Nikhil Kumar

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Nikhil Kumar

Nikhil Kumar

@nikhilkr

Building agents for reliable robotics eng, 10x faster · @godrift_ai · prev @qualcomm · 2x founder · 10+ yrs in robotics

San Francisco, CA Beigetreten Aralık 2015
1.1K Folgt373 Follower
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Nikhil Kumar
Nikhil Kumar@nikhilkr·
Drift v1.0.24 is live! for robotics engineers tired of re-explaining their project to agents every command. Shipped: 🧠 Project context - drop a DRIFT.md or SKILLS.md, it's used on every step 🤖 MuJoCo + Gazebo, end-to-end - URDF, MJCF, plugins, launch, debug, run, train ⚙️ Multi-step builds that hold context - robot -> world -> sim -> tune, one prompt
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Midjourney
Midjourney@midjourney·
Midjourney will be announcing its first hardware project tomorrow (Wednesday 6/17) at 6pm PT. Stay tuned for a livestream of our in-person launch event in San Francisco. If you're in town and want an invite, reply below, we have just a few slots left.
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Nikhil Kumar
Nikhil Kumar@nikhilkr·
This is so accurate! Let me tell you how we learned it the hard way 👇 We had a walking policy for the lower body only. So we tried to run it by jamming the upper body joints and figured the arms could just be dead weight. But they couldn't! The arm motion turned out to affect the gait cycle directly. Locking the upper body degrades the walk. Try it yourself: run with your arms pinned to your sides, you'll notice that you hit a speed ceiling fast. Turns out the body is one coupled system. There's no "just the legs", funny how the robot taught us what evolution already knew :)
Current Robotics@Curr_Robotics

Introducing Curr-0: When Loco-Manipulation Meets Dexterity Robots have learned to walk. Robots have learned to use their hands. But in the real world, you can't do one without the other. Your stance determines your reach. Your torso determines your balance. Your whole body moves before your fingers ever act. This is what makes loco-dexterous manipulation hard — and what most robots still can't do. Curr-0 is our humanoid foundation system for loco-dexterous manipulation. Locomotion, whole-body coordination, and dexterous hand control, learned together as one coupled behavior. Trained on 21k hours of real human data — including 3k hours of whole-body demonstrations — deployed on a near 70-DoF embodiment. One model. One policy. Whole body. This is Curr-0. And this is just the beginning. Tech Report → current-robotics.com/blog/curr-0

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Nikhil Kumar
Nikhil Kumar@nikhilkr·
Humanoid companies aren't rushing into factories for the labor but for the data. Every robot on a real floor generates the exact data that makes the next one way more general and the factory looks next gen. The quiet part here is that many of these factories aren't selling robots. They're selling that data to the teams building world models and VLAs. The robot is still the collection device and the data is the product.
CyberRobo@CyberRobooo

Seres has deployed bipedal and wheeled humanoid robots at its Chongqing "Super Factory" for tasks such as guided tours, inspections, and quality control; the facility is equipped with over 3,000 robots, achieving near-total automation. Humanoid robots are effectively filling the gap in the workforce for unstructured tasks. ...and form a massive automated collaborative network with robots.

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Karan Goel
Karan Goel@krandiash·
We’ve seen incredible traction this year, with enterprises transforming every part of their operations with Voice AI. We’re sharing what we’ve learned and are giving away a guide to the top 10 enterprise use cases for Voice AI. Retweet and comment "CARTESIA" on the main video and we'll send you the guide and $100 in credits so you can get started today.
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Karan Goel
Karan Goel@krandiash·
We released Sonic-3.5 and Ink-2, the #1 streaming models for text to speech and speech to text you can use in your voice agents today. New architectures enable new frontiers for speed and quality. We're now the only provider to have #1 models for both speaking and listening.
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Nikhil Kumar
Nikhil Kumar@nikhilkr·
@CyberRobooo Curr-0 feels like a glimpse of what happens when movement and intelligence finally become one system
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Dominique Paul
Dominique Paul@DominiqueCAPaul·
Over the last few years, I’ve met so many people working on robot learning across Zurich’s academic labs, start-ups, and big tech. What keeps surprising me is how little exchange happens between these groups. To change that, I’m starting a Robotics AI Paper Club for researchers, engineers, and anyone looking to get deeper into the field. Wrote a paper or method yourself? → Present it! Read a paper others should know about? → Show us what you liked and why it’s worth reading! First edition: this Thursday. Drinks, pasta & pesto are on me. Luma link below 👇🏼
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RoboIndex
RoboIndex@roboindexio·
Isaac 1 just stepped into the home robot conversation. YC-backed Weave Robotics opened its San Francisco space for a first public look, with Isaac 1 pitched as a robot for the chores nobody wants to do: laundry, tidying, bed-making, and checking on the house while you’re away. The company is keeping signups tight, with a refundable $1,000 reservation model and a limited first batch approach that looks built for early demand testing.
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Evan Wineland@evan_wineland

