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When is the ChatGPT moment for robotics?
Some say it's happened, some say it's coming. How capable are Physical AI models today? What does the adoption curve for robotics look like?
We've talked to most of the major players and make sense of it here
robostrategy.co/news/the-cha…
Andrew Kang retweeted
A talented crew (EO) spent weeks on a mini documentary on @standardbots, and it's live today.
Their crew came to our factory in Glen Cove, New York, and saw everything up close. That included the SMT room where we make every circuit board that goes into our robots, a factory floor we're growing from 30,000 to 70,000 square feet, and the team training our AI on real data from robots working in the field. A lot of the Standard Bots team came in to show them what we do and why we care so much about it.
I'm really proud of how they told our story, including the hard parts. It took us seven years to sell our first 100 robots. At one point my friends staged an intervention and told me it was time to go do something else. We kept going.
Here's why. Last year China installed 9x as many robots as the United States. Robots aren't just another kind of hardware. They're what makes everything else: semiconductors, medicines, defense systems, energy infrastructure.
Our mission is to bring robotics and manufacturing back to the U.S. and rebuild the middle class along with it. Manufacturing has always been the heart of the American middle class. Robots make American workers more productive, and that's how we earn the right to create high-paying jobs here. Instead of welding in the smoke, a worker runs six welding robots. That's a better job, a safer job and a higher-paying job.
We build robots in America, for use in America.
Thank you to the EO team, and to everyone at Standard Bots who made time for this. Watch the full episode here:
youtube.com/watch?v=T31kO2LO…
The FCC rule earlier this year restricted foreign made advanced robots. This presidential action goes further into the rest of the factory floor to include industrial arms, CNC, grinding, turning, milling, industrial stamping and pressing machines
The president will consider "establishing a program to incentivize new investment in United States production of robotics and industrial machinery"
With enough focus on automation, operational excellence, and investment, America can become as competitive on manufacturing as any other country
Andrew Kang retweeted
the white house just declared our dependence on imported robots and industrial machinery a national security threat.
no new tariffs yet. trade negotiations come first.
the bigger point: rebuilding american industry means building the machines that make everything else.
This same phenomena is happening in physical AI
Even after GPT-4 came out, I remember talking to computer scientists/ML experts that were so confident that general purpose models were overhyped and wouldn’t be able to produce real useful work soon. A lot of reductionist talk about stochastic parrots and next token predictors.
It is surprisingly difficult for a lot of career technologists to grasp non linear technological trends and how slopes can change.
Different experts in the same domain can have widely different expectations for technological advancement even 1-2 years in the future.
There is also an element of information asymmetry. Organizations on the frontier move at vastly different paces than those that don’t. They are privy to key know how and training/data collection approaches that can potentially compress R&D pace by orders of magnitude.
It’s important to remember that those that aren’t on the frontier are somewhat blind to the full state of the world even though they might not think that they are.
We see time and time again that research paradigms are always changing and the same bottlenecks that existed yesterday get solved by smart brains (and AI models) motivated enough to tackle them.
Laggards claim “we are so far”. We bet on the people that respond with “skill issue”.
Dario reveals the people who called his GPT-2 fears "pseudoscience" in 2019 are now all applying for jobs at AI labs
"I personally was super freaked out by [GPT-2]. I looked at it and I said, my God, you just scale this thing up another factor of a million and it'll be better than humans at everything. This is the defining economic and scientific moment of the modern age. We just don't know it yet. This is going to determine the fate of nations and economies and the future of humanity."
"Maybe 10% of the people around me had exactly the same reaction, and it was often the smartest ones. 90% of the people around me, because GPT-2's capabilities in any particular area were not that impressive, it could translate languages, summarize a document and write a few lines of code here and there. It was the broadness and the generality."
"But people would look at it and say, in any particular area, that doesn't seem so smart. And so many people just shrugged and they just dismissed it."
"I just look at it and I say it's the same thing over and over again. The limitations of the models, six months from now, the things that seemed hard, they're going to be easy. 12 months from now, the things that seemed impossible, the models are going to be doing them regularly."
