Fable isn't the first. In 1999 the department of defense blocked exports of the PowerMac G4 for crossing the 1 gigaflop threshold. Steve Jobs turned it into an ad.

No, you don't get it. He does not have $1 trillion sitting in cash, it is 99% stock in his companies. To make that wealth liquid would mean selling all that stock which would swiftly destroy *both* the companies (Tesla, SpaceX, others) and the wealth. If he sold it all, he'd end up with maybe $100b max, several hundred thousand people would be out of work, the companies ruined and many of their suppliers also ruined. Okay, but now Elon has $100b in cash, and can "solve the world's problems". $100b divided by the world's 8 billion people is $12 If you were in charge, several of the most innovative industrial companies in the world would be destroyed, hundreds of thousands out of work, and space would again close to human civilization for another generation. But everyone on earth could have one nice meal and you could revel in your altruism.

just be yourself -- don't try to be yourself.

The rarest object type in the universe isn't black holes. It's us. Conscious matter. The flame of life. We have a duty to expand it in scope and scale in order to preserve it.

you only need a two more 10x increases to have ten times more power in space than on earth and then at that point you can beam down excess power via microwaves to ground stations and just turn off all the Fossil fuel power plants on Earth and then bam clean worldwide energy

🇺🇸🇨🇺

Data centers are not stealing your water

Instantly identifiable AI writing isn't annoying — it's a radical shift in how fucking annoying it is.

insane alpha on X if you know where to look

Someone should come up with an exchange rate between these two currencies.

finally getting better at naming things

open-source -> open-to-attacks in fact, it's entirely possible that by next year, most open-source projects will be built by attackers to hide backdoors

we now know who the robot overlords will go after first

this is brilliant. it's a step function more helpful than many other AI UXs.

People are bearish on memory, but the leaked Claude Code source code is showing us some additional memory demand that the market hasn't priced in IMO. 1. The market thinks about AI memory demand as a server-side story: HBM on H100s/B200s for inference. What the bug reports reveal in this code is that the client-side of AI coding agents is also extraordinarily memory-hungry. Idle Claude Code processes growing to 15GB each, active sessions hitting 93-129GB. This matters because the feature flag pipeline (DAEMON, PROACTIVE, CRON) points toward future always-on background agents. If a developer has a persistent daemon agent running alongside their active sessions, you're looking at baseline memory consumption of 15-30GB just for Claude Code on a developer workstation - before they even open their IDE, browser, or anything else. This means either enterprise IT needs a big uplift to higher-RAM workstations or we move even more memory-hungry workloads towards the cloud. 2. The Auto Dream consolidation feature runs background Claude sessions to clean up memory files. One observed consolidation took 8-9 minutes processing 913 sessions. In other words, a meaningful fraction of Anthropic's token consumption is the system managing its own memory, not the user doing productive work. As memory systems get more sophisticated (team sync, cross-session event buses, memory consolidation), this overhead grows. It's a recursive cost - more memory features require more inference to manage memory. I don't think anyone is modeling this as a distinct line item in token consumption estimates. 3. 1M token context windows for Claude Code. Moving from 200K to 1M context is a 5x increase in KV cache memory per session on the server side. Combined with multi-agent (5-15x per user) and the proactive/daemon features (sessions that persist for hours/days instead of minutes), you get a compounding memory demand curve that's steeper than linear adoption growth that many analysts model. Memory demand per active user is increasing faster than user count, because each user's sessions are getting longer, wider (more agents), and deeper (larger context windows).

i remember when being an AI engineer was just telling it think step by step the nostalgia hits hard