8 ms·

Rewind your mind to 2019 and imagine reading a post that said “The experience seemed roughly on par with trying to advise a mediocre, but not completely incomp

• talldayo 2y ago
  To be honest, I have gotten 100x more useful answers out of Siri's WolframAlpha integration than I ever have out of ChatGPT. People don't want a "not completely incompetent graduate student" responding to their prompts, they want NLP that reliably processes information. Last-generation voice assistants could at least do their job consistently, ChatGPT couldn't be trusted to flick a light switch on a regular basis.
  • meowface 2y ago
    I use both for different things. WolframAlpha is great for well-defined questions with well-defined answers. LLMs are often great for anything that doesn't fall into that.
  • thelastparadise 2y ago
    Wait til you generate WolframAlpha queries from natural language using Claude 3.5 and use it to interpret results as well.
    • talldayo 2y ago
      I've tried the ChatGPT integration and it was kinda just useless. On smaller datasets it told me nothing that wasn't obviously apparent from the charts and tables; on larger datasets it couldn't do much besides basic key/value retrieval. Asking it to analyze a large time-series table was an exercise in futility, I remain pretty unimpressed with current offerings.
  • Karrot_Kream 2y ago
    How does this square up with literally what Terence Tao (TFA) writes about O1? Is this meant to say there's a class of problems that O1 is still really bad at (or worse than intuition says it should be, at least)? Or is this "he says, she says" time for hot topics again on HN?
    • sebzim4500 2y ago
      o1-preview is still quite a specialized model, and you can come up with very easy questions that it fails embarassingly despite it's success in seemingly much more difficult tests like olympiad programming/maths questions. You certainly shouldn't think of it like having access to a graduate student whenever you want, although hopefully that's coming.
  • segmondy 2y ago
    Then you have a skill issue. 10 million paying are for GPT monthly because a large of them are getting useful value out of it. WolframAlpha has been out for a while and didn't take off for a reason. "GPT couldn't be trusted to flick a light switch on a regular basis" pretty much implies you are not serious or your knowledge about the capabilities of LLM is pretty much dated or derived from things you have read.
    • jazzyjackson 2y ago
      Wolframalpha is a free service, really kind of an ad for all the (curated, accurate) datasets built into Wolfram Language Wolfram Research is a profitable company btw
    • codr7 2y ago
      FACT: The technology is inherently unreliable in its current form. And the weakness is built in, its not going to go away anytime soon.
      • jonahx 2y ago
        The same is true of search engines, yet they are still incredibly useful.
        • codr7 2y ago
          Not the same technology at all, until recently at least. EDIT: Looks like I hurt someone's feelings by killing their unicorn. It was going to happen sooner or later, and pretending isn't very constructive. In fact, pretending this technology is reliable is a very risky thing to do.
  • fnordpiglet 2y ago
    I use home assistant with the extended open ai integration from HACS. Let me tell you, it’s orders of magnitude better than generic voice assistants. It can understand fairly flexibly my requests without me having a literal memory of every device in the house. I can ask for complex tasks like turning every light in the basement on without there being a zone basement by inferring from the names. I have air quality sensors throughout and I can ask it to turn on the fan in areas with low air quality and if literally does it without programming an automation. Usually Alexa will order 10,000 rolls of toilet paper and ship them to my boss when I ask it to turn on the bathroom fan. Personally tho the utility of this level of skill (beginner grad in many areas) for me personally is in areas I have undergraduate questions in. While I literally never ask it questions in my field, I do for many other fields I don’t know well to help me learn. over the summer my family traveled and I was home alone so I fixed and renovated tons of stuff I didn’t know how to do. I work a headset and had the voice mode of ChatGPT on. I just asked it questions as I went and it answered. This enabled me to complete dozens of projects I didn’t know how to even start otherwise. If I had had to stop and search the web and sift through forums and SEO hell scapes, and read instructions loosely related and try to synthesize my answers, I would have gotten two rather than thirty projects done.
• noch 2y ago
  The important point is, I feel, that most people are not even at the level of intelligence of a "a mediocre, but not completely incompetent, graduate student." A mediocre graduate science student, especially of the sort who graduates and doesn't quit, is a very impressive individual compared to the rest of us. For "us", having such a level of intelligence available as an assistant throughout the day is a massive life upgrade, if we can just afford more tokens.
