Not OP, but speaking from a fairly deep layman understanding of how LLMs work - all anyone really knows is that capabilities of fundamentally higher orders (like deception, which requires theory of mind) emerged by simply training larger networks. Since we don’t have a great understanding of how our own intelligence emerges from our wetware, we’re only guessing.
Did you watch Breaking Bad?
Wrenched from the platonic forms through seething quantum foam as the Demiurge’s machinations reach fruition, our custom-made mounting clamps won’t fail you like your precious god.
I understand this perspective, because the text, image, audio, and video generators all default to the most generic solution. I challenge you to explore past the surface with the simple goal of examining something you enjoy from new angles. All of the interesting work in generative AI is being done at the edges of the models’ semantic spaces. Avoid getting stuck in workflows. Try new ones regularly and compare their efficacies. I’m constantly finding use cases that I end up putting to practical use - sometimes immediately, sometimes six months later when the need arises.
Part of my job is to write that kind of copy. If you take it seriously, you’ll drive yourself nuts.
I just meant I work for a corporation. I produce videos for marketing, been doing it for 25 years.
What tasks are you thinking about?
It saves me 10-20 hours of work every week as a corpo video producer, and I use that time to experiment with AI - which has allowed our small team to produce work that would be completely outside our resources otherwise. Without a single additional breakthrough, we’d be finding novel ways to be productive with the current form of generative AI for decades. I understand the desire to temper expectations, and I agree that companies and providers are not handling this well at all. But the tech is already solid. It’s just being misused more often than it’s being wielded well.
Don’t blame CEO tomfoolery on generative AI. Generative AI is amazing.
For a second, I thought he was an elf or a Vulcan.
Perplexity
So I work in a creative industry (video production), and have for like three decades. If A.I. can do a lot of the work I do just as well, no part of me wants to continue to do that work. Most of what I get paid for is not “art” in the sense that it expresses some fundamental drive in me. But I do love collaborating with A.I.s to create things that I would’ve never been able to do on my own (and that A.I. would have never been able to do without me). This is where things are going, and I totally grant that greedy corpos doing greedy corpo shit is not to be lauded. But that’s an Ubisoft problem, not a gen AI problem. People are the issue with A.I.
I understand them both well enough to implement them in my projects. I don’t see why people are anything other than excited about the implementation of more capable AI in games. Are these initial implementations garbage? Probably, but that’s just growing pains, So what is it about gen AI that actually bothers people?
The salt runs deeper than I expected.
Is Doom running on the calculator?
Which AI is the RC car?
They’re both A.I. Yes, they work very differently, but the goal is the same - simulate intelligence.
And do you believe paying for more writers will remain a better option for the foreseeable future?
What makes the “spicy autocomplete” perspective incomplete is also what makes LLMs work. The “Attention is All You Need” paper that introduced attention transformers describes a type of self-awareness necessary to predict the next word. In the process of writing the next word of an essay, it navigates a 22,000-dimensional semantic space, And the similarity to the way humans experience language is more than philosophical - the advancements in LLMs have sparked a bunch of new research in neurology.