skysight-inc/HackerNews huggingface dataset:
An interview is aimed at verifying only basics skills and then mostly general intelligence.

This narrative of "interviews should be like real work" needs to stop. It doesn't make any sense, this is not the goal of an interview.
Why not just put a tiny battery in the headset, sufficient for a few minutes of use, like an LTO battery that won't just wear out?

Or add latching to USB-C?
> Great, but what is the mismatch you speak of?

Go do some independent study and then maybe we'll talk.
I don't think companies intentionally optimise for that. It is just the fluid way of writing code that impresses whoever is watching you code.

But I do think most of what I use has grown into my muscle memory naturally, rather than memorizing anything.
For context, Peskin himself is known to verbally harass public officials while intoxicated:

> Verbal harassment

> Peskin has been known to make inappropriate late night phone calls to public officials and private citizens.[9] For example, he called the Port of San Francisco director Monique Moyer several times about cutting their funding over disagreements concerning waterfront building height limits. Mayor Newsom told the San Francisco Chronicle that people around city hall had been complaining about Peskin's behavior for years.[49] However, former San Francisco Mayor Art Agnos has said Peskin's alleged behavior falls "well within the boundaries of the system" and that it's "not unusual in politics at any level of government."[49]

> In 2018, at the scene of the St. Patrick's Day fire in North Beach, Peskin was reportedly intoxicated while he verbally berated then-Deputy Fire Chief of Operations Mark Gonzalez. Peskin has denied being intoxicated at the time but has apologized for his behavior.[50]

> In June 2021, Peskin announced in a statement that he would be entering into alcohol treatment.[51] Peskin apologized for behavior that he attributed to his alcohol problem, but also announced that he planned to remain in office while in treatment.[52]

https://en.wikipedia.org/wiki/Aaron_Peskin#Verbal_harassment
> The literal evidence proves that this approach is absolutely workable at scale, so “the worst possible way” clearly doesn’t apply.

The “worst possible” to me implies that it is possible.

Think about trying to solve the same problem by hurling engineers into an erupting vulcano. It is expensive, hurts the morale, causes staff retention issues, but also fundamentally does not solve the task of scheduled task running. I would not describe that as “worst possible” because it lacks the second factor by not being a possible solution.
Wait, pdf files aren't binary ?!
looks great. currently using Charmstone on my mac, can't imagine life without it.
People can and do have their conferences and calls and 1:1s in conference rooms. We are definitely not inventing the wheel now, this kind of setup I'm sure can be seen everywhere, and long before covid. I won't even blame the NIH syndrome, but can't stress enough: there ARE solutions to everything, and they can be (re)applied once there's a will.
I second this. Great tool. I always plug your tool in these threads too when relevant. The tree-sitter repo map was a great change. Thank you.
Where did you read top of 70k? He stated 70k and up for a team lead, not a staff engineer. 70k is the bottom for that role. Given the starting point is that for 'just' a team lead, presumably a staff engineer would start much higher, if they have that role.

I agree it's low given even a team lead role, but it depends on how many are on the low end of their pay scale.
"Our telemetry shows that many people don't use the brakes often in an electric car, so we've moved them to a sub-menu of the dashboard. We've removed the brake pedal, saving $32 per car."
> ImageReady was lean, fast and web-focused. When they killed it you had to buy a PS license and deal with the monolith PS was becoming.

To my knowledge, ImageReady 1.0 was the only version sold standalone - and that was back in 1998; the very next version (in 1999) was sold in-box with Photoshop 5.5 - but the separate ImageReady.exe program was around until 2005 - whereas the way your post is worded implies Adobe were being more customer-hostile than they usually are (hah).

I see your point about not needing the weight of Photoshop's print-and-photo tools when web-design folks back then were just wanting a flexible raster image editor - but my recollection of the web-design scene back then was that most web-designers tended to already have a background in print design work (e.g. think about all the print-shops who expanded into website-design in the late-1990s) - so it makes a lot of sense for Adobe to extend their tooling to support the web and "new media" as we called it - rather than create a new tool which would operate on a completely different, "web-first", domain-model (of course, that's exactly what Macromedia did, and they rightfully have their fans for that).
This thought just occurred to me: would it make sense to train a model to recognise vector encoded video frames?

