That's how I communicate my intention to pay a parking ticket. “Bowing to regulatory pressure”
Sure, thanks for your interest. It's an incomplete picture, but we can think of LLMs as an abstraction of all the meaningful connections within a dataset to a higher dimensional space - one that can be explored. That alone is an insane accomplishment that is changing some of the pillars of data analysis and knowledge work. But that's just the contribution of the "Attention is All You Need" paper. Many implementations of modern generative AI combine LLM inference in agentic networks, with GANs, and with rules-based processing. Extracting connections is just one part of one part of a modern AI implementation.
The emergent properties of GPT4 are enough to point toward this exponential curve continuing. Theory of mind (and therefore deception) as well as relational spatial awareness (usually illustrated with stacking problems) developed solely from increasing the parameter count describing the neural network. These were unexpected capabilities. As a result, there is an almost literal arms race on the hardware side to see what other emergent properties exist at higher model sizes. With some poetic license, we're rending function from form so quickly and effectively that it's seen by some as freeing and others as a sacrilege.
Some of the most interesting work on why these capabilities emerge and how we might gain some insight (and control) from exploring the mechanisms is being done by Anthropic and by users at Hugging Face. They discovered that when specific neurons in Claude's net are stimulated, everything it responds with will in some way become about the Golden Gate Bridge, for instance. This sort of probing is perhaps a better route to progress than blindly chasing more size (despite its recent success). But only time will tell. Certainly, Google and MS have had a lot of unforced errors fumbling over themselves to stay in what they think is the race.
I'm happy to take the time to alter your perspective, if you are open to new information.
Did you watch Breaking Bad?
Rabbit season
Our Fall is quite autumnal.
For a second, I thought he was an elf or a Vulcan.
Train LLMs on large bulks of data that meet criteria for deletion, thereby shrinking like 100 petabytes to a terabyte, albeit imperfectly. That way, you have a collection of AI bots that you can chat with about all the deleted data. And I suppose the threshold for deletion is, "How disastrous could a hallucination about this be?"
What's the deal with phones auto-correcting to unusual proper nouns? Why is that even an option, if it's literally a word I've never typed/swiped?
This is another good use case for gAI. Copy/paste the comment into a GPT and tell it to re-write the content at the desired reading or technical level. Then it's available for follow-up clarification questions.