MurphyA/hacker-news huggingface dataset:
by johnnyanmac | 2025-10-05 20:45:33+00:00
I mean, I don't know if I can specifically find new grad tech industry that gets a tech job. But definitely look at hiring numbers in tech and among the youngest demographic. They both aren't good, like pretty much all jobs right now outside of healthcare

The BLS works as well, for now. I think that's quickly going to change with future reports.

This was also making the rounds last ywar: https://futurism.com/the-byte/berkeley-professor-grads-job-m...
by maximilianthe1 | 2025-10-05 20:45:38+00:00
Looks like you've committed `.env` file with private info. I suggest you change token immediately and add `.gitgnore`! That's a *security risk*!

It's best practice to keep env files private, but commit something like `template.env` with placeholder values.

Other than that - looks like a must-use tool for every roblox studio!
by hinkley | 2025-10-05 20:45:56+00:00
They were blue when I got there and while we discussed how blue was chosen that is the extent of my recollections of the time - that it was discussed but not the rarionale. They were inspired/informed by the range of colors available in CGA, ANSI and early VGA color palettes. You can’t use a color that doesn’t exist on low end hardware.

It would have made sense for Lynx to settle on blue for ergonomic reasons. ANSI blue is a particular shade thats approximated in hyperlink colors.
Ask HN: Any advice on pivoting out of VC-backed tech?
by AbstractH24 | 2025-10-05 20:46:22+00:00
I'm exploring moving away from work with VC-backed B2B SaaS startups and towards working with B2C businesses on Main Street.

For anyone else who's felt inclined to make a similar pivot - any advice? Particularly when it comes to remaining challenged, informed, and translating valuable hype-cycle concepts to people who don't care about hype.

While it's interesting to play with shiny toys, helping investors make money by creating products related to the hype-cycle de jour that get used by other B2B SaaS companies just feels soulless.

(My background is in GTM systems and data analytics mostly, but I think the question applies to anyone)
by timschmidt | 2025-10-05 20:46:40+00:00
We're getting into the weeds here, but once I learned of the 400ft sealevel rise at the younger dryas, it seemed immediately clear to me that this could be the great flood immortalized in so much myth and legend around the world.

Researchers have verified oral histories of at least 10,000 years age among Aboriginal Australians against date-able geologic events. Consequently, it is now clear that we can maintain such socially important information across such time.

It seems to me that we most likely fudged the exact date somewhere along the way.

Ancient peoples are often underestimated. But they were as smart and capable as ourselves, and possessed of a great deal more contemplative time and opportunity to observe the natural world around them.

Scientists are trained to look for faults and reasons to invalidate. It's the fundamental skill for eliminating hypotheses. And that is OK. But I believe there is useful information to be found in ancient culture if one is willing to consider it in good faith from the perspective of someone living through it.
by DaSHacka | 2025-10-05 20:47:01+00:00
> Except many STEM graduates are having a harder time finding jobs right now than liberal arts and humanities majors: https://www.newyorkfed.org/research/college-labor-market#--:....

Is that in both respective fields of study, though?

It aplears liberal arts/humanities majors are much more willing to work non-related jobs where their STEM collegues more strictly pursue relevant titles.

https://www.forbes.com/sites/christopherrim/2023/01/11/the-p...
by Theodores | 2025-10-05 20:48:33+00:00
Fascinating article. I am giving everything AI a wide birth for now, however, I do enjoy learning about how AI works. The question I have, is what does a LLM do when it encounters a new token? Can it actually learn from context, etymology and usage?

As I child I had no idea what many of the words meant in the newspaper and in literature but I could just pretend I knew what those words meant or get by without knowing what those words meant in full. In time I would gain familiarity with these words, able to make sense of them in context but not necessarily able to pronounce said words or be able to use them in my own writing. I certainly didn't stop what I was reading to get the dictionary out every time I encountered a new word, and this is how I think most people learn to read, with gradual changes with new words going from no idea to some familiarity to confidently able to use.

We aren't tokenising like the LLMs do and our languages are the product of many hundreds of thousands of years of development. So, how does an LLM learn words that have not already been tokenised? Or is this baked in?
by Terr_ | 2025-10-05 20:48:54+00:00
Perhaps extra-relevant to a story about data-loss, Milton was an employee who fell through the cracks in a broken corporate bureaucracy.

His was supposedly laid off years ago, but nobody actually stopped his paycheck, so he kept coming in to work assuming he was still employed, getting shuffled into increasingly-abusive working environments by callously indifferent managers who assume he's somebody else's problem.
by wizzwizz4 | 2025-10-05 20:49:18+00:00
No, nobody's trying to argue that gambling is by definition bad – that is to say, nobody's defining the category boundaries of "gambling" contingent on possessing the property "is bad". Some people have constrained the definition of "gambling" such that it only contains things they view as bad, and then observed that all the things they consider "gambling" are bad, but that's not the vacuous, circular claim you make it out to be.

