skysight-inc/HackerNews huggingface dataset:
I think reasonable people can disagree about this. Trump is pretty good with the "flimsy excuse", like "look I said 'stand back' as well as 'stand by'" or "hey I said 'peacefully and patriotically'". Probably whether you're willing to give him the benefit of the doubt on these kinds of things is some kind of political ink blot test, but to me, he definitely has the instinct and pattern of "say it without saying it".

Most leaders are aware that people might cue off of what they're saying and do something very bad, so they stay far away from rhetoric like this. Trump (deliberately IMO) does the opposite for political gain. So even if I agree this is about combat, what's the difference? He's once again engaging in his pattern of dehumanizing his opponents and advocating violence against them, which has led to actual violence.

Elsewhere you pointed out this is pretty similar to Vietnam War protests. I think generally that's right (again "Fortunate Son"), but there are some differences. First is there isn't a draft; we have an all volunteer force (though there's a big discussion to be had about economic exploitation and multi-generational military families). Second, she wasn't even in Congress during Bush 2 and AFAIK had no policy making power where she was at State.

Do I love Liz Cheney? Hell no; her policy positions are one disaster after the next. I believe she should be vigorously opposed in every election she runs in. But do I think she should be subject to wink wink "sure would be a shame if something happened to Liz Cheney" rhetoric from maybe the most powerful person on Earth? Absolutely not; no one deserves that.
How does the pebble compare to the pine time?

https://pine64.org/devices/pinetime/
Similar to Mamonosweeper, a 10 year old game from a japanese dev: https://hojamaka.com/game/mamono_sweeper_h2/html5/en.html (playable in html5 there).

This game was released on android at a point (and removed from the store later). It's my favorite game ever.

This is a cross between Minesweeper and an RPG.

You gain levels by killing weak monsters and win when you defeat them all.

It's a bit different than Minesweeper in that the number you reveal when you click on a square is the total of the levels of the monsters in adjacent squares.

When you click on a tile with a monster in it, a battle begins.

First you attack, and deal damage (equal to your level) to the monster. On the next turn, if the monster is still alive, it attacks you back. Your attacks alternate until one of you dies. You don't see this, though -- the battle plays out instantly after you click.
I once posted a Youtube comment with a link. Got removed without notice. I thought it was the uploader first but no ...
I thought Zuckerberg was removing any fact checkers and platform censoring. I'm thoroughly confused. But maybe since Zuckerbergs death the company changed directions again.
I've never met a fellow software engineer who "centers divs" for 6 figures.

But then I work with engineers using FPGAs to trade in the markets with tick to trade times in double digit nanoseconds and processing streams of market data at ~10 million messages per second (80Gbps)

The truth is, a lot of P&L in trading these days is a technical feat of mathematics and engineering and not just one of fundamental analysis and punting on business plans
Headers Club
Kinda though things didn't move quite as fast back then. Knowledge didn't spread as fast yet because it was the internet itself that made this possible.
Show HN: I made an app to centralize my saved post and remember why I saved them
Hey HN,

I worked on this app alongside my 9-5 last month,

As someone who spends way too much time scrolling through Instagram and TikTok, I always struggled to stay organized with all the amazing content I saved. Recipes, DIY ideas, travel inspirations… it quickly turned into chaos!

That’s why I built this app to centralize, organize, and remember why I saved posts.

Here’s how it works:

- Save links from Instagram, TikTok, and more using the share feature (no need to quit the app).
- Add notes to remember why they’re important.
- Find everything in one place

The last app I made took me 3 years to launch. This year I plan to launch 6 apps and this is the first one.

Thanks for checking it out, and happy 2025!
Adrien
Great news! Loved my Pebble until it stopped working.
I just hope for a new Pebble Round. The only smartwatch I really cared about due to its form factor and reduzed size.
We use a combo of AI and the cheapest African contractors we could find.
oh and now the developer reopened it because it is not actually fully complete, lol. Yep, Iceburg on Clickhouse is WIP. I am actively watching this because it is relevant for my company.
Slightly tangential, but I want an LLM which can debug windows.
Open source has pragmatic merits and I love the culture. But I don't like associating it with a moral high ground because it doesn't charge you money. By this standard, we should also ask Intel/AMD to open-source their CPUs, video game studios to open-source their code and artifacts, and Google/Amazon for their search engine and infrastructure. Not all business sectors can afford to sustain with the Open Source model.
And likely massaged by the CCP.
Ye I feel like many times when people complain about email they complain about the emails' content not the concept of sending email, which is then misinterpreted.

The more I think about this, the more "don't shoot the messenger" fallacies I see around me.