"It's everything we saw with GPT-2; we're seeing it over and over again in wider and wider swaths of the world. And the world is gradually finally being convinced."
Daniela Amodei: "I remember at the time there were some very well-respected computer scientists and AI and ML leaders who basically bullied some of the researchers who worked on [GPT-2] on Twitter and were like, this is stupid. We don't know why you guys are even talking, this model is so incapable."
"It was like you were sort of a quack if you believed this was a really significant moment."
Dario: "That's all been memory-holed. All the researchers who were like, oh, this is pseudoscience, it doesn't make sense, all of them are applying for jobs at the LLM companies."
"We never say it out loud to any particular one, but we look at them and they're like, we remember what you were saying in 2019. You have no credibility on this matter."
Andrew Kang retweeted
Summing up the challenge of commercializing robots in one photo
The bar for both reliability and output quality is much higher for physical labor than it is for knowledge work. A chatbot that produces work that is just “good enough” or low quality can still be useful.
A mediocre rough draft could still save time because a person can keep what’s good and fix the rest before its final. Copywriting, slides, and contracts can all be edited.
What is considered “good enough” for physical work has much higher standards. A bad weld can ruin metal. A wrong dose given to a patient is unacceptable.
Outputs from work done by humans or robots in the physical often serve as direct inputs into the workflow that are hard to recover from if an error arises. Outputs from work done by humans or Chatbots for knowledge work are much more tolerant of errors and poor quality because supervision can be baked in before the output is used further down the workflow.
The reliability threshold is 2-4 orders of magnitude greater for physical work than knowledge work and it’s what we’ve started to achieve this year. The upside is that by optimizing for reliability, robots will be able to work at a high level of utilization and operate at higher levels of autonomy compared to general purpose AI models in 2023. Machines that can deliver up to 24 hours of work a day as opposed to minutes or hours of work.
When is the ChatGPT moment for robotics?
Some say it's happened, some say it's coming. How capable are Physical AI models today? What does the adoption curve for robotics look like?
We've talked to most of the major players and make sense of it here
robostrategy.co/news/the-cha…
Elon announced Optimus’ first autonomous demonstration video in 1-2 months.
Scott has been very spot on with Optimus predictions. He estimates V3 reveal to be in Q2 2027 and the capacity ramp to be:
2026E: 10-20k / year
2027E: ~100k / year
2029: ~1M / year
2030: Millions per year
A Tesla supplier says Optimus V3 is basically done. So why are they hiding it?
Full discussion:
0:00 Why Tesla is hiding Optimus V3
2:16 V3 hardware frozen
6:35 The pickle jar and robot skin problem
12:48 Optimus 2.5 hand tendon clip
16:06 Fingertip skin patent
22:03 Production snags in hands and joints
25:58 Theory: a 5,000 robot V3 reveal
32:02 AI5 chip and DRAM change
38:01 The Optimus factory at Giga Texas
42:41 Ramp to millions by 2030
@GoingBallistic5 @herbertong
Summing up the challenge of commercializing robots in one photo
The bar for both reliability and output quality is much higher for physical labor than it is for knowledge work. A chatbot that produces work that is just “good enough” or low quality can still be useful.
A mediocre rough draft could still save time because a person can keep what’s good and fix the rest before its final. Copywriting, slides, and contracts can all be edited.
What is considered “good enough” for physical work has much higher standards. A bad weld can ruin metal. A wrong dose given to a patient is unacceptable.
Outputs from work done by humans or robots in the physical often serve as direct inputs into the workflow that are hard to recover from if an error arises. Outputs from work done by humans or Chatbots for knowledge work are much more tolerant of errors and poor quality because supervision can be baked in before the output is used further down the workflow.
The reliability threshold is 2-4 orders of magnitude greater for physical work than knowledge work and it’s what we’ve started to achieve this year. The upside is that by optimizing for reliability, robots will be able to work at a high level of utilization and operate at higher levels of autonomy compared to general purpose AI models in 2023. Machines that can deliver up to 24 hours of work a day as opposed to minutes or hours of work.
