skysight-inc/HackerNews huggingface dataset:
That's an interesting framing, but "all other things being equal" is doing a lot of work there. In an alternate timeline where ChatGPT needed 1000x compute capacity to run, Nvidia wouldn't make 1000x the revenue from OpenAI; ChatGPT as we know it simply wouldn't exist.

The bull case as I see it is that demand for AI capacity will always rise to meet supply, at least until it starts to hit some very high natural limits based on things like human population size and availability of natural resources on or in reasonable proximity to Earth. Just as we quickly found uses for more than 640 KB RAM and gigabit+ Internet connections, there's no shortage of what could be done with 1000x more AI capacity. Best case scenario, we're eventually going to start throwing as much compute as humanly possible at running fully automated factories, automatically building new factories and infrastructure, running automated factories that build the machines that automatically build factories and infrastructure, and so on. Looking forward a bit further, it's not hard to imagine an AI-driven process of terraforming and industrializing Mars.

I don't know how much if any of that would be possible with current AI software given a hypothetical infinitely powerful GPU, but AI is still rapidly improving. Once it gets to the point where it can make humanoid robots do tasks at a lower cost than human labor, the demand ceiling will shoot sky-high and become a self-reinforcing feedback loop. AI will be used 24/7 to churn out new AI capacity, robots, power infrastructure, and so on, along with all the other things we might want it to produce (cars, cities, high-speed rail, drone carriers, food, etc.).

Imagine having an equivalent to AWS that could be used for provisioning and managing low-cost automatons with comparable physical and cognitive capabilities to average human laborers, along with self-driving cars, AI-controlled construction and manufacturing equipment, and so on. That would be on top of all the purely digital capabilities that are already commonplace and rapidly improving. Essentially, every public works project or business idea that anyone could conceive of would ultimately become viable to attempt with a dramatically smaller amount of capital than today, so long as the necessary natural resources were physically available and there were no insurmountable legal/regulatory roadblocks. We have an awful lot of undeveloped land and an awful lot of people on the planet who could certainly find interesting things to do with a glut of AI capacity.
> Alphas are just leaders.

No they are not. There are plenty of leaders who are not alphas and they lead organizations that achieve good things.

Alphas are generally just assholes who want to be leaders. They usually lead self selected friends who crave their validation and people with healthy boundaries just nope out of those systems.
Very cool! Looking forward to the future developments! :)

Even as it stands today, all the old Pebbles can still be used and are still great. On Android, it's easy using the Gadgetbridge app or even the original Pebble app. On iOS, you currently have to install the ipa-File yourself - meaning you have to have the iOS device in developer mode and re-sign the App regularly. Pebble apps can easily be installed via rebble.io. There is even still some developer activity - for example, there is a relatively recent Home Assistant app - so you can totally control your 2025 smart home with your 12 year old smart watch (even by voice).

I got my Time Steel used something like 5 years ago for around 35€ and use it most days. In a previous job, I could use different Apple and Android smartwatches as much as I wanted but I always kept the Pebble as my main and personal device.
My favourite sentence from the article: »I have had a case of body moving across a table due to maggot activity.« :D
Robotics? Chip design? With a physics sinulator connected to it, it can come up with a design to achieve certain function.
A lot of people seem to lose their minds if they hear what could be interpreted as agitation versus an ethnical out group.

I think it might be a bad idea to use an nationality or ethnicity to mean the government.
My speculation is that they used very low level software design to achieve such reliability. This could be harder to maintain but who knows...
Dugatkin, "Winner and Loser Effects and the Structure of Dominance Hierarchies" was an interesting read this morning. Thanks for the reference.

The main thing I take away from the paper is that (in computer simulations) bigger winner effects and bigger loser effects lead to strongly defined hierarchies. Fewer subjects have ambiguous positions.

I'm not sure the paper speaks much to which strategies (e.g. violence vs cooperation) are more common or effective.
> It's either intentional, which would be puzzling and unsettling, or it's a bug which has gone unnoticed.

I've long believed that a large part of technological evil comes from bugs which were introduced innocuously, but intentionally not fixed.

Like, your ISP wouldn't intentionally design a system to steal your money, but they would build a low-quality billing system and then prioritise fixing systematic bugs that cause errors in the customer's favour, while leaving the ones that cause overbilling.

This could easily be the same on Facebook - this got swept up in a false positive and then someone decided it's not a good one to fix.
Mac-minivnc – A VNC remote desktop server for vintage Macintosh computers
And in this case it's heavily capitalized open source, which scares the techbros.
I had my final pebble hardware failure just before they stopped trading. I'll give it a miss.
Zulip is vastly better for people who are willing to learn an interface. But it’s not really very “pretty”
This is not exactly what is meant by Commoditise your complements.

