skysight-inc/HackerNews huggingface dataset:
I happened to be at an investor-startup conference yesterday that had a few different companies trying to do this. It's actually not a bad idea. There were some claims made about specific companies that I couldn't verify, but interesting none the less

* Examples of specific company employees extracting information they had no access to in the regular JIRA/Confluence world, but were able to extract it via an LLM trained on company data. There are a bunch of "train LLM on the companies entire knowledgebase" startups right now. Without control on who is querying about which project. Employees can query about the RIF that is happening next month, and maybe theyll get a truthful response

* Hiding information that needs to be legally, or morally anonymized

* Anonymizing business logic and code

If it works well, itll allow companies to really throw in everything they have into LLM training, without worrying of what goes in. Plenty of companies (including my employer) still block the chatgpt URL accross all computers

The only problem I see with these shovel sellers, is that any corporation can build this in a couple of weeks tops to help sell enterprise licenses, they don't really have an edge
What European country is socially to the left of Democrats? This is only a little bit true in terms of economics.
I was avoiding the word "approximate", because that implies a connection to the original raw data.

A generative model guesses what data should be filled in, based on what is present in its own model. This process is totally ignorant of the original (missing) data.

To contrast, a lossy codec works directly with the original data. It chooses what to throw out based on what the algorithm itself can best reproduce during playback. This is why you should never transcode from one lossy codec to another: the holes will no longer line up with the algorithm's hole-filling expectations.
I'll rollback my use of the word "typical" somewhat, but it is something I see commonly among people who are strongly/ideologically associated with the Democrat Party or consider themselves "very progressive."

And the example I provided was a proposed law, not just some random internet comment. If it was a proposed law, does it really seem unlikely that people would argue for it and/or believe it? Remember, the original context of this discussion is regarding uniformity of beliefs between people in Europe vs. people in the US
To save you some headache, here's the URL you can give superbuy or any other similar proxy (not affiliated, just a happy superbuy customer): https://item.jd.com/10097209811046.html

However, unless I am mistaken there's not much of an advantage over the Gem10 based on https://i.imgur.com/G9YNO6I.jpeg (who cares about that AI?) and that's already available at https://aoostar.com/products/aoostar-gem10-amd-ryzen-7-7840h... and this one is LPDDR5 in case anyone cares about that.

One more interesting thing on this page is https://aoostar.com/products/aoostar-t-box-intel-n100-metal-... which is even smaller than a usual NUC yet quite rich inports and has a very agreeable price.
> I don't understand how so many people have come across cars with seemingly terrible auto AC systems.

> Whenever I rent a car it's always infuriating having to constantly muck with the AC system.

Am I missing something or do these not make sense together?
True, but this is probably not what was meant (mobile).

The issue with mobile is that there is way less incentive to switch browsers. iOS is a locked down prison, not making it a fair market.
Um, hello friend. Turn gesture controls off. It's in the settings.
or you just run llama on your pi4
The employees were sold a lie that their stock options were worth taking a lower salary. Every single developer effectively invested something resembling 10-30k and was totally wiped out, and if they worked there 3 years that's probably a quarter of their life savings. But the investor only demands a meager $200 million return on their $400 million investment before they recognize the workers' investments.
Bypassing Large Diffs in SubmitQueue (2023)
The majority of this is underdevelopment; at the moment it does rate limiting and PII detection.
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One of the diagrams says they're using CLIP-G/14 and CLIP-L/14, which are the names of two OpenCLIP models - meaning they're not using OpenAI's CLIP.
Yes, please. It's just so much better.
>That is why we have a system where a ~350 mile journey from London to Glasgow takes more than twice as long and typically costs more than twice as much for half the legroom compared to a ~350 mile journey from Paris to Bordeaux.

Just for my own interest as an American, I can take a 350 mile journey on a train from where I live (Jacksonville, FL) to Miami. There are two trains a day, one of which takes 11 hours and costs $72, the other takes 9 hours and costs $94. Based on my experience, both of these trains are likely to be between 3 and 6 hours later than the scheduled time. How does that compare to the London to Glasgow cost and time?
In case anyone's sufficiently motivated (no promises, but I might test it out eventually), a couple deep architectures that might address those concerns are:

1. Something like a deep support vector machine. Instead of (linear) -> (any activation), you want to create a bunch of features that look like testing the vector against a splitting hyperplane. One option is (bias) -> (matmul) -> (1-bit sigmoid). Applying a bias term _for each row_ let's you choose the branch location, the matmul's result will be positive or negative at each output feature depending on which side of the hyperplane normal to the vector described by the corresponding row you happen to fall on. Then just bring that down to -1 or 1 so you can't sneak much nonstationary drift variance into the output (perhaps train with a normal sigmoid annealed to behave more like this one, and a suitable regularizing term to keep the network from sneaking in values near 0 to thwart your annealing).

