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> How is it early days? When you have exponential growth, it's always early days. Other than that I'm not clear on what you're saying. What is in your mind th

> How is it early days? When you have exponential growth, it's always early days. Other than that I'm not clear on what you're saying. What is in your mind the difference between how we should plan for the societal impact of AI in the short vs the long term?

seadan83 1y ago
Is it early days of exponential growth? The growth of AI to beat humans in chess and then Go took a long time. Appears to be step function growth. LLMs have limitations and can't double their growth for much longer. I'd argue they never did double, just a step function with a slow linear growth since. The crowd claiming exponential growth have been at it for not quite a decade now. I have trouble separating fact from CEOs of AI companies shilling to attract that VC money. VCs desperately want to solve the expensive software engineer problem, you don't get that cash by claiming AI will be 3% better YoY
quonn 1y ago
> When you have exponential growth, it's always early days. Let‘s take the development of CPUs where for 30-40 years the observable performance actually did grow exponentially (unlike the current AI boom where it does not). Was it always early days? Was it early days for computers in 2005?
- falcor84 1y ago
  In a way, yes, I think that rise smartphones and the resulting proliferation of cheap mobile processors was ground-shattering in terms of what we consider to be a computer. If I'm reading the numbers correctly, there are about 2B people with their own pc/laptop while there are about 5B people with their own smartphone. So 60% of people using computing do so on a type of device that didn't exist in 2005. And this is before we talk about new modalities that might take over in the future, like VR/AR, wearable AI "pins" (which is what I assume that Johnny Ive is working on), neural interfaces, and maybe even quantum computing. So I personally don't see any issue of thinking of what happened 20 years ago, and what's happening at the moment as "early days for computers". This is of course a semantics argument, but in my mind "early days" is a term for the time before things stabilized, and I'm very unclear on what that means for a field that's continuously undergoing rapid growth. As another extreme case - what would you say were the "early days" for life on planet Earth? I assume that most people wouldn't be thinking of just the first 50 years after the first RNA molecules got enclosed in a membrane.

seadan83 1y ago

Is it early days of exponential growth? The growth of AI to beat humans in chess and then Go took a long time. Appears to be step function growth. LLMs have limitations and can't double their growth for much longer. I'd argue they never did double, just a step function with a slow linear growth since. The crowd claiming exponential growth have been at it for not quite a decade now. I have trouble separating fact from CEOs of AI companies shilling to attract that VC money. VCs desperately want to solve the expensive software engineer problem, you don't get that cash by claiming AI will be 3% better YoY

quonn 1y ago

> When you have exponential growth, it's always early days. Let‘s take the development of CPUs where for 30-40 years the observable performance actually did grow exponentially (unlike the current AI boom where it does not). Was it always early days? Was it early days for computers in 2005?

falcor84 1y ago
In a way, yes, I think that rise smartphones and the resulting proliferation of cheap mobile processors was ground-shattering in terms of what we consider to be a computer. If I'm reading the numbers correctly, there are about 2B people with their own pc/laptop while there are about 5B people with their own smartphone. So 60% of people using computing do so on a type of device that didn't exist in 2005. And this is before we talk about new modalities that might take over in the future, like VR/AR, wearable AI "pins" (which is what I assume that Johnny Ive is working on), neural interfaces, and maybe even quantum computing. So I personally don't see any issue of thinking of what happened 20 years ago, and what's happening at the moment as "early days for computers". This is of course a semantics argument, but in my mind "early days" is a term for the time before things stabilized, and I'm very unclear on what that means for a field that's continuously undergoing rapid growth. As another extreme case - what would you say were the "early days" for life on planet Earth? I assume that most people wouldn't be thinking of just the first 50 years after the first RNA molecules got enclosed in a membrane.