The showing we got for Isaac 1 yesterday was everything we could've hoped for Roboticists, engineers, designers, students, kids, grandparents all in one place Seeing how home robots will change the way we live for the better

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Nikhil Kumar
Nikhil Kumar@nikhilkr·
Everyone thinks the robotics problem is building smarter robots. It's not. We've already taught machines how to see, reason, move, write code and even drive cars. The harder challenge is dealing with reality and it's messy but how? > a box is slightly crushed > a tool isn't where it's supposed to be > a package arrives upside down > a human does something unexpected The list goes on and honestly, the world is an endless stream of edge cases which humans barely even notice. But robots do and they work exactly on these edge cases I believe that the companies that win the next decade won't necessarily have the smartest AI but they will build systems that keep working when the environment stops being predictable. Because the real breakthrough isn't automation but it's adaptability.
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Brian Zhan
Brian Zhan@brianzhan1·
Excited to be on the Business Insider list of top robotics investors. The data wall is falling. For years, the bottleneck was teleoperation: slow, expensive, narrow. Now robots can learn from human video, practice in simulation before touching reality, and there is enough funding to scale data deployments. Robotics is finally running the playbook that took LLMs from autocomplete to reasoning. There are still many open frontiers. General manipulation. The right API layer for the robotics models. Application robotics. That's exactly why I'm bullish. We've just found a recipe that works. Thanks to @ryajetha for compiling the list.
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shirish
shirish@shiri_shh·
"one day it won't rebalance. It'll respond 😭"
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Steven Cheng
Steven Cheng@stevencheng·
A parallel SCARA robot that combines both speed and precision. It’s truly a genius design.
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Space and Technology
Space and Technology@spaceandtech_·
Researchers at ETH Zurich have developed ANYmal, a quadruped robot that can play badminton with humans. The robot tracks the shuttlecock, predicts its path, and moves into position to return shots. Its control system coordinates vision, movement, and racket swings to play the game effectively.
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Nikhil Kumar
Nikhil Kumar@nikhilkr·
Just attended Saturday Robotics Reading Club Session with a fantastic talk by @DanielXieee from Origami Robotics. We’re moving beyond binary success rates and the old taxonomy to rich multi-axis dexterity metrics: spatial precision, temporal composition, contact richness, coordination & tool use. Dexterity for robots is accelerating to reality 🚀
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Anirudh
Anirudh@anieasyy·
Perry stops Dr Doofenshmirtz from misusing Fable Major Monogram and Carl were the ones who found the jailbreak, have it on good authority
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Weave Robotics
Weave Robotics@weaverobotics·
Isaac 1 Today, 4.30pm - 6.30pm 285 7th St, San Francisco
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mete
mete@VaderResearch·
Figure 03 makes it look easy to walk down the stairs Yet this a difficult engineering problem for humanoids 🔵 When you walk downstairs, your foot swings out over empty air before finding the next step 🔵 The robot can't fully see where it's landing; cameras & depth sensors struggle with stair edges & shadows 🟢 The entire upper body is already tilting forward from gravity so if the foot lands even a few cm too far forward/back, the humanoid will fall 🔵 Humans fix this with a lifetime of balance training the body does unconsciously 🔵 Humanoids have rigid flat feet and milliseconds of latency between sensing and correcting
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