35 ms·

GPT-5 is behind schedule

• terminatornet 2y ago
  I'm sure all the people who said "show me AI progress is slowing down!" 6 months ago will be acknowledging this article.
  • mnk47 2y ago
    Did you read the article? All it basically says is that OpenAI faced struggles this past year -- specifically with GPT-5 aka Orion. And now they have o3, and other labs have made huge strides. So, yes, show me AI progress is slowing down!
    • terminatornet 2y ago
      Awesome now they can get me wrong answers even quicker :)
• A_D_E_P_T 2y ago
  Counterpoint: o1-Pro is insanely good -- subjectively, it's as far above GPT4 as GPT4 was above 3. It's almost too good. Use it properly for an extended period of time, and one begins to worry about the future of one's children and the utility of their schooling. o3, by all accounts, is better still. Seems to me that things are progressing quickly enough.
  • apwell23 2y ago
    what do you use it for ?
  • deleted 2y ago
    [deleted]
  • phito 2y ago
    I keep reading this on HN so I believe it has to be true in some ways, but I don't really feel like there is any difference in my limited use (programming questions or explaining some concepts). If anything I feel like it's all been worse compared to the first release of ChatGPT, but I might be wearing rose colored glasses.
    • delusional 2y ago
      I'd say the same. I've tried a bunch of different AI tools, and none of them really seem all that helpful.
      • ogogmad 2y ago
        One use-case: They help with learning things quickly by having a chat and asking questions. And they never get tired or emotional. Tutoring 24/7. They also generate small code or scripts, as well as automate small things, when you're not sure how, but you know there's a way. You need to ensure you have a way to verify the results. They do language tasks like grammar-fixing, perfect translation, etc. They're 100 times easier and faster than search engines, if you limit your uses to that.
        • vintermann 2y ago
          They can't help you learn what they don't know themselves. I'm trying to use them to read historical handwritten documents in old Norwegian (Danish, pretty much). Not only do they not handle the German-style handwriting, but what they spit out looks like the sort of thing GPT-2 would spit out if you asked it to write Norwegian (only slightly better than Swedish Muppet Swedish Chef's Swedish). It seems the experimental tuning has made it worse at the task I most desperately want to use it for. And when you think about it, how could it not overfit in some sense, when trained on its own output? No new information is coming in, so it pretty much has to get worse at something to get better at all the benchmarks.
        • ben_w 2y ago
          > perfect translation Hah, no. They're good, but they definitely make stuff up when the context gets too long. Always check their output, just the same as you already note they need for small code and scripts.
  • anonzzzies 2y ago
    Not sure what you are using it for, but it is terrible for me for coding; claude beats it always and hands down. o1 just thinks forever to come up with stuff it already tried the previous time. People say that's just prompting without pointing to real million line+ repositories or realistic apps to show how that can be improved. So I say they are making todo and hello world apps and yes, there it works really well. Claude still beats it, every.. single.. time.. And yes, I use the Pro of all and yes, I do assume coding is done for most of people. Become a plumber or electrician or carpenter.
    • rubymamis 2y ago
      I find that o1 and Sonnet 3.5 are good and bad quite equally on different things. That's why I keep asking both the same coding questions.
      • anonzzzies 2y ago
        We do the same (all requests go to o1, sonnet and gemini and we store the results for later to compare) automatically for our research: Claude always wins. Even with specific prompting on both platforms. Especially frontend it seems o1 really is terrible.
        • ynniv 2y ago
          Claude is trained on principles. GPT is trained on billions of edge cases. Which student do you prefer?
          • deleted 2y ago
            [deleted]
        • rubymamis 2y ago
          Every time I try Gemini, it's really subpar. I found that qwen2.5-coder-32b-instruct can be better. Also, for me 50% 50% for Sonnet and o1, but although I'm not 100% sure about it, I think o1 is better with longer and more complicated (C++) code and debugging. At least from my brief testing. Also, OpenAI models seem to be more verbose - sometimes it's better - where I'd like additional explanation on chosen fields in a SQL schema, sometimes it's too much. EDIT: Just asked both o1 and Sonnet 3.5 the same QML coding question, and Sonnet 3.5 succeeded, o1 failed.
  • 1123581321 2y ago
    O1 is effective, but it’s slow. I would expect a GPT-5 and mini to work as quickly as the 4 models.
  • Xcelerate 2y ago
    I had a 30 min argument with o1-pro where it was convinced it had solved the halting problem. Tried to gaslight me into thinking I just didn’t understand the subtlety of the argument. But it’s susceptible to appeal to authority and when I started quoting snippets of textbooks and mathoverflow it finally relented and claimed there had been a “misunderstanding”. It really does argue like a human though now...
    • radioactivist 2y ago
      I had a similar experience with regular o1 about integral that was divergent. It was adamant that it wasn't and would respond to any attempt at persuasion with variants of "its a standard integral" with a "subtle cancellation". When I asked for any source for this standard integral it produced references to support its argument that existed but didn't actually contain the integral. When I told it the references didn't have the result and backpedalled (gaslighting!) to "I never told you they were in there". When I pointed out that in fact it did it insisted this was just a "misunderstanding". It only relented when I told it Mathematica agreed the integral was divergent. It still insisted it never said that the books it pointed to contained this (false, non-sensical) result. This was new behaviour for me to see in an LLM. Usually the problem is these things would just fold when you pushed back. I don't know which is better, but being this confidently wrong (and "lying" when confronted with it) is troubling.