"Commoditise your complements" in this setting would mean making watch OSs free for everyone in order to make demand for watches go up.
Maybe because "private" in English can also mean non-publicly-owned, ie in private hands. This facility could easily be a publicly-owned and yet not open to the public. English is weird.
But this just doesn't match my experience with Blaze at all. For my internal usage with C++ & Go it's perfect. For the weird niche use case of building and packaging BPF programs (with no support from the central tooling teams, we had to write our own macros) it still just works. For Python where it's a poor fit for the language norms it's a minor inconvenience but still mostly stays out of the way. I hear Java is similar.

For vendored open source projects that build with random other tools (CMake, Nix, custom Makefile) it's a pain but the fact that it's generally possible to get them building with Blaze at all says something...

Yes, the monorepo makes all of this dramatically easier. I can consider "one-build-tool-to-rule-them-all isn't really practical outside of a monorepo" as a valid argument, although it remains to be proven. But "you fundamentally need a build tool per language" doesn't hold any water for me.

> That makes it easier to work on other projects, and easier to write tooling that works with all of them.

But... this is my whole point. Only if those projects are in the same language as yours! I can see how maybe that's valid in some domains where there's probably a lot of people who can just do almost everything on JS/TS, maybe Java has a similar domain. But for most of us switching between Go/Cargo/CMake etc is a huge pain.

Oh btw, there's also Meson. That's very cross-language while also seeming extremely simple to use. But it doesn't seem to deliver a very full-featured experience.
Why do you think they would be interested?
They were correct that there is no need for it to run in the kernel. They were incorrect in thinking this would affect the company's future, because of course the sales of their product have nothing to do with its technical merit.
Show HN: Meelo, self-hosted music server for collectors and music maniacs
I've been working on this alternative for Plex for almost 3 years now. It's main selling point is that it correctly handles multiple versions of albums and songs. As of today, it only has a web client.

It tries to be as flexible as possible, but still requires a bit of configuration (including regexes, but if metadata is embedded into the files, it can be skipped).

I just released v3.0, making videos first-class data, and scanning + metadata matching faster.
"Knowing" something is different from formalizing it into a mathematical model. Almost all papers are about relatively minor findings at best.

Publish and perish is real though. As are hype and bad popularization of research.
Reinforcement Learning – A Reference
While studying for an RL course, I created a reference for several algorithms with a brief description of what limitations they solve. Example:

Problem: SARSA pushes q-values towards the current policy, but ideally we'd want optimal values.
Solution: Use the best action in TD-target calculation -> Q-learning

Perhaps someone else will find it helpful!
The Bell Telephone Laboratories—an example of an
institute of creative technology
By Mervtn J. K elly

is a good read
OpenGig will launch your MVP in 1 day with SuperSprint; Details in comment
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It's because software devs are smart and make a lot of money - a natural next step is to try and use their smarts to do something with that money. Hence stocks.
Mastodon looks like a barely used social network instead.
I feel like this is a symptom of our broken economic system that has allowed too much cash to be trapped in the markets, forever making mostly imaginary numbers go up while the middle class gets squeezed and the poor continue to suffer.

A fundamental feature of a capitalist system you can use money to make more money. That's great for growing wealth. But you have to be careful, it's like a sound system at a concert. When you install it everybody benefits from being able to hear the band. But it is easily to cause an earspittig feedback loop if you don't keep the singers a safe distance from the speakers. Unfortunately, the only way people have to quantify how good a concert sounds is by loudness, and because the awful screeching of a feedback loop is about the loudest thing possible we've been just holding the microphone at the speaker for close to 50 years and telling ourselves that everybody is enjoying the music.

It is the job of the government, because nobody else can do it, to prevent the runaway feedback loop that is a fundamental flaw of capitalism, and our government has been entirely derelict in their duty. This has caused market distortions that go beyond the stock market. The housing market is also suffering for example. There is way too much money at the top looking for anything that can create a return, and when something looks promising it gets inflated to ridiculous levels, far beyond what is helpful for a company trying to expand their business. There's so much money most of it has to be dumb money.
Do you think all the export restrictions we place on our companies hurt or accelerate China's progress?

In my opinion they might hamper them very temporarily, but boosts their own developments significantly with incentive and opportunity.
Heathrow expansion plan faces sky high challenges
They are profitable for a few years now, afaik visa/master pays you a share of their profit each time customer makes a transaction(i.e. share of merchant fee). There are also credits, loans, exchange fees, subscription fees i.e. a lot products that make them money.
> “You've got a next generation who haven't engaged as a philanthropic community and volunteer community in the same way, at the same scale.”