Like, the complaints about overly bureaucratic documentation was interpreted as critique of documentation by "people". Etc.
Gmail was the first time I saw a website which could refresh the information without refreshing the page. I was a teen back then but I realized it was something momentous.
DeWeb: On-Chain Decentralized Web Gateway
RFP responses. In enterprise sales, there's a huge amount of back and forth with different teams in a customer when you're selling anything but very simple applications. Most enterprise customers require certified or authoritative responses with backup material that is tested later during formal verification.
Why do you think the human brain and chatgpt are in any way related?
Anthropic was the only company in that list not to have paid for their CEO or founder to attend the inaugeration of the current ruler of the exectuive branch of the US a week ago.
Azure Linux is Linux. Microsoft is one of the biggest contributors to Linux in general, in terms of commits/release, and has been for a lot of years now. That doesn't mean Windows is doing what Linux did - Windows is largely still entirely different from Linux at both the kernel and user's pace level, and improvements in one have little to no bearing on the other.
How about some screenshots, product galleries et cetera
Congratulations on the launch! I've been using CapRover in the past and wanted to try out Coolify recently, could you elaborate what the advantages of k3s/Longhorn might be (no experience with them)?

Are deployments from Github Actions possible (I'd assume some interface/API is needed for that)?

Thanks!
Nothing fancy. The core principles are the same, you'll need to adapt them depending upon the kind workload changes that ML introduces. For most ML systems
1. Storage infra: assuming storage for models or even data, use any blob storage like S3. Or a shared networked file system like EFS, Lustre etc.
2. Networking: if you're talking about networking using large GPUs, I am not aware of any definitive resource on this.
3. Scheduling: This is honestly a solved problem at this point, anything works - write your own coordinator that periodically runs docker image base jobs (you can hook one up quite quickly using some sort of system for metadata and triggers powered by message queuing), use Airflow, use AWS Batch for large scale jobs.

You missed model serving (I think ?). Tough and latency sensitive esp for recommender systems. Prone to latency spikes, traffic spikes. Even with a well-written Python code you can run into limitations quite quickly.
Show HN: Cloud GeoIP via DNS Test Tool
Made a configuration and guide to configure and use 3 clouds's DNS services to see where clouds such as GCP, Azure, and AWS think some computer is if some DNS names are dig'd up. I've already deployed this so it's already usable.

To be honest, I doubt this is useful for anything beyond curiosity and remediation if you see any issues is likely impossible. Kind of sadly useless I suppose.

Anyway, you don't need any tools on your computer except dig to resolve some CNAMEs. The readme is a guide.
OAuth is authorization only. The part where it is vast is the different mechanics to grant/delegate access. And that's really needed because you need to be able to have Oauth working fo humans and machines where the accessing service can be the app on your phone, or some backend server.
Life review is a stereotypical effect of some psychedelics such as ibogaine: https://www.youtube.com/watch?v=yXjLD1tDC7k

Now consider that your body naturally produces psychedelics, including DMT.
This is not a party, this is a technology forum and we prize being right
I appreciate that "tools" that are used to build the final version of a module/cli/service are explicitly managed through go.mod.

I really dislike that now I'm going to have two problems, managing other tools installed through a makefile, e.g. lint, and managing tools "installed" through go.mod, e.g. mocks generators, stringify, etc.

I feel like this is not a net negative on the ecosystem again. Each release Golang team adds thing to manage and makes it harder to interact with other codebases. In this case, each company will have to decide if they want to use "go tool" and when to use it. Each time I clone an open source repo I'm going to have to check how they manage their tools.
Lmao “I’m mad some people look nicer than me and know how to be kind to people. They suck and are only popular because of Instagram.”

My guy, comb your hair, take a shower, put on deodorant and a clean shirt. You’re fine.
I'd expect nothing less from Google and the other FAANGs.

I wonder what OSM will do?
Extremely interesting topic, unfortunately shallow article. Still I'm happy for the input.

I'd like to learn more about how abundance of food, lack of threats and other comforts of civilization distort the formerly vital instincts into all kind of dysfunctional and harming behavior. And more importantly, how to manage those.
> when “name changes vary between countries, Maps users see their official local name. Everyone in the rest of the world sees both names.

Can someone clarify this bit? What does "both" refer to: the local name and ?
Ask HN: How do you stay on top of AI tech?
The field is moving so fast, reading up on all development alone is taking up quite a bit of time. But as professionals, we should strive at being able to employ the latest tech. What's your approach to that?
I think the analysis of (2) is too simplistic because it ignores network effects. A community of developers and users around a specific toolset (e.g. CUDA) is hard to just "buy". Imagine trying to build a better programming language than python -- you could do it for a trillion dollars, but good luck getting the world to use it. For a real example, see Meta and Threads, or any other Twitter competitor.
Love how if you click no on the website it brings you to Apple Watch haha
Please note that the source needs quite a few changes before being built as all the proprietary code has been removed. It lacks (from the readme): all of the system fonts, the Bluetooth stack, the STM peripheral library, the voice codec, ARM CMSIS, the heart rate monitor driver.
The thought that there's a magical machine that I can just ask for an answer and it's going to provide the correct one is absolutely thrilling, but then I remember that at least 1/3rd of LLM-provided answers in my own domains of knowledge turn out to be wrong upon closer inspection.

