skysight-inc/HackerNews huggingface dataset:
Gaussian Splatting creates an "approximation" of a 3D scene (captured from a video) using hundreds of thousands (or even millions) of tiny gaussian clouds. Each gaussian might be as small as a couple of pixels, and all these 3D gaussians get projected onto the 2D image plane (fast in GPU) to realize a single image (i.e. a single pose of the video camera). These gaussians are in 3D, so they explicitly represent the scene geometry e.g. real physical surfaces, and an approximation of physical textures. When a camera blurs an image, the physical surface / object gets blurred across many pixels. But if you can reconstruct the 3D scene accurately, then you can re-project the 3D gaussians into 2D images that end up not blurry. Another way to view the OP is that this technique is a tweak to the "sharp images only" Gaussian Splatting work from last year to deal with blurry images.

The OP paper is cool but isn't alone, here's some concurrent work: https://github.com/SpectacularAI/3dgs-deblur

Also related from a couple years ago, using NeRF methods (another area of current 3D research) to denoise night images and recover HDR: https://bmild.github.io/rawnerf/ NeRF, like Gaussian Splatting, seeks to reconstruct the scene in 3D, and RawNeRF adapts the approach to deal with noisy images as well as large exposure variation.

In terms of Gaussian Splats vs GenAI, usually GenAI models have been trained on a prior of millions of images so that they can impute / inference some part of the 3D scene or some part of the input images. However Gaussian Splats (and NeRF) lack those priors.
Judging from the pettiness of the negative comments against Tile, I have to assume it’s the single greatest product on the market! Also, it appears your comment is being suppressed, because the age and number of replies should put it higher, but it’s now buried hours later.
We'll likely get straight to the point AI actions or answers will be quietly cherry picked among sponsor-approved ones. People is going to trust AI, just like most did with television and the Internet; pretending that AI won't be polluted by advertising would be foolish. There's just too much money at stake.
I'm not him, but the Manhatten project cost ~$25 billion dollars and didn't have access to today's physics knowledge or computer-aided design capabilities.

There are a lot of countries that can match $25 billion in expenditure - Musk spent almost twice that on Twitter - and the real cost is probably lower. We've also got a lower-bound on the difficulty of producing missiles based on what North Korea can do.
I was in the location data space. These guys got out completely. It was a big loss to the industry since they had great coverage. They definitely weren’t lying about that.
Speak to some illustrators or voiceover artists - they're talking in very bleak terms about their future, because so many of them are literally being told by clients that their services are no longer required due to AI. A double-digit reduction in demand is manageable on aggregate, but it's devastating at the margin. White-collar workers having to drive Ubers or deliver packages because their jobs have been taken over by AI is no longer a hypothetical.
What makes a good REST API?
Large Language Models in Containers Locally with Podman AI Lab
The motor you linked, and what they are using, is not direct drive. That motor has a 1:6.33 integrated gearbox.
Ruby is such an ugly monstrosity of a languages; proudly flying the crunchy fried meme of “developer productivity”
Median tenure of large cap companies is like 5 years. Those CEOs are financially incentivized to raise stock value. It's not hard to imagine that many, many executives are motivated to maximize profits even if it hurts the company in the long run. That's not even a matter of opinion. Of course half the CEOs are above the median, which means some do seem to care enough to invest for long term value.

In fact, short term gains is basically the reason private equity firms exist - extracting what value can be extracted from a company and then letting it die.
I'm sorry but no.

Something that will inevitably cause serious trouble down the road doesn't have to be fixed immediately. It can be fixed later. The proper decision for the business is whether the "interest" on waiting is worth it. There are many examples of this in the real world. It's simply not true that "fix later" is always a lie. What's more likely to be the case is that as new requirements are discovered there will be churn and it'll turn out it wasn't actually worth fixing this thing that you thought would cause serious trouble "down the road".

I'm a "boss" and I'm a software engineer. My bosses are also software people. My CEO is a software engineer. What I expect my team to do is to give me the tradeoffs. What I don't want them to do is make business calls. If we lose a huge business opportunity because we can't make a milestone with a customer because an engineer made a decision on his own to spend weeks dealing with some corner case and the whole company goes down the drain that engineer is not professional.

Again we're not talking about situations where this would be unethical, we're talking about a tradeoff a business makes to go forward with certain limitations of some software in order to meet some business goal.
Their utility is directly tied to how many Apple devices with gps and data are in close proximity to them.

