Diego Prats | ๐Ÿค–

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Diego Prats | ๐Ÿค–

Diego Prats | ๐Ÿค–

@mexitlan

Chasing nonsense in physical AI and robotics. CEO & Founder at @hapticlabsai prev. VP Engineering @NexusLabs, R&D @dfinity, Eng PhD dropout @usc, @harvard

San Francisco, CA ๊ฐ€์ž…์ผ Nisan 2011
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Diego Prats | ๐Ÿค–
Diego Prats | ๐Ÿค–@mexitlanยท
I am not sure it is appreciated how much of the @OpenAI Sora shuttering is actually a reallocation of video-generating resources away from entertainment and toward physical AI. Even though they literally said: "the Sora research team continues to focus on world simulation research to advance robotics." ๐Ÿงต
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Diego Prats | ๐Ÿค– ๋ฆฌํŠธ์œ—ํ•จ
Synthefy
Synthefy@synthefyincยท
Today, weโ€™re releasing Migas 1.5: the first foundation model to fuse text and time series. Until now, forecasting models have only looked at historical numbers. Migas 1.5 changes that by letting users incorporate real-world context directly into the forecast. This enables teams to forecast with essential context like earnings reports, policy changes, market events, supply shocks, and more. This directly results in more accurate forecasting and enables complex scenario analysis, especially when historical data is sparse. Highlights: - Highest Elo rating against leading foundation models on 86 real-world datasets - 75%+ win rate against all baselines (even Migas 1.0!) - Up to 14.2% lower MAE in short-context forecasting - Fully open source - Premade Claude skill to get you started in seconds Weโ€™re excited to open-source Migas 1.5 and eager to see what the community builds with it. Links in comments.
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Diego Prats | ๐Ÿค–
Diego Prats | ๐Ÿค–@mexitlanยท
A favorite parlor game among fellow parents in tech is โ€œwhat should I tell my kids to do/study?โ€ I do not know, but I can tell you an observation (not recommendation): 1. I have NEVER met anyone in Silicon Valley whose life would have been better by knowing 10-50% more math, physics, or CS. I never met the person who because they knew a bit more calculus, they are truly happier or more successful. 2. I have met MANY people where 5-10% more discipline, patience, curiosity, grit was the difference between a great life, a good one, or painful one. And I have seen AI only sharpen the divide.
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Diego Prats | ๐Ÿค– ๋ฆฌํŠธ์œ—ํ•จ
Chris Paxton
Chris Paxton@chris_j_paxtonยท
Live demo from Generalist AI at gtc -- inserting phone into case. Next to it you can try out doing the task yourself with a Universal Robots leader/follower setup. Its harder than the robot makes it look! Seeing demos like this live and in person always hits different
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Diego Prats | ๐Ÿค–
Diego Prats | ๐Ÿค–@mexitlanยท
We did it you guys. Since posting yesterday, @HapticLabsAI went from 3 followers to 24. 800% growth. Assuming a CONSERVATIVE 50% slowdown every day, we should reach the entire human population of Earth in about 16 days. Agent population may outpace it. youtube.com/watch?v=e6LOWKโ€ฆ
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Diego Prats | ๐Ÿค–
Diego Prats | ๐Ÿค–@mexitlanยท
My pet peeve with startup podcasts is they are usually: 1. How startup X is amazing 2. Why tool Y is amazing I find these about 50% inspiring, 25% envy, 25% depressing. What Iโ€™ve always wanted instead are real problems to chew on. So as an opening salvo for my startup @HapticLabsAI, I wanted to start with exactly that for my fellow builders.
Haptic Labs@HapticLabsAI

What problems and bottlenecks keep coming up in physical AI research? We analyzed 64 episode transcripts of the brilliant @RoboPapers podcast to see which bottlenecks robotics researchers mention the most. hapticlabs.ai/blog/2026/03/0โ€ฆ

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Diego Prats | ๐Ÿค– ๋ฆฌํŠธ์œ—ํ•จ
Nexus
Nexus@NexusLabsยท
At BASS and SBC conversations around AI and crypto circled the same question: How do we trust systems we canโ€™t see inside? @alexanderfowler and @danielmarinq argued that trust will come from infrastructure designed for proofs. Read more: blog.nexus.xyz/verifiable-ai-โ€ฆ
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Diego Prats | ๐Ÿค–
Diego Prats | ๐Ÿค–@mexitlanยท
Tanner is awesome
Nexus@NexusLabs

Meet @duveZK, zkVM engineer at Nexus. He studied logic and CS, and now works on formal verification, zero-knowledge proofs, and the infrastructure powering verifiable AI.

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