skysight-inc/HackerNews huggingface dataset:
The article has no mention of cancer. At all. What it instead does mention, is studies and a WHO warning that Splenda increases diabetes risk.

It also mentions the ADA was bribed into recommending potatoes to diabetes patients, the one thing those people shouldn't be eating.

This is a fraudulent organization claiming to improve public health, but in reality trading human lives for profit. It's despicable you're rushing to defend them with straw man arguments.
Many of the best engineers have a strong interest in the literature, even if things are not completely understood theoretically. Good engineers provide strong justification for tuning hyperparameters based both on intuition and theory. The same goes with suggesting architectures -- the best people don't guess, but they can debate the theoretical purpose of each element and how tuning it may affect the outcome. If something isn't completely understood, they may code small experiments and/or work with the math to better understand its potential impact.

Beyond this, optimizing models requires a strong understanding of the math behind them. This provides crucial insights, for example that the attention key bias does not affect the attention weights. In industry, engineers might read a paper about a new activation function. They will probably wonder whether there is (theoretical) justification for how it might affect training time or be computationally efficient in the company's architecture. A theorist would be a great fit here.

Some higher-level research could have some commercial application. For example, there are a few papers showing near-LLM performance (for certain things) attained by only searching datasets.

Ultimately, you will be successful if you can find where your skillset overlaps with what the company needs. Sometimes there is a research division which needs exactly what you research. Other times, you may need to work on things that aren't an exact fit but still utilize your skills. But as of right now, it seems that a successful theorist with coding ability would be in demand (e.g. https://www.anthropic.com/research).
With enough context, is this a job that could be replaced by an AI ? Of course there is the question of who will supervise and legal responsibilities.
I have ported multiple tab handler from piro to seamonkey back in the day, I miss xul so much, the browser used to be a very powerful tool
is there an open source equivalent of this? especially the interruption logic?
YES! That was an idea I had a year ago actually! I wanted to lobotomize models, cutting out weights and leaving only functionality that we want. Unlike distillation it would be a much more brutal process.

The idea went nowwhere for the time being, but if I ever get back to it, the project surely will be called Lobotomizer.
Not a fan but i can see a potential link between high demand and a service running in to stability issues yes.
That won't be true for much longer.

The AI Act will significantly nerf the capabilities you will be allowed to benefit from in the eu.
Perhaps men couldn't win so decided not to play.
I guess a queue handles spikes, and is OK for async-allowed operations such as generating a PDF and email it over say loading a web page.

A queue may give you time to scale up too?
So you want to do calculus ? You need algebra. What parts of algebra ? Go figure !

this is one big hurdle in learning math backwards. You discover new missing pieces at every corner. Each missing piece leading to another missing piece.

Learning math from the basics to advanced (as recommended by most) is very frustrating at how slowly you actually develop the math muscle.

At a deeper level, conceptual grasp does not make you good at math, its not enough. You may fool yourself into thinking you "get it" till you try to solve a few exercises. You need to repeat the lower levels enough to make it into muscle memory (which some people refer to as math intuition or groundwork) before embarking onto higher levels that build on it.

So working your way bottom up is slow and frustrating, top down is slow and frustrating. What do you do?

Just keep at it. One key observation for me was that at some point the misery and rabbit hole nature diminishes, quite rapidly. The groundwork of solving all those exercises repeatedly pays off and the next set becomes a little easier. Getting to calculus after spending ridiculous amount of time on algebra is the only way I have known to work.

And this is true for learning progamming too. knowing the concept of loops is essential but, you still can't write efficient code to sort an array. You need to get the syntax and write enough loops and then progress to exercising writing specific sorting algorithms repeatedly to get them into muscle memory.

But there is an inflection point beyond which the same concepts repeat but in different variations and they take progressively lesser time to get a grasp on.

thats just how I've learned math and programming. Also why a large percentage of people just give up hope and accept they just don't have the math gene. Meh.
> Sociology would be an example where math is just the wrong tool for the job.

really? Stronger statement than just saying the tools aren’t there yet.

