[amelius]

One problem with AI is that it's a winner takes all market, in the end. Training models is expensive, so we're all just building our castles in someone else's kingdom.

Another problem is that we're turning any problem into a black-box, which takes the fun out of problem-solving.

[agarren]

How is it winner-take-all? Training models is expensive, yeah, but big companies are willing to do it, and if deepseek is any lesson, it’s not as expensive as we used to think. You might be building a castle in someone else’s kingdom, but you’ve got a few kingdom’s to choose from. None have a moat and none seem to be going away any time soon.

It’s cheaper to move from one model to another than it is to train a general purpose model yourself (to say nothing of domain-specific smaller models or anything open source.)

I’m not sure about problems turning into black boxes, LLMs are pretty explicit in my experience when producing a solution (good or bad.) _How_ they came about that solution _is_ a black box, but that’s not a new problem.

[actsasbuffoon]

It may not be winner-takes-all. Study after study shows that the models are converging as they get bigger; their results are getting more similar to one another. The models themselves are becoming interchangeable commodities.

We can use OpenRouter to build agents with any LLM and switching your agent to a new model is a one-line code change. We can write MCP tools that work with most of the decent models.

Honestly, I think we may be entering a period where things start to decentralize and money starts to move towards startups building interesting tools and agent workflows instead of a handful of giant companies training frontier models.