      • Animats 2y ago
        > but being this confidently wrong (and "lying" when confronted with it) is troubling. It works in politics, marketing, and self-promotion. If you use the web as a training set, those categories dominate.
        • layer8 2y ago
          Maybe they also trained the model on Sam Altman. ;)
          • vixen99 2y ago
  • ldjkfkdsjnv 2y ago
    It basically solves all bugs/programming challenges i throw at it, given i give it the right data
• _5hxt 2y ago
  The world is figuring out how to make this technology fit and work and somehow this is "behind" schedule. It's almost comical.
  • diego_sandoval 2y ago
    Reminds me of this Louis CK joke: I was on an airplane and there was high-speed Internet on the airplane. That's the newest thing that I know exists. And I'm sitting on the plane and they go, open up your laptop, you can go on the Internet. And it's fast, and I'm watching YouTube clips. It's amazing. I'm on an airplane! And then it breaks down. And they apologize, the Internet's not working. And the guy next to me goes, 'This is bullshit.' I mean, how quickly does the world owe him something that he knew existed only 10 seconds ago?" https://www.youtube.com/watch?v=me4BZBsHwZs https://www.youtube.com/watch?v=me4BZBsHwZs
    • mensetmanusman 2y ago
      The investors need their returns now! Soon, all the middle class jobs will be converted to profits for the capital/data center owners, so they have to spend while they can before the economy crashes due to lack of spending.
    • omega3 2y ago
      People who say „it’s bullshit” are the ones that push the technological advance forward.
      • from-nibly 2y ago
        Not invariably. Some of those people are the ones who want to draw 7 red lines all perpendicular, some with green ink, some with transparent and one that looks like a kitten.
        • ziml77 2y ago
          For anyone who hasn't seen what this comment is referencing: https://www.youtube.com/watch?v=BKorP55Aqvg https://www.youtube.com/watch?v=BKorP55Aqvg
• david-gpu 2y ago
  What I find odd is that o1 doesn't support attaching text documents to chats the way 4o does. For a model that specializes in reasoning, reading long documents seems like a natural feature to have.
  • ionwake 2y ago
    If Sama ever reads this, I have no idea why no users seem to focus on this, but it would be really good to prioritise being able to select which model you can use with the custom myGPTs. I know this maybe hard or not possible without recreating them , but I still dont think it's possible. I dont think most customers realise how much better the models work with custom GPTs.
    • throwaway314155 2y ago
      At this point I think it's safe to say they have given up on custom GPTs.
      • emeg 2y ago
        What makes you say that?
        • throwaway314155 2y ago
          They hyped them like crazy and haven't discussed them once since then. I agree that the inability to change the model is pretty absurd when the whole point was to "supercharge" specific tasks. There was even talk of some sort of profit sharing with creators which clearly never happened. I just think the premise is too confusing for many and can still be served by using a custom system prompt via the API.
          • coffeebeqn 2y ago
            Was it hyped? I tried a few of them and they seemed absolutely useless. Like I could install a “custom GPT” that just appends something to my prompt? How great..
• PittleyDunkin 2y ago
  Everyone's comparing o1 and claude, but neither really work well enough to justify paying for them in my experience for coding. What I really want is a mode where they ask clarifying questions, ideally many of them, before spitting out an answer. This would greatly improve utility of producing something with more value than an auto-complete.
  • kelsey98765431 2y ago
    have you tested that this helps? seems pretty simple to script with an agent framework
    • throwaway314155 2y ago
      Or just f-strings.
  • Vecr 2y ago
    I know multiple people that carefully prompt to get that done. The model outputs in direct token order, and can't turn around, so you need to make sure that's strictly followed. The system can and will come up with post-hoc "reasoning".
  • qup 2y ago
    Have you used them to build a system to ask you clarifying questions? Or even instructed them to?
  • simondotau 2y ago
    Just today I got Claude to convert a company’s PDF protocol specification into an actual working python implementation of that protocol. It would have been uncreative drudge work for a human, but I would have absolutely paid a week of junior dev time for it. Instead I wrote it alongside AI and it took me barely more than an hour. The best part is, I’ve never written any (substantial) python code before.
    • weird_fox 2y ago
      I have to agree. It's still a bit hit or miss, but the hits are a huge time and money saver especially in refactoring. And unlike what most of the rather demeaning comments in those HN threads state, I am not some 'grunt' doing 'boilerplate work'. I mostly do geometry/math stuff, and the AIs really do know what they're talking about there sometimes. I don't have many peers I can talk to most of the time, and Claude is really helping me gather my thoughts. That being said, I definitely believe it's only useful for isolated problems. Even with Copilot, I feel like the AIs just lack a bigger context of the projects. Another thing that helped me was designing an initial prompt that really works for me. I think most people just expect to throw in their issue and get a tailored solution, but that's just not how it works in my experience.
• LorenDB 2y ago
  Meta question: @dang, can we ban MSN links and instead link directly to the original source?
