skysight-inc/HackerNews huggingface dataset:
So there is a clear effort to build enclosures around various of corpuses of material that could or would be useful to train AI. Thing is, people read books, they watch videos, they listen to music, they see and produce art and so on. How is training data distinct from "human training data"?

One could say the quantity. We're currently dealing with statistical learning models that require a huge quantity of training data. This is temporary. At some point you will be able to train an ML system with less because humans can be trained with less. What then?
Hypothetically speaking, if a chat provider used a Golden Gate Claude [1] technique to essentially create and pump a meme stock, is that a fraud?

[1] https://www.anthropic.com/news/golden-gate-claude
Full disclosure, I worked at Tribe some years ago but I think Tribe is a great example of the new generation of startups that are growing revenue sustainably as they build products rather than living off OPM.
Is the reason because montessori schools are often high-priced? Because that's definitely true (and you can easily say it's a privilege to attend one).

That doesn't, however, mean the methodologies don't work or don't apply. You can study the methods in any of her ~20ish books, or the more modernized recaps of them.
Paul Offit (infectious disease physician and vaccine expert) doesn't think that this h5n1 is likely to become a human pandemic:

Humans express the alpha-2,3 sialic acid receptor on cells that line the surface of the eye (which explains why the dairy farm worker in Texas had severe conjunctivitis). The alpha-2,3 sialic acid receptor is also found on cells that line the lung. However, and most importantly, the alpha-2,3 sialic acid receptor is NOT found in cells that line the upper respiratory tract. This means that H5 viruses cannot reproduce themselves in the upper respiratory tract and thus be easily transmitted from one person to another. It also means that H5 viruses cannot amplify themselves in the upper respiratory tract, where hundreds of virus particles can become millions of virus particles.

https://pauloffit.substack.com/p/h5n1-influenza-virus-bird-f...
CoW filesystems with frequent snapshotting, which suffices save for CoWFS-specific commands.

Spinning up a VM for testing is another Very Good Practice.
Shocking or not, I think "this company is potentially breaking the law" is always worth calling out.
Google, Microsoft offer Nvidia chips to Chinese companies
I got stuck on setting the ollama.embedding_model. No clue what to do.
I think this is a non-answer in some sense. Yes, transformers have been clearly very successful across a very wide range of tasks. But what about the approach taken in capsules is comparatively deficient?

Some kinds of explanations which I think are at least plausible (but IDK if any evidence exists for them):

- The attention structure in transformers allows any chunk to be learned to be important for any other chunk. And pretty quickly people tended towards these being pretty deep. By comparison, the capsule + routing structure (IIUC) came with a built-in kind of sparsity (from capsules at a level in the hierarchy being independent), and because the hierarchy was meant to align with composition, it often (I think) didn't have a huge number of levels? Maybe this flexibility + depth are key?

- Related to capsules being independent, an initial design feature in capsule networks seems to have been smaller model sizes. Perhaps this was at some level just a bad thing to reach for? I think at the time, "smaller models means optimization searches over a smaller space, which is faster to converge and requires less data" was still sort of in people's heads, and I think this view is pretty much dead.

- I've heard some people argue that one of the core strengths of transformers is that they support training in a way allows for maxing out available GPUs. I think this is mostly in comparison to previous language models which were explicitly sequential. But are capsule networks less conducive to efficient training?
While I generally agree with your take that it's a regression in PL design, there's no need to be inflammatory. There's lots of good software written in it.

> pretending Erlang does not exist

For better or worse it doesn't to most programmers. The syntax is not nearly as approachable as GoLang. Luckily Elixir exists.
This is why I don't eat meat anymore.

I know H5N1 had a high fatality rate before the current streak of diagnoses. If I'm reading (1) correctly, the death rate since 2022, for all known cases worldwide, is ~27%. Still bad, but a massive reduction from the 50%+ it had before. Current cases in the US are mild, according to (1).

I have little faith in pandemic response after COVID, but there are a few things to keep in mind:

1) We managed to shove a decade of viral research into 18 months due to COVID-19. We now have mRNA vaccines, which can be made far faster than other types and can be switched more easily in production. People (well, more people than before) are willing to mask if they're sick, at least in my anecdotal experience.

2) Flu has been the one that public health officials, doctors, virologists, etc. have been watching for years. If you had asked someone in those fields what their thoughts on COVID-19 were in 2015, they would have asked "what the hell's covid?", but would have been able to give you a fairly complete picture of what was happening with the different varieties of influenza. The enemy is known, to the point where rural villages in Southeast Asia can have people quarantined for the virus.

3) Again, recent cases in the Western world have been mild.

