skysight-inc/HackerNews huggingface dataset:
Building from scratch wastes a ton of time and I'm a big fan of starting with some working parts and customizing from there. I think with what's going on with AI it makes sense to use python more because all the researchers love python and make examples available through python notebooks. Then your tech stack is less split amongst many languages and there is less complexity and you can hire developers for cheaper. Ruby devs are fairly pricey because they all working in silicon valley-esque well-funded startups. There is a Django boilerplate provider that's really good https://www.saaspegasus.com/. The guy behind it, Corey, is very responsive. All in all, it's probably not the worst thing to use Ruby, as long as you use less weakly-typed javascript :P
In 5G and 6G, Biden is starting to make Trump look good
> Has anyone actually experienced this mythical "networking at the conference"?

Yes, but for me It Depends. I'm not great at starting up conversations with people I don't already know, and it makes me uncomfortable. So whether or not I'm at a conference specific to my (fairly niche) field or not makes a huge difference. If I am, I tend to socialize quite a bit as I know a bunch of people even if a bit tangentially. But when I'm at a more standard software conference I tend to keep to myself and utilize "the hallway track" a lot less.
From what we were told this morning, this is a purely Red Hat decision not influenced by IBM, primarily intended to reduce our spending and save cash in light of the increased cost of money caused by rising interest rates.

Roles affected will be "general and administrative" (apparently this is a GAAP - Generally Accepted Accounting Practices - term), and folks directly involved in developing or selling products (my interpretation: software engineers and sales) are safe.

Source: am Red Hatter, opinions/interpretations are my own.
My understanding is Elon never cared about the institution of a blue check mark and is taking them for a nice infusion of cash with the intention of phasing it out.
Key escrow and other three-way encryption algorithms exist. You wouldn't want to use them in any normal circumstances, but there's no technical reason why you couldn't. A key for you, your recipient, and your friendly government agent.

Very few people actually write cryptographic code, and even fewer write code that is safe to use. I doubt many people will bother with some kind of messenger hook/overlay keyboard to supplant the native messenger encryption. After all, in some countries SMS/MMS is still in use and nobody seems to care about encryption there.
I took me surprisingly long to convince myself the author was correct: the answer is 48 because there's 4x as many hens and 4x as many days: 3 x 4 x 4 = 48. The "wrong" way to solve this problem is to compute hen-laying in terms of hen-egg-days, and then scaling.
Agreed, the specialist I saw recommended Airsense (I have the 10) with the water tank (and I also got the heated tube, highly recommended) above most everything else for the machine, but the mask is actually a Philips respironics which are the most comfortable. They are all intercompatible.

Been using for about 5 months now and it's been great
I agree the effect is probably minimal but it is not likely to be zero.

The jury is still out, but there is certainly evidence that a person’s spoken language influences at least memory.

I don’t remember the details but there have been studies of speakers of languages where there are more names for colours (e.g. Russian with blue, Hungarian with red) are more accurately able to recall a colour that they have seen previously than a speaker of a language without such a distinction (e.g. English).
This! FIRE as fast as you can so you’re not at the whim of this class of people (management class, broadly speaking). There is no security, no one is coming to save you except you. I speak from experience.
I’ve been in similar gaming groups that had plenty of people in their 50s. While they would center around an older game like, say, Battlefield 4, the members played newer shooters as well. Further, older players probably have more disposable income for in-game purchases, even in a game highly popular with younger players.
Conspicuous consumption. To see and be seen as one of the group.
Twitter gives fake Disney account verified status
It's worth pointing out that right-wingers say precisely the opposite and can produce plenty of evidence showing the BBC's left-wing bias.
I can understand why we shouldn't assign more work to fast finishers. Should we recognize their performance as quick finishers, shall we let those times pass? How do manage the extra time he/she gets?
Yeah anything that needs specially compiled or optimized binaries is an enormous pain in the python world. You really want conda for those cases.
Mathematics is not "any arbitrary sequence of numbers".

