GenUI isn't about designing cosmetic "skins." (Usually, anyway. I guess it could be used for that)
It's generally for letting users customize the own workflows. How many times have you, or one of your users, liked a piece of software because it mostly fits an existing workflow but that remaining 20% is an annoyance, or maybe even a dealbreaker?
This is probably more common for businesses. They have existing procedures. and they want your software to fit into their existing processes and workflows... not the other way around.
GenUI is far from a one size fits all approach or magic bullet, but it can address a lot of those situations that either would have been dealbreakers, annoyances, or change requests. I suppose it can also help with user retention; once they've put the time and effort into customizing your product they theoretically are less likely to switch to a competitor.
Existing OpenAI/Anthropic models seem to already handle this pretty well. As you might expect, letting users describe their own UI is pretty easy. The hard part is making it work and making sure they don't escape their sandbox...
If running LLMs locally matters, it’s hard to imagine a “forever machine” existing in anything less than 5-10 years, probably more. This stuff is just evolving so rapidly. Buying a “forever machine” today might be like buying a “forever GPU” in 2003.
It just seems somewhat more efficient to take all the computing storage, memory processes, processors, or at least all the money that go into it… the in one spot.
If you’re running a big task or small, everything scales to the appropriate size, regardless of the hardware sitting on your lap or under your desk.
Buying a Mac specifically for serving is misguided in nearly all use cases, but as an all-in-one solution they make sense. Personally I feel like the number of boxes I need to manage has an inverse correlation to my happiness.
Macs are totally “fine” for light server duty… as is just about any computer of the last decade+. The CPUs are beasts, the disks are screaming fast.
The operating system itself may not be ideal at serving but you can just run Docker/Orbstack if you need to do something especially Linux-y.
I’d put the question back on you — what are scenarios where an Apple Silicon Mac wouldn’t cut it as a light server for one person or a handful of people? About the only scenario that comes to mind is scenarios where you expect to utilize it so heavily that the fans are running for many hours a day. At some point those are either gonna wear out or just ingest so much dust that the machine runs hotter and needs a deep clean. But even that is largely mitigated by just pointing an external fan at it.
Will Claude will act as a therapist or produce
value or produce a work of art? No. It cannot,
because it does not have a soul.
I tentatively agree, although I'm only tentative because I don't think it's an interesting question.
Here's what I do think is interesting. You!
I mean... yes, you, too but not you specifically. The plural "you" that the english language lacks.
And so here's what I think is the actual interesting question. Might AI help you create art? Or be a therapist? Or something else interesting and worthwhile?
Maybe AI won't write the next great guitar solo. I'm pretty sure it won't. But might it help you learn to play guitar? Help you fix your broken guitar amp? Help you understand some tricky parts of guitar playing? Help you work through some tricky tabulature where you can't tell if you're playing it wrong or if the tab is just bad?
I don't know. But that's my angle for finding any of this interesting.
Sol medium/high planner orchestrating -> Luna xhigh subagents doing implementation
...has been REALLY good for me. Even on xhigh, Luna is crazy cheap.
Subjectively I'd say it's way better than Sonnet at a fraction of the cost. Luna xhigh can do some decently challenging things on its own, but when orchestrated by a model that is actually good like Sol, I am finding it very very nice.
The cool kids have custom harnesses and workflows and stuff, yeah. I'm still using Superpowers in Codex. Planning in Sol, Luna subagents. https://github.com/obra/superpowers
I feel like I could be doing a lot better somehow. Regardless though Luna (xhigh specifically) is super good/cheap/fast for a lot of things
Shall the better model still have
the upper hand or will the raw speed
compensate?
At 14,000 tokens/sec there's just so much ridiculous stuff that might be possible. Let's assume that this POC proves they can take the next step, and can eventually etch a capable ~27B model into silicon. Let's call it Fred.
Ralph loops automatically get real real interesting again. 200x the iteration speed. This is such a clear win I feel like there's hardly anything to talk about. Instead of one stubborn iterating idiot, you could have dozens of idiots competing in parallel, genetic algorithm style.
The other common orchestration pattern I see is "big model for planning, small parallel subagents implementing, big model reviewing" Today it's Sol dispatching a handful of Luna subagents. Tomorrow maybe it's Sol dispatching as many Fred subagents as it could possibly want.
But what patterns have we not even thought about yet in a world where subagents are 200x faster/cheaper?
What if instead of dispatching single Haiku/Luna/etc subagents, we dispatched "teams" of Fred agents? Maybe each team is 8 Freds. Five come up with competing ideas and the other three vote on a winner.
Or what if they were heterogenous teams? One Luna and a bunch of Freds.
What if instead of a two-tier orchestration system (Sol->Luna) it was three-tier or n-tier? (Sol->Luna->Fred->...Fred)
Those ideas overlap a bit, and crazy shit like Gas Town has already explored even wilder ideas I guess. But man, 14000 tk/sec opens up so much stuff.
At 14,000t/s that's effectively a motor cortex for an android, you no longer need to train the robot to walk, it has a general idea for how to walk (baked into the 1b model), and then just corrects based on sensor input, in real time.
I still personally think that a heavy lean into MoE will be better for that sort of thing. Our brains are subdivided into large parts but I'm sure (and I'm not a brain scientist) that those parts can be subdivided even further into systems that run at various frequencies and latencies depending on what they're used for.
I was thinking about it the other day actually. How our brains evolved structure. I imagine it was purely just down to evolution adding/clustering additional cells around the areas where additional cells were needed. And after long enough a natural brain architecture emerged.
Makes me wonder if we're on the right track with transformer architecture/attention but if it'd be more effective on a larger scale, like MoE with a billion "experts".
That seems promising to me too, although, the thing I've always read is that you can't make the "experts" too narrow. Even if you had a "coding expert" it has to know a lot more than coding - if you tell it to make an online store it needs to parse your language, understand the internet, what a "store" is in this context, etc.
I am not a primary source, probably not even a secondary or tertiary source, so take this with all the grains of salt.
Oh for sure, but I think generally multiple experts are selected in an MoE pass for a token, so presumably it'd select programming related ones as well as general knowledge/language.
Only problem would be the routing layer works on the previous token as far as I understand so it might need more informational depth than just "a token" to select experts, I suppose in the same way attention works.
I wish I had the GPUs to run those sorts of experiments ha ha.
I can see an extra shade of purple. I had essentially the same lens removal cataract surgery as Monet did. Like Monet, I can see slightly into the ultraviolet range, because the retina can react to some UV frequencies that the lens normally blocks! Unlike Monet, I'm not much of a painter.
It really does defy words, for obvious reasons. The short answer is that it's "like purple... but even more purple"
The slightly longer version is: imagine moving a color slider from red to purple and then keep going a little more.
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