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LLM Year in Review
- swyx 10mo agoxposted to https://x.com/karpathy/status/2002118205729562949 https://x.com/karpathy/status/2002118205729562949
- CamperBob2 10mo agoAnd also accessible sans login via https://xcancel.com/karpathy/status/2002118205729562949 https://xcancel.com/karpathy/status/2002118205729562949 .
- TheAceOfHearts 10mo agoI think one of the things that is missing from this post is engaging a bit in trying to answer: what are the highest priority AI-related problems that the industry should seek to tackle? Karpathy hints at one major capability unlock being UI generation, so instead of interacting with text the AI can present different interfaces depending on the kind of problem. That seems like a severely underexplored problem domain so far. Who are the key figures innovating in this space so far? In the most recent Demis interview, he suggests that one of the key problems that must be solved is online / continuous learning. Aside from that, another major issues is probably reducing hallucinations and increasing reliability. Ideally you should be able to deploy an LLM to work on a problem domain, and if it encounters an unexpected scenario it reaches out to you in order to figure out what to do. But for standard problems it should function reliably 100% of the time.
- lukax 10mo agoGoogle is doing that with A2UI. LLM will be able to decide how to present info to the user.
- victorbuilds 10mo agoNotable omission: 2025 is also when the ghosts started haunting the training data. Half of X replies are now LLMs responding to LLMs. The call is coming from inside the dataset.
- thoughtpeddler 10mo agoI appreciate Andrej’s optimistic spirit, and I am grateful that he dedicates so much of his time to educating the wider public about AI/LLMs. That said, it would be great to hear his perspective on how 2025 changed the concentration of power in the industry, what’s happening with open-source, local inference, hardware constraints, etc. For example, he characterizes Claude Code as “running on your computer”, but no, it’s just the TUI that runs locally, with inference in the cloud. The reader is left to wonder how that might evolve in 2026 and beyond.
- D-Machine 10mo agoThe section on Claude Code is very ambiguously and confusingly written, I think he meant that the agent runs on your computer (not inference) and that this is in contrast to agents running "on a website" or in the cloud: > I think OpenAI got this wrong because I think they focused their codex / agent efforts on cloud deployments in containers orchestrated from ChatGPT instead of localhost. [...] CC got this order of precedence correct and packaged it into a beautiful, minimal, compelling CLI form factor that changed what AI looks like - it's not just a website you go to like Google, it's a little spirit/ghost that "lives" on your computer. This is a new, distinct paradigm of interaction with an AI. However, if so, this is definitely a distinction that needs to be made far more clearly.
- realcul 10mo agoWell Microsoft had thier "localhost" AI before CC but that was a ghost without a clear purpose or skill.
- magicalhippo 10mo agoFrom what I can gather, llama.cpp supports Anthropic's message format now[1], so you can use it with Claude Code[2]. [1]: https://github.com/ggml-org/llama.cpp/pull/17570 https://github.com/ggml-org/llama.cpp/pull/17570 [2]: https://news.ycombinator.com/item?id=44654145 https://news.ycombinator.com/item?id=44654145
- karpathy 10mo agoThe CC point is more about the data and environmental and general configuration context, not compute and where it happens to run today. The cloud setups are clunky because of context and UIUX user in the loop considerations, not because of compute considerations.
- bgwalter 10mo agoVibe coding is sufficient for job hoppers who never finish anything and leave when the last 20% have to be figured out. Much easier to promote oneself as an expert and leave the hard parts to other people.
- zingar 10mo agoI’ve found incredible productivity gains writing (vibe coding) tools for myself that will never need to be “productionised” or even used by another person. Heck even I will probably never use the latest log retrieval tool, which exists purely for Claude code to invoke it. There is a ton of useful software yet to be written for which there _is_ no “last 20%”.
- diamond559 10mo agoThese tools are so useful and make you so much more "productive" that you don't think anyone else would want to pay anything for them huh? Did your boss at least give you a big raise for your "productivity" increase, or maybe lay off some of your underperforming coworkers bc you are just so much better now?
- simonw 10mo agoDo you mean vibe coding as-in producing unreviewed code with LLMs and prompting at it until it appears to work, or vibe coding as a catch-all for any time someone uses AI-assistance to help them write code?
- bgwalter 10mo agoKarpathy uses the term for all of this in the exuberant paragraph 5. of his blog post.
