2 ms·
Things will be moving faster in 2-3 years most likely. (The recursive self-improvement flywheel is only just starting to pick up momentum, and we’ll have much m
by theptip 1y ago
Things will be moving faster in 2-3 years most likely. (The recursive self-improvement flywheel is only just starting to pick up momentum, and we’ll have much more LLM inference compute available.)
Figuring out how to stay sane while staying abreast of developments will be a key skill to cultivate.
I’m pretty skeptical there will be a single model with a defensible moat TBH. Like cloud compute, there is both economy of scale and room for multiple vendors (not least because bigco’s want multiple competing bids).
- oblio 1y agoI'm actually waiting for something different - a "good enough" level for programming LLMs: 1. Where they can be used as autocompletion in an IDE at speeds comparable with Intellisense 2. And where they're good enough to generate most code reliably, while using a local LLM 3. While running on hardware costing in total max 2000€ 4. And definitely with just a few "standard" pre-configured Open Source/open weights LLMs where I don't have to become an LLM engineer to figure out the million knobs I have no clue how Intellisense works behind the scenes, yet I use it every day. Same story here.
- theptip 1y ago“Good enough” will be like programming languages; an evolving frontier with many choices. New developments will make your previous “good enough” look inadequate. Given how much better the bleeding edge models are now than 6 months ago, as long as any model is getting smarter I don’t see stagnation as a possibility. If Gemini starts being better at coding than Claude, you’re gonna switch over if your livelihood is dependent on it.