I get significantly better responsiveness from them at an Australian airport or Singapore airport than I do at Bangkok airport. That doesn't mean they don't work, it just means it's unrealistic to expect minimum wage baggage handlers in Thailand to have an iPhone in their pocket.
Light and Shadows (2020)
I think it's absolutely cool that someone took the time to write such a good answer.
I'm sure I'm probably just less used to seeing StackExchange answers than StackOverflow answers but I am truly in awe at the length and thoroughness of the existing currently-top answer. By my quick + dirty JS console calculations, it's ~2930 words: https://matheducators.stackexchange.com/a/27841
It might not happen in that way since there are alternatives available. Google had/has a monopoly on search.
Hurl – CLI for HTTP Requests
>I wake up, £1 is worth 50p

>things cost 5%, 10% more over a period of months

In a 6 month period, these are the same.
Tim Urban was right about the exponential growth of AI
It has been 20 years since the last technological revolution - the internet. Now with AI, it was just 2 years ago that the first GPT was announced. And we can see the how fast that has grown 2 years after with GPT-4o. And it will get even faster from here.
I don't think he's saying that AGI is impossible — almost noone (nowadays) would suggest that it's anything but an engineering challenge. The argument is simply one of scale, i.e. how long that engineering challenge will take to solve. Some people are suggesting on the order of years. I think they're suggesting it'll be closer to decades, if that.
This seems implausible; Riley Goodside earlier today demonstrated an image including former President Obama, who was mentioned by name.
I am not impressed. We already have better models for text to peach and voice synthetization. What we see here is integration with a LLM. One can do it at home by combining Llama3 with text to speech and voice synth.

What would amaze me would be for GPT 4 to have better reasoning capabilities and less hallucinations.
Not when they've replaced every customer-facing position. Oh and all teachers.
Smart watches are not meaningfully larger than airtags if you take the wristband off, and a cheap prepaid plan for $5 or $10 would be more than sufficient. You also don't need FindMy because the cell network itself can triangulate.

There are also dedicated devices, such as this one - https://www.t-mobile.com/devices/iot/syncup-gps-tracker-devi... - and lots of companies in China make similar products.

There is a genuine need for anti-theft technology. Apple doesn't have to address that market, likely because they're afraid of brand damage, but stalkers already have plenty of options available.
HRMS - human resource management system
Imagine you put an AirTag somewhere deep into your suitcase, and someone malicious steals it and then drives off with it. With the current model, the thief will get notified there’s an AirTag traveling with them, and they can play a sound, find it and remove it / disable it.

Imo without these features it would be rather unlikely for a thief to find AirTags quickly or even realize it’s there.

The ~40ft range is more than enough, the global mesh network of all iPhones is the whole point of the AirTags, there’s no “gps fix”.
Ask HN: Do you find it hard to help others with tech from a remote location?
I find it can be difficult and frustrating to communicate over slack/google meet or even talking to the person you are trying to assist with programming face to face. Often I go up to them and hijack their keyboard all the while poorly explaining what I am doing. I could use something like TeamViewer but this feels like a heavy handed approach and I still feel like they are not fully understanding what I do on their computer.

Do you frequently work on computers other than your own for brief periods of time? If so, what do you do and do you try to explain what to do remotely with an app like slack/google meet, or do you perform the operations for them?

If you had access only to their terminal with no full screen mirroring like TeamViewer, do you think you could still get your job done?
> AI will be able to do "rigour" before it can do "thought provoking".

I wish. Right now, thought provoking LLMs exist, but rigorously correct ones do not. Which is a big problem if you want to use them beyond blithering.
We are always fascinated by the wrong things but that only becomes clear in retrospect.
Sketchbook Earth: Illustrated Climate Chronicles
Capacitors and batteries work very differently. Capacitors are made from two conductors separated by a non-conducting dielectric and rely on the behavior of electric fields to charge and discharge. Batteries use the energy from chemical reactions to produce electricity, and some batteries allow the reaction to run in reverse in order to store power.
You have the right to take photos of an officer without permission when they're arresting someone etc. So contrary to the article, there is effectively an exception for the police.

Whether or not officers in either country are aware of those laws, or willing to subject themselves to them is another question entirely.

https://www.prigge-recht.de/wann-polizisten-fotografiert-und...
That's funny, because I've been taking servers full of large blocking thread pools, rewriting them to be non-blocking, idiomatic Scala, Cats Effect 3 and get +50% throughout.

Blocked threads are seriously bad for performance. Yes, Java 21 project Loom will help with that (finally), if people get with the program.

There aren't any race conditions, because our classes and data model are fully immutable.

The problem with our legacy servers was that the original devs didn't know what monads were, and decided not to use them. Error handling is now great, by using...

you guessed it, monads.
How would anyone know they're being stalked that way if the device explicitly doesn't notify the person it's stalking?
The system uses 30MW, but this job used a portion of it that would consume 2.6MW.

There isn't really a figure for how much compute time it takes to train this thing, but 8x H100s have 32PF of AI compute among them. This job had 2,100 (half precision[1]) PF-in-fugaku / 158,956 nodes-in-fugaku * 13,824 nodes-in-job = 182 PF-in-job, implying it can get the job done 5.6x faster, or a little over ten days at the most optimistic.