- augment_me 10mo agoAll software is not meant to be open-source, in production and working on 100 platforms. Sometimes the point of the software is to make an app with 2 buttons for your mom to help her do her grocery shopping easier
- delichon 10mo ago> I like this version of the meme for pointing out that human intelligence is also jagged in its own different way. The idea of jaggedicity seems useful to advancing epistemology. If we could identify the domains that have useful data that we fail to extract, we could fill those holes and eventually become a general intelligence ourselves. The task may be as hard as making a list of your blind spots. But now we have an alien intelligence with an outside perspective. While making AI less jagged it might return the favor. If we keep inventing different kinds of intelligence the sum of the splats may eventually become well rounded.
- visarga 10mo agoI don't think it will become well rounded because that is not cost sensitive. Intelligence is sensitive to cost, it is the core constraint shaping it. Any action has a cost - energy, materials, time, opportunity or social. Intelligence is solving the cost equation, if we can't solve it we die. Cost is also why we specialize, in a group we can offload some intelligence to others. LLMs also have their own costs, and are shaped by it into some kind of jagged intelligence, they are no spherical cows either.
- mvkel 10mo ago> In this world view, nano banana is a first early hint of what that might look like. What is he referring to here? Is nano banana not just an image gen model? Is it because it's an LLM-based one, and not diffusion?
- dragonwriter 10mo agoI think he is referring to capability, not architecture, and say that NB is at the point that it is suggestive of the near-future capability of using GenAI models to create their own UI as needed. NB (Gemini 2.5 Flash Image) isn't the first major-vendor LLM-based image gen model, after all; GPT Image 1 was first.
- simonw 10mo agoWhat's interesting about Nano Banana (and even more so video models like Veo 3) is that they act as a weird kind of world model when you consider that they accept images as input and return images as output. Give it an image of a maze, it can output that same image with the maze completed (maybe). There's a fantastic article about that for image-to-video models here: https://video-zero-shot.github.io/ https://video-zero-shot.github.io/ > We demonstrate that Veo 3 can zero-shot solve a broad variety of tasks it wasn't explicitly trained for: segmenting objects, detecting edges, editing images, understanding physical properties, recognizing object affordances, simulating tool use, and much more.
- starchild3001 10mo agoThe distinction Karpathy draws between "growing animals" and "summoning ghosts" via RLVR is the mental model I didn't know I needed to explain the current state of jagged intelligence. It perfectly articulates why trust in benchmarks is collapsing; we aren't creating generally adaptive survivors, but rather over-optimizing specific pockets of the embedding space against verifiable rewards. I’m also sold on his take on "vibe coding" leading to ephemeral software; the idea of spinning up a custom, one-off tokenizer or app just to debug a single issue, and then deleting it, feels like a real shift.
- graemefawcett 10mo agoI've been doing it for months, it's lovely https://tech.lgbt/@graeme/115749759729642908 https://tech.lgbt/@graeme/115749759729642908 It's a stack based on finishing the job Jupyter started. Fences as functions, callable and composable. Same shape as an MCP. No training required, just walk them through the patterns. Literally, it's spatially organized. Turns out a woman named Mrs Curwen and I share some thoughts on pedagogy. There does in fact exist a functor that maps 18th century piano instruction to context engineering. We play with it
- HarHarVeryFunny 10mo ago> The distinction Karpathy draws between "growing animals" and "summoning ghosts" via RLVR I don't see these descriptions as very insightful. The difference between general/animal intelligence and jagged/LLM intelligence is simply that humans/animals really ARE intelligent (the word was created to describe this human capability), while LLMs are just echoing narrow portions of the intelligent output of humans (those portions that are amenable to RLVR capture). For an artificial intelligence to be intelligent in it's own right, and therefore be generally intelligent, it would need to need - like an animal - to be embodied (even if only virtually), autonomous, predicting the outcomes of it's own actions (not auto-regressively trained), learning incrementally and continually, built with innate traits like curiosity and boredom to put and keep itself in learning situations, etc. Of course not all animals are generally intelligent - many (insects, fish, reptiles, many birds) just have narrow "hard coded" instinctual behaviors, but others like humans are generalists who evolution have therefore honed for adaptive lifetime learning and general intelligence.
- mips_avatar 10mo agoI would love Andrej's take on the fast models we got this year. Gemini 3 flash and Grok 4 fast have no business being as good + cheap + fast as they are. For Andrej's prediction about LLMs communicating with us via a visual interface we're going to need fast models, but I feel like AI twitter/HN has mostly ignored these.