I completely forgot how video encoders work, but I do remember that some encode the differences between one frame and the next with vectores of the "motion" of pixels. The training data would be comprised of frames from a video with labels assigned to time ranges across the length of the video.

The we could feed a video stream to a model and it would learn to not only recognise still images, but also motion across time.

Make it fast enough and we would have near real time inference of video.

If this works, maybe an extension to this model would be to accept its previous inference result as an input to the next frame inference request. Then we'd have results like "a person entered the bright light seen of a sunny day in the country side".
Curious to see which of these have been discussed on HN:

1. Karl Marx and Frederick Engels, "The Communist Manifesto", 1848.

No direct submissions.

2. Margaret Mead. "War Is Only an Invention—Not a Biological Necessity", Asia, 1940.

No direct submissions.

3. Alan Turing, "Computing Machinery and Intelligence", Mind, 1950.

25 direct submissions, most discussion (13 comments) 7 years ago: <https://news.ycombinator.com/item?id=12245426>

4. Martin Luther King, "The quest for peace and justice", Nobel Peace Prize Lecture, 1964.

No direct submissions

5. Robert Trivers, "The Evolution of Reciprocal Altruism", The Quarterly Review of Biology, 1971.

No direct submissions.

Three comment mentions to date: <https://hn.algolia.com/?dateRange=all&page=0&prefix=true&que...>

6. Thomas Nagel, "What Is It Like To Be A Bat?", The Philosophical Review, 1974.

16 submissions. Two with substantive discussion: 7 years ago <https://news.ycombinator.com/item?id=13998867>, 9 months ago <https://news.ycombinator.com/item?id=35771587>.

7. Stephen Hawking, "Is the End in Sight for Theoretical Physics?", Physics Bulletin, 1981.

No direct submissions.

8. Oliver Sacks, "The Man Who Mistook His Wife for a Hat", 1985.

Two submissions, both with discussion, 9 months ago <https://news.ycombinator.com/item?id=35866734> and 8 years ago
<https://news.ycombinator.com/item?id=10144420>

9. John Wheeler, "Information, Physics, Quantum: The Search for Links", Proceedings of 3rd International Symposium on Foundations of Quantum Mechanics, 1989.

One submission, 6 years ago: <https://news.ycombinator.com/item?id=15802155>

10. John Ioannidis. "Why Most Published Research Findings Are False", PLOS Medicine, 2005.

36 total submissions, notably: 1 year ago, 80 comments <https://news.ycombinator.com/item?id=33265439> 5 years ago, 40 comments <https://news.ycombinator.com/item?id=18106679> 5 years ago, 39 comments <https://news.ycombinator.com/item?id=19016399> 13 years ago, 40 comments <https://news.ycombinator.com/item?id=1825007>
Does anyone use this method in practice? How well does it work?

I can imagine it not working well in some cases, for example when a failure can only be resolved by some new thing (e.g. when a function was replaced by some other function).

There also seems to be an implicit assumption that the tests are 'sufficient', whereas I'd wager that the whole reason a revert is needed is the fact they are, in fact, insufficient. The article even says so:

> Obviously, the Mikado Method cannot work if you don’t have a good and highly reliable automated test suite.

But if you have a good test suite, then there should be no problem shipping the big change in one go!

I imagine the mikado method can still work though, because when shit does hit the fan, you can just downgrade to the previous version while keeping most of the preliminary changes? And that should then reduce the cost of the revert.
There is no Linux flavor that is even remotely comparable with Win3.1 if you include the GUI in the comparison.
Don't remember, sorry. It was a lot of time ago. The articles should be listed in scientific indexes.

Dentists are a special group that worked a lot with mercury in the past, dunno if is related but it could be a combination of risk factors. We should ask a chemist.

