4 HN users recommended this commentary3 months2023–2025score 3
Years with an HN recommendation, 2007–2026
HN cites it for the argument that we cannot tell whether AI is early or late on its sigmoid curve until hindsight.
Tom Scott describes trying ChatGPT to fix his Gmail labels and being unsettled by how capable it was. He argues that we cannot know where we are on the technology curve, comparing it to Napster.
“Tom Scott's video[0] makes a very good argument: we don't know where we are on the technology curve.” (HN, 2024)
Tom Scotts video today re where we are on the AI's impact to society curve was interesting : [this video] I think he's probably right that we're very early on the adoption curve. (even though I always get downvote and call a dumbass when I mention it here, I still think progress in quantum computing (predictive) and AI go hand in hand towards AGI.)
I enjoyed Tom Scott's YT video monologue about this. To summarize, he postulates that most major innovations follow a sigmoid growth curve, wherein they ramp up, explode, and then level off. The question then becomes, where are we on this curve? He concludes that we will probably only know in hindsight. [this video]
Innovations follow a sigmoid curve; we only know the position in hindsight
I tried using AI. It scared me. - Tom Scott [this video] I'm also gonna recommend Accelerando - [link] As an aside, I'd also recommend Glasshouse (also by Charles Stross) as an exploration into the human remnants post singularity (and war)... followed by Implied Spaces by Walter Jon Williams... > “I and my confederates,” Aristide said, “did our best to prevent that degree of autonomy among artificial intelligences. We made the decision to turn away from the Vingean Singularity before most people even knew what it was. But—” He made a gesture with his hands as if dropping a ball. “—I claim no more than the average share of wisdom. We could have made mistakes.” for a singularity averted approach of what could be done. One more I'll toss in, is The Freeze-Frame Revolution by Peter Watts which feels like you're missing a lot of the story (but it is because that's one book of a series) and... well... spoilers.
> get an LLM that can write production code reliably it depends on what that user wanted the code to do, and how important it is. For example, an average, non-technical user could use this to generate a script to sort out their email, or a script for automation in MS Office VBA. Just because it's not perfect, doesn't mean it doesn't have a good use, and won't improve. Tom Scott's video[0] makes a very good argument: we don't know where we are on the technology curve. [0]: [this video]
Argues we don't know where we are on the technology curve
> I think the big question everyone wants to skip right to and past this conversation is, will this continue to be true 2 years from now? I don’t know how to answer that question. I still think about Tom Scott's 'where are we on the AI curve' video from a few years back. [this video]
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