Davi Muammar @dapih

@ravinsharma7 It's easier to invent a new BS definition and quote it 10k times than to came up with 10k unique ideas.

@mattpocockuk I'm unable to do it. your thread exceeded my context window.

this is a weird long post without much substance I strongly recommend against reading it ... so, do you feel like whatever you're working on right now is pointless, or will have zero value soon, due to the crazy times we're living? then, perhaps you should stop, and start working on the only unsolved problem that actually matters TODAY: ✨ replicating GPT-3 in a laptop ✨ "why is that so important?" because it would make AI incredibly cheap, which would mean everyone would have Fable-class models in their laptops, without depending on Anthropic, OpenAI, or any other hyper-scaler giant. and that's amazing, don't you think? "isn't that literally impossible?" that's the cool part: as far as computer science is concerned, no. not really. not at all. is entirely plausible and, as far as we know, most likely not even hard. it takes one good idea. one breakthrough. one great "aha moment", to go from zero to "hey, this software I wrote is producing credible English sentences" and whenever that happens: - the entire AI industry collapses - clusters are liquidated - we all get Fable at home - you become famous and rich, if that's your thing sounds fun, doesn't it? "wtf you talking, OF COURSE that is hard" so prove it. show me a paper, a lean file, anything that proves that training a Fable-class model fundamentally requires billions of dollars. you can't, because, guess what - it is not true! the only "evidence" we have is purely psychological. "many attempted over decades, and the best thing we have is GPTs, so, it is a hard problem" - but that's not a scientific argument. that's a human, psychological, sociological argument. and if that's it, consider the following counter-argument: ✨ humans are stupid as hell ✨ I mean, 10 years ago we didn't have transformers, so, that very argument could be used against GPTs existing. yet, they exist. we have them now, because someone found it. and, guess what, it isn't even complex. I mean, karpathy implemented the whole thing in a napkin. and it probably compiles. we were just too dumb to figure GPTs out... for decades. just like GPTs, there ARE other approaches, other algorithms, other architectures, equally simpler or even simpler, that do work. this is a mathematical certainty. and one of them might be astronomically faster than what we're doing right now. and you might be the one to find it! "me? why me???" because you're intelligent, creative and handsome. I see a lot of potential in you. in fact, I always believed in you. and I think you're wasting your time, doing that silly agent orchestrator. nobody wants that. quit it. take your most interesting ideas, intuition, creativity, and work in a problem that matters. do your best shot at reproducing GPT-3 in your own laptop. do NOT fork llama.cpp. do NOT train another LLM. do something... ✨different✨ it must be unique, novel, full of YOUR soul. something nobody thought of, or bothered doing. go ahead and implement that thing in C/CUDA (or Bend!). no Python! zero excuses for Python. any model is fluent in GPGPU now. build a real kernel. and then, train your thing. download wikipedia, give it time and compute to absorb the patterns of English speech. you can rent GPUs anywhere nowadays. let it train. then, ask it some questions. chances are it will just respond back. just like GPT-2 answered OpenAI. computers are incredible. don't underestimate them! "many tried. nobody succeeded. why would I?* see - that's your mistake again. turns out not many actually tried, at all. I promise you. who do you think is seriously working on that? people on Mozilla? they're busy building a browser Linus Torvalds? he is busy building an OS employees at OpenAI, Anthropic, xAI? they're paid to work on what is proven to work: GPTs. what about all the AI enthusiasts all around the world? yeah, you know they're mostly fine tuning Qwen and how about your friends? if only they weren't busy building a SaaS in the eve of AGI... how about people from the past? bro - people from the past seriously expected Lisp would be AGI. just dismiss them. they didn't have the compute, the resources, the knowledge, the MODELS that we have today. that YOU have access to. so, what's left? not much. the world looks big. it is not. truth is: ✨almost nobody is working on this ✨ "I still think it is impossible. I don't trust you" well, take my word no more. Ilya himself, in his 2019 talk on GPT-2, said: > "the story of deep learning is this: empirically old simple methods which were usually invented in the 80s and the 90s when scaled up on very large clusters work really well." and then: > "(we took) normal simple reinforcement learning method, scaled it up, and discovered that it suddenly becomes very capable of solving extremely hard problems." and again: > "you take a simple tool which is unimposing and barely works, and then you run it on a big cluster and suddenly it works, it becomes a capable tool for solving problems" do you see the point here? Ilya isn't arguing that transformers are magic. Ilya is arguing that SCALING is magic step #1: take a simple, elegant algorithm. step #2: shove compute at its face. step #3: ...? step #4: your computer is talking to you THAT is the key insight that led to GPT-3 THAT is what Ilya saw THAT is what caused the OpenAI x Anthropic war THAT is the founding principle of the ongoing era not "scaling transformers work" but "scaling beautiful algorithms works" that's the incredible lesson. yet, we all took it and... threw it way. - zurk bought 100k GPUs. to train GPTs - musk bought 100k GPUs. to train GPTs - bezos bought 100k GPUs. to train GPTs ... that's what everyone is doing. so, no. not many are trying to replicate GPT-3 through other means. we're just ants, after all... whenever we find a pile of sugar, we leave a track of pheromones, which guide the rest of the colony towards the new food source. the colony then swarms around the pile, extract all of it, until no grain is left. but piles of sugar aren't spontaneously generated in the middle of nowhere. they imply something more profound: "humans are around". and, if humans are in sight, even better things must be. like a big sweet cake. a colony that only follows the pheromone trail would miss the cake for the grains. that's why every ant species has scouts and exploratory foragers. and, just like a pile of sugar implies something more profound, LLMs also imply something quite profound: *computers are capable of thinking* a pile of sugar is never alone. GPTs are most likely not the only system capable of thinking. so, if you find yourself a bit lost, without purpose, like your work is pointless and Fable 3 will soon one shot it anyway... consider becoming a scout. find a new approach to AI. bring something new to humanity. breaking out of the massive cost associated with training GPTs is the next big step in AI, and it will only happen if people like you work to make it happen.

