Loading video...

Video Failed to Load

Go Home

ᴷᵃʷᵃⁱⁱ ᴴᵒᵘˢᵉ .*・゚

20,416 views • 1 year ago •via X (Twitter)

9 Comments

Lactar1uz's profile picture
Lactar1uz1 year ago

𝐍𝐢𝐜𝐞

pico's profile picture
pico1 year ago

れつご

FANCO's profile picture
FANCO2 years ago

NEW OFFICIAL COLLABORATION ALERT! Get your PERSONALIZED @MHAOfficial Japanese hanko stamps at for yourself, friends and family! #fanco #mha #MyHeroAcademia

Hairo's profile picture
Hairo1 year ago

まじいい!

pico's profile picture
pico1 year ago

やった〜ありがとう!

DJ moriking's profile picture
DJ moriking1 year ago

これいい ♪ ベース、コードはある感じ。 トラック的だが、秀逸でしょ、、 ここに、何か乗っけたい、、

pico's profile picture
pico1 year ago

ありがとうございます!!!!

unkn.tm's profile picture
unkn.tm1 year ago

teach mee 😹🔥🔥

熱中症になれたなら's profile picture
熱中症になれたなら1 year ago

what software

Related Videos

Karol Hausman is the co-founder and CEO of Physical Intelligence, a robotics company building a general-purpose “AI brain for the physical world.” The company has raised more than $1 billion in funding to develop foundation models that allow robots to operate across many machines, environments, and tasks rather than being programmed for a single purpose. In our conversation, we explore: • The moment a lecture from Sergey Levine convinced him to abandon his PhD research direction and pivot fully to deep learning • The case for building a general “AI brain” for the physical world rather than a single specialized robot • The role of real-world data in training robots, the limits of simulation, and how deployment could create a powerful data flywheel • The unique challenges of physical intelligence and why robots must operate with far higher reliability than language models Thank you to the partners who make this possible - Brex: The intelligent finance platform: - Granola: The app that might actually make you love meetings: Timestamps (00:00) Intro (04:05) Karol’s early fascination with robots (18:21) Karol’s entry point to robotics and PhD program (25:49) Combining robotics with LLMs: The Taylor Swift demo (30:48) The 1970s SHRDLU AI experiment (39:40) How research shapes what Physical Intelligence builds (49:07) The return of reinforcement learning in robotics (1:00:00) NVIDIA’s simulation engines (1:07:31) Compensating for missing senses

Mario Gabriele 🦊

27,871 views • 7 months ago