Excel requires some skill to use (to the point where high-level Excel is a competitive sport), and AI is mostly an exercise in deskilling its users and humanity at large.
Excel requires some skill to use (to the point where high-level Excel is a competitive sport), and AI is mostly an exercise in deskilling its users and humanity at large.
Edit: love the downvotes, but could i ever get a reason for what was actually objectionable in my comment? other than requiring you to maybe think differently about something you already had your mind made up about? i’m sorry if i offended defector.com for not properly framing the problem.
blind tribal reaction is the only way i guess.
– Love a good strawman in the morning.
Those feeling a chill in the air are the “scale only” peeps, who were all in on not thinking too hard about the problem. Those focused on more than selling LLMs have a very different framing.
As for why AI agents aren’t functional, we do actually have a better understanding that doesn’t seem to want to leak out of niche academic areas.
The amount we’ve learned about intelligent systems this past half decade feels like a whole new world.
Deskilling is an issue already without AI. To summarize, minimizing energy expenditure is very important due to evolutionary history. No just to people, but to group that creates simplified models that don’t disturb people’s normal trajectory. Cause learning a new model to predict the world takes energy. They do this by making predictable heuristics that are functional enough, but allow the daily scripts to continue unhindered. These simplified heuristics sometimes are too simple, and not robust enough to survive when the environment changes. Think pandas, who got deskilled at staying alive outside of a very specific environment.
So. In the same way humanity needs to learn to become more robust via diverse but communication focused intelligent systems. Anyone in social sciences knows that evidence strongly shows that diversity representation is weirdly good for any intelligent group.
Similarly, the better forms of AI currently being ignored are actually built from that end of things, rather than trying to force all perspectives and preferences to live simultaneously in a single model. It creates informational and contextual choke points.
Also wish i could run into more people who actually study intelligence in these threads.
Clickbait journalism is a scourge on science. At least the public awareness of sycophantic echo chambers enabling delusional spirals is something good for people to think about,
Since any idea can survive in a similar segregated confirmation bubble that mechanically cuts off outside ideas and education to preserve the existing group world model.
And i keep saying laziness should be described by such solipsism, but instead you get called lazy if you aren’t feeding your full life to the machine.
Just wish progressive public discourse was more generally informed in this area, because it’s very important to understanding society, our bodies, and intelligent systems as a whole.
I have a more than surface-level understanding of LLMs, but I am not an expert by any metric, imaginable. LLMs are great for information retrieval tasks like searching through a database of documentation, when the query is in natural language, and it works beyond keyword search like a traditional search engine. But, since they also have synthesis capabilities, they also make shit up.
The issue most people have is that LLMs are nowhere near as capable as corporations are making them out to be and also the amount of money they are spending is simply not in line with the value they can provide to any individual or corporation. Thus, it is a bubble which has always made things harder for the regular people.
If you want to have good analysis of LLMs and their capabilities, I strongly recommend a book called “AI Snake Oil”. It is written by two computer scientists, one teaches at Princeton and other I believe was a grad student under the first one.