Considering the fact that Google/Anthropic/OpenAI have WAY more compute and the race is this close, it's obvious that DeepSeek/GLM/Qwen teams are better or we're approaching a wall in terms of progress.
> I think it's very clear that DeepSeek is obviously the best AI lab in the world.
It's pretty clear they're the best at what they're optimizing for - which does seem aligned with what a lot of people on HN want from models - but not everyone...
Basically, the nice folks at OpenAI or Anthropic saying: "You distilled from our model which is built on the stolen data that we ourselves suctioned up from the entire internet without regard to copyright law! Only we get to vacuum up the whole internet. That's our special prerogative.".
"So you think in 3 years AI is going to solve longstanding math problems because it was used to write some coherent sentences?" — people with the same amount of foresight in 2023
Are you saying at anything that can solve longstanding math problems necessarily has the means, motive, and capability to kill 8 billion people in just 3 years?
No dude, it was an analogy. Sorry to pick on you, you're just another ignorant uninformed take in this thread, but come on. This technology is progressing at an insane rate, the shit it's doing now is science fiction from just a year or two ago, and people just keep on moving the goal posts, it's maddening. The technology is unpredictable and that in itself has risks. You must realize that the window of possibility is widening the further into the future we go! Can you pick people with epistemology you trust and see if there's anything you can learn in this moment? Can you try to challenge your own ideas instead of retreating into comfortable certitude? There are real risks here, they are worth taking seriously, and serious people are doing so!
I think they will be, Nvidia has released open source model that also included the data it was trained on. I think they are the only ones that have done that.
The government should give incentives to do things that benefit the future of the country. All auto manufactures had the same incentives but instead of building actual good vehicles they instead shipped more production to Mexico and continue to build the absolute most dog shit vehicles in the world.
Not a single US auto manufacturer, outside of Tesla, has a good EV, nor FSD. Waymo is buying thousands of Chinese cars because of how shit US car manufacturer are.
They are the worst of the worst. They shouldn't even be in business they are that bad at building cars which they literally invented.
Im against restricting anything related to code length this goes for function names and length, file length ect.
I rather the dots be as close as possible than trust the agent connects the dots.
I dont care if the file is 5000 lines I rather the agent reads one file and get all the context than trust it will read all the need files.
I see so many review skills that puts hard limits on these thing and it just bad.
The function name shouldn't be limited they should be as clear as possible and if for some reason it over 30 chars so be it.
I want to read the function name and the logic and it match exactly. I don't want the agent being lazy because of some limit I set.
In fact I force my agents to write long functions because I specifically tell it not to break out repeated code that doesn't actually deserve a function.
A check on a function input doesn't need to be a function. A auth guard doesn't need to be it own function.
types.go types.ts absolutely the worst file to see in any code base. Put the type next to the code that uses it.
MCP is a standard that agent harness can implement that extends the harness with things like tools and prompts. Harness can have their own internal tools. MCP tools are external tools attached to the harness.
I'm sorry, but this is pure slop. This has 26 tools and a tool for every single file operation and a tool for read tool output? What the fuck... And they call this minimalist.... Lmfao
The person who built this obviously has little understanding of harnesses.
You should have significantly less tools today with how good LLMs have become.
The start up time and binary size are quite literally the most useless stats to base a harness off of lol
Man what with Cloudflare, Vercel and all these tech companies just releasing pure slop.
Just use Pi. It's actually minimal and well thought out by people who actually understand agents.
I think part of this is to enable the interface on the web and other devices where you might not have a terminal. But yeah, agreed, it's wayyyy too many tools.
It's the complete opposite for me. The model might be the worst model I have ever used when compared to other models in the class. You just can't get it not to just write the most enterprise over complex over engineered solutions for every little thing you ask it to do.
It the first model to actually make me pissed off to use AI. I absolutely hate the model so much.
I don't even want to see the codebases this model is fucking up.
It might just be good at finding bugs that about it. That all I would ever use it for just because it works harder than Claude models.
After being stuck with using GPT-5.6 models for the past few weeks, I have renewed faith in Google and everyone but OpenAI. The GPT-5.6 models are quite obviously benchmarkmaxxed to make they seem like they are intelligent but they are quite dumb outside anything that not a benchmarked task.
I also think Google is still the best at fitting the most overall intelligences into their models, but for some reason it seems like the model architecture is just bad.
Every model release seems like it packed with wonderful research and advancements.
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