That's basically a kind way of saying that they mock the crazy old guy who shakes his fists at the cloud, and mumbles something about Microsoft and Google.
Shouldn't it be Jevons' Paradox?
+1.

Not only the heart rate sensors for most watches and fitness trackers bad, but these products have also made it so hard to find a good sensor as the search results are all dominated by the crappy ones.
Elvis is still alive 48 light years away.
Huh, I thought I played perfectly, but when I cleared the board (aside from the dragon), I had only 14 hearts left.
Mine broke down but I got it repaired by Fossil after some time for 60 Euro. Meanwhile I bought a Garmin, now the repaired Fossil sits in a drawer. Not sure what to do with it. Maybe gift it to someone, but softwarer support is probably getting worse.
Reminds me of the gobbledygook of The Architect in "The Matrix: Reloaded".

Neo: "You haven't answered my question."

Architect: "Quite right. That was quicker than the others."
Food is generally pretty inelastic.
I disagree, context size alone has exploded from 8k to 200k now and that makes a huge difference. LLMs have also progressed significantly in many other metrics, code quality, understanding, etc. The recent reasoning models have upped the ante further, especially when combined with models that are good at editing code.
We use Twist at my company. I find the emphasis on asynchronous communication refreshing. It encourages more thoughtful discussion. Basecamp also lends helpfully in this direction, although adopting Basecamp means accepting an entire project management system as well.
While I'm also interested in this, I guess there is value in independent replication as well. Assuming this is doable - and I wouldn't know.

Does anyone know how difficult it is to perform this kind of reproduction? E.g. how much time would it take (weeks? years?) and how likely it is to succeed?
If you want GGUF https://huggingface.co/unsloth/DeepSeek-R1-GGUF

Blog post about the dynamic gguf https://unsloth.ai/blog/deepseekr1-dynamic

Original deepseek can be of course found on hf as well https://huggingface.co/deepseek-ai

Here is an example how people run deepseek with cloud infrastructure that is not deepseeks https://www.youtube.com/watch?v=bOsvI3HYHgI
Some definitely do. Those tend to be the more successful examples of beginner languages

For example, look at Scratch’s website. They’re not talking to students directly. The way their site is composed is addressing the parents and educators rather than the students.
What’s a good sci fi book about that?
Amazon's chips at this point are marketing for Amazon. I've seen the benchmarks, they're not quite ready for serious use yet. I suspect Anthropic got a good discount on GPUs in return for using Amazon's own chips in any possible capacity (or maybe just for the press release claiming such use). The only real alternative to NVIDIA on the inference side that you can actually buy hardware for is Intel Gaudi which costs less and performs rather well, but everyone seems to have written it off, along with Intel itself, and it's not available in any cloud last I checked. On the training side there's really no alternative at all - PyTorch is the de-facto standard, and while there is PyTorch XLA, it's even less popular than Jax, which is already like 20x less popular than PyTorch. Bottom line: capable Jax engineers able to optimize distributed Jax programs on TPUs are unobtainable unicorns for anyone but the top labs and Google itself. Note that the training side has significantly different requirements than inference side. Inference side is much simpler to optimize and wring the performance out of.
Well in the case of Bitcoin it's just one simple hash function. ASICs were inevitable.
Follow-up question: what work has been done on client-side moderation? I know this gets dangerously close to the kind of content scanning that eg apple has tried (to very detrimental results), but hear me out: I really think this is a prerequisite to end-to-end encryption on a social network (there has to be some level of protection; even if 100% of users report 100% of bad content, imagine scrolling a feed and stumbling upon CSAM simply because you were the first person to see it). I also also think it's possible to strike a balance that preserves user agency while still protecting them, by simply inserting a manual reporting step. So, for example, potentially problematic content gets put behind an interstitial with a content warning and options to view, hide, report, etc. But again, this requires client-side content classification.

I'm aware of eg NSFWJS, which is a tensorflowJS model [1]. Is there anything else that, say, can also do violence/gore detection?

[1] https://github.com/infinitered/nsfwjs
> However, developers hate emai

I prefer email.
Email is asynchronous,
It does not interrupt my flow or my presentations,

I can decide when I spend tine responding.
Then I can fully focus on the emails and type
the response they merit.

Of course you have the person sending you an email
and 30s later they tap you on the shoulder to ask if
you got that email.
I’d actually wear my Apple Watch if I didn’t have to charge it every day. Battery life is paramount.
So not an actual DeepSeek-R1 model but a distilled Qwen or Llama model.