Disclaimer: I am not an MD, DO, MPH, PhD, or anything else of that nature. I have never claimed to be smart. I am a dude on the internet. Listen to smart people before you listen to me and my one source.

(1) https://www.cdc.gov/mmwr/volumes/73/wr/mm7321e1.htm
> I agree with you, and think the value proposition for these companies to hire junior talent is especially unappealing given the 1-2 year job hopping which has become popular of late.

If juniors can consistently hop to another job that pays them more in a year, then the job market for SWEs is strong and employers don't have this ease of hiring seniors that is being described.
This take sounds reasonable to me. But I'm not an expert, and I'd be curious to hear an opposing view if there's one.
The training of models seems less of an issue than what you do with them.

IMO, the most problematic part is generating content in the style and voice of the original human creator of the copyrighted content.

Unfortunately, this is also currently among the most user-attractive for generative AI trained on copyrighted content.
There is usually something important to learn from other people's failings
> By not following or liking a student influencers posts’, kids might be able to change the equation and allow their teachers to focus on teaching instead of competing for their students’ attention.

Sounds nice - but what percent of adults could manage to do that? And the article is about middle school kids.

At some level of disruption, the school district's least-bad option might be to put a de facto toxic influencer into her own school. One student, one teacher. She has a right to an education, not a right to derail the educations of dozens or hundreds of other students.
> An individual organism surviving for the longest amount of time is not necessarily optimal at the species level.

Though it can be argued that among social, intelligent creatures, living grandparents holds value for the species. Humans and orcas both seem to benefit from them in many ways.
It was 1.5 working days, and there are other factors not mentioned in this article which meant they were lucky to get that (I could write a whole other article about how hostile and dismissive they've been to researchers). If they had requested an extension, I may have considered, but they didn't respond at all.

To elaborate, there are no new security disclosures made in this article. The logging issue has already received mainstream media coverage, after they resolved it and published an advisory, and people have been playing with flashing custom roms via mtkclient for months (as referenced in the article).

The only new "accusation" is that they are violating GPL. I informally asked them for GPL sources months ago via their community discord server, and I'm aware of others who have asked more formally.

Asking for their input on the article was a) giving them a courteous heads-up b) a formality c) an opportunity for them to correct me if they thought I said something untrue.
Wrong. The situationist movement was politically active in the years leading up to 1968. The Society of the Spectacle was written in 1967.
Engagement being a two way thing between the teacher and student. In this case I was referring to the teacher reading and responding to the student's body language.
This is about the Pile dataset, of course we don't if it has been used to train the commercial models we use or just for the research papers mentioned in the article.
There was a discussion some days ago about one of the AI companies using a very characteristic user agent string for web crawling, but a more browser-like one for web browsing performed at the behest of the user. And there were some pertinent points there—if the AI bot is acting on an explicit request of a user, it does deserve to get treated like any other user agent more or less.
Create a private right of action. If creator A can show that AI trainer B used their works (e.g. like how we've seen Getty watermarks show up in AI generated pics), then they can sue for $X dollars.
Yeah fair, I could see why it’s good for us who has a decent chunk of experience. Kinda makes sense from managerial perspective as well - lay off bunch of under-performers/juniors, hire back other seniors from other companies that got laid off and save 25-30% while delivering about the same results. I’m over-simplifying it, but we’re going through an over-correction phase, in my opinion.
That’s true for other roles, like an MBA grad that can discuss financial principles but can’t navigate Quickbooks or use Excel.

From my admittedly limited understanding, many of those openings are filled based on resume and verbal interviews with little or no quantitative evaluation of skills.
The only thing this data shows is that the job market was briefly a bubble in early-mid 2022 and that bubble has now popped. To judge how bad things actually are, why cut the chart off at an arbitrary point (mid-2020) and not go back, say, 10 years? Are their more SDE openings today than 2012/2015/2018? I'm pretty confident that the answer is yes.
Self-Regulation Won't Prevent Problematic Political Uses of Generative AI
Robotic Blacksmith Army
Oh. My. God.

His resume starts with a quote of himself stating that he has “seen things you people wouldn't believe.”

It goes on to highlight that he purchased a domain name in 1997.

He claims to have developed “the highest performing in-memory database in the world” but complains that “nobody really wants to buy it when free worse performing choies [sic] exist.”

The part about nobody wanting to buy his product is in his resume.

His current status is “Waiting for AI apocalypse.”

This is either mega-cringe, or the best satire I’ve read in a while. Unfortunately, I think it’s the former.
If you're relying entirely on LetsEncrypt for a service which uses hundreds or thousands of subdomains (e.g. one per user) then you practically have to use a wildcard too, because generating tons of individual certs for the same top level domain will very quickly run into LEs rate limits.
A super uneducated piece of input for thought:

Perhaps it is not that it is evolutionarily beneficial, but rather a byproduct of other evolutionarily beneficial processes? Such as sending larger amounts of blood to an affected region.
How are you tracking the efficacy? Did you measure an actual deficiency in your blood? What effects are you hoping for? If you don't get the desired effects, what will you do?