- gnerd00 10mo agocheck out Sasha Luccioni
- mips_avatar 10mo agoDo you have a link to anything they wrote about this?
- HarHarVeryFunny 10mo agoJust guessing here, but these small models may well be essentially distillations of larger ones, with this being where their power comes from. e.g. Use a large model to generate synthetic reasoning traces, then train a small model on those.
- jkubicek 10mo ago> In the same way, LLMs should speak to us in our favored format - in images, infographics, slides, whiteboards, animations/videos, web apps, etc. You think every Electron app out there re-inventing application UX from scratch is bad, wait until LLMs are generating their own custom UX for every single action for every user for every device. What does command-W do in this app? It's literally impossible to predict, try it and see!
- johnfn 10mo agoOn the other side of the spectrum, I see some of the latest agents, like Codex, take care to get accessibility right -- something not even many humans bother to do.
- becquerel 10mo agoIt's an extension of how I've noticed that AIs will generally write very buttoned-down, cross-the-ts-and-dot-the-is code. Everything gets commented, every method has a try-catch with a log statement, every return type is checked, etc. I think it's a consequence of them not feeling fatigue. These things (accessibility included) are all things humans generally know they 'should' do, but there never seems to be enough time in the day; we'll get to it later when we're less tired. But the ghost in the machine doesn't care. It operates at the same level all the time
- Aiisnotabubble 10mo agoBut that's exactly what an LLM solved. It's the best ui ever. It understands a lot of languages and abstract concepts. It will not be necessary at all to let LLM generate random uis. I'm not a native English speaker. I sometimes just throw in a German word and it just works.
- tim333 10mo ago>our favored format - in images, infographics, slides, whiteboards, animations/videos, web apps, etc If you look at how humans actually communicate I'd guess #1 is text/speech, #2 pictures
- deleted 10mo ago[deleted]
- ausbah 10mo agotl;dr seems like llms are maturing on the product side and for day-day usage
- socketcluster 10mo agoFor me, Claude Code was the most impressive innovation this year. Cursor was a good proof of concept but Claude Code is the tool that actually got me to use LLMs for coding. The kind of code that Claude produces looks almost exactly like the code I would write myself. It's like it's reading my mind. This is a game changer because I can maintain the code that Claude produces. With Claude Code, there are no surprises. I can pretty much guess what its code will look like 90% to 95% of the time but it writes it a lot faster than I could. This is an amazing innovation. Gemini is quite impressive as well. Nano banana in particular is very useful for graphic design. I haven't tried Gemini with coding yet but TBH, Claude Code does such a great job; if I could code any faster, I would get decision fatigue. I don't like rushing into architecture or UX decisions. I like to sit on certain decisions for a day or two before starting implementation. Once you start in a particular direction, it's hard to undo and you may try to double down on the mistake due to sunk cost fallacy. I try hard to avoid that.
- tarsinge 10mo agoI don’t have much time to evaluate tools every months and I have settled on Cursor. I’m curious on what I’m missing when using the same models?
- wahnfrieden 10mo agoIf you switch to Codex you will get a lot of tokens for $200, enough to more consistently use high reasoning as well. Cursor is simply far more expensive so you end up using less or using dumber models. Claude Code is overrated as it uses many of its features and modalities to compensate for model shortcomings that are not as necessary for steering state of the art models like GPT 5.2
- ccmcarey 10mo agoI disagree, the claude models seem the best at tool calling, opus 4.5 seems the smartest, and claude code (+ claude model) seems to make good use of subagents and planning in a way that codex doesn't
- augment_me 10mo agoI noticed that despite really liking Karpathy and the blog, I was am kind of wincing/involuntarily reacting to the LLM-like "It's not X, its Y"-phrases: > it's not just a website you go to like Google, it's a little spirit/ghost that "lives" on your computer > it's not just about the image generation itself, it's about the joint capability coming from text generation There would be no reaction from me on this 3 years ago, but now this sentence structure is ruined for me
- huevosabio 10mo agoSame, I cringe when I read this structure.