Mathematics is the study of fundamental patterns that are present between them. Mathematics is the abstraction itself.

Banning encryption is like government banning video compression because it could be used for criminal activity.

It's not the data itself being banned, it's the abstract math it is made from.
Fishing Boats Can’t Stop Running over Undersea Internet Cables
There are certain species that are only pollinated by mosquitoes. Orchids for example.
https://archive.is/EvZol
In a way, UNIX does have automatic resource managament: when a process is killed, its memory is returned to the system, file descriptors are closed, etc...

In contrast, (IIRC) on the Amiga the OS didn't have per-process resource tracking, e.g. memory leaks would persist after a program was closed or had crashed.
> I'm curious, around when do you think that changed?

The smell of change appeared more clearly in the run-up to Brexit. Certainly post-Brexit I would say it is very much evident.

> And was there a specific story they reported on (or didn't report on) that really solidified the change for you?

To be clear (as per my Radio 4 example cited above), it is not necessarily a case of "reported on / did not report on", it is frequently more a case of bias / lack of impartiality, again as nicely exemplified by my "two hardcore Brexiteers fight over Brexit" example[1].

However, I could also give you many examples of "reported on/did not report on". Perhaps one of the most well known is Lady Mone of House of Lords fame. She is/was subject to various investigations regarding supply of PPE during CoVID.

For a long time, Lady Mone's investigations were widely reported in all mainstream media (tabloids, broadsheets, other mainstream TV/Radio news ... you name the place, it was reported there).

But the BBC ? Nope. No mention on TV/Radio news, and for a long time a search for "Mone" on the BBC News website yielded exactly zero results.

Even today although you can now find a small number of mentions on the BBC website, you'll have to go looking on other mainstream sources for the actual detail.[2]

[1] https://www.thenational.scot/news/23289638.bbc-slated-insult...
[2] https://www.thenational.scot/news/20107509.bbc-refuses-say-h...

EDIT TO ADD (because I can't reply to the @Veen directly)

> Leftists think it's an establishment mouthpiece run by the Tories.

Well....

I see how they could feel that way when the recently appointed BBC Chairman is a chap who appears to have more than a few ties to Boris Johnson[3].

[3] https://committees.parliament.uk/committee/378/digital-cultu...
Bizarre to see this YouTube love-fest in the comments. Lately I've been finding their recommendations a disaster of click-bait shorts that seem like a desperate attempt to compete with TikTok. The worst part is that the algorithm is way too sensitive so if you ever accidentally click on something, you're guaranteed to be force-fed a fire hose of that for life (good luck trying to convince the algorithm otherwise).
This is comedy

From one review: “ One paragraph starts with "As an AI language model I can't....". Unfortunately we don't have an AI who can correct a book written by an AI. Fortunately I can send it back.”

Sauce:

https://www.amazon.com/product-reviews/B0BWVH451G/ref=acr_dp...
> Audit your customers.

I know Oracle has a reputation for this, but I didn't realize IBM does as well.
Another website worth watching for this kind of thing is https://spaceweather.com/
You can work around this by chunking the data using a sliding window. Take the first X amount of sentences that fit into the token length and summarize. Now slide your window of sentences so that you still overlap just a bit with your previous selection. Summarize that information. Continue until you have a bunch of summaries for your text. You can then pass that back into the model for a more concise summary of the summaries.
While it's technically possible to use Telegram safely, I wouldn't put it in the same category as Signal. Even WhatsApp has a better underlying cryptographic system.
I've done it here and there for cheaper conferences. I refer to them as my nerd vacations. But they're also far more targeted and more likely to have high quality talks, not the larger "trade show" type conferences.
8x A100 80GB are $12/hour or so on Lambda Cloud. If you get lucky enough to snag capacity.
> Nearly all applications of Generative AI APIs by their very design and value proposition externalize cost to society

But they promise to maximize value for the individual. Which works in what is called an individualistic society.
> Also doesn't AWS have a history of Microsoft style EEE

AFAIK (but I'm far from knowing about all examples), no, they have a history of taking open-source software, forking it out of the control of the creators, and extending it there without bothering to sync the changes back.

