7 ms·

The interesting question to me at the moment is whether we are still at the bottom of an exponential takeoff or nearing the top of a sigmoid curve. You can find

• forgetfreeman 6mo ago
  "given 10-ish years at least to adapt, we probably can" Social media would like a word...
  • 8n4vidtmkvmk 6mo ago
    We can adapt by shutting down social media. We don't really need that. It's been pretty bad since before the AI wave took off.
    • fellowniusmonk 6mo ago
      We needed a better phone book we ended up in a world where most of our fellow citizens fucking casino.
• faangguyindia 6mo ago
  We are bottom. It's just a start. We are in era of pre pentium 4 in AI terms.
  • fnimick 6mo ago
    And you have evidence as basis for this very confident statement... where?
    • faangguyindia 6mo ago
      Intuition. It comes from the spiritual awakening and being aware of your consciousness. Only Time will prove what turns out be right.
      • sophacles 6mo ago
        You worship the AI?
        • faangguyindia 6mo ago
          I see AI has great utility and we'll figure out ways to better it. If I had any power, i would run Nuclear Power plants to run AI dafacenters and find other near infinite sources of energy to create deeper and deeper AIs. This level of ai tech is at its infancy, it's evidently clear. People are assuming it will stall soon, and won't go beyond a certain point. I don't believe this at all, I am believing it will go much much fatherer then this
          • leptons 6mo ago
            An LLM is never, ever going to find "other near infinite sources of energy". All it can do is predict the next word in an effort to make the user stop prompting it. That's all it does. It does not have the ability to find solutions to the worlds problems.
            • deleted 6mo ago
              [deleted]
  • hypercube33 6mo ago
    Weird comparison - The P4 was a major flop out of the gate (rambus anyone?) and at least by any good metric took three revisions (P4c - hypertheading) to make it come out where it should have ahead of its predecessor. The Pentium 3, before it that you are perhaps referring to was the peak of its era. So...it's going downhill right or what are you even saying?
• MagicMoonlight 6mo ago
  We aren’t anywhere near AGI. They’ve consumed the entirety of human knowledge and poisoned the well, and it still can’t help but tell you to walk to the car wash. A peasant villager was sentient without a single book, film or song. You don’t need this much data to be sentient. They’re using a stupid method, and a better one will be discovered some day.
  • pixl97 6mo ago
    Sentience isn't intelligence.
• echelon 6mo ago
  > The interesting question to me at the moment is whether we are still at the bottom of an exponential takeoff or nearing the top of a sigmoid curve. Even using the models we have today, we have revolutionized VFX, video production, and graphics design. Similarly, many senior software engineers are reporting 2-10x productivity increases. These tools are some of the most useful tools of my career. I don't even think the general consumer public needs "AI" in their products. If we just create control surfaces for experts to leverage and harness the speed up and shape and control the outcomes, we're going to be in a very good spot. These alone will have ripple effects throughout the economy and innovation. We've barely begun to tap into the benefits we have already. We don't even need new models.
  • ryandrake 6mo ago
    > Similarly, many senior software engineers are reporting 2-10x productivity increases. But are they making 2-10x compensation compared to before these tools? If not, these tools are not really useful to you, they are useful to your employer. The most shocking thing I find about LLM-assisted development is how gleefully we are just handing all this value over to our employers, simultaneously believing that they are great because we're producing more. Totally bonkers!
    • echelon 6mo ago
      > handing all this value over to our employers, simultaneously believing that they are great because we're producing more. You could turn the table and say that you can now launch your own business with far fewer resources. Who needs financial capital if you can do it all with solo / small team labor capital? Gossip Goblin ditched his studio and now a16z is trying to throw him money, which he's turned down. He's turning everyone down. https://www.youtube.com/watch?v=-Rzl7nUdEs4 https://www.youtube.com/watch?v=-Rzl7nUdEs4 Dude is legit talented and doesn't need studio capital anymore. This is the end of the Hollywood nepotism pyramid, where limited production capital was available to only a handful of directors. We're kind of at the start of a revolution here. I'd be way more worried if I were Disney or Paramount. Couldn't you take a sabbatical and end it with a brand new SaaS you own and control? That's entirely within reach now. The people this is going to hurt are the ICs that don't have a go-getting type personality where they take full-stack ownership: marketing, branding, design, customer relationships, etc. If you can do those things, you're going to be a rock star with total autonomy. You ought to see what the indie game devs are doing with AI (when they aren't getting yelled at on Steam by the haters). It's legitimately incredible. Game designers are taking on full-stack ownership over the entire experience, and they're making some incredible stuff.
