magimas

computer scientists/software engineers and their completely messed up sense of how long it takes for things to actually take a hold in real life is always a bit amusing to me.

Half a year is not a lot of time when it comes to meaningful change in directions that matter.

I worked a lot with and built up ultra-high vacuum systems during my PhD. At least for that level of vacuum, you introduce a lot of headache.

You can't use normal plastic or any kind of lubricant anymore because it starts degasing inside the vacuum, pump down after opening to air is a multi-day process that involves heating everything up to 150°C to get rid of the water that will settle on basically every surface when you pull the vacuum, every electricity feedthrough is a potential point of failure, transfering objects between different stages is a huge hassle etc. pp.

I'm sure there's still lots of UHV and HV systems in a chip fab, but there's no way that's easier on a full factory scale than clean room operation.

Just like all these initiatives have been failures.

The problems are pretty fundamental issues of how we set up and developed our economies since around the late 80s.

Unfortunately that also means it will take decades to right the ship (and probably at least one more decade until people are even willing to accept that there's fundamental issues), but we still have lots of money, lots of engineers and lots of scientists. We'll get out of this, but it won't be pretty for quite a while in my opinion.

>The accusation

>So, why are you still working for them?

>If the answer is the salary, say it louder, and do not force yourself to make excuses.

>If the answer is “someone worse would replace me”, say it too, and louder too.

>If the answer is “I can change things from the inside”, then show me what you changed. Haugen tried the inside. Coxon tried the inside. At the end, unfortunately, the inside did not move.

>

Okay, but what if I think that both sides are LARPing their personal science fiction stories and reality will end up much more mundane (but still incredibly beneficial) than the utopias and dystopias everyone is cooking up?

This is presupposing a moral dilemma that just doesn't exist in my opinion.

> I'm fine waiting a bit for the opportunists to shake out so we can see who is genuinely committed to bringing something valuable to the open-weight community.

that is generally a very healthy attitude in the AI space anyway in my opinion.

Some of our R&D departments haven't actually finished an interesting project in years because they keep jumping from trend to trend wanting to try out all the latest shit all the time.

You even notice that with the recent opus and fable models by Anthropic.

If you give them a wide open problem statement, they'll start talking a lot of semi intelligible gibberish.

My guess is that this happens because that's not what they are evaluated on anymore for these kinds of tasks. The generated code is evaluated (in this case the lean code). So talking a bit of gibberish in the language part so you have more test time compute is not punished.

I think in general these smaller applications of AI are seriously overlooked even though they will actually add lots of economic value for companies and lots of quality-of-life features for users.

At least my QUERTZ layout also works as expected in the simulator. You use WASD to move the duck, Q and E to kick left and right etc.

I think it's just the splash screen they didn't properly localize.

openworm: https://github.com/openworm/OpenWorm

oh please... lesswrong was full of idiots already in 2010 when people outside of that community were laughing about "self-taught expert" Yudkowsky's bullshit physics takes.

They are not "further along" the AI discussion, they are a bunch of wackos LARPing as scientists living out their personal sci-fi scenarios.

what are you talking about bro, I think you're really getting carried away here. Nobody cares about the direction of writing on the spine of a book. And your thing with sentence vs title case doesn't make sense because German doesn't even have that distinction.

but this seems quite overkill no?

I currently run pi agent in Lima on a Mac with only the code project folder mounted and an extension that prevents pi agent from reading the contents of .env files directly.

Yeah, there probably are some freak situations where this isn't safe enough, but I don't really see any realistic ways this is going to end up badly. Am I overlooking some obvious security holes?

I don't know, I don't think this "effort for effort's sake" is a very convincing argument. In particular, I think it's very much affected by recency bias in a way?

What we perceive as "effort worth taking" instead of "dull occupational therapy" is very prone to change with technology.

If you would argue that modern photographers need to take the time to physically develop their photos and use chemicals to get their effects rather than applying photoshop filters, you'd not be taken very seriously - in the 80s and 90s it would have been a very different discussion where people saw photoshop as "taking the helicopter to the summit of Mt Everest".

Same even with paper writing. I still had old school teachers in the 90s and early 2000s who insisted that writing anything on a computer was a "shortcut" that would encourage worse writing because you could undo stuff etc. They did all their handouts and worksheets on their old typewriters.

There is a discussion to be had on AI in maths, but I don't think it's this one. I think mathematicians should be talking about what the future of their field is supposed to look like in a time where AI will be able to find the proofs. Maybe maths will turn into a more "experimental" science, where you already know the proof of a theorem, but you want to find a particularly elegant way that helps humans understand it or find other ways to apply the knowledge. Or rewrite old theories from different angles based on all the new proofs generated by AI. I don't know, but I think there's a lot of mathematics to do out there for humans even in a time with AI.

I think this could be an interesting read for you, I read it last week and it kind of argues the same points: https://shakoist.substack.com/p/against-time-series-foundati...

we did some internal tests. The quality isn't bad, it works quite well. But it's essentially on the same level of an ARIMA model trained on the data just much bigger and slower.