It is hostile to people that want to gain anything from their software, but it is not against the license.
I guess youre not really seeing the actual benefits of LLMs.

Let's say I dont "learn it". I would have to make the _same_ mistake 120 times for me to actually make it worth it to take the time to "learn" it myself.

I'd figure someone somewhat smart, will look at this error and after the 2nd or 3rd time asking GPT, will see a pattern.

Its amusing how people become so reductionists with LLMs.
'_Annectodal_': "I once used a chinese backup-restoring software, cos it was the only illegal copy i found that time (wayback), searching for this specific 'warez' (closed-source software in such important areas like backups) and wonder after restoring some lost .txt-files that they were translated into traditional chinese... About what i got after translating it back again... you may 'wonder'" (-;
There are also multiple countries
What? Essentially no US factory is paying less than $15/hour. Like $20/hour is more common. And they have to pay benefits. That's more expensive than most of Europe.

In Mexico you would be lucky to make $5/hour.
Not powered, but the next room over is acceptable for a solar flare.

The issue would be that wires start getting induced current in them ( https://en.wikipedia.org/wiki/Geomagnetically_induced_curren... ) that arcs and shorts out the device.

However, if you've got a backup tape there's nothing from the current that will flip the bits on the tape itself.

There are good reasons to have the backup be off site (other physical calamities) - but the aurora isn't going to flip any bits on a backup. At worst, it will destroy the machinery from a surge from the grid and an extremely powerful one may destroy the machinery from arcing in the device itself (this would be extremely powerful)... but the media itself is fine.
There is a whole industry called "Low Content Books (on Amazon)". In short, this resembles hosting a somewhat successful blog.
This argument doesn’t land for me.

It’s like saying that Math kills people because Math is used to build bombs. Capitalism is an economic system, not a social system. There are human beings in charge of corporations doing the killing, polluting, and so on. Those individuals are responsible.
There's only one left but shout out to Strange Loop for talk quality. I've found it's less useful in terms of direct practical application to a normal person's work day, but they consistently have talks that give me a lot of food for thought.
It is the same, yes. Right now the way I see it is that we are off-loading noise generation from humans to AIs; it's not that noise didn't exist before, it's just probably going to come more frequently and in a less-recognizable way.
There is a visual illustration in the article. I thought it might be useful for understating why it's 48.
Not really bad per-say. More like a passing space weather event. They are common events, especially when coronal holes turn to face Earth every 27 days or so. It can interfere with GPS timing. My neighbor had a GPS tracked geo-fence dog collar and it was behaving oddly yesterday.
So, the future is now!

Now anyone lazy enough (to even not remove the phrase "As an AI language model I can't..." from the generated text) can "write books". And these "books" will be fundamentally plagiarism and a bunch of trivia by design.

Isn't that wonderful?

It certainly is wonderful!
Can't pass by without making a public service announcement about the average speed example: don't compute integrals using the calculus definition of Sum(f(x_i) * delta). Look up quadrature or numerical integration methods instead.

Although it is true that you can approximate the average speed by taking an average of instantaneous speed measurements, that's usually a very bad way to do it in any real world situation. Numerical difference values are always noisier than the underlying quantity, sometimes to the point of being unusable, so of course if you can just read off the quantity you want directly (total difference over time), you should do that. But even if you can't, you should use a proper integration method instead of the calculus definition.

I have seen the Sum(f(x_i) * delta) calculation in a lot of real-world code. It has bad convergence properties, bad errors when the function has large derivatives, and bad performance when the data has noise. Some of the code I've seen produces garbage results, or has thousands of function evaluations when you need, like, four. "Quadrature? I think I heard that before, but I don't remember what it means."