2. Use an attention-like mechanism, but across features (this would likely require an additional tensor channel, so that each "feature" carries information in a high enough dimensional space for this to do something meaningful). You apply the inductive bias that sparse feature interactions are important and need to be discovered.

Those two ideas also compose easily.
for simple tasks/code that I already know the answer to but just need a refresher, ChatGPT is great. when I'm dealing with something really mysterious, it starts to break down no matter the prompt, and I'm left with trying to figure it out for myself.
BBC developed standards for digitally signed information about media provenance
GraphRAG: Improving RAG performance using LLM-generated knowledge graphs
>angry that jetbrains put out a patch to fix the issue

They are angry that it was a _silent_ patch. The whole issue revolves around the _silent_ part.

More on why Rapid7 doesn't like silent patching here: https://www.rapid7.com/blog/post/2022/06/06/the-hidden-harm-...
Brother, I believe you. It seems like you feel deeply betrayed by the Church and I can resonate with where that comes from.
Please don't let this harden your heart to knowing Jesus and praying for God's grace.
I *really* don't want to see us encourage gamifying HN submissions. Something can be highly ranked for a myriad of reasons, including for technically controversial ones (e.g different philosophies in solving specific technical challenges).

A discussion here is a discussion, not a selling point. Makes me less willing to contribute to conversation about a product if the parent company promotes in this manner, though I might be in the minority there.
Because of SNAPs. Linux Mint is better as it doesn't have SNAPs.
> You see an LLM as something that copies stuff.

I see an LLM as a machine that takes an input and automatically gives an output. If that input is copyrighted, and the output is essentially a translation of that input, then it is a problem.

BTW using a camera to take a photo of your code, and then use text recognition to render it (with potential mistakes), and then use an algorithm to correct the mistakes, all that is not exactly "something that copies stuff": you will agree that there is a lot happening. Still you would say that it breaches the copyright "because it is exactly the same text". The thing is, "copyright" is not defined as "exactly the same text" (otherwise you could rename a few variables and be done with it).

> I find it immoral when an author has a say in how I use the book after buying it.

So you find it immoral for an author to sue you because you bought the book, copied it and sold cheaper copies on Amazon? Pretty sure you don't. You can't just ignore all the nuances that don't support your argument... I don't like DRMs either, but it does not mean that the concept of copyright is always wrong.
Last year I was briefly contracting somewhere using a Scala x PureScript stack. I believe their reasoning for picking PureScript in the first place out of other compiled JS options was conceptual similarity to Scala.

I would claim cons for their choice were very lengthy build times and very spotty tooling support (most devs didn’t have any IDE functionality and things like linting were done by hand). Probably the main reason is just that they had sooo much code that the LSP couldn’t handle features like definition jumping and type sanity checks. As for the linting, that was a devops oversight: it would have been an easy get that they never prioritized. Some of these tooling issues may also be resolved by more recent renditions of the LSP. Surprisingly, PS seemed to be only rarely the impediment to onboarding devs without FP backgrounds.

Pros are that, yes, it did have conceptual overlap with their backend (using Cats), and since most of their applications did the same form-based CRUD tasks just across different data sets in the domain, they had honed really efficient library idioms for rapidly building new apps with just a handful of type signatures. And they were indeed deploying a lot of apps to replace the legacy versions of their suite (a couple dozen per sprint).
and I thought I was cool for knowing about https://codeberg.org/
>What I always wonder is what is the end-goal of the current AI movement? What's the point of it all?

I also share this view. I would also argue that this is not even about the productivity. I mean, I don't think the currently automated parts were ever the bottlenecks in any good products.

There are already more stuff being produced every year from a single publisher that is more than I can consume. And most of it is just shit. Think of Ubisoft games. They are already churning out a few new games every year, each of them chock full of beautiful assets in a very boring world, with an extremely repetitive shitty gameplay. And now with AI they can produce even more beautiful assets with even more shitty gameplay and even more boring worlds, I guess.

Artists were already mostly a starving bunch (meaning the supply was already higher than the demand), good writers (and other auteurs) with strong vision were what was rare. And now, as humanity, we decided to divert some of the best engineering talent to automate the former? Why though, what is the point, really?

