🌴Marc Averitt🌴 retweetledi
Brett Adcock, Figure CEO joined our 8 hour(!) live stream where a bunch of us were bird dogging and discussing Figure’s own 8 hour livestream showing a F.03 bot doing a logistics task completely autonomously including shift changes between bots.
Here’s my summary of Brett’s remarks. The attached video is just the segment with Brett.
We were first introduced to F.03 8 months ago, but Figure has been hard at work on their next version, F.04 which has just completed design lock, so expect to see that new bot sometimes this fall. F.04 was co-designed with the latest Figure AI stack called Helix and was built specifically for data.
Brett didn’t explain what that meant, but I suspect it means the bot has many more sensors to enable better training and transfer learning.
F.04 will be the biggest leap in performance they’ve had between versions so far which is saying something.
Brett is a huge proponent of cross training the bots with many different tasks such that seeming unrelated tasks makes all learned tasks better. He gave an example of the fridge loading training which was topping out at 60% reliability until they trained the same model with kitchen shelving tasks, then they saw the fridge tasks jump to 90% accuracy.
As such, they spend almost all their time in pre-training the unified Helix model to ensure they get cross training benefits.
Figure will have almost completely localized Figure’s supply chain away from China by next quarter. They build almost everything in-house.
Figure does not appear eager to get their bots into the workforce. Brett said they could, today, push thousands of bots into customer hands, and I believe him. But their goal is full general robotics where you can describe a brand new task to a robot, maybe do a one time demonstration, just like you would to a human showing them a new task, and then have the robot do the task.
This is the holy grail of AI robotics, and Figure is laser focused on that mission.
Brett initially said there was a possibility of achieving it this year, but then guided next couple of years, which I think is much more likely. Personally, I think they’ll need at least a new generation of NVIDIA inference chips to make that leap, and a lot more data gathering, training and hardware development.
Brett said their goal with the hardware is “Apple” quality. Ie. Something as well designed and made as any Apple product.
While the F.03 hand is clearly performant as shown in the 8 hour livestream, they are building a new hand for the F.04 bot which will be even closer to the full functionality of a human hand. Brett fully believes you need a humanoid hand as close as possible in capability to a human hand, if for no other reason that transfer learning from humans works a lot better when you can exactly mimic what a human does. If the bot can’t do something a human demonstrates, then you’ve just polluted your dataset.
By now Figure has built more hands than bot versions (5-6 hands). One of the first hands they tried was a tendon driven hand, and without explaining why, Brett said that was a dead end. Their hands now have all actuators in the hand itself, and are clearly already robust. Brett said he just sat through a 100 page powerpoint design review of the latest hand - that’s how complicated it is.
Brett’s other AI company, Hark Labs, has developed a conversational voice model which is installed now in the Figure bots roaming the office. Being able to converse back and forth with a Figure bot is now a thing and will get better over time.
All in all, I came away from this segment even more bullish on Figure.
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