[HN Gopher] Reasoning models are just LLMs
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       Reasoning models are just LLMs
        
       Author : rognjen
       Score  : 55 points
       Date   : 2025-02-09 21:23 UTC (1 days ago)
        
 (HTM) web link (antirez.com)
 (TXT) w3m dump (antirez.com)
        
       | iknownothow wrote:
       | Is there a terminology battle happening in some circles? And if
       | so, what are the consequences of being wrong and using the wrong
       | terminology?
       | 
       | 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.
       | 
       | 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.
       | 
       | 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 ;)
        
         | bluejay2387 wrote:
         | So there is a language war going on in the industry and some of
         | its justified and some of its not. Take 'agents' as an example.
         | I have seen an example of where a low code / no code service
         | dropped in a LLM node in a 10+ year old product, started
         | calling themselves an 'agent platform' and jacked up their
         | price by a large margin. This is probably a case where a debate
         | as to what qualifies as an 'agent' is appropriate.
         | 
         | Alternatively I have seen debates as to what counts as a 'Small
         | Language Model' that probably are nonsensical. Particularly
         | because in my personal language war the term 'small language
         | model' shouldn't even exist (no one knows that the threshold
         | is, and our 'small' language models are bigger than the 'large'
         | language models from just a few years ago).
         | 
         | This is fairly typical of new technology. Marketing departments
         | will constantly come up with new terms or try to take over
         | existing terms to push agendas. Terms with defined meaning will
         | get abused by casual participants and loose all real meaning.
         | Individuals new to the field will latch on to popular misuses
         | of terms as they try to figure out what everyone is talking
         | about and perpetuate definition creep. Old hands will overly
         | focus on hair splitting exercises that no one else really cares
         | about and sigh in dismay as their carefully cultured taxonomies
         | collapse under expansion of interest in their field.
         | 
         | It will all work itself out in 10 years or so.
        
           | BoiledCabbage wrote:
           | There is a reason why cars and computers are sold with specs.
           | 0-60 time, fuel efficiency...
           | 
           | People need to know the performance they can expect from LLMs
           | or agents. What are they capable of?
        
             | graypegg wrote:
             | A 2009 honda civic can get an under-5 seconds 0-60
             | easily... however it does involve high a cliff.
             | 
             | Result Specs (as in measuring output/experimental results)
             | need strict definitions to be useful and I think the
             | current ones with have for LLMs are pretty weak. (mostly
             | benchmarks that model one kind of interaction, and usually
             | not any sort of useful interaction)
        
         | absolutelastone wrote:
         | Well i don't see why we need to mangle the jargon. "Language
         | model" has an old meaning from NLP (which still applies), as a
         | computer model of language itself. Most commonly, a joint
         | probability distribution over words or sequences of words,
         | which is what LLMs are too. Prompted replies are literally
         | conditional probability densities conditioned on the context
         | you give it. "Foundation model" is a more general term I see a
         | lot.
         | 
         | To say a model is "just a LLM" is to presumably complain that
         | it has no added bells or whistles that someone thinks is
         | required beyond the above statistical model. And maybe I missed
         | the point, but the author seems to be saying "yes it's just a
         | LLM, but LLMs are all you need".
        
       | aaroninsf wrote:
       | You and I are just networks of neurons (also). *
       | 
       | * applies only to meatreaders
        
       | throwaway314155 wrote:
       | > They say: "the progresses we are seeing are due to the fact
       | that models like OpenAI o1 or DeepSeek R1 are not just LLMs".
       | 
       | Would be nice if the author could cite even one example of this
       | as it doesn't match my experience whatsoever.
        
         | tucnak wrote:
         | Your experience doesn't include Le Cunn, Chollet, et al?
        
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