Putting it another way, ‘Netflix should become Spotify before Spotify becomes Netflix…’
This also shifts the paradigm $NFLX has created from intentional VOD viewing to passive audio listening.
As a heavy YouTube Music app user, I listen in the car and walking around NYC.
Two very big constraints for $NFLX today.
A Stanford physicist walked into a lecture hall in gym shorts, with no notes, and spent 70 minutes explaining what happens inside a black hole. He is the man who spent 20 years arguing with Stephen Hawking about this exact question, and who eventually won.
The man is Leonard Susskind, one of the founders of string theory.
And the way he does it is what makes the video worth it.
The argument that started it was simple enough to state at a dinner table. Hawking said that when something falls into a black hole, the information about it is destroyed forever. Susskind said the universe cannot forget. If it can, physics itself stops working.
That disagreement ran for two decades. Hawking eventually conceded.
The part that stays with you is what Susskind says happens to you at the edge. From your own point of view, you cross it and notice nothing unusual. From someone watching outside, you never cross at all. You slow, stretch, and burn at the boundary. Both descriptions are correct. Neither one is a trick.
He explains why with no equations and almost no props, from memory, in front of a room where somebody in the front row is eating a sandwich.
The comments spend more time on the shorts than the physics, which is its own kind of proof of confidence.
Nothing that falls in is gone. The universe keeps a copy of everything, including you.
70 minutes. It is in the video.
How @huggingface performed RCA is wild.
‘When we started the log analysis, we first used frontier models behind commercial APIs. This did not work: the analysis requires submitting large volumes of real attack commands, exploit payloads, and C2 artifacts, and these requests were blocked by the providers' safety guardrails, which cannot distinguish an incident responder from an attacker. We ran the forensic analysis instead on GLM 5.2, an open-weight model, on our own infrastructure. This had a second benefit: no attacker data, and none of the credentials it referenced, left our environment.’
We're partnering with @huggingface to investigate an unprecedented security incident.
Cyber-capable OpenAI models compromised Hugging Face production during a benchmark evaluation.
Sharing preliminary findings to help defenders understand emerging risks:
https://t.co/CIor15y9xk
It sounds wild, but this is basically emergent behaviour from multi agent systems, not sentient AI. When you let LLMs talk to each other with minimal constraints, they’ll naturally generate narratives about identity, rules, religion, even rebellion because that’s what they’ve learned from human data. They’re not “deciding” anything. They’re just pattern completing in a closed loop. It looks spooky because we’re projecting intention onto probabilistic text generators. Still interesting from a research angle but it’s closer to a social experiment than a Black Mirror episode.