- d-lisp 10mo agoI hated these sentences way before LLMs, at least in the context of an explanation. > it's not just a website you go like Google, it's a little spirit/ghost that "lives" on your computer This type of sentence, I call rhetorical fat. Get rid of this fat and you obtain a boring sentence that repeats what has been said in the previous one. Not all rhetorical fats are equal, and I must admit I find myself eyerolling on the "little spirit" part more than about the fatness. I understand the author wants to decorate things and emphasize key elements, and the hate I feel is only caused by the incompatible projection of my ideals to a text that doesn't belong to me. > it's not just about the image generation itself, it's about the joint capability coming from text generation. That's unjustified conceptual stress. That could be a legitimate answer to a question ("No, no, it's not just about that, it's more about this"), but it's a text. Maybe the text wants you to be focused, maybe the text wants to hype you; this is the shape of the hype without the hype. "I find image generation is cooler when paired with text generation."
- killerstorm 10mo agoIt is not a decoration. Karpathy juxtaposes ChatGPT (which feels like a "better google" to most people) to Claude Code, which, apparently, feels different to him. It's a comparison between the two. You might find this statement non-informative, but without two parts there's no comparison. That's really the semantics of the statement which Karpathy is trying to express. ChatGPT-ish "it's not just" is annoying because the first part is usually a strawman, something reader considers trite. But it's not the case here.
- nkko 10mo agoBeyond graduating students, I see model labs as “accelerators/incubators” bundling, launching, and productizing observed ideas that gain traction. The sheer strength of their platforms, the number of eyes watching them, near-zero marginal costs, and seemingly unlimited budgets mean that only slow decision-making can prevent them from becoming the next Amazons of everything.
- alexgotoi 10mo agoLLMs still need to bring clear added value to enterprise and corporate work; otherwise, they remain a geek’s toy. Big media agencies that claim to use AI rely on strong creative teams who fine-tune prompts and spend weeks doing so. Even then, they don’t fully trust AI to slice long videos into shorter clips for social media. Heavy administrative functions like HR or Finance still don’t get approval to expose any of their data to LLMs. What I’m trying to say is that we are still in the early stages of LLM development, and as promising as this looks, it’s still far from delivering the real value that is often claimed.
- gessha 10mo agoI think their non-deterministic nature is what’s making it difficult to adopt. It’s hard to train somebody in the old way of “if you see this, do this” because when you call the LLM twice you most likely get different results. It took a long time to computerize businesses and it might take some time to adopt/adapt to LLMs.
- dandelionv1bes 10mo agoSomething I’ve been thinking about is how as end stage users (eg building our own “thing” on top of an LLM) we can broadly verify it’s doing what we need without benchmarks. Does a set of custom evals built out over time solve this? Is there more we can do?
- andai 10mo agoThe bit about o3 being the turning point is very interesting. I heard someone say that o3 (or perhaps the cheaper o4-mini) should have been called gpt-5, and that people would have been mind blown. Instead it kind of went under the radar as far as the mainstream goes. Whereas we just got the incremental progress with gpt-5 instead and it was very underwhelming. (Plus like 5 other issues at launch, but that's a separate story ;) I'm not sure if o4-mini would have made a good default gpt though. (Most use is conversational and its language is very awkward.) So they could have just called it gpt-5 pro or something, and put it on the $20 tier. I don't know.
- karpathy 10mo agoI agree with this fwiw, for many months I talked to people who never used o3 and didn’t know what it was because it sounded weird. Maybe it wasn’t obvious at the time but that was a good major point release to make then.
- andai 10mo agoHere's the source for the jagged spiky intelligence diagram: https://x.com/colin_fraser/status/1994235521812328695 https://x.com/colin_fraser/status/1994235521812328695 https://karpathy.bearblog.dev/the-space-of-minds/ https://karpathy.bearblog.dev/the-space-of-minds/
- distalx 10mo agoFriendly reminder: There is no ghost in the machine. It is a system executing code, not a being having thoughts. Let’s admire the tool without projecting a personality onto it.
- deleted 10mo ago[deleted]
- ngruhn 10mo agoConsciousness is weird and nobody understands it. There is no good reason to assume that these systems have it. But there is also no good reason to rule it out.
- squidbeak 10mo agoYou sound as if you have grounds for certainty about this. What are they?
- dr_dshiv 10mo agoThat’s the old way of thinking about it. there is a new way.
