Ty

848 posts

Ty

Ty

@TyneeWorld

Robot man 🤖

Katılım Temmuz 2025
578 Takip Edilen852 Takipçiler
Ty
Ty@TyneeWorld·
@markgrinev Best breakfast in a minute 😤
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Mark Grinev
Mark Grinev@markgrinev·
@TyneeWorld bro really liked the breakfast we had this morning 😂
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Ty
Ty@TyneeWorld·
One of the best feelings in the world is working with a team of cracked people that you also enjoy spending time with
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chris
chris@chrislevan·
who's working on cool things in physical ai in canada 🇨🇦
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Jim Fan
Jim Fan@DrJimFan·
Announcing DreamDojo: our open-source, interactive world model that takes robot motor controls and generates the future in pixels. No engine, no meshes, no hand-authored dynamics. It's Simulation 2.0. Time for robotics to take the bitter lesson pill. Real-world robot learning is bottlenecked by time, wear, safety, and resets. If we want Physical AI to move at pretraining speed, we need a simulator that adapts to pretraining scale with as little human engineering as possible. Our key insights: (1) human egocentric videos are a scalable source of first-person physics; (2) latent actions make them "robot-readable" across different hardware; (3) real-time inference unlocks live teleop, policy eval, and test-time planning *inside* a dream. We pre-train on 44K hours of human videos: cheap, abundant, and collected with zero robot-in-the-loop. Humans have already explored the combinatorics: we grasp, pour, fold, assemble, fail, retry—across cluttered scenes, shifting viewpoints, changing light, and hour-long task chains—at a scale no robot fleet could match. The missing piece: these videos have no action labels. So we introduce latent actions: a unified representation inferred directly from videos that captures "what changed between world states" without knowing the underlying hardware. This lets us train on any first-person video as if it came with motor commands attached. As a result, DreamDojo generalizes zero-shot to objects and environments never seen in any robot training set, because humans saw them first. Next, we post-train onto each robot to fit its specific hardware. Think of it as separating "how the world looks and behaves" from "how this particular robot actuates." The base model follows the general physical rules, then "snaps onto" the robot's unique mechanics. It's kind of like loading a new character and scene assets into Unreal Engine, but done through gradient descent and generalizes far beyond the post-training dataset. A world simulator is only useful if it runs fast enough to close the loop. We train a real-time version of DreamDojo that runs at 10 FPS, stable for over a minute of continuous rollout. This unlocks exciting possibilities: - Live teleoperation *inside* a dream. Connect a VR controller, stream actions into DreamDojo, and teleop a virtual robot in real time. We demo this on Unitree G1 with a PICO headset and one RTX 5090. - Policy evaluation. You can benchmark a policy checkpoint in DreamDojo instead of the real world. The simulated success rates strongly correlate with real-world results - accurate enough to rank checkpoints without burning a single motor. - Model-based planning. Sample multiple action proposals → simulate them all in parallel → pick the best future. Gains +17% real-world success out of the box on a fruit packing task. We open-source everything!! Weights, code, post-training dataset, eval set, and whitepaper with tons of details to reproduce. DreamDojo is based on NVIDIA Cosmos, which is open-weight too. 2026 is the year of World Models for physical AI. We want you to build with us. Happy scaling! Links in thread:
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Ty
Ty@TyneeWorld·
Physical intelligence of robots is surpassing the average physical intelligence of most humans. The combination of incredible manufacturing scale, rapid customer deployments, great research partners along with large volumes of hardware sales is Unitree’s winning formula. We’re closing in on the ChatGPT moment for robotics. What a time to be alive!
CIX 🦾@cixliv

We got break dancing humanoids before GTA 6

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Ty
Ty@TyneeWorld·
@jbillingsley @MeckaAI The days are long indeed but wouldn’t have it any other way 🤝
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Dhravya Shah
Dhravya Shah@DhravyaShah·
average waterloo guy
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Chinmay Jindal@chinmayjindal_

Hey everyone, I wanted to share an update regarding my offer at @GroqInc / @nvidia. I was set to join Groq in Summer 2026 to work on distributed systems and software infrastructure that support their next-generation inference technology. However, following the recent $20B agreement between @nvidia and @GroqInc, my offer was unfortunately rescinded. While the timing is disappointing, being selected to work on low-level systems supporting large-scale inference was a meaningful validation of the work I’ve been doing in systems and ML infrastructure. I’m grateful for the opportunity and for the engineers and recruiters I met throughout the process. That being said, I am now actively recruiting for Summer 2026 roles centred around ML systems, training infra, or foundational models. If your team or someone you know is building in this space, I’d love to connect and talk about my past work. My DMs are open.

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Aaron
Aaron@AaronAnandji·
moving montreal to toronto. joining @opensesame_dev as head of growth. birthday today. new year. lfg. back to building.
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Ty
Ty@TyneeWorld·
how's the LA startup scene? asking for a friend :p
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Ty
Ty@TyneeWorld·
2025 was a wild year. And 2026 is going to top it 🤖
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chris
chris@chrislevan·
unemployment for 2 weeks what should i do?
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Aaron
Aaron@AaronAnandji·
I’m launching silmaril ventures with one simple thesis: I will back every startup with a lord of the rings name. DM me your deck if this sounds like you. Current portcos include palantir, annatar Rivendell, anduril, and more. Also FoF into mythril capital.
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chris
chris@chrislevan·
thank you for everything @PanacheVC, it has been an insane adventure since the start of the year. in the new year i will be back operating and joining @hkimia doing all things growth. more to come soon!
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ameen
ameen@neamiax·
financial planning is broken in Canada. not only because Toronto is too expensive - but also because 75% of Canadians can't afford a financial advisor We built FriedmannAI - the ai-native financial planning interface it's the hands-free AI associate for financial and insurance advisors that enables you to: > Go from voice-to-plan in seconds > Show transparent reasoning and calculations > Model real-time scenarios > Maintain enterprise-grade compliance and audit trails built to show clients, not bore them. co-built with @IBM. Backed by @dmzhq ventures
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Anson Lin
Anson Lin@ansonlin·
chat do i take a gap year?
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