In any case today the facts can be very different.
Too many Trumps :)
Tiny Caribbean Island of Anguilla Making a Fortune from .ai Top Domain
teenager + apple pie = pregnancy
For software engineering interviews (all kinds of interviews/tests?), using any outside resource should be assumed to be cheating by default, unless you've asked for, or been given, permission.
That can be confusing. More here: <https://news.ycombinator.com/item?id=39213144>
If you want North to be up, tap the compass icon.
I don't see anything in that article, but 60s style care free sex, with willing partners. Not even remotely perverted.

Sex is not ugly, and sex with willing participants, is not ever perverted.

Not sure what thr GP is talking about.
> Interpreting an image in the concept of a machine baffles me, it doesn’t have eyes

Your mistake here is thinking what machine has understanding of anything. It doesn't. But if you know how human learning works, what is a compression and what is a lossy compression then it is quite easy to understand.

Machine is fed with tons of images with word references what is in the image. Then it finds what is similar in the images of a similar objects, ie works just like a compression algo, except it doesn't store the exact matches but relationships of some markers it finds in the images. That's why it doesn't and doesn't need to understand where is sofa and what is a sofa, it just have a relationship between something what has a relationship to the word 'sofa' and relationship with something what we, human describe as 'position'.
Good job and totally worth the fee. I'm not even kidding: with minimal effort you now have some things to consider and after that some now reasonably intelligent questions to bring to a real lawyer. You are much further ahead.
I usually use tasks where they would build in an existing codebase like setup. Frontend or backend and they have to add features to or find bugs.

The whole algorithm and leetcode thing just seems so off and unpractical to me.

Then once they have done the exercise there are so many practical things we can discuss about the existing code. Peformance, quality, etc, etc.
You know what the end of leetcode interviews looks like, right?

It is the age of take-home assignments that take days to complete.

Only absolutely incompetent people would want this over leetcode.
Number go up.

More seriously, it looks like a potential reduction in the cost to train a neural network.

You can think of every meaningful step forward in deep learning as a reduction in the cost of training, or an improvement in the ability of the signal to propagate.

https://arxiv.org/abs/2001.08361
It's not so much that the team isn't interested in building it, more that there there were some volunteers that indicated they started work on APIs already so I moved on to work on other areas of the codebase. Those draft PRs have since been closed as stale... so I'm planning to come back to doing the API myself in the next major version cycle.
We are experimenting P2P distribution of live video content over WebRTC datachannels. Would love to hear your feedback and what kind of latencies you are getting. https://clock.streamr.space (best experienced in browsers that support MSEs)
Was discussed before these (mostly throughput) benchmarks in https://news.ycombinator.com/item?id=39173229
Show HN: OasysDB rewritten as embedded and efficient vector database
OasysDB is now available as Rust crate which you can add using "cargo add oasysdb" command. OasysDB supports incremental update on the collection index by default. This means, you can insert, modify, or delete vector records without rebuilding the index.

Context
OasysDB was initially written with client-server architecture. We pivoted and rewrote it as embedded vector database.

Feedback will be very much appreciated.
Not something new.

In 2000 the EU Lisbon strategy announce that it would be "the most competitive and dynamic knowledge-based economy in the world capable of sustainable economic growth with more and better jobs and greater social cohesion", by 2010
Find unused files, dependencies and exports in your JavaScript and TS projects
For me VR for office use doesn't survive the "timeline reversal thought experiment".

Imagine that from the very beginning computers only had virtual reality headsets as the only interface. In the time of ENIAC it would be extremely huge grotesque steampunk helmet that you would put on but as the time goes by smaller and smaller headsets developed and eventually today we would arrive exactly where we are now with this Apple VR headset. And now, someone invents desktop PC monitor. It will be revolutionary. No longer you have to strap on headset and wear it for 8 hours when you're in the office. Instead of $4000 fragile gear you buy cheap $100 dollar flat panel with double the resolution. No motion sickness, no batteries, no cables around your neck. Everybody would switch and VR headsets would become niche product.
Thx. These discussions are so often based on assumed intents and interpretations (for better or worse) rather than the actual texts. Not saying one should be ignorant of context, but the ground text matters.
> Obviously they cannot all be right.

