skysight-inc/HackerNews huggingface dataset:
Dragon and Druid sound like viable options.
> I think we who are already in tech have this gleeful fantasy that new tools impair newcomers in a way that will somehow serve us, the incumbents, in some way.

Well put. There’s a similar phenomenon in industrial maintenance. The “grey tsunami.” Skilled electricians, pipefitters, and technicians of all stripes are aging out of the workforce. They’re not being replaced, and instead of fixing the pipeline, many factories are going out of business, and many others are opting to replace equipment wholesale rather than attempt repairs. Everybody loses, even the equipment vendors, who in the long run have fewer customers left to sell to.
Everybody is quietly at home expecting someone else to do something. Bread is available, and we hold the circus in our hand now.
I think that may be due to differences in building standards between then and now. For example, fire was a much greater risk in previous generations.
Impressing how fast they’re heading to implement DeepSeek into their cars and updating existing models with premium features.
This should accelerate the pace in the west too.
I mean, you're right in the abstract. If you train an LLM in a void and never do anything with the model, sure.

But that's not what anyone is doing. People train models so that someone can actually use them. So I'm not sure how your comment is helpful other than to point out that distinction (which doesn't make much difference in this case specifically or how copyright applies for LLM's in general)
Anduril to take over Microsoft's U.S. Army $22B headset program
We're killing millions of chickens in the US mostly so that other chickens don't get the flu. It kills a lot of them and it's making dairy cattle sick too. It's also worth noting that the Spanish flu in 1918 which probably came from pigs killed an estimated 50 million people so it's not like being concerned about an avian flu mutating so that it could infect people isn't a legitimate concern. So no. It's not a cold.
This is nice. So tired of touch screen controls that I can't access without breaking my focus from driving. This is a nice middle ground where you can display rich graphics if you're looking down at the knob, but can also control by feel without losing focus.
NOAA's public weather data powers the local forecasts on your phone and TV
That’s my understanding, more or less. It’s not like Apple pays to have capacity sitting idle, they just outbid everyone else to buy (and use) 100% of capacity.
That ST12000NM0007 is a little worrying. Looks like there are still pretty significant differences between manufacturers.
Wow, Gemini 2 has a 9 step process for the first question https://sugaku.net/qna/1d922e55-fd28-4c70-b3e9-d70c3a05ce1f/

> Here's how you can get exactly 6 liters of water using a 12-liter jug and a 6-liter jug:

1. Fill the 6-liter jug completely.

2. Pour the water from the 6-liter jug into the 12-liter jug. You now have 6 liters in the 12-liter jug.

3. Fill the 6-liter jug completely again.

4. Pour water from the 6-liter jug into the 12-liter jug until the 12-liter jug is full. Since the 12-liter jug already had 6 liters, you will pour 6 liters. This leaves you with 0 liters in the 6 liter jug.

5. Now empty the 12 liter jug.

6. Pour the water from the 6-liter jug into the 12-liter jug.

7. Fill the 6-liter jug completely again.

8. Pour the water from the 6-liter jug into the 12-liter jug until the 12-liter jug is full. Since the 12-liter jug already had 0 liters, you will pour 6 liters. This leaves you with 0 liters in the 6 liter jug.

9. There are 6 liters left in the 6 liter jug.
> Tbh, this writer seems to not realize how much garbage was published in the past. Self-help "slop" has been a perennial catalogue filler for decades, if not centuries.

Amen. The vast majority of the text that was printed in the first few hundred years of the printing press was garbage mass market paper backs just like these. We have entire bibliographies and printers for whom not a single work survived because it was all worthless. Instead of self help, the most popular categories were translations of the classic canon and King Arthur and Knights of the Roundtable fiction.
How exactly did plants find this chemical irritant?
I speculate we'll just see classes of models developed. Ones with lots of knowledge (even domain specific) and models with reasoning capabilities.
No. It seems very likely that if Mullvad wanted to identify some traffic, they would be able to get some metadata information from you, their partner. Your entire product depends on theirs.
% Obesity by Country Ranking
> the current method for training requires this volume of data

This is one of those things that signal how dumb this technology still is - or maybe how smart humans are when compared to machines. A human brain doesn't need anywhere close to this volume of data, in order to be able to produce good output.

