skysight-inc/HackerNews huggingface dataset:
Google Wants to Track Your Digital Fingerprints Again
> the data wasn’t accurate enough to identify what a supplier was actually manufacturing

how did the LLM help with that challenge?
Why not just study a bunch of different things to Master's level then? Learning something genuinely new seems like it has a much lower return to effort.
I would even say that Ollama is a step back. For example llama.cpp supports vulkan, which is a huge gamechanger for consumer grade hardware. Ollama does not support vulkan, eventhough it's probably fairly easy to do so.

If you care about running efficiently on your hardware, then llama.cpp is they way to go, not ollama.
I suspect the real concern is there would be a push to relax the restrictions once the industrial facility has been built. Astronomical observatories have faced such problems in the past, to the point where research goals had to be fundamentally altered or where they ceased to be research facilities.

That said, if the goal is to reduce the lighting to the point where it has no impact, one has to ask: what is the point of having lighting at all? I suppose lighting could be restricted to indoor use only, but most commercial operations will expect some outdoor lighting.
Four cores, each with more computing power then existed in the known universe when I was born.
I know what I was doing at 14, and it landed me in the NET.LEGENDS FAQ.
Attention models learn what to pay attention to.

It's been found that data that begin with "Wikipedia:" are automatically weighted higher by language models during training, completely unsupervised.
> If this is true

It's not true. It's a blatant lie, as the embedded video in the article proves.
You really can't take anything OpenAI says about this kind of thing seriously at this point. It's all self-serving.
Just because such a thing is beyond your experience doesn’t mean it’s rare or unimportant. I see this attitude in students who have worked mostly on toy (assigned) problems, but at least they are aware this is the case.
Getting Organized with Todo.txt
Both those indexes are complete frauds. Believe your eyes and your soul instead of some fake numbers from the rulers. Or at least believe your wallet, if you are more cynical than emotional.
Dynamic semantic VSLAM with known and unknown objects
There are an endless number of budget phones with essentially identical specs to this, yes.
Likely one of the earthquakes in this tsunami is Twitter firing 80% of employees and then coming out of it financially better.

If Jason Fried did it, people would laugh it off as an outlier, but the richest man in the world did, and so he's a genius and every other CEO will try out the same magic idea and hope for the same improvement. This is... going to lead to a tsunami of some kind.
I created an account just to respond to this. I’ve been using keybr.com to learn to type on my very different ergonomic keyboards. I paid for keybr and spent about 30 minutes a day on it. I can type regular English on those keyboards great now. Every time I need to write code, though, I slide it aside and go back to the MS sculpt I’ve been using for 13 years now. I’ll be trying this out. Thanks.
I really like the game!

looks like the keyboard doesn’t work that well on mobile though (iOS). You need to press the keys below the key you want to type (eg if I want to type a T, I need to press G for it to work)
For truly locked-down environments that's the way to go. You can only be sure the code will always be the same if it's 100% local and offline, or verifying signatures somehow.
Sure. But building a stable platform out there?
Because we are not allowed to program in another language that 'most' programmers can't understand immediately.

We are cursed to use the lowest common denominator of choices of programming.
Android? Meh…
Wouldn't you agree though that from YC Head to being the driving force of OpenAI was largely due to his own merit.

In fact, he started spending less time at YC and more time at OpenAI. At that time, OpenAI had no clear path to becoming the unicorn it is today, and YC was definitely better from a career standpoint. Instead, he went all-in on OpenAI, and the results are there for everyone to see.
the quote in question was not coming from the journalist that "bashed out some text" tho but from a team member. Thanks anyway for lashing out at the profession in general coz who do they think they are, right. Gotta know your limits, right?
If you're coaching a girls' team and you advocate that boys who say they are girls should be allowed to play on the team too, then that should be grounds for dismissal from the coaching role, as you'd be disadvantaging the girls on the team that you're supposed to be supporting.

This would be an entirely warranted "punishment for opinions" because of your failure to adequately safeguard young female athletes.
The only group under low pressure, free to do anything they want in Academia are tenured profs who have established themselves well or grad students who don’t care at all about remaining in Academia (and presumably have NSF fellowship or similar so that they don’t need to listen to their advisor either). Everyone else needs to grind, profs without tenure are arguably under the highest pressure, PhDs who want to stay in academia have high pressure etc. If your prof is tenured but not established and is struggling for grant money, even he is under high pressure to publish and win grants, something I learnt the hard way. The grant acceptance rate is what, like 20% these days.