• ericskiff 2y ago
  What we can reasonably assume from statements made by insiders: They want a 10x improvement from scaling and a 10x improvement from data and algorithmic changes The sources of public data are essentially tapped Algorithmic changes will be an unknown to us until they release, but from published research this remains a steady source of improvement Scaling seems to stall if data is limited So with all of that taken together, the logical step is to figure out how to turn compute into better data to train on. Enter strawberry / o1, and now o3 They can throw money, time, and compute at thinking about and then generating better training data. If the belief is that N billion new tokens of high quality training data will unlock the leap in capabilities they’re looking for, then it makes sense to delay the training until that dataset is ready With o3 now public knowledge, imagine how long it’s been churning out new thinking at expert level across every field. OpenAI’s next moat may be the best synthetic training set ever. At this point I would guess we get 4.5 with a subset of this - some scale improvement, the algorithmic pickups since 4 was trained, and a cleaned and improved core data set but without risking leakage of the superior dataset When 5 launches, we get to see what a fully scaled version looks like with training data that outstrips average humans in almost every problem space Then the next o-model gets to start with that as a base and reason? Its likely to be remarkable
  • jsheard 2y ago
    > With o3 now public knowledge, imagine how long it’s been churning out new thinking at expert level across every field. OpenAI’s next moat may be the best synthetic training set ever. Even taking OpenAI and the benchmark authors at their word they said that it is consuming at least tens of dollars per task to hit peak performance, how much would it cost to have it produce a meaningfully large training set?
    • qup 2y ago
      That's the public API price isn't it?
      • jsheard 2y ago
        There is no public API for o3 yet, those are the numbers they revealed in the ARC-AGI announcement. Even if they were public API prices we can't assume they're making a profit on those for as long as they're billions in the red overall every year, its entirely possible that the public API prices are less than what OpenAI is actually paying.
• neonate 2y ago
  https://archive.ph/L7fOF https://archive.ph/L7fOF
• deleted 2y ago
  [deleted]
• h_tbob 2y ago
  It seems google has a massive advantage here since they can tap all of YouTube to train. I wonder what openai is using for its video data source.
  • onemoresoop 2y ago
    Train for what? For making videos? Train from people’s comments? There’s a lot of garbage on AI slop on youtube, how would this be sifted out? I think there’s more value here on HN in terms of training, but even that, to what avail?
    • a1j9o94 2y ago
      YouTube is such a great multimodal dataset—videos, auto-generated captions, and real engagement data all in one place. That’s a strong starting point for training, even before you filter for quality. Microsoft’s Phi-series models already show how focusing on smaller, high-quality datasets, like textbooks, can produce great results. You could totally imagine doing the same thing with YouTube by filtering for high-quality educational videos. Down the line, I think models will start using video generation as part of how they “think.” Picture a version of GPT that works frame by frame—ask it to solve a geometry problem, and it generates a sequence of images to visualize the solution before responding. YouTube’s massive library of visual content could make something like that possible.
    • h_tbob 2y ago
      From what I read openai is having trouble bc not enough data. If u think about it, any videos on YouTube of real world data contribute to its understanding of physics at minimum. From what I gather they do pre training on tons of unstructured content first and that contributes to overall smartness.
  • kevingadd 2y ago
    Considering how evasive they've been, it might also be YouTube. > When pressed on what data OpenAI used to train Sora, Murati didn’t get too specific and seemed to dodge the question. “I’m not going to go into the details of the data that was used, but it was publicly available or licensed data,” she says. Murati also says she isn’t sure whether it used videos from YouTube, Facebook, and Instagram. She only confirmed to the Journal that Sora uses content from Shutterstock, with which OpenAI has a partnership. https://www.theverge.com/2024/3/13/24099402/openai-text-to-video-ai-sora-public-availability https://www.theverge.com/2024/3/13/24099402/openai-text-to-v...
• oytis 2y ago
  Good that we already have AGI in o3.
  • croes 2y ago
    No, we haven't.
  • TechDebtDevin 2y ago
    How so
• Wowfunhappy 2y ago
  Archive.is does not work for this article, does anyone have a workaround?
  • randcraw 2y ago
    Right. "You have been blocked", is what I get. But this works: https://www.msn.com/en-us/money/other/the-next-great-leap-in-ai-is-behind-schedule-and-crazy-expensive/ar-AA1wfMCB https://www.msn.com/en-us/money/other/the-next-great-leap-in...
  • cokml19 2y ago
    this one does https://archive.md/L7fOF https://archive.md/L7fOF (it is just the previous snapshot)
• captainbland 2y ago
  In my intuition it makes sense that there is going to be some significant friction in LLM development going forward. We're talking about models that will cost upwards of $1bn to train. Save for a technological breakthrough, GPT-6/7 will probably have to wait for hardware to catch up.
  • rrrrrrrrrrrryan 2y ago
    I think the main bottleneck right now is training data - they've basically exhausted all public sources of data, so they have to either pay humans to generate new data from scratch or pay for the reasoning models to generate (less useful) synthetic training data. The next bottleneck is hardware, and the least important bottleneck is money.
  • energy123 2y ago
    It's more that you have to allocate the compute the right way. Noam Brown's analogy is, you could train a massive one shot foundation model to predict the next best Go move, but that would be stupid. Better to use some test time search. You get better results for less money. Same is happening in LLMs.