I don't think the human brain is evolved to deal with a machine that promises to have all the answers, always speaks with an authoritative tone, and is trained to be agreeable. As a species we like shortcuts and we don't like to think critically, an easy to get answer is always going to be infinitely more appealing than a correct answer, no matter how wrong it is.

Right now there's a generation of kids growing up who believe that they don't have to learn anything because LLMs have all the answers. World leaders don't seem concerned about this, likely because a dumb population who doesn't know how to think critically is easy to control.
Maybe I am underestimating the course complexity but this sounds like an entry level course. Up until Model explanability tools, most of the stuff looks fairly straightforward tbh. Although, they're using industry standard tools for most use-cases which is good I think.
The US models are also full of censorship. For example the US is much more sensitive to anything related to sexuality and here in Europe it's quite frustrating to deal with that censorship.
Across 300 years of lighting technology decreases in cost consistently led to much larger increases in light use every time. Until about the past 50 years or so when increased light use started to fall behind the drop in costs.

https://www.researchgate.net/profile/Roger-Fouquet/publicati...

Cheaper models are good for industry. But the demand for better more reliable models is immense. The models won't stay cheaper.
Caching downloads on a CDN helps offload work from the main server, it doesn't meaningfully change the bandwidth picture from the client's perspective.
“Clear evidence he’s wrong”

Good science is dead, isn’t it?
no wealth, no loss
I've got an original Apple ][ reference manual (red cover) with the hand annotated ROM listing.

Also have SMALLTALK-80 book with it's railtrack diagrams of syntax on the inside covers.

What's really interesting about the AI mania we're in is that no one has shown that what we have now will get to AGI and how. We have great models that simulate reasoning, but how close are they?

How do we measure their quality? Benchmarks? Tooling?
People developing statistical models that are excercising the financial market at scale are the quants. These people don't come from financial degree background.
That's a useful performance improvement but it's incremental progress in line with what new models often improve over their predecessors, not in line with the much more dramatic reduction they've achieved in training cost.
You totally see this in other folks. Look at Ben Carson, and his magical surgery expertise on running the department of Housing and Urban Development.
Both Slack and (most) email clients allow you to mark items as unread and set reminders. Being pinged all the time sounds more like an organisational issue, where comms channels are left to grow wild and unstructured. It's definitely not down to Slack.
Googled in 5 minutes.
Quite right. Its just software engineering with a fancy name. This work classification is only slightly better thought out than DevOps. In most companies ML engineers are engineers that understand software and some parts of ML and in best cases are good at both, in worst cases are terrible at both.
Trump First Week, OpenAI, $500B Stargate, Cloudflare 5.6Tpbs DDoS
DeepSeek hit with large-scale cyberattack
I chose native language as English and it did create a lesson plan.

Yes, it did create a lesson plan but it didn't explain the basics. It just told me to repeat sentences after it and I couldn't follow because I barely know any words.

Also, I'd love to be an early user for your product and join your beta group (if that exists...) to gove you constant feedback.
Still going huh?
They linked the wrong hotel in the BBC article... Here's the correct link: https://www.svartsonorra.se/
an incentive is meant to encourage, not to force.

They are not equivalent. A digital currency turns suggestions into orders.
Every week to me means the frequency, not the duration. So having 52 events in a year that are spread out somewhat evenly but for which many take longer to develop than a week would count. If I count Deepseek as one of these I can’t find another 51 that are on this level. But I’m sure there was at least one per week that was exciting, just not to this degree.
You have a trillion dollars in incentive. You can use it for more than just creating the software, you can offer incentives to use it or directly contribute patches to the tools people are already using so they support your system. Moreover, third parties already have a large motivation to use any viable replacement because they'd avoid the premium Nvidia charges for hardware.
They probably mean endonymy and exonymy.

https://en.wikipedia.org/wiki/Endonym_and_exonym

Different groups can have different names for the same thing. For example, country names change depending on the language.
I see everybody that voted got it from 4 pages or more down ;-) I posted at an unpopular hour, that's why.
Young people are too busy with being blasted in the ass financially to focus on hobby side projects.

Boomers pulled up the ladder and now they're wondering why noone is climbing up.
Brought to you by "the 2020 elections were rigged".
> can one score a random painting

You can get very mechanical in scoring an image. Ask any art student. If you want to or if your instructor or audience wants to. For example "fits rule of thirds?" yes is a point to common attraction, no is a point to unexpected at the risk of outsider-ness. You can do that in color, composition, recognizing objects and fitting that to memes or associations or non-associations. Too many points in "unexpected" is meta points in "unpleasant chaos" and so a strong downgrade in common attraction. You can match all this to images in the library (see how copyright or song recognition operates in the music category) and get out of that some kind of familiarity vs edge score (where too much edge goes against common attraction.)

