skysight-inc/HackerNews huggingface dataset:
This problem is only going to get worse. for my thegreatestbooks.org site i used to just get indexed/scraped by google and bing. now it's like 50+ AI bots scraping my entire site just so they can train a LLM to answer questions my site answers without having a user ever visit my site. I just checked cloudflare and in the past 24 hours I've had 1.2 million bot/automated requests
I kinda trust
https://aider.chat/docs/leaderboards/
https://www.bizjournals.com/sanfrancisco/inno/stories/news/2...
google is selfish
> has anyone ever attempted image -> html/css model?

I had a discussion with a friend about doing this, but for CNC code. The answer was that a model trained on a narrow data set underperforms one trained on a large data set and then fine tuned with the narrow one.
The problem of 'model collapse': how a lack of human data limits AI progress
Repeated a few times: [https://news.ycombinator.com/item?id=40909407]

Your usual anti-regulatory screed.
unless distilled
Indeed. Today's advantages are all about steering air around the car, since most teams have access to wind tunnels now.
Not sure when this story took place but now you have riders who WANT the tan lines.
Google is selfish
The last dictator buisness model is always to demand exitfees from the hell on earth you unleashed.
Thanks, any ideas why it's not possible to build a generic eval for this? Since it's about asking a set of questions that's not public knowledge (or making stuff up) and check if the model says "I don't know"?
As I understand it, like 1 year stability. Some of the isotopes we have discovered on the shores have a half-life of around a minute already.
> this is peer reviewable

It's not peer-reviewable in any shape or form.
For some time, we have been at a plateau because everyone has caught up, which essentially means that everyone now has good training datasets and uses similar tweaks to the architecture. It seems that, besides new modalities, transformers might be a dead end as an architecture. Better scores on benchmarks result from better training data and fine-tuning. The so-called 'agents' and 'function calling' also boil down to training data and fine-tuning.
This kind of nit is not worth picking, imho. Jumping off a bridge doesn’t kill you; hitting the ground or water does. But not always.

So is jumping off a bridge not the cause of death? Should we say blunt trauma?
Yes, Tom Boonen was ill-suited for going up an 18% grade.
surely firefox is the more interesting example, since they have orders of magnitude less alternative revenue?
You can apply additional static checks to Wasm, e.g. control flow analysis, and reject programs without obvious loop bounds or unbalanced locking operations. Or you could apply dynamic techniques like tracking acquired locks and automatically releasing them, or charging fuel (gas). The latter is quite common for blockchain runtimes based on Wasm.
They own a non-exclusive worldwide right to it. You own the copyright, they have a license to use it however they see fit.
While I agree with you, have you found anything related to how you would essentially ration goods in a system where AI could provide and everything was free?
Have you experienced the corruption issues mentioned in the original article?
How could anything be positively predicted by gender?
More seriously, selection effects should be much stronger than gender, age and ethnicity, and yet there should still be some correlation in one direction or another, wish there were power and confidence values given
What if sponsors competed to provide the standardized bikes?
I guess they need that IPO to happen sooner
>“replication crisis” were small-effect-size social science experiments that fundamentally weren’t that important outside of popular science news.

I don't know that this is accurate. Some of these make their way to large-scale public policy, or give bona fides to people who craft far-reaching policy. This includes changes to 401k allocations to car-insurance rates and other mundane, but consequential policies.

The truth is most of science is not important outside of popular science news. So we shouldn't be surprised that the bulk of replication crises are also in the same category. Claiming this means the replication crises is not really impactful may be a case of base rate neglect.

It's also important to note that your example of medical replication is a relatively highly regulated area, where most other science is much less so.
Compared to chat bots of even 5 years ago the answer of two is still mind-blowing.
> however this progress is still worth it if we can deploy it to improve millions and eventually billions of people's lives

Has there been any indication that we're improving the lives of millions of people?
My bad, I directly linked to the C file instead of the project here:

It is a program that given a model file, tokenizer file and a prompt, it continues to generate text.