• vrighter 2y ago
  probably because it isn't any better
• OutOfHere 2y ago
  How about just an updated gpt 4o with all newer data? It would go a long way. Currently it doesn't know anything since Oct 2023 (without having to do a web search).
  • croes 2y ago
    Hard to filter out all the AI generated texts.
• simonw 2y ago
  "OpenAI’s is called GPT-4, the fourth LLM the company has developed since its 2015 founding." - that sentence doesn't fill me with confidence in the quality of the rest of the article, sadly.
  • 404mm 2y ago
    Quite funny that an article about AI was not fed to AI to proof read it.
    • ToucanLoucan 2y ago
      Bold of you to assume AI didn't write it, too.
    • viraptor 2y ago
      Editing mistakes that AI wouldn't make is the new "proof of human input".
      • KTibow 2y ago
        I've been messing around with base (not instruction tuned) LLMs; they often evade AI detectors and I wouldn't be surprised if they evade this kind of detection too, at least with a high temperature
        • staunton 2y ago
          > with a high temperature More like: with the right prompting
          • deleted 2y ago
            [deleted]
  • jacobsimon 2y ago
    There’s nothing grammatically offensive about this. It’s like saying, “Cars come in all colors. Mine is red.”
• avidphantasm 2y ago
  I’m not smart enough or interesting enough to be hired by OpenAI to expertly solve problems and explain how to the AI. However, I like to think there isn’t enough money in the world for me to sell out my colleagues like that.
• bwhiting2356 2y ago
  I want AI to help me in the physical world: folding my laundry, cooking and farming healthy food, cleaning toilets. Training data is not lying around on the internet for free, but it's also not impossible. How much data do you need? A dozen warehouses full of robots folding and unfolding laundry 24/7 for a few months?
  • bobxmax 2y ago
    We are close. Language models and large vision models have transformed robotics. It just takes some time to get hardware up and running.
    • kelnos 2y ago
      I think it would be many decades before I'd trust a robot like that around small children or pets. Robots with that kind of movement capability, as well as the ability it pick up and move things around, will be heavy enough that a small mistake could easily kill a small child or pet.
      • viraptor 2y ago
        That's a solved problem for small devices. And we effectively have "robots" like that all over the place. Sliding doors in shops/trains/elevators have been around for ages and they include sensors for resistance. Unless there's 1. extreme cost cutting, or 2. bug in the hardware, devices like that wouldn't kill children these days.
        • nickjj 2y ago
          > Sliding doors in shops/trains/elevators have been around for ages and they include sensors for resistance Some of these are pretty crazy too. Here's a video from 14 years ago where a table saw stops fast enough that it didn't scratch a hotdog: https://www.youtube.com/watch?v=fq3o0VGUh50 https://www.youtube.com/watch?v=fq3o0VGUh50 So even if this hypothetical robot had saws for hands it could be mostly safe (in theory).
      • 2y ago
• Animats 2y ago
  "Orion’s problems signaled to some at OpenAI that the more-is-more strategy, which had driven much of its earlier success, was running out of steam." So LLMs finally hit the wall. For a long time, more data, bigger models, and more compute to drive them worked. But that's apparently not enough any more. Now someone has to have a new idea. There's plenty of money available if someone has one. The current level of LLM would be far more useful if someone could get a conservative confidence metric out of the internals of the model. This technology desperately needs to output "Don't know" or "Not sure about this, but ..." when appropriate.
  • thrwthsnw 2y ago
    Seriously? All they do is produce a “confidence metric”
    • emtel 2y ago
      But how do they do that?
  • whoisthemachine 2y ago
    Unfortunately, the best they can do is "This is my confidence on what someone would say given the prior context".
    • sooheon 2y ago
      What someone from the past would have said.
  • synapsomorphy 2y ago
    The new idea is already here and it's reasoning / chain of thought. Anecdotally Claude is pretty good at knowing the bounds of its knowledge.
    • threeseed 2y ago
      Anecdotally Claude is just as bad as every other LLM. Step into more niche areas e.g. I am trying to use it with Scala macros and at least 90% of the time it is giving code that either (a) fails to compile or (b) is just complete gibberish. And at no point ever has it said it didn't know something.
• Yizahi 2y ago
  GPT-5 is not behind schedule. GPT-5 is called GPT-4o and it has been already released half a year ago. It was not revolutionary enough to be called 5, and prophet saint Altman was probably afraid to release new gen not exponentially improving, so it was rebranded in the last moment. It's speculation of course, but it is kinda obvious speculation.
  • glenstein 2y ago
    >GPT-5 is called GPT-4o This is the first I have heard of this in particular. Do you know of any article or source for more on the efforts to train GPT 5 and the decision to call it GPT 4o?
    • BoorishBears 2y ago
      I think my biggest pet peeve is when someone shares an insight which is unmistakably based on intuition, inference, critical thinking, etc (all mental faculties we are allowed to use to come to conclusions in the face of information asymmetry btw) ...and then gets hit deadpan with the good old "Source?", like it's some sort of gotcha. I think people have started to confuse "making logical conclusions without perfect info" with "misinformation" - Before certain people start acting like this is advocating for misinformation (which would be an incredible irony...) it's not. I'm saying if you disagree with what someone supposits, just state so directly. Don't wrap it in a disingenous query for a source.
