The amplifying mirror analogy works best here. LLMs are ultimately a reflection of your own interactions with its weights, the tone you use, the structure with which you construct your prompt, aspects of an issue you tend to focus on, your breadth of vocabulary and world knowledge and whatnot. People who (carefully) use it as an extension of their own mind and senses will very likely thrive, and those who use it as a…
ELI5 is the way to go. I have Claude break down high level physics "as if I'm a farmer standing in a field" - works beautifully.
LLMs reward expertise
241–250 of 607 posts
Re: LLMs reward expertise
#242Re: LLMs reward expertise
#243Earlier quoted context omitted.
This "instant" loop is so fast because it doesn't involve the part where you learn
You seem to be hung up on the part about "learning". Do you know how x86 registers work? Or atomic instructions available on ARM, SPARC, or POWER architectures? No, of course not. Because all of that got abstracted to higher-level instructions decades ago.
Re: LLMs reward expertise
#244Earlier quoted context omitted.
I’d love to see this experiment executed with Claude design. Particularly with something static, I don’t think they’d fail to get a result. But without domain knowledge I think they’d misunderstand prototype with finished product. Without knowing what it’s doing, it’s hard to know what it’s not doing.
> Particularly with something static Apps ain’t static.
Re: LLMs reward expertise
#245Earlier quoted context omitted.
> the terminal is a scary place Isn't the the powerful, unlimited, unopinionated blank LLM text input waiting for your instructions eerily similar to a scary terminal? WIMP and GUI paradigms are the exact the opposite: intentional dis-empowering, by design restrictions, enumeration of your few possible options. Those feel more constrained therefore safer.
> WIMP and GUI paradigms are the exact the opposite: intentional dis-empowering Are you kidding? WIMP and GUI democratized computing!
Re: LLMs reward expertise
#246Re: LLMs reward expertise
#247I actually don't feel like Tao's recently published conversation is the best example of this idea. As intelligent as Dr. Tao is, and surely more so than me, I got the feeling that he wasn't running up against failure states of the model, which I'm not sure you could attribute entirely to his expertise. I honestly think it was more a matter of luck that the model apparently had so much training data on the topic or th…
Re: LLMs reward expertise
#248Earlier quoted context omitted.
It's not. The majority of people regularly using GCC to develop C code (IOW, the primary use case of GCC) are familiar with assembly.
How familiar? Do they ever look at the .S files? know what ar and nm do? Deal with objdump? How important are those details for day-to-day compiling of C code for regular programmers?
Re: LLMs reward expertise
#249recently i start to rewrite a core part of one of my iOS VPN app to rust, which previously use fd.io vpp as it's networking core, the original vpp port is 1.5 years ago manually by myself, given i know a lot about how the vpp does and how vpp coroutine and runtime scheduling works.
the rewrite is in good shape and solve many issues such as pre allocated memory heap using mmap apis and some scheduling issue of back2back tcp session terminated in the vpp host stack.
also by addressing the issus, i am now can easily integrated tailscale as a addon interface for moving in/out l3 packets between tailscale and the core.
All those i think cannot be done easily without domain knowledge about those networking and system stuffs.
Re: LLMs reward expertise
#250Not sure I agree with this. The math guy at anthropic's prompts are essentially: "suppose you’ve gotta resolve the $CONJECTURE, like absolutely have to, everything depends on it. think really hard, and try to come up with a bunch of ideas to try. but remember to trust yourself and not necessarily in conventional wisdom!!" https://claude.ai/share/25740bd5-aa97-4bd7-bf58-c4df3793fda7 https://xcancel.com/__alpoge__/stat…
My working theory at the moment is that for programmers it was relatively "clean" and took the form of an inside-out transformation of the work, where AIs directly produced the central work product more or less adequately and relatively early on, but for other forms of work it will appear as some mixture of inside-out (in which case it will appear similarly first as a tool, then as something more than mere tool) and outside-in (the things surrounding their work and the supports their work processes rely on will be progressively automated). This is going to give rise to all sorts of pathologies in the white collar world, we'll get all kinds of variations on denial/negotiation, and so on, until it fully transforms the division of labor.
One interesting point of reference here: Yuval Harari gave a talk recently about the radical changes that will take place relatively quickly, in which he noted the AIs are not quite as good at writing as he is yet, although he expects they will be relatively soon. He then gave the timeline for what he considered "soon": 10 years! So we find the denial ("I still have time, they're not as good as me yet, maybe in 10 years...") even among the most vocal "prophets," among those supposedly most wised-up to what's going on and where the capability frontier lies.