Electricity costs for these nodes for ten days looks fairly similar to the rental costs of 8xH100s for 60 days according to my research. Lambda labs seems to have very cheap instances for 8xH100, but AWS and its ilk are much higher. However, the comparison is a little weird, as Fugaku is also a few years old now, and the contemporary GPU at the time of its release was the A100 (1/13th of an H100). The next Fujitsu chip may well narrow the power/performance gap between itself and (say) Blackwell or whatever is current at the time.

[1] https://www.fujitsu.com/global/about/innovation/fugaku/speci...
Perhaps they discovered that wearing a mask wasn’t a particularly big deal for them and they don’t see a reason to stop. If I had the choice between wearing a mask in the office and getting one cold per year I would seriously consider the mask.
If there's a critical security update they can release an update within days. So it's got nothing to do with the complexity of releasing a new OS, it's just that they found IndexedDB not important enough to warrant an out of cycle update.
I don't see it as 'irrational fear' to fear having these small poison containers run by the lowest bidder about everywhere with about as good oversight as the increased number allows.
Problem is, people aren't machines either: someone who's getting bombarded with phishing requests will begin to lose it, and will be more likely to just turn off their Wi-Fi than allow an AI to run a hundred iterations of a many-armed-bandit approach on them.
> or just.. training data.

I have a much less "utopian" view about the future. I remember during the renaissance of neural networks (ca. 2010-15) it was said that "more data leads to better models", and that was at a time when researchers frowned upon the term Artificial Intelligence and would rather use Machine Learning. Fast forward a decade LLMs are very good synthetic data generators that try to mimic human generated input and I can't think somehow that this wasn't the sole initial intent of LLMs. And that's it for me. There's not much to hype and no intelligence at all.

What happens now is that human generated input becomes more valuable and every online platform (including minor ones) will have now some form of gatekeeping in place, rather sooner than later. Besides that a lot of work still can't be done in front of a computer in isolation and probably never will, and even if so, automation is not a means to an end. We still don't know how to measure a lot of things and much less how to capture everything as data vectors.
I promise that for every one of these posts from me, I suppress the urge multiple other times. But it would be amazing to see things like this published as a Nix flake instead of some debian image chucked over the wall. Seeing the flake would be a definitive, at-a-glance, reference for what is upstream and what is being pulled from some BSP.
It's even worse than that. A space elevator, the only thing that could conceivably replace rockets, requires materials so strong that they don't exist in our universe.

Space is like the internet. You can communicate through it, but sending matter is nigh impossible.
As you can imagine, a cloud of NIMBY is breaking out about this, and with no site picked, and elections in states and federal level this has about as much chance of coming to fruition in the next electoral cycle as Fusion power has of delivering power to the public networks.

I am not personally opposed to a dump. The income stream for what is basically passive income as rent would be astronomically beneficial to the location, and the economy. We have some obligation to take back the products of our uranium mining, and compared to other choices Australia is a good pick to store radionucleotides in. We're stable politically, economically, and geologically.

I would be entirely happy for the dump to be dug underneath my house. I live on a floodplain with acid sulphate soils but I imagine at some depth, there's a good structural basis to do it. There are probably far better locations.

it may be in AUKUS, but can I point out that the US has already refused to confirm if Australia will have sole control of the Virginia class subs we've been half-promised, nor has the promise been kept in any real sense because there is already a supply chain crisis behind the subs, we've paid the US to keep the factories alive, and we don't know what the AUKUS class will look like or who will actually make them or when.. yet.

This deal is half-baked, at best.
It's absolutely not a threat if it cannot be purchased or registered in the US because it lacks certified homologation for road use.
We’ve reached a stage, where it would be advisable to not release recent photos of yourself, nor any video with sound clips to public, unless you want an AI fake instaperson of yourself starting to reach out to member of your externally visible social network, asking for money, emergency help, etc.

I guess we need to have an AI secretary to take in all phonecalls from now on (spam folder will become a lot more interesting with celebrity phone calls, your dead relative phoning you etc)
Sure, all tech has 'real' effects. It's kinda the definition of tech. But all of these concerns more or less fall into the category of "add it to the list of things you have to watch out for living in the 21st century" - to me, this is nothing crazy (yet)

The nature of this tech itself is probably what is getting most people - it looks, sounds and feels _human_ - it's very relatable and easy for a non-tech person to understand it and thus get creeped out. I'd argue there are _far_ more dangerous technologies out there, but no one notices and / or cares because they don't understand the tech in the first place!
I just recently pulled out an old phone that originally ran Android 6 for a project, hardware wise it still runs perfectly. The only thing wrong with it is that I can't upgrade it to a newer Android version.
I appreciate gen z/alphas surrealism, often a blend of blown out audio, weird lingo, and heads in toilets with exaggerated expressions.