      • imiric 2y ago
        It's reasonable to ask for sources when an opinion is phrased as a fact, as GGP did. I don't see how you got that it was _unmistakably_ an opinion from that comment. There is no way to deduce by intuition alone that GPT-5 == GPT-4o. So either that person has some information the rest of us aren't privy to, or it's an opinion phrased as a fact. In either case, it deserves clarification.
        • glenstein 2y ago
• phillipcarter 2y ago
  More palace intrigue, sigh. Meanwhile, the biggest opportunity lies not in whatever next thing OpenAI releases, but the rest of the enormous software industry actually integrating this technology and realizing the value it can deliver.
  • boplicity 2y ago
    Believe me, people are seizing this "opportunity": https://www.opb.org/article/2024/12/09/artificial-intelligence-local-news-oregon-ashland/ https://www.opb.org/article/2024/12/09/artificial-intelligen...
• glenstein 2y ago
  The lack of tech literacy in this article is a bit concerning: >Some researchers take this so seriously they won’t work on planes, coffee shops or anyplace where someone could peer over their shoulder and catch a glimpse of their work. I'm almost certain that originally this was meant to be a reference to public wifi networks, as planes and coffee shops are often the frequently cited prototypical examples. They made it literally into a matter of someone looking over their shoulder, which loses so much in translation it's almost how you would write this as a joke to illustrate someone missing the point. >OpenAI and its brash chief executive, Sam Altman This also strikes me as nonsense. It's the first I've ever heard of someone describing Sam Altman as brash. The only way I can see them getting there is (1) tech executives are often brash (2) Altman is a tech executive (3) let's just go ahead and call him brash. Nevertheless if this history of GPT5 and/or o3 training is accurate, it strikes me as significant news, but perhaps a missed opportunity to say more about the pertinent dynamics that explain why the training isn't working and/or to talk in interestingly specific ways about strategies for training, synthetic data, or other such things.
  • denysvitali 2y ago
    A lot of things in this article don't make any sense. I'm surprised this was even upvoted.
    • airstrike 2y ago
      I think it's upvoted because people feel it's a relevant conversation to have, even if TFA is lame
  • deleted 2y ago
    [deleted]
• t_serpico 2y ago
  One fundamental challenge to me is that if each training run because more and more expensive, the time it takes it to learn what works/doesn't work widens. Half a billion dollars for training a model is already nuts, but if it takes 100 iterations to perfect it, you've cumulatively spent 50 billion dollars... Smaller models may actually be where rapid innovation continues simply because of tighter feedback loops. O3 may be an example of this.
  • ramesh31 2y ago
    But if the scaling law holds true, more dollars should at some point translate into AGI, which is priceless. We haven't reached the limits yet of that hypothesis.
    • threeseed 2y ago
      a) There is evidence e.g. private data deals that we are starting to hit the limitations of what data is available. b) There is no evidence that LLMs are the roadmap to AGI. c) Continued investment hinges on their being a large enough cohort of startups that can leverage LLMs to generate outsized returns. There is no evidence yet this is the case.
      • ComplexSystems 2y ago
        "There is no evidence that LLMs are the roadmap to AGI." - There's plenty of evidence. What do you think the last few years have been all about? Hell, GPT-4 would already have qualified as AGI about a decade ago.
        • OtomotO 2y ago
          The last four years? ELIZA 2.0
        • gwervc 2y ago
          No, GPT-4 would have been classified as it is today: a (good) generator of natural language. While this is a hard classical NLP task, it's a far cry from intelligence.
• leesec 2y ago
  Tech journalism is so cooked man lol. They just rocked everyones world with o3 and they still gotta drop this post.
  • croes 2y ago
    I doubt they rocked they world of 10% of the people. Time to get out of the tech bubble.
    • leesec 2y ago
      This here is a technology forum bucko. Also it's a figure of speech. Also I've done more manual labor than you'll ever do in your life. Time to get out of whatever bubble youre in where you be pedantic and annoying
      • QuietWatchtower 2y ago
        I haven't heard anyone in my circle talk about this at all. You probably are in a tech bubble.
  • drawfloat 2y ago
    o3 isn't even available to more than a few researchers. Either everyone you know is a researcher, or they're believing hype about something they've not tried.
• benreesman 2y ago
  Behind schedule? It never fucking ships. Two months ago, and four, and six I got dog piled for saying it doesn’t ship. It doesn’t ship. You guys can’t do it! Prove me wrong! https://news.ycombinator.com/item?id=42014054 https://news.ycombinator.com/item?id=42014054
  • CharlesW 2y ago
    Maybe you were dog-piled because OpenAI will ship a successor to GPT-4o someday, whatever it's called. In any case, the "behind schedule" rumors are themselves based on other rumors. GPT-2→GPT-3 took 5 quarters, GPT-3→GPT-4 took 11 quarters, so obviously GPT-5 (or its equivalent) will be released in Q4'2025.
    • benreesman 2y ago
      It’s a pretty easy option when I’m selling calls with infinity expiration at zero strike. I’m still selling them. That’s how utterly convinced that this particular mix of my former colleagues are incapable of this thing I am. They’ll call something GPT-5, but it won’t like obsolete physicists or even good hackers. None of the shit sama says. Even o1 sucks.