To get it to work, you need to clone and build this: https://github.com/trholding/llama2.c

So the steps are like this:

First you'll need to obtain approval from Meta to download llama3 models on hugging face.

Go to https://huggingface.co/meta-llama/Meta-Llama-3.1-8B-Instruct, fill the form and then go to https://huggingface.co/settings/gated-repos see acceptance status. Once accepted, do the following to download model, export and run.

huggingface-cli download meta-llama/Meta-Llama-3.1-8B-Instruct --include "original/*" --local-dir Meta-Llama-3.1-8B-Instruct

git clone https://github.com/trholding/llama2.c.git

cd llama2.c/

# Export Quantized 8bit

python3 export.py ../llama3.1_8b_instruct_q8.bin --version 2 --meta-llama ../Meta-Llama-3.1-8B-Instruct/original/

# Fastest Quantized Inference build

make runq_cc_openmp

# Test Llama 3.1 inference, it should generate sensible text

./run ../llama3.1_8b_instruct_q8.bin -z tokenizer_l3.bin -l 3 -i " My cat"
lol! Producing academic papers for future training runs then.
>I didn't see people explaining why this was ridiculous.

Because of how it affects priorities and incentives.

E.g.: as of 2024, CrowdStrike didn't implement staggered rollout of Rapid Response content. If you spend a second thinking why that's the case, you'll realize that rapid and staggered are literally antithetical.

>CrowdStrike say of the update that caused the crash: "This Rapid Response Content is stored in a proprietary binary file that contains configuration data. It is not code or a kernel driver."

Well, they are lying.

The data that you feed into an interpreter is code, no matter what they want to call it.
Were any air traffic control systems affected, or just the computer systems of various airlines?
idk man i bet you five bucks and a handshake it's just going to play out like the existing startup grift.

There's an established player with institutional protections, then a scrappy upstart takes a bunch of VC money, converts it into runway, gives away the product for free, gradually replaces and becomes the standard, then puts out an s-1 document saying "we don't make money and we never have, want to invest?" and then they start to enjoy all the institutional protections. Or they don't. Either way you pay yourself handsomely from the runway money so who cares.

The upstart gets indexed and has an API, the established player doesn't.

The upstart is more easily found and modular but the institutional player can refuse to be indexed to own their data and they can block their API to prevent ai slop from getting in and dominating their content.
I see... I'm a little out of my depth, but I did see that Meta has some documentation that talks about fine-tuning using LoRA and QLoRA, and at a glance it sounds like its doable on consumer hardware. Are you familiar with those? Am I misunderstanding? https://llama.meta.com/docs/how-to-guides/fine-tuning/
That is chatting, but it will not change the code.
reminds me of time an AI startup offered me a $50 gift card to do something for them. a $50k contract would have been more appropriate. I told them to take a hike (diplomatically worded.)
Outlaw it so you don't regulatory resources. This is about companies dynamically setting (increasing) prices based on the demographics of the user. This is anti-market activity.
I don't understand what you're getting at, how does that relate to what I said above?
Ask HN: Will Online Prediction Markets Continue to Grow?
CrowdStrike blames a test software bug for Windows wipeout
I'm not sure anyone is asking you to take it at face value or implicitly trust them? There's a 92-page paper with details: https://ai.meta.com/research/publications/the-llama-3-herd-o...
Designing a self-service installation experience for Hybrid SaaS
True, but the question is why they can keep getting away with that.
I have no idea what the potential compatibility issues might be with mobile. This has only been tested on PC. Any way to provide debugging info?
The first airline where women can request not to sit next to men
When Rust's ecosystem was booming, the JS/npm way of a myriad small libraries was viewed as superior. I think that there have been dozens of articles pre-left-pad about why it is good and why it's the future.

I don't quite blame them, remembering how Python's ecosystem tried to mimic Java back in the day, how PHP tried, consciously or not, to do the same.

I'm just wondering what the 2024-2025 dominant fad is going to look like.
> the only thing you can compete on is how many parameters it takes and how cheaply you can serve that to users.

The problem with this strategy is that it's really tough to compete with open models in this space over the long run.