I also don’t really get the alternative.. surely the phrase “modeling” has connotations of formality and predictive power for any domain, this is desirable, and a “model” should be more of a useful artifact than other subjective interpretations of history (like say an op-ed).

Anyway they do mention complex adaptive systems. But whether that means building a model with it, or just nodding vaguely towards it as generally supporting their thesis, I’m not sure
CHERI enables a rather high level of memory safety. It uses dynamic hardware checks rather than the safe-Rust static checks, which means that existing C/C++ code can often be ported to CHERI C/C++ with minor changes. Of course, as others note, "memory safety" is not a simple single thing, and there are certainly some cases that CHERI C/C++ don't depend on (as noted in this paper by Vadim Zaliva and others in our group). But in examples like this one from another comment:

struct buffer {
char *data;
size_t capacity;
size_t length;
}

the pointer 'data' will in CHERI have to be a valid capability, not just a virtual address, to permit access. It should normally have been instantiated with the correct bounds from the appropriate allocation, separately from the 'length' field, so the hardware will do the right check.
>> They have the same problem as Google, an initial cash cow and not really able to invent something new.

Which I would also add means they chase fads and have to buy their way into these developing markets, hoping they essentially find their own "facebook" to invest in that then hits big.
The PostgreSQL community debates ALTER SYSTEM
I always enjoyed calculus, I thought it was kind of magical and didn't worry too much about where the magic came from. I've known the derivative of x^2 is 2x for nearly 50 years but just found out why due to your formatting correction here. Thanks! Also gratitude for the poster who explained that the fundamental theorem of calculus (i.e. reverse differentiation is integration) is essentially just the calculation involved in going from an odometer reading to a speedometer reading then back again!
>>This work showed that GPT-4 performance is comparable with that of physicians on official medical board residency examinations. Model performance was near or above the official passing rate in all medical specialties tested. Given the maturity of this rapidly improving technology, the adoption of LLMs in clinical medical practice is imminent.

Specifics sub-scores:

>GPT-4 ranked higher than the majority of physicians in psychiatry, with a median percentile of 74.7% (95% confidence interval), and it performed similarly to the median physician in general surgery and internal medicine, displaying median percentiles of 44.4% (95% CI) and 56.6% (95% CI).

>GPT-4 performance was lower in pediatrics and OB/GYN but remained higher than a considerable fraction of practicing physicians, with a median score of 17.4% (95% CI) and a median score of 23.44% (95% CI).

>GPT-3.5 did not pass the examination in any discipline and was inferior to the majority of physicians in the five disciplines. Overall, GPT-4 passed the board residency examination in four of five specialties, revealing a median score higher than the official passing score of 65%.

...so glad I dropped out of medskool.
the hardest part of doing calculus is fluency in arithmetic, algebra and trigonometry.

the most important idea in calculus is often glossed over, weakly presented or omitted entirely: the continuity of the reals. i feel that once this is fully understood, most of the ideas in calculus become intuitive.
Sure but under the current system the 5th still applies in other cases, granted in the context of this thread it was ruled that it does not, but it still went through the courts. OP was wrong because a fingerprint isn't really speech, I'm guessing.
It would have to be defined to begin much earlier, perhaps 26ky ago, when the mass extinctions and geological changes began to happen.
> Do you think using ChatGPT in this situation was inappropriate?

Of course, what ever the bot generated communicates to the human who received that message (and was able to discern the "voice" of the LLM), without words, that the receiver didn't think of it as high enough priority to actually engage in a conversation. The LLM might have gone through the motions, but why on earth would that salesperson think that your report (to whom the feedback was directed) actually means what stochastic parrot barfed out. Frankly, I would also assume the opposite. Using a GenAI communicates, you are not worthy of my precious keystrokes. Or as McLuhan said: The medium is the message.
What's the second axiom?
Some of the references are interesting. "PREDICTING AND PREEMPTING THE CORPORATE HEART ATTACK" (all caps in original, paywalled) looks promising. That's the management consultant view. It's a good question, though. How can you tell in advance when an organization is in trouble? Consider Boeing and General Electric.
Accounting does not capture what's broken. It's possible to capture that info in stable production environments, which is what the Toyota Production System and Deming are all about.
It's not clear what to measure in a more dynamic situation or over longer time scales.