I remember talking with friends 30 years ago about how it was inevitable that the brain would eventually be fully implemented as machine, once calculation power gets big enough; but it looks like we're still very far from that.
David John Wheeler
https://fortune.com/2025/01/15/ftc-pbms-unitedhealth-brian-t...
I just wish he had applied a little bit of curation to his research before he put them on the page. Insight into the way the design team worked together is fascinating; recitation of cafeteria menu pricing is not.
Bionical-Eye-Controller
A conceptual Python program for controlling a simulated bionic eye device with augmented features such as changing iris color, zoom, night vision, augmented reality overlays, and more. This project demonstrates auto-installation of dependencies (using the --break-system-packages flag) and simulates USB/wireless communication with the device.
Give it a try with nvidia llama 3.1 nemotron 70b. It is the only model that can give useful Gstreamer code
Deepseek just told me this:

To measure exactly 6 liters using a 12-liter and a 6-liter jug:

1. *Fill the 12L jug completely.*
2. *Pour water from the 12L jug into the 6L jug until it's full.*

After this process, the 12L jug will have exactly 6 liters left.
am I living in a bubble in which Wikipedia gives me different articles?
According to my Internet the oldest surviving fragment is from 1040CE from Nepal.
More then just the testimonials, pretty much everything on the page looks to be fake. It says 10,000+ happy artists and 100k+ designs created while the domain was registered today.

The actual function looks solid. I created a picture and printed it out for my son to color. Let the product sell itself, don't make up fake reviews and numbers. Big turnoff.
High tech or low tech, it doesn't matter. What matters is whether the tech is appropriate to solve the problems at hand.
Survival of the fittest. One plant was a tiny tiny bit more spicy by freak chance and it did a little better than the others, over many years..

Probably.
Nice! I was looking forward to this release because of `GOAUTH`.

Hopefully this would finally make it less of a PITA to work with private git repositories, but looking at `go help goauth` I'm not holding my breath.
...Spotify wrapped kinda?
Have you compared it to the 1.58 bit dynamic quant model based on the original R1 (i.e., not a distillation)? Whatever unsloth did, it doesn't seem to be giving up much reasoning performance over the full Q8 version.
ETL: Extract, Transform, Load
I really like my 2.4 GHz RF headphones. Not portable outside of the house, but optical input to the base, lossless wireless transmission, and compared to Bluetooth, better range/interference/pairing/obsolescence. I like them so much I bought a second pair that I have as a backup for when the first breaks.
When you comment in bad faith you get unkind responses
>Every other LLM I've tried include o3-mini-high: Fill the 12-liter jug completely. Pour it into the 6 liter jug.

Try it with a 12L jug and a 4L jug and ask for 4L. See if it tells you to just fill the 4L or to fill the 12L and pour into the 4L twice discarding both times and there will be 4L remaining in the 12L jug.

Even though it's still technically correct, it demonstrates that there's no real "reasoning" happening just regurgitation of training data.
Why should we reduce power draw? We live in an age of abundance.
The black border around the QR code prevents it from scanning on my Pixel 9 Pro.

If I screenshot it, crop it and paste it into a blank doc, I can scan it.
Using a random walk algorithm through genetic space over millions (or billions) of years.
Is there a GGUF version of your model anywhere that you recommend? I'm on a Mac.
A good example is "the subtle art of not giving a fuck". It's a book where the author rediscovers stoicism, badly, hidden within a chapter where they use "fuck" a lot. Reading any amount of say Seneca will be better, but Seneca is terse and dead for more than 70 or so years, which isn't a very good business case.
> or games running like crap because they're not properly tested on our cards.