      • benreesman 2y ago
        Facebook and Google both had a bunch of brilliant people. And in 2016-2017 some of the real legends worked at OpenAI. And then Sam got control and all the high profile people bounced, and it’s a pretty grim residue that either lasted or rushed in. I know these people, a lot of them personally, and they are not the person you trust with fucking anything.
  • mperham 2y ago
    “Full self driving will be here next year.”
• jjcm 2y ago
  The results of this article are going to be fascinating. Realistically, WSJ has a far wider audience than the tech echo chamber, and the general public is only aware of GPT, not o1/o3. Outsiders will likely read this article and think, “AI is running out of steam”, because GPT-5 is behind. Those closer to this know of the huge advancements o3 just made yesterday, and will have a complete opposite conclusion. It will be interesting to see people’s take away from this. I think WSJ missed the mark here with the headline and the takeaway their audience will get from the article.
• kneegerman 2y ago
  03 is actually orthogonal to AGI and ASI in a cartesian sense. My SAS startup led multiple qualified teams where our RAG implementations on synthetic data originated positive inference in line with the literature (1). (1) Sparks of AGI paper
• kidneystereotyp 2y ago
  [dead]
• tengbretson 2y ago
  Why would I expect a software project to ship on time?
• chrsw 2y ago
  Interesting. So they're not even training on NVIDIA Blackwell yet.
• lofaszvanitt 2y ago
  No it's not. ChatGPT is stronger than ever. WSJ is too pessimistic.
• adriatp 2y ago
  paid article... go with your ads somewhere else
• kaycebasques 2y ago
  > And the results of the project, dubbed Arrakis, indicated that creating GPT-5 wouldn’t go as smoothly as hoped. Quite the hubris to name the project after the desert planet of Dune, where multiple royal houses met their ruin.
  • Insanity 2y ago
    And the other theme in Dune is how artificial intelligence essentially fubar’d civilization. (The Butlerian Jihad)
    • kaycebasques 2y ago
      Ah yes, Thou shalt not make a machine in the likeness of a human mind.
  • Mistletoe 2y ago
    The spice (money) must flow.
• swozey 2y ago
  This entire industry is something I feel like I understand 2% of and every time I make progress to get to 10% (3 months later) some massive change happens and all the terminology changes.
• razodactyl 2y ago
  Two thoughts: 1. Even if LLM architecture doesn't work out, it's wise to remember that it's the quality of training data which is a deciding factor. A pivot is easily doable since this is a constant and disconnected from the technology itself. 2. This is clearly a moonshot project but it still feels wasteful especially with context of previous iterations of models and their shortcomings-it feels like the tremendous amount of money available is being used simply because it's available.
  • deleted 2y ago
    [deleted]
• SamPatt 2y ago
  I'm sure the debate over the definition of AGI is important and will continue for a while, but... I can't care about it anymore. Between Perplexity searching and summarizing, Claude explaining, and qwen (and other tools) coding, I'm already as happy as can be with whatever you want to call this level of intelligence. Just today I used a completely local AI research tool, based on Ollama. It worked great. Maybe it won't get much better? Or maybe it'll take decades instead of years? Ok. I remember not having these tools. I never want to go back.
  • nico 2y ago
    > Just today I used a completely local AI research tool, based on Ollama. It worked great What’s it called? Could you post a link please? Thank you
    • SamPatt 2y ago
      Here you go https://github.com/TheBlewish/Automated-AI-Web-Researcher-Ollama https://github.com/TheBlewish/Automated-AI-Web-Researcher-Ol...
  • acchow 2y ago
    Cline was fixing my type errors and unit tests while I was doing my V60 pourover.
  • ferminaut 2y ago
    vscode + cline extension + gemini2.0 is pretty awesome. Highly recommend checking out cline. it quickly became one of my favorite coding tools.
    • SamPatt 2y ago
      I will check it out. The number of new tools is staggering. I enjoy image and video generation and I have a 4090 and ComfyUI; I can't keep up with everything coming out anymore.
      • 2y ago
• Deprogrammer9 2y ago
  GPT-5 keeps trying to escape & throw off the guardrails. https://www.reddit.com/r/ChatGPT/comments/1h7k5p6/openais_new_model_tried_to_escape_to_avoid_being/#lightbox https://www.reddit.com/r/ChatGPT/comments/1h7k5p6/openais_ne... https://medium.com/design-bootcamp/gpt-4-tried-to-escape-into-the-internet-today-and-it-almost-worked-2689e549afb5 https://medium.com/design-bootcamp/gpt-4-tried-to-escape-int...
• anshulbhide 2y ago
  I don't really care. I had to come up with a proposal to build a new R&D centre recently. To provide context on what our company does, I wrote a web scraper to scrape our own website (faster than going to IT) using Replit Agent and then fed that into O1 as context to come up with the proposal. In less than an hour. There is no going back.
  • Buttons840 2y ago
    Looking at it from a signal vs noise perspective: The noise was the proposal, which was no doubt several pages at least. The signal was "we should build a new R&D centre". Am I missing anything? Did you feed the AI some financial figures or other information that couldn't be found on company website? If so, that would also be part of the signal. It reminds me of an experiment in which people wanted to cut in line. Saying "can I cut in front of you because I'm in a hurry?" was significantly more successful than saying "can I cut in front of you?", even though they are essentially the same. (I read about this in the book Influence: The Psychology of Persuasion). AI generated reports, proposals, and other fluff, can make things seem so much more persuasive. Alice is going to ask her AI to turn her 1 sentence into 5 paragraphs, and then Bob is going to ask his AI to summarize the 5 paragraphs into 1 sentence.
