199 karma · joined May 19, 2023
e.g. how useful is this LLM for 1) code debugging, 2) (accurate) fact retrieval, 3) daily task planning
They're a dime-a-dozen. Good job tanking your reputation and business, zoom!
FWIW, I have lived in SF for the last 8 years and I agree wholeheartedly.
The field moves too fast and the convenience is just not there otherwise.
edit: also the branding makes me think of MK-ultra which is probably something to avoid
When I see Nature pubs, I tend to enjoy the aesthetics of the articles, but discount them a bit to account for the mainstream-ness.
It's like everything they build is a demo and they have to drum up PR around it. Hasn't this been continually happening for the better part of the last decade?
It would be wise to move away from the VC mentality for critical things like state/federal infrastructure.
I feel that this happens a lot with well thought out "PhD-level" software. Someone with dollar-sign eyes (who is capable of understanding it) takes the FLOSS and wraps it with a different UI, thereby profiteering off the backs of grad students...
Does that mean you should ignore them? No. But as I read through the preferences on a lot of options, they are seemingly haphazard takes. For example, I'm seeing people saying facebook messenger is the best text chat client and MS Teams is the best video chat? These are among the worst options out there (even setting aside ethos, they're bug-ridden!).
Just be careful, I think many recommendations in this particular thread are limited in perspective.
edit: i wrote this because hackernews tends to be a "ground truth" for a lot of people when they are trying to form their own opinions on geeky stuff
Sometimes I edit my markdown files in other editors like Bear (or web interfaces). Sometimes I draw handwritten notes on my ipad and insert them as images.
It all works pretty well.
FTR, I think youtube is one (among a few) exceptions to this overall trend from google.
They thing to keep in mind about the "Boston Dynamics approach" is that in order to solve the hardest real world problems, you need to do one of two things: 1) Overshoot the capabilities of the system so that it is robust when actually deployed subject to the uncertainty of the real world (e.g. motivating athletic intelligence). 2.) Grossly constrain your environment so that uncertainty is not a factor. This is (and has been) happening in warehouses and factories for decades.
I am also a big fan of the human rating style of evaluation [0]
I think they are complementary approaches.
[0] https://colab.research.google.com/drive/1kK6xasHiav9nhiRUJjP...
These days, when I see content from Lightning AI, I prepare for a contrived approach to doing something that fits within the ecosystem. I can't help but feel they are trying to induce "vendor lock-in" where there really isn't a business case for it...
Anyways, I tried to follow these steps and hit a dead-end. I have to say the content put out by huggingface is always way more straightforward and gets me to where I need to be when I want to spin up quickly.
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