A less apocalyptic question is, how do you tell if a system is stuck in a state well below optimum? What are the risks associated with getting out of that state and into a higher state?
Yeah, more tests are needed. I got some feedback on using KL instead of the token similarity - initial tests seem to show that it is workable (compared to Q8), but not awesomely amazing - will be working on that next week and publishing.

As for treating effort+Mistral as a separate model - I wouldn't do that comparison. The model stays the same, all the weights from it are still being used, just not all of the time - we don't really lose information from the source model.
Whenever I see integrals I think "area under the curve" and when I see derivatives I think "slope of a function"!
There was an interesting aproach to this, in an experimental language some time ago

fn f1 (x, y) #-> // Use C calling conventions

fn f2 (x, y) -> // use fast calling conventions

The first one was mostly for interacting with C code, and the compiler knew how to
call each function.
Not gonna lie though, VR is way better for porn than VHS.
Now I can join the meeting "in a suit" while being out paddleboarding!
That’s basically what super computers have been for the last twenty years: large computer optimized data centers. The main differences in hardware are usually infiniband (and its RDMA capabilities) paired with a really powerful parallel file system cluster. Occasionally they’ll be exotic compute accelerators or lately just variants of the gpus specific to the cluster. On the software side it’s usually slurm managing code that leverages MPI, openMP and CUDA. Having a large homogeneous cluster that has a ~10 year lifespan means that you you have a lot of tuning up and down the stack from specific MPI implementations for your infiniband hardware to optimization tricks in the science code tuned for the specific gpu and cpu models. All of this has gotten even less specialized since GPUs started to take off and those trends have accelerated with ML having the same needs. ML is also prompting clouds to provide the same kinds of hard ware with infiniband and rdma.
https://x.com/afterveil/status/1746168116546093291?s=46
It's a good balance IMHO. I appreciate what they have released.
> After all, MacOS already has some foundation features (such as similar command line tools) borrowed from Linux.

For me this set the tone of the article. I think that the author in more on the "end user" spectrum rather than on the "dev" spectrum. No harm in that specifically, but some things might not be 100% accurate.
Read again, he's very clear in his claim that the GDPR is a 'protection racket' aimed at corporations outside of the EU.

It's obvious that he is running some kind of grift relying on the audience being ignorant of EU law and its application.
I respect that. The reason I left a snarky comment was because the description said "predict the future", which is almost the opposite of 一期一会. I'm trying to think of a tag line that would be more encompassing of what you're getting at... An AI fortune teller to connect you with the moment?

Anyway, good luck
In my current role, we currently have to think about things like holidays across the world to understand if usage patterns are low due to issues or just holidays. Being an engineer at Spotify adds another layer to the usage patterns, namely artist release patterns. I'm curious if they have a team (multiple?) that work on predicting future load based on news/artist tours/release schedules?

All of this reminds me of the TV pickup [0] phenomenon in the UK that involves kettles during commercial breaks, albeit on a longer timescale and maybe less predictable.

[0] https://en.wikipedia.org/wiki/TV_pickup
Yes, he got incredibly lucky that he found an alternative use for his GPU investment.
Yeah, even if they just use LLMs to do all the work, or are a LLM themselves, as long as they can do the work I guess.

Weird implications for various regulations though.
Do you find it surprising though?

Certainly not everyone is in the same place in their learning journey as you. Material on calc, at a university level, is typically going to focus on calc. Yes it is assumed that you have learned the fundamentals before taking that course.

