar, Droplarla geçen güzel bir hafta oluyor. Artık geride kaldığını hatta işe yaramaktan çok zarar verdiğini düşündüğümüz airdrop marketing'i piyasaya yeniden etki etmeye başladı. Özetle, yeni kullanıcıları çekmek için yeni servet hikayeleri ortaya çıkmaya

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@defigod_eth @build_on_bob @cookiedotfun Where is snapschat? we need it.. @cookiedotfun

@build_on_bob gBOB

bro wtf kind of deal is that? @phantom blocks @stakedhype as a scam/phishing site 😂

@inkonchain gmink

jokerace.io/contest/ink/0x…

Ink @inkonchain takip eden varsa, son 2 gündür ağın resmi maskotunun ve dolayısıyla meme token’ının adı tartışılıyor. Ekip @jokerace_io üzerinden bir oylama açtı; 0.0001 ether ile oy kullanabiliyorsunuz. Şu an 20 dakika kadar süre kaldı ve en çok oyu $anita almış görünüyor (risk alındı :D) Oy kullanmadıysanız, aşağıdaki linkten kapanmadan önce siz de oy verebilirsiniz

GM 🌞 SuperStacks are where onchain activity meets social momentum. ⚡️ We’re tracking who’s rising across the Superchain — networks and dapps like Optimism, Soneium, UniChain, Uniswap, USD₮₀, Base, and more are all competing for the spotlight. 🚀 Social signals are shaping who climbs the SuperStacks leaderboard and who’s truly capturing the Superchain’s energy. At SuperSocialScore, we’re working on a deep-dive social analysis report that will reveal: ✅ Which protocols lead social engagement ✅ Who’s gaining momentum fast ✅ Where the next wave of onchain alpha is emerging This isn’t just numbers — we’re uncovering the narratives, key voices, and communities shaping the future of the Superchain. We’re putting the final touches on our comprehensive SuperStacks social analysis report, packed with data-driven insights, protocol rankings, and trends you won’t want to miss. It’s your roadmap to who’s truly winning the social layer of the Superchain. 🔥 👉 The report drops soon — follow us and stay ahead of the alpha!