My 2 cents, you will be more likely to encounter creative coders who are passionate about a field in the right industry team than Academia. Unfortunately getting into the right industry team is also a grind, and you likely won’t get there right out of undergrad, but within 10 years, if you put effort and grind, you can get there. I think it’s better odds and more fun than going to academia, but your mileage may vary.
This is where Microsoft has the advantage, all those Teams calls can provide context.
The advantage of JSON for streaming is on serialization. A server can begin streaming the response to the client before the length of the data is known.

JSON Lines is particularly helpful for JavaScript clients where streaming JSON parsers tend to be much slower than JSON.parse.
> Ask yourself, how many of those talks in day 1, have accompanying code? is it even 25%?

57 out of 93 papers (61%) published at POPL 24 have an artifact available. Note that this may also be automated proofs etc, it's not necessarily "running code".

But I also think focusing on POPL as a representation of the PL community isn't entirely fair. POPL is the primary conference focused on type systems within the PL community. It's a niche within a niche. Conferences like OOPSLA, ECOOP, or ICFP are much broader and much less likely to be so focused on mathematical proofs.

[1] https://dl.acm.org/toc/pacmpl/2024/8/POPL
The cores aren't slow so much as software was designed for more powerful devices. It's a shame, really.
Sure didn't and this is probably the fundamental misunderstanding the author had too. You can receive all the frequencies (this is easy and what you and the author are claiming is all you need to do). You cannot listen to all of them at once as the title suggests because it is impossible to demodulate it for all frequencies at once.

Nuance and understanding are important before you credulously say "well they say they built it so what they say must be true"
You can verify signatures of JS and CSS files to make sure they are only loaded if they are exactly what you expect them to be by using the "integrity" parameter, see https://developer.mozilla.org/en-US/docs/Web/Security/Subres...
Bloomberg may be the last company to be concerned about free information, thinking about their five digit annual fees for the terminal.
Show HN: Vision, PDF reading and Python
"built upon a blend of synthetic datasets, data from filtered public domain websites, and acquired academic books and Q&A datasets"

Does this mean the model was trained without copyright infringements?
TLDR; Mullenweg made a poorly received joke/trolling post on Reddit on Christmas. It could have been perceived as reconciliatory
/self deprecating or trolling depending on your perspective. That was the straw in the camel’s back that led the sustainability chief to resign. Mullenweg then disbanded the entire sustainability team which he announced by taunting them on slack.
I have heard a few people mention issues but I haven’t been able to reproduce nor understand the scope of the issue. Any more details you can share? You’re getting HTML but JS or CSS assets aren’t loading, right? What status and headers do you see for static assets?
> American regulators seem to prefer regulating a fewer # of large banks over many smaller banks

I'm sure the remaining banks prefer that too.
> Another key area this device hasn’t cut back on is its security. Quarterly security updates for 2 years² will help keep everything safe and sound.

That's a criminally short support period, and a great way to produce even more e-waste.
Great essay. This is 100% right about the technical side, but I think it misses the “product” aspect.

Building a quality product (AI or otherwise), involves design and data at all levels: UX, on-boarding, marketing, etc. The companies learning important verticals and getting in the door with customers will have a pretty huge advantage as models get better. Both in terms of install base, and knowing what customers need. Really great products don’t simply do what a customer asks, but are built by taking to a ton of customers over and over, and solving their problems better than any one of them can articulate.

It’s true we will need less and less custom software for problems. But it isn’t realistic to say the software wrapper effort is going to zero when models improve.

Plus: a lot of software effort is needed for getting the data AI needs. This is going to be a huge area - think Google maps with satellites, camera cars, network effect products (ratings), data collection (maps, traffic), etc.
Executing more bloat, than all of the code that existed when you were born
I am making software for myself to learn, and to help my kids. I am using AI to essentially make A LOT of language exercises. It's really, really good at that. And learning is a lot more fun if you're creative with prompts.

I made javascript for a range of question types (things like fill-in, multiple-choice, ...) and have AI use that to e.g. generate short stories where you have to complete the verbs. Or replace some english words with german ones ... that sort of stuff.

Oh, and any time I need either tests or do something to a large range of variables, do what needs to be done to the first variable, copy over (using the reference) the list of fields, comment out the list of fields, and ask AI to suggest what to do. Usually only needs 1 or 2 changes.

And yes, I've noticed the hallucination. If you ask AI to correctly do a scatter-gather parallel processing in Go ... it's incredible how many errors it makes and it's infuriating how you have to explain every one of it's errors again and again. You have it output a basic structure, because that's still fast, and then rewrite the whole thing. I think it still gains me a bit of time ... but I see the point.
Actually both are a problem. We got reflectors + bike helmet laws, and little else.

At a minimum any vehicle going 15+ MPH should be making enough noise to get people’s attention.

