impulser_

They even made fun of cloud providers being down when AWS was down.

Now you can have people producing videos without needing a crew of people.

I don't think using AI to write code is AI psychosis or bad at all, but if you just prompt the AI and believe what it tell you then you have AI psychosis. You see this a lot with financial people and VC on twitter. They literally post screenshots of ChatGPT as their thinking and reasoning about the topic instead of just doing a little bit of thinking themselves.

These things are dog shit when it comes to ideas, thinking, or providing advice because they are pattern matchers they are just going to give you the pattern they see. Most people see this if you just try to talk to it about an idea. They often just spit out the most generic dog shit.

This however it pretty useful for certain tasks were pattern matching is actually beneficial like writing code, but again you just can't let it do the thinking and decision making.

Both of the Codex apps are very good.

I tried this out and it works significantly better than Claude's remote control in fact the first few times I tried Claude's remote control it didn't even work and to this day is very buggy.

This has always been the way Google has worked. This is why they are literally the most successful company in the history of the world.

Go for example has significantly less training data than Python, but LLMs are the best at it. Why? Go is often written the same. You go from project to project and the code looks all the same. There only a very few ways to write Go.

There is literally not enough compute dude. If we had infinite compute we would see everyone building Mythos size models.

"Right.. and computers were once the size of a large room vs now fit into a pocket."

Yeah because we offload much of the compute to off device. You think we would have these small computers in our pockets if the internet didn't exist?

You can just embed the C library into the binary of the Go app call it directly in Go. Most of the time I have found calling C from Go faster or on par with calling C from Python.

https://github.com/ebitengine/purego

Once computer constraints ease up, you will see much larger models. The reason LLM seems to have stalled a bit is because there just not enough compute.

You have more people using AI which requires more compute, and you want to build larger models which requires more compute and you have limited compute. What do you do?

All you need is Apple and Google Oauth.

Since Feb when we got Gemini 3.1, Opus 4.6, and GPT-5.3-Codex we have seen GPT-5.4 and GPT-5.5 but only Opus 4.7 and no new Gemini model.

Both of these are pretty decent improvements.

Cursor is essentially all the Claude Code products but without the horrible bugs of Claude Code products.

You can transfer from CLI to web and it actually works.

The problem is they can't compete with Anthropic and OpenAI because they can't sell Opus and GPT at a discount to subscribers like OpenAI and Anthropic do with their subscriptions.

So they either need to build a competing model or slowly die.

Especially the “If you want” at the end of every single reply.

The ironic part about this is GPT models are by far the worst models to chat too.

I think I rather talk to a wall than GPT-5.4. It so unpleasant. I feel bad for anyone who only experience with AI is ChatGPT.

Might as well not release anything.