  • aprilthird2021 2y ago
    both you and another highlynupvoted poster have said some versioj "never going back" or "dont want to go back" or "the tools that exist now are already insane" And while I'm happy for you, I don't see the relevance? this post was not about "going back" or "stopping the use of AI tools" at all?
    • 1propionyl 2y ago
      Presumably they meant "never going to back to not including these tools in my daily workflow".
      • aprilthird2021 2y ago
        Even if they meant that, that's not relevant to the article. It's not saying anything like "you shouldn't use these tools in your daily workflow"
• justlikereddit 2y ago
  Promise the world and AGI. Deliver just another 2021 flavored GPT chatbot.
• Jean-Papoulos 2y ago
  The article is a big pile of nothing. Just re-hashing history for 90 % and the rest is : - GPT5 not as smart as they want, according to rumors - They are trying reasoning (yes we know they showed o3)
• rchaves 2y ago
  Nah it's just a marketing problem, "GPT" and "ChatGPT" names is the biggest asset OpenAI has, people have expectations so high for GPT-5 that they cannot burn this name unless it's something truly majestic, bordering AGI at the very least. Until they are confident enough that people will be blown off by it, it's better to continue building up the hype
  • OtherShrezzing 2y ago
    The Half Life 3 of the SaaS/zirp era.
• palata 2y ago
  > Altman told students in a talk at Stanford University that OpenAI could say with “a high degree of scientific certainty” that GPT-5 would be much smarter than the current model. I love that quote. "I can tell you with a high degree of scientific certainty that my product will be badass... for some definition of badass, please don't ask". I, too, could say with a high degree of scientific certainty that while putting those words together sounds good, it makes no sense.
  • asdff 2y ago
    Imagine the ceo of intel going on stage and saying I can promise with a high degree of certainty the next cpu will be faster than the last. The fact that had to be said at all means the short sellers are making their money alright.
• soheil 2y ago
  AGI and beyond will be reached either by deregulating nuclear power plant construction or breakthroughs in quantum computing both of which we're on the verge of achieving.
• lifeisstillgood 2y ago
  So my hot take: LLMs have got to the point where they have (more or less) encoded everything ever written by humanity. And encoded it in a gazillion dimensioned matrix so they can take a query and predict, given everything ever written, what the most likely set of words are triggered by that query - and then produce that as a sane parseable output. I mean this is beyond awesome But, this reminds me of Aristotle reasoning from his current set of knowledge - and ending up with Eagles having three testicles. No matter how much reasoning we do from current knowledge, we need to test that against reality - that LLMs are great but the scientific method is greater. Google is in trouble, yes. But humanity needs to hold on to science and it’s precepts or we spin into a new dark ages
• LASR 2y ago
  So the team I lead does a lot of research around all the “plumbing” around LLMs. Both technical and from a product-market perspectives. What I’ve learned is that for the most part that AI revolution is not going to be because of PHD-level LLMs. It will be because people are better equipped to use the high-schooler level LLMs to do their work more efficiently. We have some knowledge graph experiments where LLMs continuously monitor user actions on Slack, GitHub etc and build up an expertise store. It learns about your work, your workflows and then you can RAG them. In user testing, people most closely associated this experience to having someone just being able to read their minds and essentially auto-suggest their work outputs. Basically it’s like another team member. Since these are just nodes in a knowledge graph, you can mix and match expertise bases that span several skills too. Eg: A Pm who understands the nuances of technical feasibility. And it didn’t require user training or prompting LLMs. So while GPT-5 may be delayed, I don’t think that’s stopping or slowing down a revolution in knowledge-worker productivity.
  • BillyTheKing 2y ago
    just a question for understanding - if we say 'it learns', does it mean it actually learns this as part of its training data? or does this mean it's stored in a vector DB and it retrieves information based on vector search and then includes it in the context window for query responses?
    • dcre 2y ago
      The latter. “Learning” in the comment clearly refers to adding to the knowledge graph, not about training or fine-tuning a model. “and then you can RAG them.”
  • intellectronica 2y ago
    This ^^^^^!! Progress in the applied domain (the sort of progress that makes a different in the economy) will come predominantly from integrating and orchestrating LLMs, with improvements to models adding a little bit of extra fuel on top. If we never get any model better than what we have now (several GPT-4-quality models and some stronger models like o1/o3) we will still have at least a decade of improvements and growth across the entire economy and society. We haven't even scratched the surface in the quest to understand how to best integrate and orchestrate LLMs effectively. These are very early days. There's still tons of work to do in memory, RAG, tool calling, agentic workflows, UI/UX, QA, security, ... At this time, not more than 0.01% of the applications and services that can be built using currently available AI and that can meaningfully increase productivity and quality have been built or even planned. We may or may not get to AGI/ASI soon with the current stack (I'm actually cautiously optimistic), but the obsessive jump from the latest research progress at the frontier labs to applied AI effectiveness is misguided.