  • thewanderer1983 2y ago
    >A mediocre graduate science student, especially of the sort who graduates and doesn't quit, is a very impressive individual compared to the rest of us. Incorrect. University graduates shows a good work ethic, a certain character and a ability to manage time. It's not a measure of being better than the rest of humanity. Also, it's not a good measure of intelligence. If you only want to view the world through credentials. Academics don't consider your intelligence until you have a Ph.D and X years of work in your field. Industry only uses graduates as a entry requirement for junior roles and then favors and cares only about your years of experience after that. Given that statement I can only assume you haven't been to University. You are mistaken to think, especially in time we are in now that the elite class are any more knowledgeable then you are.
    • ahnick 2y ago
      Here are the key points outlining why thewanderer1983's response misinterprets noch's comment and contains inaccuracies: Misinterpretation of the Original Point: Intelligence vs. Moral Superiority: Noch discusses the intelligence level of a mediocre graduate science student compared to the general population. Thewanderer1983 misreads this as a claim of moral or inherent superiority over "the rest of humanity," which was not implied. Conflation of Educational Levels: University Graduates vs. Graduate Students: The response conflates undergraduate university graduates with graduate science students. Noch specifically refers to graduate students who have pursued advanced degrees, which typically require higher levels of specialization and intellectual rigor. Incorrect Assessment of Intelligence Measures: Graduate Studies as a Measure of Intelligence: Successfully completing graduate studies, especially in science, often requires significant intellectual capability. Dismissing this as "not a good measure of intelligence" overlooks the challenges inherent in advanced academic work. Irrelevant Focus on Credentials and Industry Practices: Credentials vs. Intelligence Discussion: Noch's comment centers on intelligence levels, not merely on holding credentials. Bringing up how industry values experience over degrees shifts the focus away from the original discussion about intelligence. Unfounded Assumptions About Noch's Background: Ad Hominem Attack: Suggesting that Noch hasn't been to university is an unfounded personal assumption that does not contribute to the argument and detracts from a respectful discourse. Introduction of the 'Elite Class' Notion: Straw Man Argument: Thewanderer1983 introduces the concept of an "elite class," which Noch did not mention. This misrepresents the original comment and argues against a point that wasn't made. Overgeneralizations About Academia and Industry: Academia's Recognition of Intelligence: Claiming that academics don't consider intelligence until one has a Ph.D. and years of work is an overgeneralization. Intelligence is recognized and valued at various academic levels. Industry's View on Graduates: Stating that industry only uses graduates as an entry requirement ignores the significant roles that advanced degree holders often play in innovation and leadership within industries. Ignoring the Core Benefit Highlighted: AI as a Life Upgrade: Noch emphasizes how access to AI with the intelligence level of a graduate student is a substantial benefit for most people. Thewanderer1983 fails to address this key point, instead focusing on unrelated issues. Misunderstanding of the Value of Graduate Education: Work Ethic vs. Intellectual Achievement: While a good work ethic is important, graduate education in science also demands high intellectual capability, critical thinking, and problem-solving skills. Logical Fallacies: Red Herring: The discussion about industry preferences and academic credentials diverts from the main argument about the intelligence level of graduate students. Ad Hominem: Attacking Noch's presumed lack of university experience instead of addressing the argument presented.
• meroes 2y ago
  I mean paying several hundred to thousands of grad students to RLHF for several years and you get a corpus of grad-student text. I'm not surprised at all. AI companies hire grad students to RLHF in every subject matter (chemistry, physics, math, etc). The grad-students write the prompts, correct the model, and all of that is fed into a "more advanced" model. It's corpi of text. Repeat this for every grade level and subject. Ask the model that's being trained on chemistry grad level work a simple math question and it will probably get it wrong. They aren't "smart". It's aggregations of text and ways to sample and then predict.