I was in a similar situation as you. If you really want to learn it there's no substitute for skipping over the fundamentals. I did that and did fairly well but it's all long forgotten. Never use the stuff :)
You can build a machine that can run 70b models at great TpS speeds for around 30-60k. That same machine could almost certainly run a 400b model with "useable" speeds. Obviously much slower than current ChatGPT speeds but still, that kind of machine is well within the means of wealthy hobbyists/highly compensated SWEs and small firms.
Action reply on a snes? I use to mess around with this too as a ten year old
Do they really need “free RLHF”? As I understand it, RLHF needs relatively little data to work and its quality matters - I would expect paid and trained labellers to do a much better job than Joey Keyboard clicking past a “which helped you more” prompt whilst trying to generate an email.
As usual, having access to lots of money is the real hack here.

Also, I'm not your lawyer (or even a lawyer). But when someone says something like this....

> Think about the O1 as a fundraising process—it’s storytelling. You’re pitching the government on why they should invest in you long-term. Rather than “ticking boxes” with criteria, you need to think about how to structure the narrative so it’s compelling to the reader. The criteria and evidence, such as letters, support that overarching narrative.

...my spidey-sense starts tingling and I head for the door. The idea that you should "structure a narrative" when dealing with law enforcement (and immigration in particular) seems like just terrible terrible advice of the sort that could seriously mess up someone's life. I have a decent risk tolerance for some things, but this feels like someone telling you to douse yourself with gasoline and light a match[1].

[1] I mean, what's the worst that could happen? You want to be warm don't you?
HN discussion:[0] (278 points, yesterday, 160 comments)

[0]: https://news.ycombinator.com/item?id=40067575
I agree. For me, a person living in Southeast Asia, Prime Video is a great choice - very cheap monthly price combined with a decent number of good movies and shows from Hollywood as well as across the region. Disney+ is cheaper than Netflix but the content is disappointing, unless you have young children who like all things Disney. Personally, I subscribe to Netflix opportunistically, e.g., I'll do so when the latest season of Stranger Things start airing and discontinue after watching the episodes.
A very weird list with only "better command line package management" and "middle-click paste" being obviously reasonable items in it.

> Different desktop environments

Standardized coherent desktop experience arguably is the number-one thing people love Macs for.

> Desktop Cube, wobbly windows

Arguably the most pointless Linux features ever. A perfect example of a feature which exists purely "just for fun" and for no other reason.

> Snap or Flatpak

... are the Linux world's attempts to clone the way apps are managed on Mac.
Yes and this was just on HN:

https://tonsky.me/blog/centering/
What I would like to know here is whether the suggested serving amounts in those countries are adjusted, as well.

Sugar is bad for our health, sure, but it's not like it is rat poison. It gives easily digestible calories and in a product like baby formula, where you have defined amounts of that product to consume every day, "added sugars" in a vacuum does not seem to be such a big problem to me.
He also says he'll be the last to sell Tesla stock
>With multiple wheel vehicles, if you apply the brakes to some wheels and not others, the tires lose traction.

Which vehicles don't brake on all wheels? I can only think of cruiser bicycles.
I experienced this 30 years ago and it still haunts me. In a fascinating way. Such cool creatures.
For real, I used to love the amount of detail they put on bungie.net . It really is still unmatched even today, as far as I've seen. So good <3
> OpenAI’s mission is to ensure that artificial general intelligence (AGI)—by which we mean highly autonomous systems that outperform humans at most economically valuable work—benefits all of humanity. We will attempt to directly build safe and beneficial AGI, but will also consider our mission fulfilled if our work aids others to achieve this outcome.

No current LLM is that, and Transformers may always be too sample-expensive for that.

But if anyone does make such a thing, OpenAI won't mind… so long as the AI is "safe" (whatever that means).

OpenAI has been totally consistent with saying that safety includes assuming weights are harmful until proven safe because you cannot un-release a harmful model; Other researchers say the opposite, on the grounds that white-box research is safety research is easier and more consistent.

