It won’t take anyone on X regularly five years.
— Robert Scoble (@Scobleizer) 5 mai 2026
Maybe two. https://t.co/bACqyPvYGH
It won’t take anyone on X regularly five years. Maybe two.
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It won’t take anyone on X regularly five years.
— Robert Scoble (@Scobleizer) 5 mai 2026
Maybe two. https://t.co/bACqyPvYGH
It won’t take anyone on X regularly five years. Maybe two.
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I am with Grady about consciousness and AI.
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@blevlabs is advertising for one of them

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A reminder that telling the AI that it is an expert in a field is no longer helpful in making the AI better at that field.
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I like it actually. But I have expensive rugs too.
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Part 2 🧊
— Satya Mallick (@LearnOpenCV) 5 mai 2026
In Part 1: accuracy is a trap.
In Part 2: failure modes ARE your fine-tuning dataset.
Probe the public model → collect data on exactly what it breaks on → fine-tune → repeat.
That's the loop most CV teams skip.
Dr. Satya Mallick 👇#ComputerVision #AI #YOLO… pic.twitter.com/6QheiFOfKh
Part 2 In Part 1: accuracy is a trap.
In Part 2: failure modes ARE your fine-tuning dataset.
Probe the public model → collect data on exactly what it breaks on → fine-tune → repeat.
That's the loop most CV teams skip.
Dr. Satya Mallick #ComputerVision #AI #YOLO
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I think that really undersells co located lidar and color pixels on the same chip producing 3d vision with perfect spatio temporal alignment
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Willie Nelson follows me. Is there better?
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Is what you are seeing real?
— Robert Scoble (@Scobleizer) 5 mai 2026
Remember you are looking at numbers displayed on a screen.
Looks real awesome here. https://t.co/L96A4bZ516
Is what you are seeing real? Remember you are looking at numbers displayed on a screen. Looks real awesome here.

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At nearly every AI party I attend in San Francisco they ask you to take off your shoes. Most parties are in people’s homes with expensive rugs.