101–110 of 303 posts
We already know the answer, it's identical to the answer for: what if everybody had UBI. Most of the population wouldn't do anything with it. They got 5g mainframes in the palm of their hands and they watch sports, play Candy Crush or doom scroll TikTok. We know what they do with their spare time and we've known for generations. See: decades past + TV viewing time. Swap TV viewing time for TikTok et al. They get GPT…
> Someday, such as in 2040, there may be available, for every human being, the performance equivalent of 'a B300 GPU for contemporary LLMs'. What would this world be like? If we talk about just LLMs, given how things have been going since ChatGPT, my bet it would not change that much. LLMs are not foundational technology such as Internet or Steam engine or Rail roads were. There are very few products that can build u…
I disagree with this take. While LLMs themselves are currently unreliable, the work done in the math community on hooking up creative LLMs to reliable verifiers like Lean show that it’s possible to construct systems where the unreliability is suppressed. For now, that still requires experts to set up and monitor, but I do believe that in a couple of decades we’ll make progress on how to do more mundane tasks in a rel…
The same thing for my job: creating insurance premiums is somewhat hard but not stellar. A combination of skills, data, tools and people. I can imagine a future where you can post a 'have good weather on holiday or money back' bond on a platform. (I can think of more serious applications...) The sheer diversity and amount of liquidity AI's can create is enormous. (Switching to a very general outlook here.) And with liquidity hopefully comes more specificity in the ROI on saving our planet. (Or the disproving of the necessity thereof, if that is your outlook.)
Earlier quoted context omitted.
The more I use Fable the more impressed I am with it. I am still learning how to use it, same with gpt-5.6-sol. I don't think the model has changed much, but both models have gotten smarter in leaps and bounds as I've improved the documentation, context, how I provide work to them and how I specify success. (And generally that consists of keeping only the very most relevant details and deleting a lot of the boilerpla…
>I am still learning how to use it I find it interesting that we are still talking in terms of modifying our behaviour to accommodate the tools. Surely the point of LLMs is not to "learn how to use it" but as an extension of our own unique capabilities - the most personalised tool in all of history.
> Someday, such as in 2040, there may be available, for every human being, the performance equivalent of 'a B300 GPU for contemporary LLMs'. What would this world be like? If we talk about just LLMs, given how things have been going since ChatGPT, my bet it would not change that much. LLMs are not foundational technology such as Internet or Steam engine or Rail roads were. There are very few products that can build u…
I feel like this is incredibly simplistic, and if you changed "LLM" to "computer" or "internet" and went back decades, it's highly likely you'd read the exact same takes in the newspaper back then about those things.
It's also at the same time downplaying just how valuable "nice productivity tools for highly motivated expert knowledge workers" could be, just like computers did for us "highly motivated expert knowledge workers" in the first place. Or computers isn't a "foundational technology" either?
We already know the answer, it's identical to the answer for: what if everybody had UBI. Most of the population wouldn't do anything with it. They got 5g mainframes in the palm of their hands and they watch sports, play Candy Crush or doom scroll TikTok. We know what they do with their spare time and we've known for generations. See: decades past + TV viewing time. Swap TV viewing time for TikTok et al. They get GPT…
The working population only actually works part of their life. The rest of their life they are provided for as well. In fact, in many modern countries the amount of people that are allowed to vote and yet is not considered part of the working population is approaching 50% or actually more than 50%. There are lot of retired people, students, stay at home parents, chronically ill/disabled, etc. that are not considered to be pariahs in most societies and yet they don't really perform any payed labor. They are not counted as unemployed. And plenty of them actually do very useful things of course.
And if you start looking at what it is people actually do for money these days, things get weirder. Sure, they get paid. But there are some seriously weird things people do for a living. A lot of which you might label as redundant, frivolous, or so abstract it's questionable what the actual benefit is. Arguably, a lot of the work that gets done unpaid by the non working class is a lot more useful and essential than quite a disturbingly large amount of stuff done by the working classes these days. A lot of those working the hardest doing the most useful things get paid the least.
You could label a lot of "work" as busy work for people to give them an income. It's not all that consequential if they stop doing it for a while. The lockdowns a few years ago were instructive in how minimal the disruption was when masses of people stopped showing up for that work. Many people doing actual real work of course never stopped working. But many of us were just confined to our home office where we got to sit on zoom calls, bake bread, or do whatever it was we did to keep ourselves busy. While still getting paid.
I think that was a little glimpse of the future. Minus the restrictions on movement and freedom. We'll still do stuff for each other. And some of us will still work quite hard. It was never about the money.
Hopefully in this world, someone figures out how to deliver the performance equivalent of a B300 GPU for about 1/100th the power of a current B300 (which can be up to 1400 watts), or the world will bake.
Especially if cognitive technologies mean that we need to travel less (eg communiting to work, or ineffecient supply chains).
Earlier quoted context omitted.
The more I use Fable the more impressed I am with it. I am still learning how to use it, same with gpt-5.6-sol. I don't think the model has changed much, but both models have gotten smarter in leaps and bounds as I've improved the documentation, context, how I provide work to them and how I specify success. (And generally that consists of keeping only the very most relevant details and deleting a lot of the boilerpla…
>I am still learning how to use it I find it interesting that we are still talking in terms of modifying our behaviour to accommodate the tools. Surely the point of LLMs is not to "learn how to use it" but as an extension of our own unique capabilities - the most personalised tool in all of history.
LLMs don't read minds. There's always a chasm between you (your ideas) and them becoming reality. Exactly how people cross that chasm is all the rage right now, and there are a million ways to do it - but just expecting the LLM to pull details out of a few words isn't going to produce anything decent.
Earlier quoted context omitted.
The more I use Fable the more impressed I am with it. I am still learning how to use it, same with gpt-5.6-sol. I don't think the model has changed much, but both models have gotten smarter in leaps and bounds as I've improved the documentation, context, how I provide work to them and how I specify success. (And generally that consists of keeping only the very most relevant details and deleting a lot of the boilerpla…
>I am still learning how to use it I find it interesting that we are still talking in terms of modifying our behaviour to accommodate the tools. Surely the point of LLMs is not to "learn how to use it" but as an extension of our own unique capabilities - the most personalised tool in all of history.
Going further, even programming languages "asks" that you change the way you work to make the most use of them. A Clojure developer has a very different development process than a Rust developer, and they're both efficient, right and correct in their ecosystem, but the experience differs vastly and Clojure for example would change you to fit itself, rather than the opposite.
> Someday, such as in 2040, there may be available, for every human being, the performance equivalent of 'a B300 GPU for contemporary LLMs'. What would this world be like? If we talk about just LLMs, given how things have been going since ChatGPT, my bet it would not change that much. LLMs are not foundational technology such as Internet or Steam engine or Rail roads were. There are very few products that can build u…
> Someday, such as in 2040, there may be available, for every human being, the performance equivalent of 'a B300 GPU for contemporary LLMs'. What would this world be like? If we talk about just LLMs, given how things have been going since ChatGPT, my bet it would not change that much. LLMs are not foundational technology such as Internet or Steam engine or Rail roads were. There are very few products that can build u…
We've moved from LLMs being able to work on a task for about 2 minutes to about 2 hours in the last 18 months, and that's mostly limited by the context window size filling up. In 14 years time I don't really see a reason why that wouldn't have extended a time frame that's effectively continuous forever, or at least a ceiling that's indistinguishable from that.
The question really becomes "why would we want that?". The main reason you'd want an AI that can focus on a task forever is to completely remove the human from the loop. That's something we should be cautious about.