If you look at OpenAI's homepage right now they're trying to promote "ChatGPT on your desktop", so it's clear even they realize that most people are looking for a local product. But once again this is a problem for them because open models run locally are always going to offer more in terms of privacy and features.

In order for proprietary models served through an API to compete long term they need to offer significant performance improvements over open/local offerings, but that gap has been perpetually shrinking.

On an M3 macbook pro you can run open models easily for free that perform close enough to OpenAI that I can use them as my primary LLM for effectively free with complete privacy and lots of room for improvement if I want to dive into the details. Ollama today is pretty much easier to install than just logging into ChatGPT and the performance feels a bit more responsive for most tasks. If I'm doing a serious LLM project I most certainly won't use proprietary models because the control I have over the model is too limited.

At this point I have completely stopped using proprietary LLMs despite working with LLMs everyday. Honestly can't understand any serious software engineer who wouldn't use open models (again the control and tooling provided is just so much better), and for less technical users it's getting easier and easier to just run open models locally.
maybe you could just delete the messaging app that receives text messages? though if you're not pon an unlimited plan, maybe you'll still get charged for them?
I am using the broad definition of bots to include large numbers of accounts controlled by small groups of people to influence online discourse.

Between those bots (for nefarious, mundane, or marketing reasons) and previous attempts at automated bots, “broad” internet discourse was already ruined. Now people recognize it. This will have the effect of pushing communities back to smaller sizes, I think this is a good thing.

People shouldn’t have trusted all the things they read online from untrusted sources in the first place.
Not only are Marvel movies slop, they are very concentrated slop. The only way to increase the concentration of slop in a Marvel movie would be to ask ChatGPT to write the next one.
Any pitfalls with python or C/C++ i should be aware of? Agree that a large labview project is quite tricky
As of the time of writing there are 8 search matches in this thread: 1 from you, the rest from Colin (CEO of said company).
this is so inspiring. thanks for posting.
Not all Marvel films are slop. But, as a fan who comes from a family of fans and someone who has watched almost all of them; lets be real. That particular film, really and most of them, contain copious amounts of what is absolutely slop.

I don't know if the utility is worse than an LLM that is SOTA for 2 months that no one even bothers switching to however - at least the marvel slop is being used for entertainment by someone. I think the market is definitely prioritizing the LLM researcher over Disney's latest slop sequel though so whoever made that comparison can rest easy, because we'll find out.
Fitbod might do the trick. Thanks! The availability of equipment was a difficult thing for me to incorporate into a fitness program.
My town almost has zero renters - something like 5-7%. Most of those are accessory dwellings or STR for the lake in town. Very low property tax (paying $1200/year on a $400k 2k sq foot home with 5 acres). Shares a school district with 4 other local towns/villages.

The developer/advocates for this initiative tried to sell residents on "local businesses need employees..." - Sorry, I don't give a shit. If you can't hire people, pay them more + offer better benefits. Building "affordable" houses so you can import minimum wage worker populations that also benefit from state welfare/ebt/insurance is not good policy.
This is so wild that it must be a prank.
But if it's real, then I guess whoever is in charge of CrowdStrike's PR is as incompetent as their CTO.
That's exactly it. The $20 is not an assessed value of the code; it's to establish consideration. $1 would have been legal. It's legal to make asymmetric contracts that benefit one party more than the other, just not contracts that are completely one-sided. They probably did $20 just so it wouldn't seem quite as insulting.

Anytime you see stories of "[insert name of rich CEO or politician] takes salary of only $1", that's why. They can't work literally for free, or the rest of the contract becomes nonbinding.
One of the best product feedback comments I've seen on here and I've been lurking for a long time. Nice.
No, it is basically gambling except arbitrated by untrusted third-parties.
If they kept their API open then by now the entirety of the site would be ai slop that was built with chatgpt and launched with the api.

Then again most of what that site does is just blend and regurgitate the information that's currently on it anyway.
Source code in a vacuum is still valuable as a way to deal with missing/inaccurate documentation and diagnose faults and their causes.