I would expect you could get better than most humans at recognizing shapes in an image and drawing associations from that. Such associations are a plus in unexpected / surprise if they are rare in the culture or a plus in common attraction is they are common.

After that, to be cynic about it, you can randomize and second guess yourself so your audience doesn't catch on the 1st level mimicry.

Creativity is not normally used as an absolute with a unique measure. It's not "length". And you only need to please part of the audience to be successful - sometimes a very small part, some of which loves surprise and some hates it, etc. Someone elsewhere objected on the grounds that creativity or attractiveness is culture based - yeah so? if you were to please much of just one whole culture, you would have an insane hit on your hands.

Sounds feasible to me.
This nitpicking is pointless.

DeepSeek's gifts to the world of its open weights, public research and OSS code of its SOTA models are all any reasonable person should expect given no organization is going to release their dataset and open themselves up to criticism and legal exposure.

You shouldn't expect to any to see datasets behind any SOTA models until they're able to be synthetically generated from larger models. Models only trained on sanctioned "public" datasets are not going to perform as well which makes them a lot less interesting and practically useful.

Yes it would be great for their to be open models containing original datasets and a working pipeline to recreate models from scratch. But when few people would even have the resources to train the models and the huge training costs just result in worse performing models, it's only academically interesting to a few research labs.

Open model releases should be celebrated, not criticized with unreasonable nitpicking and expectations that serves no useful purpose other than discouraging future open releases. When the norm is for Open Models to include their datasets, we can start criticizing those that don't, but until then be gracious that they're contributing anything at all.
1.)

Dylan Patel (SemiAnalysis):

"Never said that. Hopper. Some my clients executives misinterpreted that as H100, but includes H20 and H800."

https://x.com/dylan522p/status/1883934275516654060

2.)

https://stratechery.com/2025/deepseek-faq/

"Scale AI CEO Alexandr Wang said they have 50,000 H100s.

I don’t know where Wang got his information; I’m guessing he’s referring to this November 2024 tweet from Dylan Patel, which says that DeepSeek had “over 50k Hopper GPUs”. H800s, however, are Hopper GPUs, they just have much more constrained memory bandwidth than H100s because of U.S. sanctions.

Here’s the thing: a huge number of the innovations I explained above are about overcoming the lack of memory bandwidth implied in using H800s instead of H100s. Moreover, if you actually did the math on the previous question, you would realize that DeepSeek actually had an excess of computing; that’s because DeepSeek actually programmed 20 of the 132 processing units on each H800 specifically to manage cross-chip communications. This is actually impossible to do in CUDA. DeepSeek engineers had to drop down to PTX, a low-level instruction set for Nvidia GPUs that is basically like assembly language. This is an insane level of optimization that only makes sense if you are using H800s.

Meanwhile, DeepSeek also makes their models available for inference: that requires a whole bunch of GPUs above-and-beyond whatever was used for training."
The cost of pissing of devs is so high, why cant companies just knuckle under- stop attacking add-blocking browsers like firefox or dev-operating systems. Why would you want to enter that world of pain of getting a ton of adversaries with while balancing on stack o swiss-cheese and duct tape?
What is going wrong in those decision maker heads.
Participants here are afraid of losing "points" and care about "winning" points.

So you end up increasing the bias towards what gets you points rather than frank conversations based on a bigger array of facts than just the convenient facts.

Corona made this painfully visible. With facebook and others only admitting 4 years later that they completely muffed the other side of the conversations with downvotings, shadowbanning, suspending accounts when those voices had a perfectly valid reason to argue and question the official narrative.

The funny thing is that 99% of the users here will look with disdain to the burnings on public squares, but they behave exactly that way in a digital format today.

We won't change that system since it is human nature, but at least it will be recorded in history that some humans we're trying to revert that situation.
It doesn't matter if they are not open sourcing their models they are already loosing the game, sure they are making money now.
Not loving the cutesy names (https://somesocks.github.io/dryad/docs/02-concepts/01-the-ga...). I want my build tool to be boring.
You can make a keylogger in CSS
> Agree with the headline

Which of them -- the original (and still on TFA), "Once You're Laid Off, You'll Never Be the Same Again", or the current one here, "A layoff fundamentally changed how I perceive work"?

(And YTH did it change to something else??? Weird.)
Tearing hasn't been a thing under X.Org for me since the introduction of Option "TearFree".
Is the message here that it is the America in "USA" or the whole continent America in the alleged name of the gulf?

I guess I just should be glad the Navy wasn't involved somehow.