helpfulmountain's comments

I don't understand this:

"In the new study, led by Abra Jeffers of Massachusetts General Hospital, researchers were able to do two additional analyses: one that looked at cardiovascular disease risk in people who use cannabis but had never used tobacco products and a second one that looked at people who used cannabis but had never used tobacco products or e-cigarettes. Without tobacco use, the higher odds of heart attack and stroke persisted for people who used cannabis. For those without tobacco or e-cigarette use, only the higher odds of stroke remained."

Are't e-cigarettes tobacco products?

I think this is a wonderful idea and begins to create a foundation of data richness and interoperability for a very exciting new approach to PCB design, as I commented elsewhere in this thread

However I do want to mention that I think it might be necessary to be able to "cross-compile" to visual schematic format, and back. Or perhaps there is an open schematic tool that can be extended?

The issue is that I think electrical schematics are significantly more familiar to EE types, contain more legible information. Instead of reinventing the wheel there, it'd be nice to see a system that can switch back and forth between text and visual schematic.

How are schematics described as files currently? Is there an open standard? Can it be converted to atopile format, and back?

As someone who just taught themself Kicad to make a simple MIDI controller PCB usi an STM32F4, I was totally blown away, coming from software, how "manual" everything was, how abstruse and arcane.

It's quite difficult as a beginner to know that a design is "correct", or perhaps "correct enough", with respect to component placement and EMI.

It seems like even top EE who specialize in board design utilize rules of thumb rather than rely on simulation.

I was also blown away that the state of the art autorouter for traces seems to be from the early 2000's -- no recent AI magic going on here.

Where is my "autoplacer"? It seems like an AI trained on millions of schematic/pcb combos, even just gerber files via image ingestion, ought to be able to generate a pretty decent layout + routing given constraints.

Or perhaps I'm spoiled coming from software and web because it's so much further removed from physics. But it's still the case that there are a ton of modular components with "API's" that should have a templating language, so very much bravo to this project.

I agree. It may be primarily about integrating the new construction process and a proof of concept for more ambitious projects, but my overall impression is definitely that this is a poor showcase for the technology: it feels sort of embarrassingly academic.

Headphone jacks are hardly obscure hardware

Enjoyed this but upon reflection seems odd that they would have a word "meat" and yet be unfamiliar with biological systems / consciousness in animals.

Yeah this speaks to the fragility of current machine learning techniques. It wasn't trained to play handicap go, so it's quite bad at it.

Similar to what is being called hallucination in LLM area

There is no chance that humans can beat the best Go AI anymore, since the paradigm of AlphaZero (which was trained in the absence of human game records, and beat the version which beat Lee Sedol essentially 100-0)

It is unlikely, also, that a committee of players would be significantly better than a single master, due to lack of coherence -- but that's an interesting idea! I wonder if a committee of the top 100 go players playing a game by vote could beat someone in the top 10 more than 20-0 or something; i doubt it -- it might even go the other way (that the single player would win the series)

I don't think this counts as the real "start of the singularity" because Alphazero was not able to (or capable of) altering its own algorithm, but rather just adjusting its weights.

Something more akin to being in the long march toward general AI.

As a personal note the whole issue of large LLM's capacity for intelligence, beauty, humanity, morality, logic, etc etc was softened in my mind and heart by witnessing with rapt attention this epochal shift in computing.

I had held Go up as a paragon of human brilliance and beauty -- to see that standard fall was a complex process of grief and discovery for me, which I feel has better prepared me for understanding and appreciating the emergence of LLMs

This is kind of blowing my mind, but I'm looking for people discussing the proposal here and can't quite find the valence that seems most potentially viral or self-perpetuating:

There seems to be a really exciting incentive to share lots of links, to regularly hit a hotkey to add the current page to a link list, because there is a kind of graph traversal thing that can emerge, akin to recommendation engines spotify or youtube use, whereby your (anonymized) "like history" -- might be interesting to include some metadata, including when it was liked, how you arrived there, whatever -- will connect you with other people who have intersecting likes, and then blow open entire other leaves of search trees you didn't know you wanted.

I have this feeling on the net recently where I feel like starved, it just feels so stale and bland, hard to find actually good content, going back to HN or Twitter or Reddit or whatever, these little linear "feeds" with discussions etc.

I want a feeling of opening-up, branching, discovery, excitement.

I feel like if a bunch of people shared their like histories in a pseudonymous fashion, you could see these fascinating interest clusters emerging and if there was a compelling UI for navigating them, it could really be self-perpetuating and awesome.

Sort of like visualizations of LLM embeddings, showing regional clusters of information domains, but with a navigable, social aspect, and where because it's pseudo-anonymous you don't mind running AI recommendation engines on it for you and others.

Does this exist? Should it? I would love something like this!

This has already been demonstrated with AlphaGo Zero in a limited domain; so perhaps a more generalized version of this kind of approach (no human "expert" data) will tick the box.

Hard to understand why something this simple would need iOS 17? Seems potentially worth it to digging into ehy you can't do a slight refactor to support ios 15,16

Why would it be wrong to use floats?

That would have been my default assumption

Definitely apply to jobs on Upwork, sounds like you would be well qualified for a lot of stuff.