So in my opinion it currently falls into a kind of void. If your use case is worth predicting and you put a data scientist on it, you're better off just training cheaper ARIMA models.

this completely misses how crazy word2vec is. The model doesn't get told anything about word meanings and relationships and yet the training results in incredibly meaningful representations that capture many properties of these words.

And in reality you can use it in much broader applications than just words. I once threw it onto session data of an online shop with just the visited item_ids one after another for each individual session. (the session is the sentence, the item_id the word) You end up with really powerful embeddings for the items based on how users actually shop. And you can do more by adding other features into the mix. By adding "season_summer/autumn/winter/spring" into the session sentences based on when that session took place you can then project the item_id embeddings onto those season embeddings and get a measure for which items are the most "summer-y" etc.

mh, maybe it's cheating because it's still a STEM degree but I have a PhD in physics without any real computer science courses (obviously had computational physics courses etc. though) and I managed to 100% solve quite a few years without too much trouble. (though far away from the global leaderboard and with the last few days always taking several hours to solve)

yeah that's actually what I was thinking about. I have a PhD in physics, so I easily notice when ChatGPT just keeps agreeing with me even though we're on very shaky ground. But I worry about the times it does this when we're talking about stuff I'm not as knowledgeable about.

And you can see the influx of people on r/physics and the like who are convinced they've solved dark matter/quantum gravity/... because ChatGPT kept agreeing with them when they presented their ideas to it. Just recently there was a post by a guy who essentially "rediscovered" 17th century physics with the help of ChatGPT but was convinced his formula would explain dark matter because ChatGPT told him so.

one of the more important ones in my opinion would be a prompt to make ChatGPT much less agreeable. Unless explicitly asked for, it never really challenges your observations and will just keep being supportive and telling you how well of an argument you're making.

I fear this will push even more people into deep rabbit holes they won't be able to get out of because they think this neutral AI has confirmed their suspicions/ideas/observations.

To my knowledge the original authors promised they would send out samples in the future but want to wait till they have a finalized paper approved for publication. Whether that's reasonable or not is very hard to tell.

IF they are correct and they have an RT superconductor, then it's a highly political decision on who gets sent some samples. Like, all their former colleagues and collaborators will be pissed if they don't get any. But you also would want to send some samples to someone who you know has 1) all the necessary equipment to confirm your claim, 2) has the necessary publication history to make him/her a trustworthy expert on high temperature superconductivity that others would believe, 3) would not want to slow down your progress just so he/she can gain an advantage.

And with something with such huge potential for applications as RT superconductivity, you then also get vested national interests where your national physics society or research ministry might be pissed off if you don't involve enough researchers from the country which funded your research.

Honestly, if I was in their shoes I'd be delaying me sending out my samples into the world as well.

Of course this all hinges on whether they actually have a room-temperature superconductor or not. If they don't actually have one then the delay tactic could also just be in hopes for this all to blow over without them having to prove their findings.

replication happens over time. For example, when I did my PhD I wanted to grow TaS2 monolayers on a graphene layer on an Iridium crystal. So I took published growth recipees of related materials, adapted them to our setup and then finetuned the recipee for TaS2. This way I basically "peer replicated" the growth of the original paper. I then took those samples to a measurement device and modified the sample in-situ by evaporating Li atoms on top (which was the actual paper but I needed a sample to modify first). I published the paper with the growth recipee and the modification procedure and other colleagues then took those instructions to grow their own samples for their own studies (I think it was MoS2 on Graphene on Cobalt that they grew).

This way papers are peer replicated in an emerging manner because the knowledge is passed from one group to another and they use parts of that knowledge to then apply it to their own research. You have to see this from a more holistic picture. Individual papers don't mean too much, it's their overlap that generates scientific consesus.

In contrast, requiring some random reviewer to instead replicate my full paper would be an impossible task. He/she would not have the required equipment (because there's only 2 lab setups in the whole world with the necessary equipment), he/she would probably not have the required knowledge (because mine and his research only partially overlap - e.g. we're researching the same materials but I use angle-resolved photoemission experiments and he's doing electronic transport) and he/she would need to spend weeks first adapting the growth recipee to the point where his sample quality is the same as mine.

horrible take. Taking the LK99 situation as an example: simply copying and adapting a well described growth recipee to your own setup and lab conditions may take weeks. And how would you address situations where measurement setups only exist once on the earth? How would you do peer replication of LHC measurements? Wait for 50 years till the next super-collider is built and someone else can finally verify the results? On a smaller scale: If you need measurements at a synchrotron radiation source to replicate a measurement, is someone supposed to give up his precious measurement time to replicate a paper he isn't interested in? And is the original author of a paper that's in the queue for peer replication supposed to wait for a year or two till the reviewer gets a beamtime on an appropriate measurement station? Even smaller: I did my PhD in a lab with a specific setup that only a single other group in the world had an equivalent to. You simply would not be able to replicate these results.

Peer replication is completely unfeasible in experimental fields of science. The current process of peer review is alright, people just need to learn that single papers standing by themselves don't mean too much. The "peer replication" happens over time anyway when others use the same tools, samples, techniques on related problems and find results in agreement with earlier papers.