I always feel a bit of FOMO whenever supplements are being discussed, then again if I bought all the supplements every time I'd have a whole apothecary...
Alternate perspective: Everything is a remix and "intellectual property" guardians are the middle men skimming profit from this continuum.
> Proof News also found material from YouTube megastars, including MrBeast (289 million subscribers, two videos taken for training), Marques Brownlee (19 million subscribers, seven videos taken), Jacksepticeye (nearly 31 million subscribers, 377 videos taken), and PewDiePie (111 million subscribers, 337 videos taken). Some of the material used to train AI also promoted conspiracies such as the “flat-Earth theory.”

I'm not going to grok through all their thousands of videos, but these specific creators sure didn't get this big on reactions only.
I don’t see anything wrong with these companies using YouTube content to train AI in a sense. I think the creators of the videos should be fairly compensated and their permission should be sought, but I don’t think of Google/Alphabet in that way. Sorry but even if Google runs the YouTube platform, I just don’t think they ethically or morally have an exclusive right to the content the world creates, just because they have various monopolies that are immune to competition due to anti-competitive moves and the power of network effects. As far as I am concerned they are a utility service that needs to be heavily regulated.
He is as much of an expert as it gets, as he is the leader of the Loom project.
tech companies are in a long-term process of moving most roles (not all) to lower-comp

that often means relocating the job or just low-balling people here

there will always be an elite who are very well paid, but we are now seeing the long-term reformat of the rank-and-file

step 1 is to freeze hiring and let attrition move the numbers down...this builds up a body of desperate job-seekers who will work for less
It’s like fishing. We have laws for that not because one person with a pole and a line can catch a handful of fish. It’s because that eventually evolved into a machine with many lines and nets harvesting too many fish. They’re both “fishing” but once you reach a scale beyond what one person can reasonably do the intent and effect becomes completely different.
Well, an “AI” has accessed those items because it was forced (strictly speaking) by a human to do so. Thus, the human doing that is not making “fair” use of those sources.
Sad? Or maybe an indication that your opinion isn’t the universal truth…
I tend to believe you are right... But neither one of us can tell it for sure.

Notice that you have written a trademark on your comment? Only the people that work on that place get to know, or to decide if there will be a scam or not. They get full control of what's happening.
This answers and solves nothing new. SSL exists.
I'd generally say that disclosure should be enough (and is currently insufficient in the US outside of California), but I am weary that much of your life now involves "Pay us with Venmo" or "Customer service via Twitter," such that one cannot really opt-out without paying a significant cost.
"Retroactive Why's" are useful because on evolutionary timescales, and it must be if it impacts mice and people, even a very tiny selective pressure causes harmful traits to be selected against.

If as few as 1 in 10,000 reproductions were prevented by a trait then we should expect that trait to be gone in a million years. And our last common ancestor with mice was likely 65 of those past.

Harmful traits can linger if they confer some other benefit. Other's have already worked through this and are rightfully asking, "If this is so harmful it should be have been selected against, what does it do to help us get to successful reproduction in the environment it evolved in?"
It doesn't look especially specific to me - slightly hack the structure in https://github.com/libtom/libtommath to make sense to your garbage collector and you're pretty much done. That somewhat punts on the testing question but I doubt add/mul/bitops from that library are buggy.
People do make the claim that this ought to be considered "fair use" under the law. There are an numbers of prominent cases were AI companies are getting sued, and we'll see if this defense actually works.

If the question is about what is "fair" I don't see how you could be surprised that artists, journalists, musicians, Youtube creators, would object to huge tech companies using their stuff without permission to replace them. It is entirely to be expected that many people find this unfair.

If enough people file this to unfair and outragous, even if the courts found the "fair use" arguement cogent, the laws could be changed.
It's awfully hard to imagine any specific kind of harm that video creators will suffer by having AI trained on their subtitles...
This thing won't take long to collapse. We already see this happening when it comes to security: every major company has already been hacked, frequently quite easily. The web search industry is already serving 99% ads instead of proper results, the job market is completely broken, social networks are saturated with bots, and AI companies are proposing to replace knowledgeable people with machines that fabricate their own dreamed of solutions.
> Your precise GPS locations (which are also sent to their servers). ... The IDs of nearby cell towers (even with no SIM card inserted, also sent to their servers).

Is this sent to the server all the time? Or just with requests? It shouldn't come as a surprise to anyone that a device designed to respond to questions like "What's a good restaurant near me?" is also sending location context with requests.