Raw training datasets similarly has some value as you can analyze it for different characteristics to understand why the trained model is under/over-representing different concepts.

But yes real FOSS should be "open-build" and allow anyone to build a test-passing artifact from raw source material.
"Any contract requires consideration"

I am not a lawyer and I don't understand this phrase. But many legal systems require that a contract is at arm's length.
The "physics PhD" is also posting fake reviews on his website...
Dropping cash for Netscape/Mozilla is the big one.
A big difference you're missing is the I-95 corridor is linear, so you have huge pockets of density all close together along just one single highway / train line, which makes it easier to connect than randomly spread out. Philly is kind of a podunk city for the northeast yet it is denser than metro London, which is arguably one of the top 3 cities in the world. You are kind of proving my point!
PhD students are in training, and replicating a published result is a great training exercise. PhD students ARE paid. But this work won't be prioritized by their PI unless it's also a requirement of the program.
Perhaps Crowdsrike has been compromised and this was a test run?
I really dislike reading website that take over half the screen and make me read off to the side like this. I can fix it by zooming in but I don't understand why they thought making the navigation take up that much of the screen or not be collapsable was a good move.
I've just found this for the exact same reason, for 2-10 sets. The gradient descent is done client-side (Tensorflow.js):

https://www.deepvenn.com/

I've stress-tested it with ~5 sets around ~50k items, comes back in seconds, well under a minute.
Pirate Bay is probably not the most optimal analogy, more like Anna's Archive imho [1], individually offered by web property scrape runs compressed into a package, maybe served by torrents like this Academic Torrents site example [2].

Scraper engine->validation/processing/cleanup->object storage->index + torrent serving is rough pipeline sketch.

[1] https://hn.algolia.com/?dateRange=all&page=0&prefix=false&qu... ("HN Search: annas archive")

[2] https://academictorrents.com/details/9c263fc85366c1ef8f5bb9d... ("AcademicTorrents: Reddit comments/submissions 2005-06 to 2023-12 [2.52TB]")
You can view RAG as a bigger word2vec. The canonical example being "king - man + woman = queen". Words, or now chunks, have geometric distribution, cluster, and relationships... on semantic levels

What is happening is that text is being embedded into a different space, and that format is an array of floats (a point in the embedding space). When we do retrieval, we embed the query and then find other points close to that query. The reason for Vector DB is (1) to optimize for this use-case, we have many specialized data stores / indexes (redis, elastic, dolt, RDBMS) (2) often to be memory based for faster retrieval. PgVector will be interesting to watch. I personally use Qdrant

Full-text search will never be able to do some of the things that are possible in the embedding space. The most capable systems will use both techniques
That would make each API call cost at least $3 ($3 is price per million input tokens). And if you have a 10 message interaction you are looking at $30+ for the interaction. Is that what you would expect?
Except: Meta doesn't sell AI at all. Zuck is just doing this for two reasons:

- flex

- deal a blow to Altmann
If you iterate the game, it’s obvious. I, as the responder, control the proposer’s income. Extend to infinity with knowledge of iteration and you reach symmetry between proposer and responder.
I use Unpoly instead of HTMX and vanilla js for the rest.
This is the greatest. Who authorized this redemption strategy? Please walk them to the door. If it was the CEO - I'm sure they are already figuring out their exit.
Show HN: I made a collection of digital planners for Goodnotes
Thanks, sorry, I commented before getting my facts in order. Comment still stands as applied to CrowdStrike.
There's a new setting in Cloudflare to block AI/scraper bots. https://blog.cloudflare.com/declaring-your-aindependence-blo...
Does anyone have pictures of the new xAI GPU cluster in Memphis?
Watch out for "work-for-hire doctrine" erm... assumptions.

Last time I looked work-for-hire law only takes effect if there is explicit mention of the term "work-for-hire" in the contract, otherwise it's not "work-for-hire". And I have never seen a contract actually mention "work-for-hire".