Personally I’d like to see insurance and licensing requirements on any e-bike with more than 50w of assistance. Because constantly going moderately faster means dramatically more danger as KE = V^2. So going a little bit faster and slightly less in control can be a lot more dangerous to others.
The Cortex-A53 is certainly a respectable processor within its design constraints. It is from 2012, and I think it is either the smallest or the second-smallest implementation of AArch64 that Arm have designed. It is very power-efficient, and that was the design goal. You definitely can make an SoC that only has “efficiency” cores, and it can even run Android, but putting it in a smartphone indicates that pure manufacturing cost is your only design consideration.
I think you're suffering from some survivorship bias here. There are lot of technologies that don't work out.
Whether it's a beach of copyright law is what the court cases are to decide. I wouldn't bet either way.
Bummer, I can’t reproduce. Could you share more details?
You tell me if for any definition of "beneficial to humanity" that all or most Ph.Ds would fit that definition presumptively/intrinsically.

I chose arbitrary fields that I suspected most readers of HN wouldn't be in, be familiar with, or necessarily esteem just to make the case more obvious. For example, a Ph.D in dance.

There are lots and lots of PhDs in all kinds of things. You can get a Phd in videogames, food hygiene, librarianship, gender studies, ancient greek, theology.

I am sure they are (mostly) worthwhile, and I'm not knocking any of them.

I don't see how they would, by default, be seen to benefit humanity. Some small number might. A very small number. Possibly an extremely small number.

According to one random website there are over 70,000 new PhDs every year.

That's a lot of assumed benefit to humanity. Or.. is it?
Almost all my books are pdfs so I just load them in the reader and then navigate using the spacebar. I mostly focus on headings, asides highlight, the first and last lines of each paragraph, the figures. The goal is to familiarize myself with the structure of the book and some of the concepts, so I tend to skip examples, stories, and techniques. It’s about 3 to 15 seconds for a page, but I can linger on a section I like.

As for explanations, they tend to be contextual. So if someone tells me they have issue with time management, I can briefly explain the gtd method. If someone tells me about some habit they’re trying to follow, I advise to use the atomic habits principles. I also have a few WhatsApp groups spanning my interests, so I can share there too. I keep the explanations short and expand if asked.
A drop in remote worker will still require their work to be checked and their access to the systems they need to do their work secured in case they are a bad actor.
https://hbr.org/2024/07/u-s-commercial-real-estate-is-headed... it could be retarded ad bit, not avoided.
> R&D are costs which a company needs to pay to get a vehicle on the road. Whether the car, as a whole, is making a loss or not depends on whether it can pay for the R&D costs over its lifetime.

You’d think this “101” information would not be needed to be said here, but here we are having to explain it.

> At least in the EU expected EV growth was much larger than actual EV growth.

We should also try to quantify things, because using terms like “much” in italics when it comes to EVs has been so misused that people don’t trust it anymore. We were told that they are much heavier, but then this turns out to be as little as 10-15%. We were told that they lose massive range in the winter, but it can be the same ballpark of 10-15%.
Ford predicted more growth than they got because they are selling a shitty product.
macOS No Longer Ships with Emacs
weird targeted regions. I thought those phones would be mostly sold in the poorest of the poor regions, not the richest nations of the Commonwealth.
I wonder what else he is lying about ?
"With nearly 900 people moving to Florida each day ..."

Over 800 people in Florida die each day.
> are those places not filled with the most horrible vultures on the planet?

Why do you think this?
You’re arguing about highly specific cases while the vast majority of institutions get on with the job of educating large numbers of students and doing what research they can.
I don't think it's that binary. We've had a lot of progress over the last 25 years; much of it in the last two. AGI is not a well defined thing that people easily agree on. So, determining whether we have it or not is actually not that simple.

Mostly people either get bogged down into deep philosophical debates or simply start listing things that AI can and cannot do (and why they believe why that is the case). Some of those things are codified in benchmarks. And of course the list of stuff that AIs can't do is getting stuff removed from it on a regular basis at an accelerating rate. That acceleration is the problem. People don't deal well with adapting to exponentially changing trends.

At some arbitrary point when that list has a certain length, we may or may not have AGI. It really depends on your point of view. But of course, most people score poorly on the same benchmarks we use for testing AIs. There are some specific groups of things where they still do better. But also a lot of AI researchers working on those things.
Interesting that many people take this as a further prof that Ehrlich was wrong, when actually he was unlucky. This "bet" doesn't further our understanding of how anything works, and the article probably should drive the point across more forcefully. The bet itself is useless to tell us anything about "the long run". In the "long run" everyone is dead, so your lifetime isn't enough to predict a trend. You could have seen all your life an indicator heading in one direction, die, getting revived 200 years later, and the trend vanish, because someone discovered a better way.
Agreed, this would be a hard no and makes me think if feature updates will be on an even shorter lifecycle.