• nostrademons 6mo ago
  Somewhere around 2005-2007, when people were wondering if the Internet was done, PG was fond of saying "It has decades to run. Social changes take longer than technical changes." I think we're at a similar point with LLMs. The technical stuff is largely "done" - LLMs have closer to 10% than 10x headroom in how much they will technologically improve, we'll find ways to make them more efficient and burn fewer GPU cycles, the cost will come down as more entrants mature. But the social changes are going to be vast. Expect huge amounts of AI slop and propaganda. Expect white-collar unemployment as execs realize that all their expensive employees can be replaced by an LLM, followed by white-collar business formation as customers realize that product quality went to shit when all the people were laid off. Expect the Internet as we loved it to disappear, if it hasn't already. Expect new products or networks to arise that are less open and so less vulnerable to the propagation of AI slop. Expect changes in the structure of governments. Mass media was a key element in the formation of the modern nation state, mass cheap fake media will likely lead to its fragmentation as any old Joe with a ChatGPT account can put out mass quantities of bullshit. Probably expect war as people compete to own the discourse.
  • tossandthrow 6mo ago
    You are very strong on the "slop" bias. Why? In managing a large to enterprise sized code base, I experience the opposite. I can guarantee a much more homogenous quality of the code base. It is the opposite of slop I am seeing. And that at a lower cost. Today,I literally made a large and complex migration of all of our endpoints. Took ai 30 minutes, including all frontends using these endpoints. Works flawlessly, debt principal down.
    • chaps 6mo ago
      Which company do you work at so we can avoid your migrated endpoints?
      • tossandthrow 6mo ago
        Wtf. You don't even know what the migration was about?
• peterbell_nyc 6mo ago
  I model this as "stacked sigmoid curves". I have no reason to believe that any specific technological implementation will be exponential in impact vs sigmoidal. However if we throw enough money and smart people at the problems and get enough value from the early sigmoid curves, the effective impact of a large number of stacked sigmoids could theoretically average to a linear impact, but if the sigmoids stay of a similar magnitude (on average) and appear at a higher velocity over time, you end up with an exponential made up of sigmoids* * To be fair, it has been so long since I have done math that this may be completely incorrect mathematically - I'm not sure how to model it. However I think in practice more and more sigmoids coming faster and faster with a similar median amplitude is gonna feel very fast to humans very soon - whether or not it's a true exponential. I'm honestly having a very hard time thinking through the likely implications of what's currently happening over the next 2-10 years. Anyone who has the answers, please do share. I'm assuming from Cynafin that it's a peturbated complex adaptive system so I can just OODA or experiment, sense and respond to what happens - not what I think might happen.
• fny 6mo ago
  Why is everyone so damn obsessed with the singularity? You don't need superintelligence to disrupt humanity. We easily have enough advancement to change the economy dramatically as is. The adoption isn't there yet.
  • Quarrelsome 6mo ago
    Moreover the singularity makes this crass assumption that a single player takes all. It seems to ignore a future of many, many AI players, or many, many human + AI players instead. Furthermore, regardless of how smart one thing is, it cannot win towards infinite games of poker against 7 billion humans, who as a race are cognitively extremely diverse and adaptive.
    • ikrenji 6mo ago
      that's kind of optimistic. for example a misaligned super AI might engineer a virus that wipes out most of the 7 billion humans. that would put a damper on the adaptability of the human race...
      • Quarrelsome 6mo ago
        and then might overfit the lack of danger in that aftermath, leading to those fragmented humans doing something to overthrow it. For all we know this AI might get bored and decide to make a cure, or turn itself off, or anything really.
    • fzzzy 6mo ago
      The singularity does no such thing.