Do current employment contracts state "work-for-hire"?
I think the direct action of a person taking their idea and thoughts and going through it many times (making changes / updates / fixes) fits better than eating something. however, I do think you still some form of validation data to ensure these are good changes.

However, I do get the spirit of the article, that as more information generated online is done by LLms, the validity and use of the output decreases
Both still compute FP16 gradients. It comes back to the original point that Mac is just going to be too slow even on 8B model.
I think their desktop app still runs the actual LLM queries remotely.
> It seems increasingly apparent that we are reaching the limits of throwing more data at more GPUs

Yes. This is exactly why I'm skeptical of AI doomerism/saviorism.

Too many people have been looking at the pace of LLM development over the last two (2) years, modeled it as an exponential growth function, and come to the conclusion that AGI is inevitable in the next ${1-5} years and we're headed for ${(dys|u)topia}.

But all that assumes that we can extrapolate a pattern of long-term exponential growth from less than two years of data. It's simply not possible to project in that way, and we're already seeing that OpenAI has pivoted from improving on GPT-4's benchmarks to reducing cost, while competitors (including free ones) catch up.

All the evidence suggests we've been slowing the rate of growth in capabilities of SOTA LLMs for at least the past year, which means predictions based on exponential growth all need to be reevaluated.
I think the whole point of a type fully understanding the constraints of your data suggests it would ideally.

Typescript is able to do this with strings when using templates.

type Suit = "C" | "D" | "H" | "S";
type Rank = "A" | "2" | "3" | "4";
type Card = `${Suit}${Rank}`;

const club = "D";
const ace = "A";

const aceOfClubs: Card = `${club}${ace}`;

Even though I have not declared the club or ace as a Suit or Rank, it still infers the Card correctly in the last line. This is a stronger form of typing than what you are settling for where 1..100 doesn't know its own range.

This is the difference I'm referring to.
Regarding paper tape, our first home computer (this was in the mid-to-late 70's) had a paper tape reader and punch. I do not miss paper tape as a storage medium, but I have to say the little punched-out dots were fun to use as confetti at high school football games.
burn n’churn until you find one, then cry when they eventually leave or retire.
are there cases of anyone doing that and being allowed back?
Two features that may help in bigwav:

1) You can add more timestamps by adding paragraphs with enter.

2) You can playback at any word by highlighting it and pressing space. You can also cut with right click on the wav ui.
You can always find something to be unimpressed by I suppose, but the fact that this was fixable with plain english is impressive enough to me.
What exactly is doing the validation?
Mistral forgot to say which benchmark they were using for that chart, without that information it's impossible to determine what it actually means.
> bing probably has the money to reach a deal, smaller companies without monopolies is less likely, and that's the problem.

Reddit can charge smaller companies less money. So if there's a problem, again, the problem is 100% with Reddit.

Google is absolutely blameless here. You may not like Google, and you can certainly blame them for plenty of other things. But in this situation, literally all of the blame is with Reddit for deciding to remove their content from all search engines unless they pay. Reddit didn't have to do that. Google didn't make them do that.

Reddit did this. Not Google.
Why use msys2 over WSL?
We do. It can take months and months of interviews to find them though. Which might be why.
It was later reduced to 4 cents, and later overturned.

https://www.tcpalm.com/story/news/local/st-lucie-county/2022...

All involved very split juries - so I think the low amount was kind of a compromise by the jury in each case.
Non sequitur? I never said that.

Good venues include main track NeurIPS, ICML, ACL, e.g.

Nature is notorious for publishing PR pieces that don't reproduce, and their ML theory publishing has been quite poor. They do pretty well on things like AlphaGo, materials science, or weather modeling because it's more in their wheelhouse and the results don't require a deep understanding of info theory or ML practice.
Totally. I wrote about this when they announced their dev-day stuff.

In my opinion, they've found that intelligence with current architecture is actually an S-curve and not an exponential, so trying to make progress in other directions: UX and EQ.

https://nicholascharriere.com/blog/thoughts-openai-spring-re...
I can't imagine that it's much to look at. Once you've seen one warehouse filled with 1u server racks, you've seen them all.