They could all be right that their market share will be higher if they adopt this policy than if they don’t.
The Chinese companies are leading in innovation of these robots though
> According to SEMI, China will have 8.6 million 8 inch equivalent wpm capacity this year, Taiwan will have 5.7 million wpm, Korea will have 5.1 million wpm, Japan will have 4.7 million wpm, the USA will have 3.1 million wpm, Europe will have 2.7 million wpm, and S.E.Asia will have 1.7 million wpm.

In the not quite unrealistic scenario of tensions between China and US increasing, with China possibly annexing Taiwan, it is clear that chips will have to come from Europe, US, Japan and maybe South Korea for the Western market. I think most of these investments are considering that scenario, and then they have to tweak the numbers and make unrealistic estimates to sell that idea as a regular business plan.
I'm not saying you're wrong, but that reasoning is why I have to prepare for interviews. I'm _really_ bad at remembering that stuff, I think it really depends on how you think while programming.

I've got an abstraction that I think in that then needs to be translated to code. e.g. if I want to append to a list, I think "push to list", regardless of language/framework/whatever. Then somehow my hands will translate that automatically to code in the language I'm working in. If I'm not in my usual editing environment, that magic just sort of breaks, and I just look incompetent.

It's not a huge deal, but I have to actively sit and memorize that stuff before an interview. Usually by writing it out on paper or writing it in some foreign editor that I'm not used too.

It probably wouldn't be _too_ bad today, because I just sit and write Typescript everyday, but when I was switching between perl/ruby/python/tcl/kotlin/javascript/bash/csh/lisp my brain was basically mush. I couldn't tell you how to do any basic operation in any language.
Lambda functions can scale 12 times faster when handling high-volume requests
Since you raised the idea of abstraction (and having typed my fair
share of Lambdas) I'd say that it's a powerful idea we can both focus
on. Not all abstractions are mystified. Some are. Clearly there are
things that do not exist yet retain utility as concepts; money,
democracy, wellness. And there are "real" things that only muddy the
waters.

Yes, one can point to a specific computer and say that it is part of
The Cloud, just as you can point to a neuron or person and say that
is part of a brain or a society. But what does that really tell us
about societies, brains or clouds? I'm obviously channelling an inner
Douglas Hofstadter here.

The Cloud is something mystical not because it's an abstraction but
because people don't care. It's more of an abdication than an
abstraction. You can read a thousand comments here on HN literally
saying stuff like "I don't care how it works".

We positively celebrate it's mystery.

It's not a noble-savage argument to ask, whether there is more
intelligence and honour in the hopelessly unscientific, lost person
who in their heart knows astrology is nonsense, but cares.... or the
well educated scientist who has the capacity to deeply understand the
Cloud but chooses not to as a "don't care" coping mechanism for
complexity. That is what I mean by modern mysticism .
I don't understand the example. How do you fix the issue in the test, when the issue only exists in the version 7 branch, which you deleted?
For those unaware, OpenAI recently announced [0] an API change where they said their newer models are using Matryoshka representation learning for shortening embeddings. Basically you can use a shorter prefix of the full representation to do query/lookup for cheaper without losing much quality. Quote:

“Native support for shortening embeddings:

Using larger embeddings, for example storing them in a vector store for retrieval, generally costs more and consumes more compute, memory and storage than using smaller embeddings.
Both of our new embedding models were trained with a technique [Matryoshka Representation Learning] that allows developers to trade-off performance and cost of using embeddings. Specifically, developers can shorten embeddings (i.e. remove some numbers from the end of the sequence) without the embedding losing its concept-representing properties by passing in the dimensions API parameter. For example, on the MTEB benchmark, a text-embedding-3-large embedding can be shortened to a size of 256 while still outperforming an unshortened text-embedding-ada-002 embedding with a size of 1536.”