In summary, please don't compute derivatives as (f(x_i+1)-f(x_i))/delta, or compute integrals as Sum(f(x_i) * delta), and especially, please don't do the first immediately followed by the second. Which also happens. Look up numerical methods instead.

This has been a public service announcement.
See also: Einstein Ring [0], where a light source passes 'through' a strong gravitational source which refocuses the light spreading out, and the Einstein Cross [1], similar, but where the light source (a quasar) passes a gravitational source and shows up as four points of light "due to the elongated shape of the lensing galaxy and the quasar being off-centre"

[0] https://en.wikipedia.org/wiki/Einstein_ring

[1] https://en.wikipedia.org/wiki/Einstein_Cross
I agree that it's exciting to move toward a mathematical approach to characterize what can, and what can not be learned by a DNN!

Maybe someone else has the knowledge to give you some more precise answers.

As far as I understand we need to differentiate between higher order relations that can be learned by message parsing and those that cannot.
Some higher order relationships can be represented in a graph (of pairwise relations) and, furthermore, can be learned by iterating out from a focal node through the paths (think centrality). GNNs can learn those.

But GNNs can't learn all Graphs because not all such relations are amendable to message parsing. So, not all higher order information contained in a graph are learned by GNNs.

In the present case, the authors seem to make the point that there are higher-order relations (say, node-set) which are also not representable by a graph (or a collection of graphs).

I actually do not know whether that is obviously true. For instance, hypergraphs can be modeled as a collection of graphs. But if the claim stands, then we'd need topological deep learning to move further. Otherwise, like you say, it is maybe a more general framework to understand information processing in DL - or more efficient to learn node-node or node-set information.

Either way, I have not yet quite figured out how Category Theory and Topological DL relate to each other (each generalising Geometric Deep Learning).
> Java was perceived (quite rightfully) as a C++ with the rough edges filed off.

Java has only familiar surface syntax.

Semantics has almost nothing common with C++. Different object model, memory model, execution model, ...

That's the genius of both Java and Javascript. Make it look familiar without being one at all.
Agree on SSMs: they look promising. They're on my list of "things to explore more thoroughly." I've done very little with them so far. I'm still making my way through the related papers, trying to get a superficial but accurate/intuitive understanding of these models.
The only software-developing organization I know of that truly values institutional knowledge is the U.S. Dept. of Defense.

Civil-service rules make it very difficult to fire most employees anyway, but that dovetails nicely with an appreciation for institutional knowledge.
If you want to learn more about this business model, search for "Low Content Books (on Amazon)".
This makes sense in isolation, but the way that Elon has approached managing Twitter has turned the verified status into a symbol of allegiance with one side or another. So now being verified doesn't just communicate something about your account, but about your political ideology and whether you agree with Elon's decisions or not. It's this aspect that's a bit of an ethical hot potato here.
Very fair point. I guess the part of me that keeps wanting folks to consider is sort of analogous to perhaps guns or other kinds of weapons.

My strong belief is that SOMEONE is absolutely going to be using this stuff. It's going to be a thing, a big and very influential thing. Might as well get ahead of it and understand it and possibly use it for good?
The checkmark means "paid $8", not "verified".
Git LFS is very slow for lots of files. It is also inefficient space-wise and bandwidth-wise if you update big files.

The integration with Git is also very clunky since it's based on smudge/clean filters (that were really meant to update templates in your text files or change line endings, not download big files).

The server options are also limited and not easy to deploy. Not a problem if you use a central repository on the cloud, but a non-starter if you want direct sync between devices.
I started my career in the early nineties. It's different now. Not sure if worse or better. Different.

What I enjoyed about the 90's is that there was still plenty of meaningful work implementing published algorithms. I remember for example, coding Delaunay triangulation, our own Quartenions etc in C++. These days you just download and learn an API to do it.

What this means is now you can build comparable stuff much quicker. It's all been implemented and you're mostly gluing libraries.