      • Quarrelsome 6mo ago
        well that's certainly cleared it all up.
    • kaibee 6mo ago
      > regardless of how smart one thing is, it cannot win towards infinite games of poker against 7 billion humans, AI isn't one thing though. Really its kind of a natural evolution of 'higher order life'. I think that something like a 'organization', (corps, governments, etc) once large enough is at least as alive as a tardigrade. And for the people who are its cells, it is as comprehensible as the tardigrade is to any of its individual cells. So why wouldn't organizations over all of human history eventually 'evolve' a better information processing system than humans making mouth sounds at each other? (writing was really the first step on this). Really if you look at the last 12,000 years of human society as actually being the first 12,000 years of the evolutionary history of 'organizations', it kinda makes a lot of sense. And so much of it was exploring the environment, trying replication strategies, etc. And we have a lot of different organizations now, like an evolutionary explosion, where life finds various niches to exploit. /schitzoposting
• juped 6mo ago
  Neither! A logistic curve is just an exponential with a carrying capacity - it is still an exponential! There is no reason to believe that AI capability, which grows logarithmically with the handwaved-resources used on it (roughly, this is compute and training data), grows, has grown, or is growing exponentially! I know this sounds like "the moderate position" to people but you are accepting that something logarithmic is somehow in fact exponential (these are inverse functions of one another) based on no evidence or argument. Here is Sam Altman, the one man in the world with the most incentive to overstate AI capability, accepting the extremely-well-known logarithmic growth: https://blog.samaltman.com/three-observations https://blog.samaltman.com/three-observations What we see in reality is a basically-linear growth pattern due to pushing exponentially more resources into this logarithm.
• keeda 6mo ago
  I've said it before, but it would be a mistake to just focus on the models, and ignore everything else that is changing in the ecosystem -- tools, harnesses, agents, skills, availability of compute, etc. -- things are changing very quickly overall. The thing that is changing most rapidly, however, is the understanding of how to harness this insanely powerful, versatile, and unpredictable new technology. Like, those who experimented deeply with LLMs could tell that even if all model development completely froze in 2024, humanity had decades worth of unrealized applications and optimizations to explore. Even with AI recursively accelerating this process of exploration. As a trivial example, way back in 2023 anyone who got broken code from ChatGPT, fed it the error message, and got back working code, knew agents were going to wreck things up very quickly. It wasn't clear that this would look like MD files, Claude Code, skills, GasTown, and YOLO vibe-coding, but those were "mere implementation details." I'm half-convinced an ulterior goal of these AI companies (other than the lack of a better business model) to give away so many cheap tokens is to encourage experimentation and overcome this "capability overhang." Given all this, it's very hard to judge where we are on the curve, because there isn't just one curve, there are actually multiple inter-playing curves.
• joquarky 6mo ago
  Anyone who believes in materialism should recognize that there is still a lot of room to improve.
• HappMacDonald 6mo ago
  I don't think the kind of exponential you are looking for (and especially not "the singularity") can manifest until the product (AI) is at a point where it can meaningfully take over the task of improving itself directly. I would say we have certainly seen a bottleneck in the ability of LLMs to handle any kind of broad abstractions or master the architecture of coding. That is the hinge of why "vibe coding" is as trashy of an approach as it is: the LLM can't cut the mustard on any actual software design. So they have nothing close to the deep understanding required to improve their own substrate. They can be exceptionally good at understanding what humans mean when they say things, far better than poking keywords into a google search for example, especially when said keywords are noisy and overloaded. And they can be a very good encyclopedic store of concepts (the more general the idea the less likely they hallucinate it, while the details and citations are far more frequently made up on the spot). But they suck at volition, and at state representation (thanks to those limited context windows) which cuts them off at the knees if they ever have to tenaciously search for anything including performing creative problem solving. We do have AI models which can get somewhere on theorem proving or protein folding or high level competitive game playing, but those only sometimes even glancingly involve LLMs, and are primarily custom-built amalgams of different kinds of neural networks each trained on specific tasks in their fields. None of that can directly move the needle on actual AI research yet.
• moritzwarhier 6mo ago
  How would you label the y axis?