When is the ChatGPT moment for robotics?
Some say it's happened, some say it's coming. How capable are Physical AI models today? What does the adoption curve for robotics look like?
We've talked to most of the major players and make sense of it here
robostrategy.co/news/the-cha…
We are hiring top talent from research to marketing to distribution to more
robostrategy.co/careers
Andrew Kang retweeted
Figure held an all-hands this week, and I've decided to share it here publicly
Given our rate of progress, our roadmap has completely changed over the last year, and the team has doubled
It's important to get everyone aligned on our mission going forward
Andrew Kang retweeted
Evan Beard of @standardbots on where robotics is today:
“Robots are in their infancy. It’s like the 1973 equivalent for the computer industry.”
With millions of use cases coming, their answer is an AI platform:
“We’re building a platform, not just robots, but the whole software ecosystem. That’s what we’ve tried to do from the beginning, to be that common layer across all these different use cases.”
Standard Bots CEO @evanbeard breaks down their new AI platform and how it could revolutionize American manufacturing.
"This allows you to essentially vibe code your robot"
Full interview:
0:00 Intro
6:39 Vibe coding robots
8:19 Locate vision system
11:52 400+ customers
13:58 Origin story
16:08 Where are the competitors?
18:56 Vertical integration is key
22:29 Why robot arms over humanoids
27:04 Robots vs the car industry
29:23 The thing to fear as a builder
31:31 America vs China
34:21 Congress and FCC robot ban
38:31 99% of US arms made abroad
42:31 Building everything inhouse
44:47 The plan to win
47:10 Targeting 10% of US installs
49:22 How the next decade will look like
Andrew Kang retweeted
Standard Bots CEO @evanbeard breaks down their new AI platform and how it could revolutionize American manufacturing.
"This allows you to essentially vibe code your robot"
Full interview:
0:00 Intro
6:39 Vibe coding robots
8:19 Locate vision system
11:52 400+ customers
13:58 Origin story
16:08 Where are the competitors?
18:56 Vertical integration is key
22:29 Why robot arms over humanoids
27:04 Robots vs the car industry
29:23 The thing to fear as a builder
31:31 America vs China
34:21 Congress and FCC robot ban
38:31 99% of US arms made abroad
42:31 Building everything inhouse
44:47 The plan to win
47:10 Targeting 10% of US installs
49:22 How the next decade will look like
Introducing Standard Bots AI
“We chose Standard Bots for two reasons: the speed of development is highly compressed, and the interface for programming the robot is so much simpler. With Standard Bots AI, that's even faster.” — Adrian Nistler, President and CEO, Path Machining & Automation
Standard Bots AI robots deliver dramatically faster setups, faster changeovers, and faster paybacks. This is why robots are the new essential power tool of the 21st century.
Our mission is to expand human capacity with the world’s most accessible robots. We’re building this future in Glen Cove, New York, and on hundreds of factory floors, and counting.
Say yes to more: standardbots.com/ai
I love humanoids but it’s awesome to see the step change evolution of the robot arm from essentially a 1970s PC to something you can now vibe code
Programmable robots -> instructable robots
"If you have an iPad, you can vibe code robots. And potentially save your company millions of dollars while you’re at it."
@Forbes robotics reporter @johnkoetsier interviewed @evanbeard for an exclusive on the launch of Standard Bots AI.
Read the story here: forbes.com/sites/johnkoetsie…
Robotics research output is accelerating
More accessible and cheaper hardware, tooling, talent and capital waves, better general purpose models are all major contributors here
RoboStrategy going public is just the start of our journey to establish a new model for Venture Capital
REITs broke out in the ‘90s, ETFs in the ‘00s and the era of public VC is next, starting with the companies building the future of the physical world
We are hiring for top talent from research to distribution to marketing to more:
robostrategy.co/careers