the problem is that I'm not convinced by 1). At all. Researchers with an EA bent? Sure. C-suite? Oh yeah, I'm just SURE the power-seeking is for pure altruistic reasons lmao. And who has the power matters, a lot more than the researchers intentions (tech people are notoriously good at believing whatever narratives are thrown at them uncritically)

watching these scary stupid bots rushing to reply anything can be a traumatic experience

roon @tszzl

2 months ago

you dont have to believe in existential risk or job loss for this to be scary: ai is real, you can replicate human thought in machines. it is redefining what it means to be human. even if they are strictly corrigible tools that do what we ask, this can be traumatic

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1/n A physical book is a real object, anchored. If you read a particular edition, you remember not only the contents but the object itself: its cover, typography, smell, even where a passage sat on the page. Books organize themselves in memory by place --the ancient method of loci. Digital text does not exist.

Nassim Nicholas Taleb @nntaleb

2 months ago

My new library does not have tall bookshelves, intentionally so all books are in easy reach. Non #Lindy books are ditched except those that can be useful are in a hallway not in the main rooms. [Same material as Umberto Eco's but shorter]

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This chart should terrify policymakers. Indonesia’s middle class did not merely slow down. It went into reverse. After two decades of expansion, the middle-class population peaked at 61.5 million people in 2018, representing 23% of the population. By 2026, that figure had fallen to just 46.6 million people, or 16.6%. That is not a cyclical slowdown. That is structural deterioration. For years, policymakers celebrated GDP growth, infrastructure projects, commodity booms, and headline investment numbers. But the ultimate scorecard of an economy is whether ordinary people become wealthier over time. This chart suggests millions of Indonesians are moving in the opposite direction. The middle class is the economic engine of every successful country. They buy homes, cars, insurance, consumer goods, education, travel, financial products, and healthcare. They generate tax revenue. They create small businesses. They drive domestic demand. When the middle class shrinks, the economy loses its most important customer. The uncomfortable question is simple: where did the gains go? If GDP is growing, if conglomerates continue expanding, if commodity exports remain large, then why are fewer Indonesians qualifying as middle class than eight years ago? More importantly, if you are born poor in Indonesia today, what ladder exactly are you supposed to climb? If you are exceptionally good looking, perhaps you can monetize attention through social media. If you are academically gifted, perhaps you can break into an ultra-competitive institution like MBB, survive years of brutal expectations, and eventually use that platform to do something bigger. If you are entrepreneurial, maybe you build a business against overwhelming odds. If you are lucky, perhaps you benefit from family connections, inheritance, or access to opportunities unavailable to most people. But an economy cannot rely on exceptionalism. A healthy economy creates millions of pathways upward, not a handful of lottery tickets. The situation becomes even more concerning when you consider that well-paying white-collar jobs are becoming increasingly scarce. Many multinational companies that once established regional operations, technology centers, shared-service hubs, and professional offices in Indonesia have either downsized, relocated, or shifted future expansion elsewhere. Those jobs were not valuable merely because of the salaries they paid. They were valuable because they transferred knowledge, management expertise, technical skills, global best practices, and professional networks into the local workforce. Over time, they