I lean towards the former, not because I fear LLMs specifically, but because the irreversibly and the fact we don't know how close or far we are means it's a habit we should turn into a norm before it's urgent.
Source paper (linked): Fast current-induced skyrmion motion in synthetic antiferromagnets https://www.science.org/doi/10.1126/science.add5751
Honestly, I have a similar theory about the Sonic design incident. I think there's characteristics to that incident (the timing, mainly) that make it at least seem suspicious.

My theory is not that it was marketing, but that the horrifying design was an order from above, and the trailer was a maneuver to create blowback against the design.

This is baseless, of course.
Denial isn’t the sole Big River, it seems.
I used it in 1995 and that's how I learned HTML (CSS didn't exist yet).

Today the BlueGriffon Editor[1] fulfills a similar purpose. At least that is what my daughter used in class.

[1] https://en.m.wikipedia.org/wiki/BlueGriffon
That don't work for font that have bounding box disconnected to visual. Like the article just mentioned.

Thus you need canvas if you absolutely need to figure out how bad is the bounding box of given font. Because it's the only way to get pixels in js.
Fine tuning can take a fraction of the resources required for training, so I think the original point stands.
> If you’ve never seen this film, give it a shot.

The atmosphere in the film is quite special, you almost feel like it was made in modern times, just adjusted in post to be black and white.
And that is indeed a service worth paying for. LSEG data set has decent coverage for businesses outside US and Europe, and they are one of the few who offer fairly reliable UBO ("universal beneficial owner") data on top.

They're not cheap, but comparing to the cost of spending double-digit number of hours trying to find the same information in house - you are quite likely to come out ahead.

For those wondering, UBO research is not unlike investigative journalism.
Yes, and for NFL. It’s one of my favorite shared hobbies of ours!
thanks. i tried it and i am underwhelmed. claude.ai sonnet performs better for the few tests that i did.
https://www.facets.cloud/facets-for-startups-2
I imagine it's a given at this point, but I figured it was worth noting that it seems they trained this using OpenAI outputs. Using meta.ai to test the model, it gave me a link to a google search when questioned about a relatively current event.

When I expressed surprise that it could access the internet it told me it did so via Bing.

I asked it to clarify why it said Bing, when it gave me an actual link to a google search, and if this meant it was trained on OpenAI outputs. It said yeah but at this point I think it's just a bit gibberish given that it said that's why it linked to Google.

Screenshot of chat - https://imgur.com/dZglhPY
Drugs hijack a mesolimbic pathway that processes homeostatic need
I'm reminded of an evening fairly early on at Facebook where it took a few minutes to realize traffic had dropped because the Academy Awards were on.
Yes, these are all very good points. You’ve got me awaiting the future of the tech a bit more eagerly.
A friend had a skin transplant — inside thigh to foot, IIRC? it was a long time ago — but I do recall that they told me that the hairs come with the skin, and continue to grow as if they were in-situ.
Did the later remastered collections have these problems? (Genuine question, I'd like to know best options for playing halo games)

Edit , just started the video, I think it goes into this
> Mozilla SeaMonkey still has the HTML editor (and has been updated within a
year!)

+1 to that. I still use SeaMonkey every time I need to edit HTML docs directly. Works great, haven't found anything better. (Admittedly haven't looked too hard for anything better because SeaMonkey works just fine.)
Supabase Storage now supports the S3 protocol
I’d say it’s more analogous to the debate over whether cigarettes or leaded petrol are harmful.
A baby's digestive system is not set up to digest sugars other than lactose for the first few months.
that reminds me of this:

https://www.youtube.com/watch?v=P5ieIbInFpg
It’s a shitty designer that includes cancer et. al. in the spec.
I have been using Seamonkey since when it was called Netscape, but there are so many sites that do not work with it that I been forced to switch to Firefox. I still use Seamonkey for my mail though, I prefer it to Thunderbird.
Why Leaving the US Is the New American Dream [video]
Introduce Tool Intelligence
Haha that's a funny video!
Oh, man, that username is just too perfect for a comment like this.

"Fuck the poor; they deserve it." -Jesus Christ.