Despite not fully understanding it, I genuinely appreciate that youth are finding their surrealist touchstones and developing a shared cultural lexicon. It's so fun to watch them building the things they'll be nostalgic for in 35 years.
> Not to mention the consequences of having your humanoid robot hacked remotely could be quite horrific...

Hacked or not, I would be suspicious of anything closed source and connected to the Internet, especially if it has cameras, mikes, can roam around and possibly access to the local network too.
This robot is insanely cool, but to me the chances that it contains code that phones home to do more than simply upgrading it are too high, like in every closed device.
Zero buses where I live, chief.
I've got "2024/2025 Summer Climate Crisis" as "Things that will fuck up C-Suite plans for return to work".

Good luck to them
Probably "A Primer on Memory Consistency
and Cache Coherence"
Apollo did feature a bunch of interesting first in electronics. We would have gotten there, and we did, but the Apollo program had stuff like the first fly-by-wire vehicle. That's a great invention!
I mostly work on Windows apps. People still complain when software drops support of Windows 7 released in 2009, or Windows 8 released in 2012. Despite none of them are supported by Microsoft.
Both of you are arguing about fluid numbers which reflect political expediency and local economics, not actual power-cost-scale-efficiency numbers.

Nuclear works fine. So does Wind and Solar. All three have proponents and opponents and which has more pace, or likelihood of deployment is not subject to their actual ability to supply power, but to external forces which do not relate to that power at all.
And it's very difficult to secure SMT from side channel attacks without sacrificing a big chunk of performance gain.
Not offensive, but much more often wrong than person.
These models literally need ALL data. The amount of work it would take just to account for all the copyrights, let alone negotiate and compensate the creators, would be infeasible.

I think it’s likely that the justice system will deem model training as fair use, provided that the models are not designed to exactly reproduce the training data as output.

I think you hit on an important point though: these models are a giant transfer of wealth from creators to consumers / users. Now anyone can acquire artist-grade art for any purpose, basically for free — that’s a huge boon for the consumer / user.

People all around the world are going to be enriched by these models. Anyone in the world will be able to have access to a tutor in their language who can teach them anything. Again, that is only possible because the models eat ALL the data.

Another important point: original artwork has been made almost completely obsolete by this technology. The deed is done, because even if you push it out 70 years, eventually all of the artwork that these models have been trained on will be public domain. So, 70 years from now (or whatever it is) the cat will be out of the bag AND free of copyright obligations, so 2-3 generations from now it will be impossible to make a living selling artwork. It’s done.

When something becomes obsolete, it’s a dead man walking. It will not survive, even if it may take a while for people to catch up. Like when the vacuum tube computer was invented, that was it for relay computers. Done. And when the transistor was invented, that was it for vacuum tube computers.

It’s just a matter of time before all of today’s data is public domain and the models just do what they do.

…but people still build relay computers for fun:

https://youtu.be/JZyFSrNyhy8?si=8MRNznoNqmAChAqr

So people will still produce artwork.
Well, at least if they sell in the EU, warranty laws are event stricter, which is good imho. But still a shame
What a great project, thank you. I appreciate that you can link to specific chapters, for example [0], or the one that I haven't been able to stop thinking about for twenty years [1],--though the latter would really benefit from the illustration.

[0] https://patternlanguage.cc/Patterns/Connection-to-the-Earth-...
[1] https://patternlanguage.cc/Patterns/City-Country-Fingers-(3)
> For example- If it can write code 90% of the way, and then debug in a loop, it’d be much more performant than any single shot algorithm.

OOC, Would this make the academics including algorithms as more or less important in their curriculum? That's a bad win for soceity if it's true.
Have you seen this video from Microsoft, uploaded to YT in 2012, the actual video could be even older: https://www.youtube.com/watch?v=Nu-nlQqFCKg
Real mode profiling and debugging is damn easy, it's protected mode debugging that requires more work. I used Turbo Debugger for years.
I use voice assistants and find them quite useful, but I've had to learn the interface and memorise the correct trigger phrases. If GPT-4o works half as well in practice as it does in the demos, then it's categorically a different thing.
It's in the URL, I too missed it until pointed out
> ChatGPT took off on Word of Mouth alone.

I remember for a good 2-3 months in 2023 ALL you could see on tiktok / youtube shorts was just garbage about 'how amazing' ChatGPT was. Like - video after video and I was surprised of the repeat content being recommended to me... No doubt openAI (or something) was behind that huge marketing push
Yes but they're heavy and generate CO2 from transportation.

During communism we used to recycle all food and drink glass containers, but one would only get a few glass shapes and a few jar shapes. They only took back the containers clean and without labels. Most of the work was washing off the paper labels and bone glue. Kids were earning ice cream money doing the cleaning and recycling.