helped develop intellectual capital that could later be recycled into entrepreneurship, leadership positions, startups, and domestic businesses. When those opportunities disappear, the loss is not limited to employment. The country also loses a training ground for future managers, engineers, consultants, analysts, and business leaders. Human capital compounds just like financial capital. Once that pipeline weakens, rebuilding it can take years or even decades. The bigger risk is that social mobility slows. When people stop believing hard work leads to a better life, trust in institutions weakens. Aspirations decline. Consumption slows. Talent leaves. The country’s most productive people increasingly look elsewhere for opportunity. This is why Indonesia’s biggest economic challenge is no longer growth. It is upward mobility. A country cannot thrive without a growing middle class, a steady pipeline of high-quality jobs, and a clear path for ordinary people to join it. And right now, all three appear to be moving in the wrong direction.

@GergelyOrosz “Tell me how you measure me and I’ll tell you how I will behave.” ― Eliyahu M. Goldratt, Critical Chain

I think the tech industry should fight back by doing "a day without data centers"

CEOs are uniquely prone to AI psychosis because they’re sufficiently distant from the last mile of work that still has to happen to generate most value with AI. So when they play with AI, they see the happy path results, often not considering the next 10 or 20 things that have to happen to get sustainable results from agents. “Look I made this awesome product prototype”. Yes but you didn’t have to review the code before it went into production and fix a bunch of issues. “Look I generated a contract”. Yes but you didn’t verify all the terms before it goes out to the counterparty and didn’t have to wire up all the past contracts to work with. The best thing you can do as a CEO is to use AI a *ton* to figure out the real implications of agents in the enterprise, and come out the other side with an appreciation for both the upside and the real work that goes into them.

Michal Malewicz @michalmalewicz

2 months ago

CEOs are the most delusional about AI. Detached from reality.

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@yunta_tsai weekend projects are built for dopamine products are built for responsibility very different emotional architectures

Bot replies Bot replies Bot replies Bot replies No need to use Browserbase - playwright/chromium does it better Bot replies Bot replies Bot replies Bot replies I’ve been using this for months Bot replies Bot replies Bot replies Bot replies 😂😂😂Ai noise killing the real Ai momentum 🤦🏻‍♂️

In many ways the argument I'm forwarding isn't new: I basically think that AI companies won't have the data to produce domain-general superintelligences. But I think this holds even if "sample efficiency" improves dramatically. I also don't think the missing data can be simulated.

Dijkstra on why he believed programmers should stop using the term "bug"

people are walking around with their laptops slightly ajar to keep their agents running

@akramcodez My first PC in 1987: IBM PC XT-8088 with OS MS-DOS 3.1, RAM 640KB, HDD 40MB, 5.25" Floppy Disk Drive, 4-colors CGA Monitor.

@trikcode if you're a genius you will learn C++ and let AI manage higher level languages.

anthropic killed this, anthropic killed that, why cant anthropic kill LinkedIn

Single claude.md does not prevent anything, even opus with max effort does not remember shit after only around 15-20% context nowadays You need to push harder using hooks, accumulating wiki for lessons learned and using another llm model like gpt 5.4 as advisor to audit claude's outputs/reasonings if you cant review by yourself what it is doing

@ml_yearzero @akshay_pachaar @karpathy I m absolutely convinced that one day @karpathy will tweet a simple “hello there !” And some stupid guys will find that so wonderful and will opensource “How Karpathy said Hello There “ in a GitHub repo 🤣