Is there a terminology battle happening in some circles? And if so, what are the consequences of being wrong and using the wrong terminology?<p>I follow the rnd and progress in this space and I haven't heard anyone make a fuss about it. They are all LLMs or transformers or neural nets but they can be trained or optimized to do different things. For sure, there's terms like Reasoning models or Chat models or Instruct models and yes they're all LLMs.<p>But you can now start combining them to have hybrid models too. Are Omni models that handle audio and visual data still "language" models? This question is interesting in its own right for many reasons, but not to justify or bemoan the use of term LLM.<p>LLM is a good term, it's a cultural term too. If you start getting pedantic, you'll miss the bigger picture and possibly even the singularity ;)
There was an HN thread that talked about how “just” is a 4 letter word. It significantly risks underestimating emergent properties and behaviors.<p>Every time you see “X is just Y” you should think of emergent behaviors. Complexity is difficult to predict.<p>> R1 Zero has similar reasoning capabilities of R1 without requiring any SFT<p>In fact R1 zero was slightly better. This is an argument that RL and thinking tokens were a genuinely useful technique which I see as counter to the author’s thesis.<p>I also think a lot of what the author is referring to was more generously arguing against next token prediction (exact match of an answer) rather than the sequence-level rewards in R1.
I think this is a response to Gary Marcus: <a href="https://xcancel.com/GaryMarcus/status/1888606569245679893#m" rel="nofollow">https://xcancel.com/GaryMarcus/status/1888606569245679893#m</a><p>“The architecture of the DeepSeek SYSTEM includes a model, and RL architecture that leverages symbolic rule.”<p>Marcus has long been a critic of deep learning and LLMs, saying they would “hit a wall”.
> They say: “the progresses we are seeing are due to the fact that models like OpenAI o1 or DeepSeek R1 are not just LLMs”.<p>Would be nice if the author could cite even one example of this as it doesn't match my experience whatsoever.