[0] https://openai.com/blog/new-embedding-models-and-api-updates
Is there anything that allows one to mount an IPFS dir as a read/write FUSE drive yet? Once they have that, I'm all in, even if it's slow...
Obviously they cannot all be right.

As a percentage of the market, that's true, but if the subsidies grow the whole market then every block's dollar value of market share can all go up.

Every startup learns this lesson quite early on. It's a heck of a lot easier to grow a market by 5% than it is to take 5% of the market from a competitor, mostly because competitors do things to try to stop you.
Not verboten.

Truly dubious researchers will just tinker with the analysis to get the result they want without telling anyone what they've done, which absolutely was not the case here. These researchers followed the accepted best practice of publishing their intended outcomes and analysis methods before starting the trial, which is laudable.

The original paper used standard frequentist methods that are generally accepted by clinical journals, while their follow-up used more esoteric (and arguably more advanced) Bayesian methods. The decision to publish the re-analysis was justified, they were completely transparent about it, it doesn't reflect badly on their professionalism or integrity in any way whatsoever, but it does slightly smack of desperation.

Similarly, some of the authors of that paper subsequently published a paper criticising the validity of the main outcome measure they used, the QIDS-SR-16. The points they make are perfectly reasonable, the paper is informative, it's entirely plausible that they only lost confidence in the instrument because of what they learned from the trial, but it does seem a tiny bit desperate to be making those arguments after the fact.

https://pubmed.ncbi.nlm.nih.gov/37122239/

To be absolutely clear, the team at the Centre for Psychedelic Research at ICL are good guys. They're serious, they do all the right things in terms of research integrity and they clearly care deeply about patients. They worked through a dreadful mire of legal and bureaucratic barriers to get psychedelic research done on a meaningful scale. Nutt and Carhart-Harris and others are absolutely passionate about this area of research, and I just hope that they can find a way through if this disappointing finding proves to be the beginning of a dead-end.
Machine-guided discovery of a real-world rogue wave model
https://techpays.eu/europe/netherlands
24 Seconds to view the product images on Amazon's website
(this discussion is quite nuanced so I apologize in advance for any uncharitable interpretations that I may make.)

> I'm not really trying to rebut Michael's argument -- I think it's true, to an extent, some of the time. But I think it's more true more of the time in the reverse direction.

I understand you to be saying:

Michael: Pro AI capabilities people are ignoring AIXR ideas because they are very excited about benefiting from (the funding of) future AI systems.

Reverse Direction: ainotkilleveryoneism people are ignoring AIXR ideas because they are very excited about benefiting from the funding of AI safety organizations.

And that (RD) is more frequently true than (M).

IMO both (RD) and (M) are true in many cases. IME it seems like (M) is true more often. But I haven't tried to gather any data and I wouldn't be surprised if it turned out to actually be the other way.

> So I don't think it's a good argument.

I might be misunderstanding you here because I don't see Michael making an argument at all. I just see him making the assertion (M).

> And more importantly, I think it fails to properly grapple with the ideas, instead using an ad hominem approach to discarding them somewhat thoughtless.

I am ambivalent toward this point. On one hand Michael is just making a straightforward (possibly false) empirical claim about the minds of certain people (specifically, a claim of the form: these people are doing X because of Y). It might really be the case that people are failing to grapple with AIXR ideas because they are so excited about benefiting from future AI tech, and if it were, then it seems like the sort of thing that it would be good to point out.

But OTOH he doesn't produce an argument against the claim "AIXR is just marketing hype." which is unfair to someone who has genuinely come to that conclusion via careful deliberation.

> On your last point, I do think it's important to note, and reflect carefully on, the extremely high overlap between those funding ai notkilleveryoneism and those funding capabilities development.

Thanks for pointing this out. Indeed, why are people who profess that AI has a not insignificant chance of killing everyone also starting companies that do AI capabilities development? Maybe they don't believe what they say and are just trying to get exclusive control of future AI technology. IMO there is a significant chance that some parties are doing just that. But even if that is true, then it might still be the case that ASI is an XR.