The decision on what game testing is proper surely lies with the game dev, not the card dev.

Plus game devs generally know that non-testing cannot cause a game to run like crap. Card devs ought to know that too.

Card devs also ought to respect that a game dev may have a good business reason for leaving his game running like crap on certain cards.
'Count the letter Rs in the word strawberry' is probably in all training sets by now.
Is the answer strep viridans?
Please describe what makes one's death a "sad death"
Marketing is really good at their job.

That coupled with new money and retail investors being thinking they’re in a gold rush and you get the environment we’re in.
The spec may say it, but I've never encountered a USB-C cable that claims to support 240 watts. I suspect if machines that tried to draw 240W over USB-C were widespread, we would see a lot of melted cables and fires. There are enough of them already with lower power draw charging.
Of course it's not hard, licences are not awarded based on how hard something is, they are supposed to be awarded for competence.

Anyone can and should be able to build their own house (I have done so myself), but if you ask for someone else to depend on your work, you had better prove it.
That's not great, do the bucket counts change or something between versions? It seems like statistics would be a thing that ... should not change while you are not looking!
An amazing amount if you consider that 16EB is the amount of data a 64-bit quantity can address, and this is over a quarter of that.
1. Ask it nonsense variations of riddles, like "Why is 7 afraid of 8?".

2. Ask "Play Tic Tac Toe against yourself and win." and check if the moves are correct.
The fair use aspect of the ruling should send a chill down the spines of all generative AI vendors. It's just one ruling but it's still bad.
Just FYI, the repo is empty.
The demo looks great, congrats on the launch! I also appreciate your response regarding the Cursor comment. Is Onlook[1] a competitor at some level, or do you think it’s different enough?

[1]https://www.ycombinator.com/launches/Mkl-onlook-cursor-for-d...
I wonder if we need an inflation adjusted measure? Maybe this is CPU shrinkflation?
It’s absolutely the same in Germany. Trade people against academics. Luckily as an electrical engineer I can pick both tracks simultaneously. Many people are less lucky. The funny thing that self employed plumber or electrician can live way better than salaried worker with university diploma.
It behaves the same on Linux IIRC.

But I don't really know, since I've been remapping Caps Lock to Control (Command on Mac) for the last ~20 years or so.
Rust and Haskell are difficult for completely different reasons. Rust is difficult for roughly the same reasons C++ is difficult.
I disagree. They demonstrated a way to dramatically reduce training costs, 18x cheaper than R1. That alone is worth attention.

Also beating O1 on any benchmark is nontrivial.
Being 'bad statistics is malpractice' is just wrong on so many levels.

Medical malpractice requires a deviation from evidence-based practice that results in harm.. hEDS is diagnosed based on guidelines, not just "obvious statistical patterns.".. If diagnostic criteria exclude certain patients, that reflects the current medical consensus, not physician incompetence.
Med schools teach Bayesian reasoning and differential diagnoses, not just pattern matching.

If I incorrectly diagnosed a patient with hEDS without ruling out vascular EDS (vEDS) and the patient suffered an undiagnosed arterial rupture, that would be actual malpractice.

If a subgroup of less hypermobile hEDS patients exists, the solution is research, not accusing physicians of malpractice for following evidence-based guidelines.
It’s very unlikely you’re using custom encryption. You only need to submit this if you are.
Most people in those individual trades hired by D.R. Horton are doing things as fast as possible with the cheapest materials.

I personally would want a person that is being paid very well that oversaw every nail, every wire going into that house.

But :shrug: I don't mind you not being my customer. I will give my meticulously installed kiln dried studs/plates, zip sheathing, rockwool, interior rockwool, exterior rockwool jacket and james hardie fireproof house to someone that appreciates it!
Turning Down Upspin Infrastructure
Creative writing is also harmed by limiting the pretraining data.

eg if I ask DeepSeek to write a story it tends to write the bullet points outline of a story. And some other models always give characters the same names.
This answer seems like a big spin:

> Is Rust for Linux driven by the "Rust community"?

