Top stories in robotics today: – Unitree robot dog runs 11 mph, hauls 143 lb.
– Honor teases humanoid alongside robot phone
– Audi brings robot hands to the assembly line
– UK’s Wayve nabs $1.2B for $8B valuation
– Quick hits on other robotics news
HARDWARE
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Robotics breakthroughs: robot dogs, humanoids, autonomous vehicles investments
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Burning model into chip achieves 51k tokens per second
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now add this to silicon that burns the model into the chip. And we will go from 17.000 token/s to 51.000 tokens/s inference throughput will go on to expand so much faster than we ever could have predicted. This will make for the most absurd applications.
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AI-Powered Materials Science: New Era of Automated Discovery
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🔬 New Science pod with @cusp_ai!
— Latent.Space (@latentspacepod) 25 février 2026
We are entering a new era where materials science and discovery is transitioning from slow, manual experimentation, to a high-speed search problem powered by generative AI and "physics processing units." @wellingmax argues that the foundation… pic.twitter.com/UKZ5xH9NK4🔬 New Science pod with @cusp_ai! We are entering a new era where materials science and discovery is transitioning from slow, manual experimentation, to a high-speed search problem powered by generative AI and "physics processing units." @wellingmax argues that the foundation of all modern technology—from GPUs to climate solutions—is a materials problem, and that unifying the mathematics of stochastic thermodynamics with generative AI will unlock a new paradigm of automated scientific discovery.
→ View original post on X — @wellingmax, 2026-02-25 17:50 UTC
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CPU Shortage in AI: Less Extreme Than Memory Crisis
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and yes – we even talk about the cpu shortage! just less extreme than memory.
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Liquid AI releases LFM2-24B-A2B model for on-device inference
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ollama run lfm2:24b-a2b .@liquidai's latest on-device model is here! It's the largest LFM2 model yet, and is designed to run fast on device, and fits on devices with 32GB of unified memory. Liquid AI (@liquidai) Today, we release our largest LFM2 model: LFM2-24B-A2B 🐘 > 24B total parameters > 2.3B active per token > Built on our hybrid, hardware-aware LFM2 architecture It combines LFM2’s fast, memory-efficient design with a Mixture of Experts setup, so only 2.3B parameters activate each run. The result: best-in-class efficiency, fast edge inference, and predictable log-linear scaling all in a 32GB, 2B-active MoE footprint. 🧵 — https://nitter.net/liquidai/status/2026301771539202269#m
→ View original post on X — @maximelabonne, 2026-02-24 14:36 UTC
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Liquid AI Releases Largest LFM2-24B-A2B Model with Fast Inference
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Early checkpoint of our biggest LFM2 model to date 🎉 It shows good scaling and extremely fast inference vs. gpt-oss-20b and Qwen3-30B-A3B We'll release an LFM2.5 version with more pre-training and RL in a few months Liquid AI (@liquidai) Today, we release our largest LFM2 model: LFM2-24B-A2B 🐘 > 24B total parameters > 2.3B active per token > Built on our hybrid, hardware-aware LFM2 architecture It combines LFM2’s fast, memory-efficient design with a Mixture of Experts setup, so only 2.3B parameters activate each run. The result: best-in-class efficiency, fast edge inference, and predictable log-linear scaling all in a 32GB, 2B-active MoE footprint. 🧵 — https://nitter.net/liquidai/status/2026301771539202269#m
→ View original post on X — @maximelabonne, 2026-02-24 14:31 UTC
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Meta and AMD Partner on GPU Integration for 6GW Data Center Expansion
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Meta 🤝 AMD
— AI at Meta (@AIatMeta) 24 février 2026
Today we’re announcing a multi-year agreement with @AMD to integrate their latest Instinct GPUs into our global infrastructure. With approximately 6GW of planned data center capacity dedicated to this deployment, we’re scaling our compute capacity to accelerate the… pic.twitter.com/a6lNWsfRciMeta AMD Today we’re announcing a multi-year agreement with @AMD to integrate their latest Instinct GPUs into our global infrastructure. With approximately 6GW of planned data center capacity dedicated to this deployment, we’re scaling our compute capacity to accelerate the
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TT-Boltz now runs on Tenstorrent QuietBox with 4x speedup
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Finally! TT-Boltz now runs on a @tenstorrent QuietBox, fully parallelized across all four Blackhole cards.
— Moritz Thüning (@moritzthuening) 23 février 2026
This yields a 4x speedup, making QuietBox the best product for anyone who wants to run Boltz-2 locally at scale.
Very soon we'll parallelize it on all 32 processors of a… pic.twitter.com/jYKhkmzgKUFinally! TT-Boltz now runs on a @tenstorrent QuietBox, fully parallelized across all four Blackhole cards. This yields a 4x speedup, making QuietBox the best product for anyone who wants to run Boltz-2 locally at scale. Very soon we'll parallelize it on all 32 processors of a Galaxy server. It’s pretty clear by now that GPUs aren’t the best bet for LLM inference. The same shift will happen to other fields like biotech.
→ View original post on X — @tenstorrent, 2026-02-23 20:05 UTC
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OpenAI struggles with computing power as Stargate project stalls
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Incredible reporting from @anissagardizy8 in @theinformation about OpenAI's struggle to get more computing power as Stargate—its $500B data center buildout—has floundered. theinformation.com/articles/… It includes this detail. We are in the dirt-eating phase of the AI hype cycle.
→ View original post on X — @_karenhao, 2026-02-23 14:12 UTC
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Greater Foundation for High-Performance Computing and Data Science
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A Greater Foundation for High Performance-Computing. #BigData #Analytics #DataScience #AI #MachineLearning #HPC #IoT #IIoT #Python #RStats #TensorFlow #JavaScript #ReactJS #Serverless #DataScientist #Linux #Programming #Coding #100DaysofCode https://
geni.us/Greater-HPC