The about us page even states "We make phones that last for years" as their company quest[0].

[0] https://www.hmd.com/en_int/about
Revenue or profits per employee is a good start.
I wouldn't call their electric division a success if they're writing off nearly 2 billion dollarydoos in investments

https://www.theguardian.com/business/article/2024/aug/21/for...

about $6,700 per EV sold in 2024.
He's making the ecosystem generally unstable and there are a lot of businesses that depend on that stability.
https://www.salesforce.com/ap/agentforce/
Along the same lines: https://assethunts.itch.io/.
> > "There are two genders." The belief comes from watching birds and bees.

> Nature has many examples of physical gender not being straightforward; egg tempreture determining development in crocadiles and other reptiles for one.

Temperature-dependent sex determination results in offspring of one sex or the other, so how does this refute the observation across species that there are two sexes? Please explain your reasoning.
He's been doing so much more: https://gist.github.com/adrienne/aea9dd7ca19c8985157d9c42f7f...

Again, I hold no sympathy for Silver Lake, but I hope they fuck him up good.
> but I won't pretend that anyone would really notice

I've got a /24 that I obtained back in the Wild West days of the early 1990's, when all you had to do was send an email form and a few minutes later you'd get one assigned. I haven't used it in over 20 years now, but nobody has ever come to take it from me.
Maybe a first phone for kids?
This assumes that the AI bros care about building useful products. They don't for the most part, they care only about building a startup that can plausibly get VC funding. So what if in five years your LLM on the blackchain app fails, you got to blow throw a few million dollars over a few years going around to conferences and living the high life.

That's a success in anyone's book.
> That's a criminally short support period,

No. Sincerely, GCHQ.
He himself clearly showed it's a lie as he admitted on Threads that he started said team. Utterly bizarre.
Takes away jobs from Americans and exploits cheap Indian labor.
> not the richest nations of the Commonwealth.

Aren't there any poor in Britain ?
i started lemmy with a programming instance, as it's a bit more focused on what i want to see. on android i use an app 'Sync for Lemmy' which makes it a little easier when i want to branch out into viewing all of lemmy.

honestly, any platform these days is going to need a lot of filtering to cut out what you don't want to see

https://programming.dev/
HMD is Nokia's successor-in-spirit
Expensive devices turns to ewaste in shorter time frames for reasons other than support. This is a poor metric to pick on.
Lamport's rationale is that after an architect designs a building, the builders may still put electrical sockets in the wrong place and make other mistakes. But that's not a reason to start construction without a plan at all.
Toniebox Hacking – How to get started (2022)
> Texas is dry and hot as a rule

Brownsville and Houston would like a word… (Texas is a huge state and coastal Texas is not dry.)
It looks like it was originally just a channel on Slack, that eventually evolved into a “team” without Mullenweg paying much attention to it.

The Sustainability agenda , quoted by the article, appears excessive to me as well - and it resonates with me why Mullenweg is asking for a different approach.

With the dramas going on, shutting down the channel was a dick move , though.
And it's even worse

> ²From the global launch date of HMD Key.

So if you buy it in 12 months time it'll only recieve 1 year of security updates.

How long do you reckon this will be on the market for?
If this works, then why is tidal power not more widely used?
> …Mullenweg threatening to physically dismantle their booth in the middle of the show

This is crazy if true.
I feel like the author glosses over some nuance in the point he is trying to make and his conclusion doesn't incorporate the nuance.

The nuance is that even though AI researchers have learned this lesson, they are still building purpose built AIs because it's not possible to build an AI that can learn to do anything (i.e. AGI). Therefore, building on top of an existing AI model to meet a vertical market demand is not that crazy.

It's the same risk when building on any software platform. That is the provider of the platform may add the feature/app you are building as a free addition and your business becomes obsolete.
Never in history? Not in feudal Europe? Not in Egypt under the Pharaohs? Never?

I really doubt that...
> could be a libre fork of the project

They should call it PressWord.

Then get a ton of free publicity when Microsoft sues them.
- https://web.archive.org/web/20110117190122/http://wpblogger....
Like a raspberry pi 3?
I can only second this after having advised a few students from bachelor to PhD level. The ones who do well are (usually) the ones who are genuinely excited. Not only about the thing they're doing, but in general. It really helps getting over the lows.

Furthermore, do not underestimate the importance of sheer luck. Exaggerating a bit, deep learning was just another subfield of ML, until GPU-powered DL really took off and made the researches behind the most fundamental ideas superstars. This is not a given, and it might take years or decades until it's really clear whether you're making an impact or not.

I wish you the best of luck, InkCanon, and stay excited!