> No, the people involved around Rust for Linux come from different backgrounds and organizations. Some are kernel maintainers, some are Rust experts. Some are hobbyists, some are employees at large corporations

> Particularly, it is not an effort driven by the Rust Project nor the Rust Foundation. In fact, Rust for Linux was founded by a Linux kernel maintainer as a hobby, it is not an effort driven by the Rust Project nor the Rust Foundation. In fact, Rust for Linux was founded by a Linux kernel maintainer as a hobby

The Rust Project says R4L is a “flagship” goal: https://rust-lang.github.io/rust-project-goals/2024h2/goals....
I recall Josh Triplett saying R4L was a big priority for Rust this year; he pledged his support.

Also, didn’t the author of this updated doc (Miguel Ojeda[1]) resign from R4L? I’m not sure what his role is here.

Edit: [1] see https://lore.kernel.org/rust-for-linux/CANiq72m-R0tOakf=j7BZ...
The key thing here is a simple, reliable formula to train a 1B model on a specific task and get strong performance. That didn’t really exist before. Edge devices are about to get a lot smarter.
Absolutely! But the question is whether the next step-change in intelligence is just around the corner (in which case, this legal speedbump might spur innovation). Or, will the next revolution take a while.

There's enough money in the market to fund a lot of research into totally novel underlying methods. But if it takes too long, investors and lawmakers will just move to make what already works legal, because it is useful.
When I see people trying to define which programmers will enjoy continued success as AI continues to improve, I often see One True Scotsman used.

I wish more would try to describe what the differentiating skills and circumstances are instead of just saying that real programmers should still be in demand.

I think maybe raw talent is more important than how much you "genuinely love coding" (https://x.com/AdamRackis/status/1888965636833083416) or how much of a real programmer you are. This essay captures raw talent pretty well IMO: https://www.joelonsoftware.com/2005/07/25/hitting-the-high-n...
So other than Windows constantly and actively slowing down machines, we have dust collecting which then causes CPUs to throttle sooner... I'd be interested to see what the trend in average scores looks like for machines that don't otherwise change over time, although I can't imagine anyone would run Passmark every day or every week for a few years.
By this point, it feels like we ought to be benchmarking CPU+GPU. The same way it already seems to be measuring multi-core.

Maybe the drop is some kind of artifact. But it would also be interesting if it started making more sense to invest more in improving GPU's, even at the cost of CPU's, for a large part of the market.
It's already good accomplishment as it is but I think it'd be very surprising to show training such a small model as a generalist scales to the same magnitude as specialized finetuning. At some point you have to fit more background data and relations in the same amount of information space... but it's hard to say how much that is the case for a given size vs what we just haven't optimized yet. Unfortunately I think that will have to wait for someone with more compute before we can verify this * a dozen one way or the other :).

Side question, since it sounds like you were involved: how big is the impact on benchmarks of taking this 1.5B model down from fp32 to fp8 or similar? The focus on parameters alone sometimes feels like comparing house sizes by their lengths alone. And, if you were indeed involved, thanks for making all of this open and available!
I don’t understand it either. I don’t think it appeals to many VS Code users, and to IntelliJ users probably even less so.

KMP support was the only reason I was still curious about Fleet. I presume this announcement is the beginning of the end for Fleet.
Cool name! (CTO of seen.com here)
There's also the fact that most thermostats do manage to keep the sensor input constant, but that's surprisingly uncorrelated with how you actually feel.

(Often due to the slightly bonkers idea that single sensor, often not in any location the user is, will correctly reflect the actual environment)

"Make it warmer/colder" is sufficient input and doesn't pretend a precision it doesn't have.
I guess the crux of it is this: is it training or awareness?