If they're sending a constant stream of location all the time for no reason, that would be concerning.

> Your WiFi network name. ... Your internet-facing IP address. The user token used by the device to authenticate with Rabbit's back-end API.

A device must store WiFi network names to reconnect to them. An IP address showing up in local logs isn't really surprising either.

Storing the user access token on the device is also a necessity for reconnecting without logging back in every time you turn it on. The fact that it's stored directly in logs isn't a good practice, but when those logs are stored on the same storage as the db or config file that contains them, it's also not really a new issue by itself. If they were uploading logs directly to their servers, that would be an issue of course.
Virtualising Darwin on L4 (2007) [pdf]
I'd also point out about AWS cost, which is pretty high, getting IOPS is easy. Getting Redundant IOPS is hard part.
The end users have been lied to for half a century as the fossil fuel companies spent billions on PR campaigns, buying politicians, setting up think tanks and fake research groups, etc. claiming that something their own scientists were confident was happening was not happening.

Imagine the alternative where they’d gone to Nixon with their research and worked with governments to gracefully transition, support rather than oppose efficiency improvements, etc. The difference in deaths will be measured in millions, and the cost to the global economy would have been trillions of dollars less.
That's talking about one project, not a company. A company might have repressed demand and more people could allow it to take on more projects and/or take care of tasks that are being left behind.
Show HN: I made a website to learn and practice mental math
Sure, up to you. In any case I take it they still haven't responded?
No thank you. Keep Big Brother out of the classroom.
Sometimes if a web page claims to require JavaScripts, the text can still be viewed if you disable CSS as well as JavaScripts. Another thing you could try is view source; sometimes the text or data will be visible in there, or you can find a link.

An idea which might be able to help more, is a script substitution feature, allowing the user to substitute their own scripts for some or all of the existing ones (and enable or disable or limit the rest of the scripts), by the URL or by the hash (if there is a integrity attribute, then it will not be necessary to download the file in order to determine its hash).
While the analogies are often useful, everyone reading HN comments should be very aware and very skeptical of just how often computer/tech people rely on computer/tech analogies to understand things that are fundamentally not computers/tech.

It is very very easy for smart people with functionally specific jobs/hobbies/ways of thinking to see all reality through that narrow window. It often leads to important details being glossed over or entirely missed. The more self-confident ones quickly start seeing the analogies as fundamental facts, usually with negative consequences like loss of empathy or a tendency to see big picture generalizations as specific universal truths.

Mushrooms have had a similar effect on me at times. You can start feeling like you KNOW big sweeping Truths. Similar to religiously “knowing” something. And that feeling of knowing is hard to overcome. But it is just a feeling.
In the email I got from AT&T regarding this data breach was: "Protecting customer data is a top priority. We have confirmed the affected system has been secured. We hold ourselves to high privacy standards and are always looking for ways to improve our security practices."

Well, now I feel better. 8^)
Hi Jason, we had discussions at Caltech on some of these ideas many years back. We do have a patent, now lapsed, on doing spaced repetition on knowledge graphs:
https://patentimages.storage.googleapis.com/ff/ae/6d/3483859...

Math pedagogy in the US leans to understanding being more important than practice. This is wrong. As you point out, understanding more often comes from practice. To correct this imbalance, software like your company is developing is useful, as are platforms like ALEKS, iReady, etc.

The challenge is addressing the social aspect of learning -- the benefits students get from working and learning together. Is it still a classroom if all the students are doing different things?

Of course, students come in with different abilities and levels of preparation. Differentiation that works in a class setting is very hard. Software is the easier part. Students who are motivated to learn and can grow with guidance from a computerized tutoring environment -- helping them is also the easier part.
It seems like every autocompleter or recommendation feature was trained on data obtained this way. The form of the output is very different and perceived very differently. I imagine Pandora had to train their recommendation on recorded music and then using that entire body of knowledge chooses a song to stream and pay royalties.

Every music service has something like this, are they delivering just the value of the streamed music? Great then they only owe those royalties. Are they delivering the value of EVERY song they trained on every time a new song is chosen? I sure wasn’t asking that question until generative results became the product.
It's the chicken egg problem (?). ChatGPT couldn't make LLM so valuable without stealing. It's just forcing the freemium model, if google accepts settlement/later payments without any crime charges
They used to in 2020-2022 cycle. I don’t think they can right now, but the social contract of employees staying at the company for a long time has been completely broken. So now everyone just expects short retentions, and market forces drive for senior hires.
It is one of the fastest-growing OSS projects focusing on a great user experience. Not all open-source projects focus on UI, as the OpenMetadata team does.