91–100 of 332 posts
Amazing. This is the Internet moment of AI. The Internet took something that used to be slow, cumbersome, expensive and made it fast, efficient, cheap. Now we are doing it again.
I am a big proponent of AI. To me, this experiment mostly shows how not to use AI.
Why would you need webapps when you could just talk out loud to your computer ? Why would I need programs with colors, buttons, actual UI ? I am trying to imagine a future where file navigators don't even exist : "I want to see the photos I took while I was in vacations last year. Yes, can you remove that cloud ? Perfect, now send it to XXXX's computer and say something nice." "Can you set some timers for my sport se…
Voice interfaces are not the be all and end all of communication. Even between humans we prefer text a lot of the time.
It's orders of magnitude cheaper to serve requests with conventional methods than directly with LLM. My back-of-envelope calculation says, optimistically , it takes more than 100 GFLOPs to generate 10 tokens using a 7 billion parameter LLM. There are better ways to use electricity.
What people want isn’t code - they want computers to do stuff for them. It just happens that right now, code is the best way you can do it.
The paradigm WILL change. It’s really just a matter of when. I think the point you make that these are problems of DEGREE, not problems of KIND is very important. It’s plausible, now it’s just optimization, and we know how that goes and have plenty of history to prove we consistently underestimate the degree to which computation can get faster and cheaper.
Really cool experiment!
This is amazing. It very creatively emphasizes how our definition of "boilerplate code" will shift over time. Another layer of abstraction would be running N of these, sandboxed, responding to each request, and then serving whichever instance is internally evaluated to have done the best. Then you're kind of performing meta reinforcement learning with each whole system as a head. The hard part (coming from this direc…
I thought this didn't work? You basically end up fitting your AI models to whatever is the internal evaluation method, and creating a good evaluation method most often ends up having a similar complexity as creating the initial AI model you wanted to train.
Why would you need webapps when you could just talk out loud to your computer ? Why would I need programs with colors, buttons, actual UI ? I am trying to imagine a future where file navigators don't even exist : "I want to see the photos I took while I was in vacations last year. Yes, can you remove that cloud ? Perfect, now send it to XXXX's computer and say something nice." "Can you set some timers for my sport se…
>Can you set some timers for my sport session, can you plan a pure body weight session ? Yes, that's perfect. Wait, actually, remove the jumping jacks." Better yet, why exercise -which is so repetitive- if we can create a machine that just does it for you, including the dopamine triggering, why play an arcade video game where we can create a machine that fires the neuron needed to produce the exact same level of a ex…
"Make me happy"
"Make me happy"
"Make me happy"
The question posed sounds like "why should we have deterministic behavior if we can have non-deterministic behavior instead?" Am I wrong to think that the answer is obvious? I mean, who wants web apps to behave differently every time you interact with them?
Like, for sure you can ask the AI to save it's "settings" or "context" to a local file in a format of its own choosing, and then bring that back in the next prompt ; couple this with temperature 0 and you should get to a fixed-point deterministic app immediately
The question posed sounds like "why should we have deterministic behavior if we can have non-deterministic behavior instead?" Am I wrong to think that the answer is obvious? I mean, who wants web apps to behave differently every time you interact with them?
Like, for sure you can ask the AI to save it's "settings" or "context" to a local file in a format of its own choosing, and then bring that back in the next prompt ; couple this with temperature 0 and you should get to a fixed-point deterministic app immediately
Not quite the case. Temperature 0 is not the same as random seed. Also there are downsides to lowering temperature (always choosing the most probable next token).
It's orders of magnitude cheaper to serve requests with conventional methods than directly with LLM. My back-of-envelope calculation says, optimistically , it takes more than 100 GFLOPs to generate 10 tokens using a 7 billion parameter LLM. There are better ways to use electricity.
Try to convince the investors. The way the industry is headed is not necessarily related to what is most optimal. That might be the future whether we like it or not. Losing billions seems to be the trend.