Gluing stuff is a lot less fun than doing it from scratch and you learn much less but it's the only way to stay competitive.

If you want to build something rapidly to show off though, today it's much easier.

Web development seems to suck more with every year passing. I wasn't all that into it in the 90's as it was very nascent and primarily for text and images due to bandwidth limitations. But VRML was mighty impressive if you used it on a LAN.

Web devs seem to reinvent wheels more than other types of devs. Everything is hailed as a breakthrough in productivity that subsequently fails to materialize. They impress each other with how concise the framework du-jour makes the code, forgetting that troubleshooting ease is much more important.

Troublueshooting stuff was much easier in the 90's even with the simple tools. Not many systems were distributed. It was considered craziness to build distributed software unless you really needed it and had a massive budget.

Everyone builds distributed systems now, whether they need it or not.

AI/ML is amazing today. None of this was possible in the 90's we had nothing approaching the crunching power required to produce decent results. So a lot of ML work was deemed a failure even though it's being exonerated now.

I think with the resurgence of ML the software engineering field is exciting again. Things were rather boring for the last two decades when hipsters kept reinventing mundane stuff only to go back to tried tested and true (vide resurgence of SSR or RDBMS).

Overall, I think the 90's were fun. More fun than what followed. ML/AI might make things fun again.
There has been a total of 126 cougar attacks, 27 of which were fatal in North America in the last 100 years. I wouldn't worry too much.

https://en.m.wikipedia.org/wiki/List_of_fatal_cougar_attacks...
I really hope the next generation of developers start using GPT instead of string.replace() haha

Looking forward to the billable hours speeding up webapps and lowering GPT costs :)
Great, I'm going to read a book. Recognizing and respecting them is the best way to do this, it really is an art of motivating team members.
I was around then, and I was/am interested in things like this, and I paid zero attention to these things because I didn't know about these things, because things like these just weren't well known like they are now.

there weren't entire categories of Wikipedia articles about things like this. there weren't widespread communities welcoming new users or lots of YouTube videos explaining everything and getting viewers excited.

yes, that was the time to be into Inferno and projects like it, but the entire internet was a different place.

Maybe I just wasn't looking in the right places for this stuff or maybe I was too invested in other things, but I recall these things being terribly hard to penetrate even if you did find out about them.
World military spending up to an all-time high
Welcome to life under Meta, Google, Disney, Microsoft, Amazon, Salesforce, SAP, should i go on?

They're pretty much last to the layoff race, and with smaller numbers
I suspect you’re trying to be sarcastic and/or facetious, but:

Both ideally sure. The more backups and more locations the better. Diminishing returns pretty quickly but why not if the data is important.

Electromagnetic energy from the sun only has a chance of damaging equipment and only some of the bits of that equipment will be affected. You could have two servers in the same datacenter where one gets hit and the other does not. Or even two drives in the same chassis. And even then, it might not be all the data on that drive.

Of course no security is absolute (learned that early from my uncle that owned a convenience store at a lake: He spent extra on doors, locks, windows, etc and someone drove a truck through the brick wall to rob the place). Same here: if a solar event happens that would wipe out all of your onsite and offsite servers “on the surface” then there is a much bigger problem.
If he's that desperate for money why would he phase it out?
Some tree was chopped to print this garbage. Think about it.
Oh no, that's not all.

There are also fake positive reviews.

Now everything is really great!
Except they've made a big deal out of letting everyone know that verification isn't a thing anymore. (EDIT: or actually, by now it is a thing again, but not with a blue checkmark, but a golden one. So this is even more clearly pretending that the account pays for blue, not it being verified!)
Devise does integrate with SSO, but you still have to set everything up yourself for all the main providers which takes a good bit of time with a lot of custom frontend work needed and a bit of extra backend as well. It would be nice to have SSO out of the box without the need for a bunch of manual setup which was kind of the promise of this bullet train thing.