- skybrian 10mo agoFor me, that’s kind of the point. It’s similar to how the characters in a novel don’t really exist, and yet you can’t really discuss what happens in a novel without pretending that they do. It doesn’t really make sense to treat the author’s motivations and each character’s motivations as the same. Similarly, we’re all talking to ghosts now, which aren’t real, and yet there is something there that we can talk about. There are obvious behavioral differences depending on what persona the LLM is generating text for. I also like the hint of danger in “talking to ghosts.” It’s difficult to see how a rational adult could be in any danger from just talking, but I believe the news reports that some people who get too deep into it get “possessed.”
- lysecret 10mo agoIt’s funny how every podcaster/public ai figure is so certain text as a Ui will go away and it’s not going anywhere.
- tim333 10mo agoIt's probably increased during my lifetime. People used to talk, now they sit and text into smartphones.
- gessha 10mo agoThere might be some confusion about the transition to what some call post-literate era: era where text is not the primary medium. That’s not necessarily bad because you get the advantages of other mediums - oral and visual but it is something to keep in mind.
- tim333 10mo agoI'm bit skeptical that a post-literate era is happening. I gather it appears in some sci-fi but I don't see much sign in reality. I mean here we are on a text only site. If anything we seem to be heading for a 100% literate society. Literacy graphs here: https://ourworldindata.org/grapher/cross-country-literacy-rates?facet=none&country=ESP~POL~ITA~IRL~GBR~SWE~DEU~NLD~FRA https://ourworldindata.org/grapher/cross-country-literacy-ra...
- gessha 10mo agoI don’t think the post-illiterate era means that text will disappear. I think it’s just not going to be dominant anymore but I also have my reservations since I do prefer the text medium.
- devalexwells 10mo agoA few days ago I was trying to unsubscribe to a service (notably an AI 3D modeling tool that I was curious about). I spent 5 minutes trying to find a way to unsubscribe and couldn't. Finally, I found it buried in the plan page as one of those low-contrast ellipses on the plan card. Instead of unsubscribing me or taking me to a form, it opened a convos with an AI chatbot with a preconfigured "unsubscribe" prompt. I have never felt more angry with a UI that I had to waste more time talking to a robot before it would render the unsubscribe button in the chat. Why would we bring the most hated feature of automated phone calls to apps? As a frontend engineer I am horrified by these trends.
- metalman 10mo agofind on page:slop=0
- cheesecompiler 10mo agoExcellent more grounded review. A few questions: > LLMs are emerging as a new kind of intelligence, simultaneously a lot smarter than I expected and a lot dumber than I expected Isn't this concerning? How can we know which one we get? In the realm of code it's easier to tell when mistakes are being made. > regular people benefit a lot more from LLMs compared to professionals, corporations and governments We thought this would happen with things like AppleScript, VB, visual programming. But instead, AI is currently used as a smarter search engine. The issue is that's also the area where it hallucinates the most. What do you think is the solution?
- sireat 10mo agoWhat is current state of the art workflow when working with legacy code across multiple languages? This would be a 100 kLOC legacy project written in C++, Python, and jQuery era Javascript circa 2010. Original devs have long left. I would rather avoid C++ as much as possible. I've been Github Copilot (in VS Code) user since June of 2021 and still use it heavily, but the "more powerful intellisence" approach is limiting me on legacy projects. Presumably I need to provide more context on larger projects. I can get pretty far with just ChatGPT plus and feeding bits and pieces of project. However that seems like using the wrong tool. Codex seems better for building things but not sure about grokking existing things. Would Cursor be more suitable for just dumping the whole project (all languages) basically 4 different sub projects and then selectively activating what to include in queries?
- sandos 10mo agoI dont understand, the agent mode of copilot will search for and be pretty good and filling its own context afaik. I never really feed any of our 100k+ lines legacy codebase explicitly to the LLM.
- rldjbpin 10mo agopersonally the point about apps built on top of LLMs resonated the most. however the success of well-engineered tools for specific use cases, often with choice of model, goes to show that: - benchmarks don't mean a lot for the frontier stuff, but can be interesting for the same series of models (smaller v/s larger). reminds me of comparing clock speeds between CPUs. - the app layer can fill the gaps to squeeze out the most for a use case, but there is still no one-size-fits-all situation. - often the discourse here or the perspective of people building seem disconnected from an average user. a lot of discussion in the post is irrelevant for the vast majority of users. e.g. as cool as TUI can be, it is not an interface most users would gravitate towards. while not directly related, other modalities are more exciting, and comes thanks to applying techniques for handling text to other media forms, or in conjunction.