If you find an idea that you love, and want to take it forward, we are working to either make funds available or connect you to investors who might be willing to fund. My whole goal is to cause more great startups to be formed via idealab.ai..

There's already a permanent underclass for those with the eyes to see.

Dario’s press training team needs to be fired, episode 793

pretty interesting that the category is converging on the same visual grammar almost comically fast too. you’ve got a blob, a face, some “eyes”, you gotta give it some soft geometry, add in some emotions via animations, & of course a very friendly affect.

I asked Opus 5.5 to build a working computer from scratch. And holy fuck did it deliver. 277k logic gates in JS, an OS on top, and games on the OS. This isn't a mockup... it's a computer. Run it: somethingbig.ai/computer

TOMMY TUBERVILLE WARNS THAT “MANY” PILOTS, FLIGHT ATTENDANTS AND AIR TRAFFIC CONTROLLERS ARE FURRIES: “Lord help us. It’s terrifying when you think about this.” Tuberville claimed on the Senate floor that airline workers being part of the furry community poses a danger to passengers, saying a pilot “could have a deranged fetish of dressing up like an animal.”

Updated:

Does the message board have consciousness?

I've been so AI pilled, that I've done a complete 180. AI is a money incinerator. It's a collective hallucination. Everyone sees everyone else shoveling money into the incinerator and starts doing the same. Everyone just keeps shoveling money hoping that one day the engine starts running. And maybe it will. But it isn’t. AI is expensive. Especially when you have to actually pay for tokens. And the real systemic work, the stuff that replaces people because it is autonomous, runs on tokens. The question isn’t whether your AI systems are cheaper than Americans. It’s whether they’re cheaper than people in Latam, Southeast Asia, or Africa. They aren’t. AI also suffers from broken clock syndrome. When we task AI with doing a specific task, it can often give a quality or correct output. But the problems arise when we ask an AI to produce that type of output with different inputs. If you don't know the process it used to give you the initial correct output, there's no way to know if it can take your input type and generate a quality output repeatedly or if it is just a broken clock that happened to be right. So in order to build durable results with AI, you need to build the process the AI is going to use to generate the output. You need to build in oversight. And the more varied the inputs, the more complex the output, the more granularly you need to control the functions within the black box. Otherwise, your fail rate is going to be high. And this failure rate increases whenever there is nested processing and thinking. Then there is the cost of building these systems in the first place. If you actually want something that works, you need to invest considerable resources into the build. Senior talent to develop it, token costs during calibration, ongoing maintenance when it breaks, etc. The common argument against this is to “let AI do the building on its own.” The problem with this is AI doesn’t think. It doesn’t reason. It guesses the next most likely thing in a series. So it will build something for you that will look like a house, but you go in the basement and the foundation is upside down. It’s got wires running through water pipes. The hot and cold water taps are reversed. It looks right from a distance, but any deeper level of scrutiny the illusion falls apart. Nobody is making money from the “work” that AI is doing. If they were, we would have such a rapid consolidation of wealth nobody would know what is happening. Every industry would be consolidated overnight into unassailable monopolies. I hear from lots of people who say they are making money from using AI. And my question to them is how much did it cost to build and what’s the payback period. Large companies are pulling back on AI investment. These are the companies that should be most able to realize a positive ROI on AI. So the question is whether they are uniquely incompetent at development and deployment or are smaller businesses bad at calculating cost and ROI? This results in our current environment: The only people making money in AI are the people who are selling it. It remains to be seen when using AI is profitable and how much work it can profitably replace.