In lieu of re-quoting other parts of the thread, I'll instead ask you to please re-read the arguments people have made, more slowly.
by AndrewKemendo | 2025-10-05 20:49:38+00:00
Then its firmly an organizational problem with how reward is allocated in human society.

Humans haven’t figured out how to include all humans and ecological systems into the same “tribe” and therefore the infighting between artificially segregated human groups, disconnected with ecological “externalities” which prevents a sustainable cooperative solution.

So most likely it will continue to be a small number of humans dominating the rest with increasingly powerful tools that reduce the number of humans required to act in active domination or displacement roles.

Humanity long ago decided that its everyone for themselves and to encode “might makes right” into ritual, mythology and organizational formation-operations.
by westurner | 2025-10-05 20:49:41+00:00
> "In the general field of electronics, one manipulates electron charge to process information," explains Xing Zhu, co-first author and PhD student in the unit. "In the field of spintronics, we exploit the spin of electrons to carry information. Going further, in valleytronics, the crystal structure of unique materials enables us to encode information into distinct momentum states of the electrons, known as valleys." The ability to use the valley dimension of dark excitons to carry information positions them as promising candidates for quantum technologies. Dark excitons are by nature more resistant to environmental factors like thermal background than the current generation of qubits, potentially requiring less extreme cooling and making them less prone to decoherence, where the unique quantum state breaks down

ScholarlyArticle: "A holistic view of the dynamics of long-lived valley polarized dark excitonic states in monolayer WS2" (2025) https://www.nature.com/articles/s41467-025-61677-2
Show HN: I hate paying for GPUs while developing – this is how I solved it
by Adithya-Kolavi | 2025-10-05 20:50:02+00:00
So let's face it, if you’re doing anything with deep learning, GPUs are essential.

They’re expensive, and setting up infrastructure is painful. Most of the time, your GPUs sit idle while you’re coding, yet you still pay for uptime when scripts fail on the first try.

I ran into this as a “GPU poor” researcher. Tasks like downloading datasets or transforming data don’t need a GPU, but traditional setups force you to use one. Cloud setups don’t help—VMs with GPUs require manual environment setup, CUDA installations, or Docker containers just to get started. Multi-GPU training adds more headaches: not all images support NCCL, so communication between nodes can fail

At my research lab[1], we run experiments across model training, synthetic data generation, and RL. We needed a setup that was flexible, reliable, easy to use and collaborate.

When I went looking for a solution that would let me write code locally and run it on GPUs instantly, without worrying about infrastructure, multi-node setups, or idle GPU time, I stumbled upon Modal [2], and after a year of using it, it’s been a game-changer: it increases our research throughput and productivity, saves a ton on GPU costs and infrastructure management, and allows us to ship really fast.

I’ve compiled everything we’ve learned into this blog + hands-on tutorial [3], with three examples showing different ways to use Modal: rapidly develop on GPUs, deploy at scale, and do it all without breaking a sweat over infrastructure.

Here’s what we cover in the blog: - Wrapping existing code to run on Modal’s serverless infrastructure. - Handling datasets on Modal with volumes for seamless access. - Writing training scripts using Unsloth and Axolotl for easy fine-tuning. - Serving models in a scalable, high-throughput way with vLLM.

By the end, you’ll know how to write and experiment locally and run on GPUs instantly—no idle bills, no complex environment setup, no multi-node headaches.

[1] https://cognitivelab.in [2] https://modal.com [3] https://aiengineering.academy/LLM/ServerLessFinetuning/
by Veedrac | 2025-10-05 20:50:22+00:00
It's wild that after a hundred years there is still exponential progress in the power output of cars. The most unusual part to me is how EVs are fundamentally a consumer technology, so it all rapidly falls into mass production territory; eg. Xiaomi sells a 1527hp car for $73k. Horsepower is rapidly reaching 'solved' territory; even at its record speed, BYD's car wasn't even power limited.
by terminalshort | 2025-10-05 20:50:58+00:00
This argument, which I find very typical of arguments in favor of humanities education, kind of drives me nuts. It's very nebulous in terms of how these benefits are actually related to humanities classes. I place very little value on degrees in general, but at least I can sometimes see very clearly how other engineers I work with sometimes know useful things that I don't know from CS classes because they are directly related to the subject matter at hand. But nothing you are mentioning here is at all like that.

Yes, of course it is beneficial to be "more aware of/able to comprehend situations involving others and their motivations," but there isn't a class on that and I see no relation between social skills and education (at any level or field of study). I would take a HS dropout sales guy over a phd in humanities any day in terms of this particular skill.
by Veserv | 2025-10-05 20:51:31+00:00
Elon Musk currently owns 12% of Tesla. Claiming he gets “ZERO compensation” outside of stellar performance is nonsense. If Tesla actually reached a 8T dollar valuation his net worth would increase to 1T dollars without any additional grants or investor dilution.