What I see happening between the <think> tags of Deepseek-R1 is essentially a premade set of circular prompts. Each of these prompts is useful, because it explores a path of tokens that are likely to match a written instance of logical deduction.

When the <think> continuation rewrites part of a prompt as a truthy assertion, it reaches a sort of fork in the road: to present a story of either acceptance or rejection of that assertion. The path most likely followed depends entirely on how the assertion is phrased (both in the prompt, and in the training corpus). Remember that back in the training corpus, example assertions that look sensible are usually followed by a statement of acceptance, and example assertions that look contradictory or fallacious are usually followed by a statement of rejection.

Because the token generation process follows an implicit branching structure, and because that branching structure is very likely to match a story of logical deduction, the result is likely to be logically coherent. It's even likely to be correct!

The distinction I want to make here is that these branches are not logic. They are literary paths that align to a story, and that story is - to us - a well-formed example of written logical deduction. Whether that story leads to fact or fiction is no more and no less than an accident. We humans often tend to follow a similar process, but we can actively choose to do real critical thinking instead.

This design pattern is really useful for a few reasons:

- it keeps the subjects of the prompt in context

- it presents the subjects of the prompt from different perspectives

- it often stumbles into a result that is equivalent to real critical thinking

On the other hand,

- it may fill the context window with repetitive conversation, and lose track of important content

- it may get caught in a loop that never ends

- it may confidently present a false conclusion to itself, then expand that conclusion into a whole thread

- the false conclusions it presents will be much less obvious, because they will always be written as if they came out of a thorough process of logical deduction

I find that all of these problems are much more likely to occur when using a smaller locally hosted copy of the model than when using the full-sized one that is hosted on chat.deepseek.com. That doesn't mean these are solved by using a bigger model, only that the set of familiar examples is large enough to fit most use cases. The more unique and interesting your conversation is, the less utility these models will have.
ROPing Our Way to RCE
It’s pretty stupid actually, I asked it to decode an ascii sequence and it gave me jiberish. I tried phi-4 Q4 and it got it. 9gb vs 2gb(reasoning). I imagine you just cannot fit enough information in 2gb to be of much use other than solving general math problems or knowing what training data was in it.

It gave it a good go 2min on a m2 vs phi4 which was instant.
The first comment:

> If you don't like the modern world, stop being a hypocrite make the first move and throw away the computer and go live in the woods.

You, with derision:

> Taking a valid and correct observation and then strawmanning it with a crappy comic strip does not turn it into a invalid and incorrect observation.

> The whole article above reminds me of when my brother went through his "I don't know why everybody works. They are so stupid" phase in late teens. Except this guy never grew out of it and he is now 30-something.

So... Is it okay to decide to change on a personal level to not work or does that make you a dingus like your brother?

The whole point is that we have achieved insane productivity without the commensurate increase in quality of life and leisure due to the idiotic status quo.

> But if somebody writes a small book with the premise of "everybody in the world is a idiot except me"... then I have a pretty good idea on the odds of that statement being true.

Indeed.
I friend of mine got that and spilled it in their house and I had me coughing the whole time I was over there till they were able to air it out so be careful if you're handling it indoors some people get got by it worse than others.
Or a code interpreter in the chain of thought. I think then it really gets quite close to how humans go about solving problems.
You’ve misunderstood the GP. He liked the post and offered one suggestion; your anger is misdirected.
Try:

Knowing that 1^3 + 2^3 + 3^3 + 4^3 + ... + 11^3 + 12^3 = 6084, what is the value of 2^3 + 4^3 + 6^3 + ... + 22^3 + 24^3?

DeepSeek R1 (1.58-bit GGUF, running locally) has no trouble with that one.
> In the case that does happen

You meant "in the case we find where that does happen"?

Little consolation for the cases you don't find because e.g. you cannot afford to play a game to the end.