  • fnordpiglet 2y ago
    Except you’re talking about a general purpose foundation model that’s doing all these subjects at once. It’s not like you choose the subject specific model with Claude or gpt-01. The key isn’t whether these things are smart or not. The key is that they put something that can answer basic grad level questions on almost any subject. For people that don’t have a graduate level education in any subject this is a remarkable tool. I don’t know why the statement that “wow this is useful and a remarkable step forward” is always met with “yeah but it’s not actually smart.” So? Half of all humans have an IQ less than 100. They’re not smart either. Is this their value? For a machine, being able to produce accurate answers to most basic graduate level questions is -science fiction- regardless of whether it’s “smart.” The NLP feat alone is stunning, and going from basically one step above gibberish to “basic grad school” in two years is a mouth dropping rate of change. I suspect folks who quibble over whether it’s “real intelligence” or simply a stochastic parrot have lost the ability to dream.
    • meroes 2y ago
      Well ya once each project, e.g. “grad level math”, “k—12 math”, “undergrad math”, “k-12 chemistry”, etc is sufficient they are all fed into a larger more powerful model. Maybe my RLHF work does make it harder for me to dream, but I teach models math which means a lot of prompt writing, and yet I have not found a way to have the model teach me math I don’t know yet (and there’s a lot I don’t know). It’s fun to play around with, but I still gravitate toward the isolated texts, not the aggregation as too much is lost or averaged in my opinion/experience. But hey maybe I’m overtrained on the traditional learning methods.
• JumpCrisscross 2y ago
  The first profession AI seems on track to decimate is programming. In particular, the brilliant but remote and individual contributor. There is an obvious conflict of interest in this forum.
  • dartos 2y ago
    No, the first profession AI was on track to decimate was artists, but that didn’t really happen. AI just destroyed shutterstock.
    • mkarrmann 2y ago
      Is most code being written the equivalent of high-art or Shutterstock?
      • dartos 2y ago
        I think most code being written is like a custom car made out of the most cost effective parts available. Not pretty, but it gets the job done for the specific use cases of a given business. Real production code doesn’t and have a shutter stock equivalent. If you think most code is stock, then you just haven’t had enough experience in industry yet.
        • mkarrmann 2y ago
          I actually like that analogy. It's somewhere in between. Enough that LLMs can help in many ways, but the current models are still far away from doing everything.
          • dartos 2y ago
            Yeah, they’re not useless, but I don’t really see them replacing the profession of programming. Just another tool in the kit.
    • energy123 2y ago
• TrackerFF 2y ago
  Even more amazing, there plenty - PLENTY - of posters here that routinely either completely shit on LLMs, or casually dismiss them as "hype", "useless", and what have you. I've been saying this for quite some time now, but some people are in for a very rude awakening when the SOTA models 5-10 years from now are able to completely replace senior devs and engineers. Better buckle up, and start diversifying your skills.
  • zeroonetwothree 2y ago
    Not sure how this post is evidence of AIs replacing senior devs.
  • ramraj07 2y ago
    The way I see it these models especially O1 is an intelligence booster. If you start with zero it gives you back zero. Especially if you’re just genuinely trying to use it and not just trying to do some gotcha stuff.
  • achierius 2y ago
    Diversifying to what? When AI can fully replace senior developers the world as we know it is over. Best case capitalism enters terminal decline: buy rifles. Worst case, hope that whatever comes out the either side is either benevolent or implodes quickly.
  • skeks6272 2y ago
    [flagged]
• roboboffin 2y ago
  [dead]
• bamboozled 2y ago
  Remind your mind to 1850, imagine seeing a lightbulb.
• fumeux_fume 2y ago
  Rewind your mind to 1950 and reading that the future is chatting with bots about solving math homework.
  • nathanasmith 2y ago
    They would be wondering why it took so long.
    • deleted 2y ago
      [deleted]
• ksec 2y ago
  Which is why I think the AI era isn't hype but very much real. Jensen said AI has reached the era of iPhone. We wont have AGI or ASI, whatever definition people have with those terms in the next 5 - 10 years. But I would often like to refer AI as Assisted or Argumented Intelligence. And it will provide enough value that drives current Computer and Smartphone sales for at least another 5 - 10 years. Or 3-4 cycles.
• j_timberlake 2y ago
  Terry is a genius that can get that value out of an LLM. Average Joe can't do anything like that yet, both because he won't be as good at prompting the model, and because his problems in life aren't text-based anyway.
  • fnordpiglet 2y ago
    I think this is where multi modal LLMs are so powerful. The ability to directly speak to the LLM with your voice is huge.