From DeepSeek-R1 paper:

> As shown in Table 5, simply distilling DeepSeek-R1’s outputs enables the efficient DeepSeekR1-7B (i.e., DeepSeek-R1-Distill-Qwen-7B, abbreviated similarly below) to outperform nonreasoning models like GPT-4o-0513 across the board.

and

> DeepSeek-R1-14B surpasses QwQ-32BPreview on all evaluation metrics, while DeepSeek-R1-32B and DeepSeek-R1-70B significantly exceed o1-mini on most benchmarks.

and

> These [Distilled Model Evaluation] results demonstrate the strong potential of distillation. Additionally, we found that applying RL to these distilled models yields significant further gains. We believe this warrants further exploration and therefore present only the results of the simple SFT-distilled models here.
Just a decade and a half as it turns out! (though things definitely felt dizzyingly fast back then - think Google was launched just 5 years after HTML)

- HTML first released in 1993

- AJAX in 1999

- Websocket first proposed in 2008

https://en.wikipedia.org/wiki/HTML
https://en.wikipedia.org/wiki/Ajax_(programming)
https://en.wikipedia.org/wiki/WebSocket
I dont' know what the surprise is here. the human brain consumes about 20 watts. literally a rounding error compared to what chatgpt uses. so we already know that there was plenty of room on the table to improve.

incidentally, I love these kinds of market crashes. just moved a big chunk of my savings account into stocks last night :). Buy and hold. dont' sell during a dip lol
At the same time, I hope it's priced high enough so that the company can thrive without taking external funding. PE and VC fuck everything up.
> Corporations are required by law to have Presidents and Chairmen

Varies by jurisdiction. Common ones are a president, secretary and treasurer. (They can be the same person.)
"be the change you want to see in the world" - just start doing it.

It's amazing how differently people interact with each other when collaborating on a passion project. For me, opensource software is the best way to do it. Pick a topic you're passionate about and start contributing somewhere :)
Sorry to hear that. I could imagine that leadership actually didn't know you were being laid off. So the VPs and C-level execs might actually be pissed that someone laid off their go to person.
Another perspective I'd like to offer is one of renewal. You can move forward and find something that suits you even more. Something I am quite envious about right now to be honest. Maybe a sabbatical?
The VCs thinked that the scaling law may build a moat for very large computing powers like Google and OpenAI, and VCs rushed into the area the foundation models.

The emerging of DeepSeek V3 and DeepSeek R1 somehow make the moat vulnerable with their much smaller training cost. The fact verified the claim of Google.
More than three quarters of Americans live in suburban or rural areas. If you tried to run an hourly bus down a suburban street in the middle of the day, it would have one passenger. You can't run bus service at the density of the suburbs, with single passengers it's just a slower, more expensive and less efficient Uber.

Then you get traffic congestion in the city because those people come into the city in their cars. But you can't just add mass transit where the traffic is because those people still need to traverse the part of their path where it isn't.
you could use some cheaper LLMs for this, even GPT-3.5turbo could excel at this or the moderations API (but that in my experience was more trained to obey the laws of USA, for example guns were okay to be asked about but are pretty much illegal in my country). The simplest way is a blocklist of terms which was what we had previously used containing an insane number of terms beyond the regular abusive terms, but it would need some updating from time to time.
Actually inference got more efficient as well, thanks to the multi-head latent attention algorithm that compresses the key-value cache to drastically reduce memory usage.

https://mlnotes.substack.com/p/the-valleys-going-crazy-how-d...
Why do you need an exciting and vibrant display for your watch? Are you looking at movies?
The alternative is just as grim. I heard[1] that Excel went with the slogan "kill your dependencies" at least during Joel Spolsky's time. This ended with Excel team building and shipping their own C compiler.

Imagine NIH so hard, you start rewriting the compiler.

[1]https://blog.codinghorror.com/dependency-avoidance/
There's no consumer demand for AI?

In a thread full of people who have no idea what they're talking about either from the ML side or the finance side, this is the worst take here.

OpenAI alone reports hundreds of millions of MAU. That's before we talk about all of the other players. Before we talk about the immense demand in media like Hollywood and games.

Heck there's an entire new entertainment industry forming with things like character ai having more than 20M MAU. Midjourney has about the same.

Definitely. An industry in its infancy that already has hundreds of millions of MAU across of it shows that there's zero demand because of some ad no one has seen.
> This is exactly why it is not “US vs China”, the battle is between heavily-capitalized Silicon Valley companies versus open source.

Ah yes the "open source" code that was not released by the DeepSeek team and the tens of thousands of professional grade GPUs that were contributed by the "community".

DeepSeek is based on Llama which was produced by ... Meta.