I don't know when was the last time I really felt bored. I am sure I am not alone in that. What is the point of exponentially increasing the content production rate? I am really struggling to understand the appeal here.
I've often thought that an interesting application of single-nucleotide resolution, large context-length models would be to train them on GWAS data to predict phenotypes from large DNA sequences (possibly the whole genome) and see if the model can perform better than current polygenetic scores. I'm not a geneticist nor an expert on machine learning, so I don't know how feasible this is given current technology and datasets.
Forward-Forward looked promising, but then Hinton got the AI-Doomer heebie-jeebies and bailed. Perhaps someone picks up the concept and runs with it - I'd love to myself but I don't have the skillz to build stuff at that depth, yet.
I'm too young to have seen any refueling races by the time I could watch F1, but I can agree with you that over-regulation seem to stifle innovation. Even if the innovation it stifles is "we put a w16 engine in a car just to see if it would work" (it didn't) it made for races you weren't totally sure who would even take part since there were more teams than grid slots, and qualifying actually had more excitement than just seeing who had pole. Did that quirky team with the experimental aero package make it into the race, or did the team with the heavier engine and worse braking make it?

Regarding tires, the lack of refueling means they have to make some kind of choice to add strategic opportunity and forcing at least one tire change per race is about the only thing they can do. It's a lot more interesting to watch something like IMSA where a damaged car is put into the pit, a mechanic jumps on the bent hood to squash it back down, and then they put some sturdy duct tape on it to hold it down for the rest of the race. In F1 any damage means you won't get into the top 10, so you won't get points, so you may as well not even finish the race.

Racing still needs to be a spectacle at some point, and I can only imagine being a fan who watched Senna in the wet back in the day, engine screaming, passes made with skill, and comparing it to a modern race where the engines are quiet and they had to add push to pass systems like DRS and the "add 160 horsepower" electric motors just to try to allow drivers to pass in the first place because the cars are so much larger than they used to be. I'll always be a motorsport fan but F1 kind of seems like a shell of what it could have been.

I suppose this is where it "gets political" but the F1 regulations are also attempting to reduce the carbon footprint of the sport. A lofty and worthy goal, but I don't think the cars themselves make up the bulk of the carbon footprint - transporting the cars all around the world does. So how about we make the cars fun to watch again? Improve the carbon footprint of the transport, and don't restrict the cars to try to offset it. Just let the cars be cars! It feels like artificially limiting the amount of food you can feed a champion race horse just to say "We reduced grain dependence across the whole sport!"
Wouldn't you run into the autonomous/not-autonomous problem?

Delegating or not delegating buy power is a binary choice. There's no real middle ground (past "do it securely" best practices).

Or are you looking at this from a centralized revokation lever perspective?

If that, then use the same architecture patterns that enterprise credential stores use -- authorizing credentials only at rest in the credential store, pulled temporarily by automated systems, with credentials rotated regularly.
I don't think it's "creepy". They're just not points of interest. They don't have a label for this Facebook data center, either. https://www.google.com/maps/@41.6649119,-93.5130914,1223m/da...
Whether it's wise or not, many students are using generative AI to solve their homework problems. That's what we have to wrestle with.
And even that, in woodworking there's been three "new" methods of sharpening in the last decade or so which all became trends (and counter-trends); and new tools, new jigs, new tricks pop up all the time, so...
Aside from conventional rate limiting and bot protection technologies, how would you propose protecting a site from being scraped for a specific purpose through technology?

I would argue that there isn't an effective technology to prevent scraping for AI training, only legal measures such as a EULA or TOS that forbids that use case, or offensive technology like Nightshade that implement data poisoning to negatively impact the training stage; those tools wouldn't prevent scraping though.
I'll throw out a VC's perspective on liquidation prefs:

1) I think 1x is very fair and meant to protect investors from bad company behavior. If you didn't have 1x preference, this would be an easy way for an unscrupulous founder to cash out: raise $X for 20% of the company, no liquidation preference. The next day, sell the company and its assets ($X in cash) for, say, 0.9x. If there's no liquidation preference, the VC gets back 0.18x and the founder gets 0.72x, even though all that the founder did was sell the VC's cash at a discount the day after getting it.

2) >1x liquidation preferences are sometimes the founder's fault and sometimes the VC's fault. Sometimes it's an investor exploiting a position of leverage just to be more extractive. That sucks. But other times it's a founder intentionally exchanging worse terms for a higher/vanity valuation.

For example, let's say a founder raised a round at $500m, then the company didn't do as well as hoped, and now realistically the company is worth $250m. The founder wants to raise more to try to regain momentum.

A VC comes and says "ok, company is worth $250m, how about I put in $50m at a $250m valuation?"

Founder says "you know, I really don't want a down round. I think it would hurt morale, upset previous investors, be bad press, etc. What would it take for you to invest at a $500m+ valuation like last time?"

VC thinks and says "ok, how about $500m valuation, 3x liquidation preference?"

The founder can now pick between a $250m and a 1x pref, or $500m and a 3x pref. Many will pick #1, but many others will pick #2.

