Jack A great achievement. It's almost not nice to put it in perspective that nature can do two more things: achieve lots of copies with variations that self discover their niche (adaptability) and generate self-healing within the lifecycle. But, nevertheless, this is really cool.

Cool concept - turn night to day with ‘Light as a Service’. This concept beams - day light to specific location using reflective satellites. The product doesn’t exist yet just a simulated demo. Question: what’s the use case

Do we think humanoids will follow same path as low-cost cobots? > Initial hype > Explosion of companies competing for the same value prop > Eventual commoditization > Chinese companies end up winning with cheap/functional products

Continual learning is a big deal - ‘if you want to teach an existing deep learning model something new, you'll likely have to retrain it from the ground up’ Which costs millions…

"If you can’t be right, at least be sure when you’re wrong" Errors are always going to happen in robotics but they need to meet 3 criteria to be acceptable - 1. Safe to the robot & people 2. Minimal intervention to correct 3. Minimal false positives/negatives Deep learning

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Meme of the week - Are the AIs getting better or are we getting worse?

This is good to remember, tech can follow 3 phases: • Fear and resistance • Gradual acceptance • Daily life integration There is an argument that ai is different due to the speed & impact of disruption. I also think it’s worth pointing out that there is a negative &

Aggregators won the Internet era by owning demand and not owning supply. The exact opposite model will win the Techno-Industrial era. Vertical integration is back.

AGIBOT a Chinese startup, unveiled 5 new commercial humanoid robots. It has impressive manipulation demos - even showing off the fine motor skills required to thread a needle. They predict orders of 300+ this year...

👀👀👀

The hand is where the mind meets the world. NEO's 20 Degrees of Freedom hand enables human-like dexterous manipulation. New video:

where it started vs today

#1 - Many tasks in robotics are better done without ML Coming from a software/ML background, I asked myself why traditional robotics hasn't been replaced with ML. I learned that ML often comes at the cost of speed & predictability over many traditional statistical approaches.