52·
3 months agoYes China does all of those things. Really awesome to see you’ve challenged your own flawed reality so quickly 😄
- 0 Posts
- 22 Comments
Joined 5 months ago
Cake day: February 28th, 2026
You are not logged in. If you use a Fediverse account that is able to follow users, you can follow this user.
What? He’s always consistently been the heel of the show. The writers explaining his psychopathy to make you understand is not the same thing as signing off on it. They’ve made that more clear as the seasons have progressed.
You realize the implication of what you wrote right? You understand what an implication is? Trying to be cute and hiding behind technicalities is pathetic and cowardly. Which honestly is par for the course for pseudo intellectual tankie trash lmao
What academic sources have you read …
Did you read your comment? It’s you. No spin needed.
If you told me this was a satirical Wikipedia article I would have believed you
Eh it’s the illusion of speed. Scaling brought enormous returns from GPT-3 -> GPT-4 but it’s been far less significant for every major release since. To compensate for this, every research lab is coming up with new ways to extract value of it of models: CoT, RL, Agent Harness etc
However, these are all hacks to make LLMs more efficient or (try) to make them more reliable. They still have significant drawbacks which will take years (probably decades) to ever get them to the point where they can reliably replace knowledge workers. China knows this and is taking a far different approach to LLM development (not a tankie fyi). Scaling is a horrible idea which will burn billions of dollars with an astronomically low chance of return.
Honestly you’re not wrong. I started to proxy and honestly it feels so good. I’m so sick of spending so much money on cards.
1·4 months agoWhat’s wrong with Funcom?
1·4 months agoI can agree with that largely but I still contend you’re conflating a few things to make that argument. Fundamentally an LLM will make predictions based on probability (ignoring temperature) and probability does not equal certainty.
It’s temperature primarily. That being said there is still a chance that an LLM can output values that are unexpected even at low temperatures.
What are you saying precisely? It’s well known that LLMs have non-deterministic output (Ilya Sutskever even claims as such). Are you saying the way it goes about retrieving tokens as deterministic?
Ah gotcha. I guess Fox engine is dead then
How is it dead through? They recently released the remake to MGS3 and it uses the Fox engine (looks like it anyway) 🤔
Jfc dude get help. Seriously.