He currently directly shares 12% of the growth of Tesla, far more than most executive teams which are viewed to be adequately aligned with far less ownership. Claiming there is no incentive to perform is nonsensical and incoherent.
by 1718627440 | 2025-10-05 20:52:03+00:00
Well, there is immigration and there is immigration. There are people that move between similar socialized countries, directly from one high-paying job to the next. Every country wants to have them. Then there are basically refugees, that are only named immigrants, because they happen to flee through another country. They might also have had a well paying job, but they often need to learn the language, they often need to learn the economic system, the law system, the social norms, etc. This takes quite some investment, both in time and money from them and the society they migrate to. Learning these things already takes years for young people, whose only job is to do this. It's much harder for an adult, because learning complete new things is harder for adults and they also need to cover the bills. They can be the smartest person in their country, but they will still struggle. On top, they need to fight with the immigration offices, have family abroad they want to support, might intend to return to their home, instead of settling. Thus, they will be an investment first, rather then an asset. Some place the time frame for this to be 18 years. I question whether investing in children is really the worse approach. Even when it is, then it is quite immoral to let another poorer country pay the bills for their education and then import them.

> Immigrants built America.

These were masses building a new country, not integrating into an existing; they had a way lower living standard, a lot of them died. It did not go well for the existing society in America. The people forming the government were british rich aristocrats. And don't think these situations are comparable.
by numpad0 | 2025-10-05 20:52:08+00:00
The reasons we're here are:

- By far the most popular use case of digital pens is drawing arts on a computer. Often anime, sometimes 3D. - Wacom is the king for artists. They also still hold some patents btw. - Wacom is DEFINITELY NOT THE KING for note taking and other non-art purposes. Laggy, parallax is huge, API is proprietary, etc. - Due to above, both Microsoft and Apple tried to replace Wacom by various means with not anime art use cases in mind but not ruling it out completely, from buying Israeli startups to reinventing stylus. - The situations up until here threatened Wacom enough that it started upgrading and fragmenting pen implementations. - The situations down to this line caused bunch of players to join into the game, further fragmenting implementations. - And that had caused bunch of incompatible pen implementations, with limited successes with various standardization attempts. And here we are. - And by the way, Wacom is still the king for most pen buyers.
by alwa | 2025-10-05 20:52:26+00:00
Not sure “sane backup strategy” and “park your whole government in a private company under American jurisdiction” are mutually exclusive. I feel like I can think of a bunch of things that a nation would be sad to lose, but would be even sadder to have adversaries rifling through at will. Or, for that matter, extort favors under threat of cutting off your access.

At least in this case you can track down said officials in their foxholes and give them a good talking-to. Good luck holding AWS/GCP/Azure accountable…
by simonw | 2025-10-05 20:52:41+00:00
Glitch tokens should be tokenizer-specific. Gemini uses a different tokenizer from the OpenAI models.

The origins of the OpenAI glitch tokens are pretty interesting: the trained an early tokenizer on common strings in their early training data but it turns out popular subreddits caused some weird tokens to be common enough to get assigned an integer, like davidjl - a frequent poster in the https://reddit.com/r/counting subreddit. More on that here: https://simonwillison.net/2023/Jun/8/gpt-tokenizers/#glitch-...
by magnetar20 | 2025-10-05 20:52:48+00:00
Tinnitus, the perception of ringing or buzzing in the ears without an external source, is often described as a lifelong condition. While there is currently no universal cure, living with tinnitus does not mean you are without hope. The human brain has an extraordinary ability to adapt and rewire itself through a process called neuroplasticity, which can be harnessed to help reduce the impact of tinnitus and train the brain to tune it out.

Understanding Tinnitus and the Brain Your brain is built from complex networks of nerve cells that communicate through structures called synapses. In tinnitus, some of these networks in the auditory system become hyperactive and start sending false signals. These signals are misinterpreted by the brain as sound, which creates the constant ringing, buzzing, or hissing sensation.

Neuroplasticity is the brain’s natural ability to reorganize its connections. In simple terms, it is the brain’s way of reprogramming itself. This ability can be used to form new pathways and weaken the brain’s response to the abnormal signals that cause tinnitus. Over time, this process can reduce how noticeable or bothersome the condition feels.

How to Trigger Neuroplasticity Neuroplasticity is not something that happens passively; it can be encouraged and strengthened through different activities. Several methods have been shown to help:

1. Mental Stimulation Challenging your brain with activities like learning a new skill, reading, or solving puzzles stimulates new connections in the brain. Regular mental engagement helps the brain adapt and can reduce how strongly it focuses on tinnitus sounds.

