In my limited experience, using LLMs to code up things unrelated to LLMs (robotics for instance) is significantly less productive than using LLMs to code up things related to LLMs. It works, just not very well and requires a lot more leg work on the user end than in other areas.
Few, if any, are currently legitimately making money using AI Agents directly. Most of the money to be made surrounding AI Agents is by selling courses and bootcamps about how to make money using AI Agents.
Right. If you are wealthy enough to go retire and live off interest, but STILL choose to work for a company you morally disagree with...then what sort of person are you?
I have attempted to replicate the "workflow" LLM process where several LLMs come up with different variations of a way to solve a problem and a "judge" LLM reviews them and the go through different verification processes to see if this workflow increased the accuracy of the LLM's ability to solve the problem. For me, in my experiments, it didn't really make much difference but at the time I was using LLMs significantly dumber than current frontier models. HOWEVER...When I enable "Thinking Mode" on frontier LLM's like ChatGPT it DOES tend to solve problems that the non-thinking mode isn't able to solve so perhaps it's just a matter of throwing enough iterations at it for the LLM to be able to solve a particular complex problem.
>The 40 year old who won't date a real girl because he is in love with a bot I'm more concerned with.
I think on the Venn diagram of 40-year-olds only willing to date bots and 40-year-olds capable of actually dating real women, the overlap is incredibly small at this point in time.
Alignment has a lot more to it than simply which answers an AI provides. In the future when agents are commonplace and when AI can do things in the physical world, alignment will be especially important because it will dictate how the AI chooses to accomplish the goals humans set out for it. Will it choose to accomplish them in a way that the human requestor does not want and did not anticipate, or will it choose to accomplish them in a way any human with common sense would choose?
Moreover, in the not so distant future if there is an AI that is acting totally autonomous and independent of human requests for long periods of time, weeks or months or longer, and it's doing good important things like medical research or environmental restoration, alignment will be incredibly important to ensure every single independent decision it makes is done in the way its designers would have intended.
The problem is you're overloading the word "alignment" with two different meanings.
The first is, does the thing actually work and do what the user wanted, or is it a piece of junk that does something useless or undesired by the user?
The second is, what the user wants is porn or drugs or a way to install apps on their iPhone without Apple's permission or military support for a fight that may or may not be sympathetic to you depending on who you are. And then does it do what the user wants or does it do what someone else wants? Is it a tool that decentralizes power or concentrates it?
Why should we assume that LLMs would be stagnant at current levels when, so far, they haven't stopped improving? I remember when simply using Copilot to just auto-complete 1 line of code was a groundbreaking unimaginable advancement. That was only a few years ago. New and improved models are being released nearly every week. The open-source models are nearly as advanced as the closed source models (if you have the hardware to run them at full capacity).
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