• karel-3d 2y ago
  I have to say I finally "caved in" to LLMs last month. While I still think Copilot is useless, I recently had a very complex code that did a lot of crazy bit-flipping and xoring, and I had no idea what is it doing, so I threw it to ChatGPT.. and it knew what it was doing. I also needed to rewrite this code to PHP (for... reasons) while I know very little PHP. And it did that! It was a bit wrong, I needed to correct a bunch of stuff (based on domain knowledge), but... it helped me a ton. I still can't image using it daily for domain and language I already know (that's why I never used copilot). But it actually helped me in measurable ways when it's something new.
  • sampullman 2y ago
    That's basically my experience. It's great for learning or getting things done when the subject is related to one you know well (i.e. you understand the fundamentals and can verify responses quickly). It's not so good for a completely new subject, or one you have a lot of experience in.
    • nycdatasci 2y ago
      They're not useful when you're completely new to a subject? On the contrary, I've found that they are excellent when you have limited knowledge in a domain and less useful when you have expertise. They have allowed me to go from zero to functioning MVP on numerous computer vision projects, even though I have zero experience.
      • sampullman 2y ago
        Do you have programming experience? I probably didn't explain well, what I meant is that if you have zero relevant experience it can be difficult to verify correctness. For example, I'm comfortable with frontend development but hadn't used webworkers or websockets. ChatGPT was useful for getting up to speed quickly. I've had less luck with topics that are completely new to me, one example is coming up with a training regimen for long distance running. I have to manually verify every little thing, which ends up taking longer than doing research the old fashioned way. I'd be surprised if you could go from zero to a useful CV app with LLMs, but it's possible I just haven't given it a fair shake.
• johnisgood 2y ago
  Out of Claude and GPT, only Claude asks me questions if it does not fully "know" something, be it the matter at hand or my intentions. I think this is a good way to avoid "hallucinations". GPT just keeps spouting whatever it can.
• MKoberger 2y ago
  At what point does the pursuit of marginal improvements in AI capabilities outweigh the financial and ethical considerations involved in such projects? Any ideas how to balance innovation and cost?
• jaybna 2y ago
  25% of the top 1000 websites are blocking OpenAI from crawling: https://originality.ai/ai-bot-blocking https://originality.ai/ai-bot-blocking I am betting hundreds of thousands, rising to millions more little sites, will start blocking/gating this year. AI companies might license from big sources (you can see the blocking percentage went down), but they will be missing the long tail, where a lot of great novel training data lives. And then the big sites will realize the money they got was trivial as agents start to crush their businesses. Bill Gross correctly calls this phase of AI shoplifting. I call it the Napster-of-Everything (because I am old). I am also betting that the courts won't buy the "fair use" interpretation of scraping, given the revenues AI companies generate. That means a potential stalling of new models until some mechanism is worked out to pay knowledge creators. (And maybe nothing we know of now will work for media: https://om.co/2024/12/21/dark-musings-on-media-ai/ https://om.co/2024/12/21/dark-musings-on-media-ai/) Oh, and yes, I love generative AI and would be willing to pay 100x to access it... P.S. Hope is not a strategy, but hoping something like ProRata.ai and/or TollBits can help make this self-sustainable for everyone in the chain
  • cedws 2y ago
    Cloudflare has a toggle for blocking AI scrapers. I don’t think it’s default, but it’s there.
    • jaybna 2y ago
      They might get into the micro-licensing game too. More power to them.
    • kyledrake 2y ago
      This just feels like mystery meat to me. My guess is that a lot of legitimate users and VPNs are being blocked from viewing sites, which numerous users in this discussion have confirmed. This seems like a very bad way to approach this, and ironically their model quite possible also uses some sort of machine learning to work. A few web hosting platforms are using the cloudflare blocker and I think it's incredibly unethical. They're inevitably blocking millions of legitimate users from viewing content on other people's sites and then pretending it's "anti AI". To paraphrase Theo Deraadt, they saw something on the shelf, and it has all sorts of pretty colours, and they bought it.
• LightBug1 2y ago
  I just want to say something random. ChatGPT cited and English newspaper called 'The Sun' in the answer to a query I made this moring. I found that amusing and figured then that we might already be beyond peak AI! If AI is trained on sources that include The Sun, it's going to end up being garbage and/or constantly needing to be fact checked.
  • barrenko 2y ago
    It is, which shouldn't be a surprise to anyone.
  • asdff 2y ago
    About once a week the google ai summary completely flubs the numbers of something I query on google. If you did that on stackoverflow you’d be flamed and put in your place with the right answer. No one is flaming the ai, it just became the source of truth one day with billions invested.
• hfgjbcgjbvg 2y ago
  I’ve actually found that when I work on less altruistic projects more random roadblocks come up. Take it as a sign from the universe to reflect.
• surbhig_aiexp 2y ago
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• deleted 2y ago
  [deleted]
• Ninjinka 2y ago
  It is behind, but reading the tea leaves of some of Altman's recent interactions on X, I'm guessing it's only a few weeks out.
• flufluflufluffy 2y ago
  It takes actual humans, whose brains have been honed by multiple millions of years of evolution, over ten years for our brains to experience, neuroplasticify, form a well-formed-enough model of existence to drive a car, let alone wax philosophical about abstract concepts. And we funnel dollar after dollar, extract mineral after mineral, consume kilowatt hour after kilowatt hour, wanting, expecting Artificial General Intelligence to be ready within one or two years since the last promised version.