It's a rational VC offer -- if the company is worth $250m but wants to raise at $500m, then a liquidation preference can bridge that gap. The solution is kind of elegant, IMHO. But it can also lead to situations like the one described in the article above where a company has a good exit that gets swallowed up by the liquidation preference.

3) generally both sides have good lawyers (esp. at later stages of funding), so the liquidation preference decision is likely made knowingly.

Related to #3, if you're fundraising, please work with a good lawyer. There are a few firms that handle most tech startup financings, and they will have a much better understanding of terms and term benchmarks than everyone else. Gunderson, Goodwin, Cooley, Wilson Sonsini, and Latham Watkins are the firms I tend to see over and over.
Many people never move their laptop from their desk.
Sergey Brin seems a bit embarrassed by it.

>“We definitely messed up on the image generation,” Brin said Saturday. “I think it was mostly due to just not thorough testing. It definitely, for good reasons, upset a lot of people.”

Mike Solana, the author suggests he may fire Sundar
https://twitter.com/micsolana/status/1764723032042725531
Complying with the Digital Markets Act
so is it only the website that gone or even the software that we already download and play also gone ? i just finish my daily play on story of seasons and suddenly "X" trending have yuzu and nintendo on trending and i just found that citra also involved of takedown , MANNNNNN what a luck TnT
Abortion in France was already a law, for decades, nothing was added nor removed by adding it to the constitution, and no one in France was questioning that right besides fringe sub 1% parties

So again, either the law is enough, and if it is enough it is enough for abortions, or it isn't enough for abortion, but in that case: which laws are constitution worthy and which aren't ?
Fully agree. Depending on your choices ChatGPT can either enhance of fully remove your learning.
Even for large ML/LLM models, how large is the part of the code that interacts with CUDA? In other words, how much of a moat does nvidia have if a better competitor comes up? My intuition is that the code itself could probably ported in a few weeks, ie if there is a moat, it doesn't consist in the CUDA implementation.
Do you think there is always a positive relationship between production/consumption and quality of life? It seems to me this statement confuses what we should be ultimately optimizing for.
Capture and analyze mobile traffic without Wi-Fi proxy
Traffic analysis is a very important part of mobile application development and debugging, whether it is data mocking or malware analysis. Our most common method is to setup a Wi-Fi proxy on the mobile and proxy the traffic to the MITM server of the desktop apps, such as Charles and Fiddler. But this is not an efficient way.
They stopped communicating with Rapid7. When you stop, you know, coordinating with the researchers they are free to do what they want. Rapid7 likely gave them their entire process, set expectations and coordinated with JetBrains up front. This is sort of an “ethical standard” most firms and security researchers follow. The timeline’s they use and the exact process they follow varies. The key goal is to keep the vulnerabilities public and properly credit the researchers. Coordinated disclosure is an olive branch, so you know exactly what to expect and how to behave. It is generally very reasonable. If you break the terms or spirit of this process the researchers have no reason or real recourse but to release their info whenever they want and feel is appropriate. Don’t break the faith, the researchers are essentially doing you a favor by following this policy. It really is not hard to communicate and act in good faith on both sides. I have coordinated the release of dozens of vulnerabilities. I have definitely disclosed them after companies ghosted us or threatened us hoping to make the issue go away.

JetBrains got cute and cut the researchers out of the loop. Now future researchers will likely treat JetBrains as a bad faith actor and proceed accordingly.
It is mind-boggling that we are at this point.

I understand that reducing buttons has a cost-saving and reliability benefit, but it's unfathomable that core and frequently used controls are reduced to touch screens while emphatically stating that a driver must not be distracted by the screen while driving. I've lost all trust in car manufacturers that do this, it's not just wrong, it's obviously dangerous.
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We're seeking someone with heavy experience in 3D computer vision applications and API-first to be a manager for our engine group.
More discussion a few days ago: https://news.ycombinator.com/item?id=39576200
Powerful Caching in Elixir with Cachex
I can imaging a future where human writers will claim they don't use AI to write their stories while they most definitely are using AI. Kind of like the scourge of natural fitness influencers using gear.
On the basic premise EU is working wonderfully.

It's the longest period in our thousand years history that we Poles have not had to fight Germans.

We have lost maybe even 1/3 of population in wars with Sweden, 1/5 of population in war with Germany.

Poland didn't exist or 123 years under Russian, Prussian and Austrian occupation.

Given that as a baseline, I'm really grateful for the EU.
This is tangential, but that paper has some amazingly good plots for an ML paper.
>and provide the details 30 days after patch is made available.That way it hurts users less.

The bad guys will figure out how to go about exploiting the vulnerability almost immediately after the patch releases, if they aren't already exploiting it. It makes 0 sense and protects 0 people to hold onto details after the patch is made available.
Reliability benefit?