2. Physical Activity Light to moderate exercise, such as jogging, yoga, or cycling, can promote neuroplasticity. Physical activity improves blood flow, reduces stress, and encourages the release of growth factors that help the brain form new neural pathways. Stress reduction is particularly important, as stress often worsens tinnitus perception.

3. Sound Therapy One of the most researched methods for tinnitus management is sound therapy. By introducing carefully selected sounds, the therapy encourages the brain to shift focus away from tinnitus and reorganize its response to auditory input.
Show HN: Orchestro – Trello for Claude Code (open-source MCP server)
by danielepelleri | 2025-10-05 20:52:50+00:00
I built Orchestro, an open-source MCP server + web dashboard for Claude Code. The short version: “Trello for Claude Code” — with a built-in “scrum master” that keeps the board honest and agents that move cards from goal → tasks → code as work happens.

Why - Hidden state in prompts, invisible dependencies, lossy handoffs goal→tasks→code. - PMs and devs don’t share the same live view of progress.

What it does - Kanban that actually executes: plan on the board, MCP tools drive the flow. - Auto “scrum master”: decomposes stories, sets deps, enforces sane state transitions. - Agents prepare context-rich prompts for Claude and move cards across columns. - Realtime board (Socket.io), dependency graph, audit trail. - Local-first: your data lives in your Supabase project. MIT licensed.

Quick start (~2 min) npx @orchestro/init npm run dashboard (opens http://localhost:3000) restart Claude Code, then ask: “Show me orchestro tools” (~60 tools)

Tech TypeScript MCP server, Next.js dashboard (React Flow), Supabase (PostgreSQL + RLS).

What I’m looking for - Heavy Claude Code users to test and tell me what hurts (missing tools, bad UX, slow paths). - Real-world feedback on the “agents move the cards” model. - PRs/issues welcome. A star helps discoverability if it’s useful.

Links Website: https://www.orchestro.org/ Repo: https://github.com/khaoss85/mcp-orchestro
by jncfhnb | 2025-10-05 20:52:56+00:00
Idk man I think maybe you should consider that there’s no upside to this insecurity.

I’ve blitzed through the formerly famous Tokyo subway system mindlessly without a clue.

I have utterly no idea what the different us highways in my area are but it’s never really affected me besides being unable to join in mundane discussions of traffic on 95 or whatever
by evanreichard | 2025-10-05 20:53:15+00:00
This year I redid my whole lab as well and prioritized declarative everything so it'd be easy to go from scratch if needed. So I've got nix to create RKE2 images with cloud-init for XCP-ng templates, Terraform with XenOrchestra provider, and ArgoCD for the K8s cluster.

I've got two R640's so I can live migrate, and an R720XD with TrueNAS (democratic-csi for K8s persistence). QSFP (40Gb) for TrueNAS / R720XD, and SFP+ (10Gb) for R640's linked to a Brocade ICX 6610.

So I can update the hosts, and K8 nodes with 0 downtime. Do I need it? No, but I learned a lot and had / have fun deploying and maintaining it.
by westurner | 2025-10-05 20:53:19+00:00
> Those specific risk factors, the data revealed, were:

> - Blood pressure ≥120/80 mm Hg or on treatment

> - Total cholesterol ≥200 mg/dL or on treatment

> - Fasting glucose ≥100 mg/dL, diagnosis of diabetes or on treatment

> - Past or current tobacco use

ScholarlyArticle: "Very High Prevalence of Nonoptimally Controlled Traditional Risk Factors at the Onset of Cardiovascular Disease" (2025) https://www.jacc.org/doi/10.1016/j.jacc.2025.07.014
by Johnny555 | 2025-10-05 20:53:33+00:00
I think that alluded to that earlier in the article:

>However, due to the system’s large-capacity, low-performance storage structure, no external backups were maintained — meaning all data has been permanently lost.

I think they decided that their storage was too slow to allow backups?

Seems hard to believe that they couldn't manage any backups... other sources said they had around 900TB of storage. An LTO-9 tape drive holds ~20TB uncompressed, so they could have backed up the entire system with 45 tapes. At 300MB/sec with a single drive, it would take them a month to complete a full backup, so seems like even a slow storage system should be able to keep up with that rate. They'd have a backup that's always a month out of date, but that seems better than no backup at all.
by hinkley | 2025-10-05 20:56:12+00:00
We’ve had Byzantine crypto key solutions since at least 2007 when I was evaluating one for code signing for commercial airplanes. You could put an access key on k:n smart cards, so that you could extract it from one piece of hardware to put on another, or you could put the actual key on the cards so burning down the data center only lost you the key if you locked half the card holders in before setting it on fire.
by a_wild_dandan | 2025-10-05 20:56:14+00:00
This might be a dumb question but like...why does it matter? Are other companies reporting training run costs including amortized equipment/labor/research/etc expenditures? If so, then I get it. DeepSeek is inviting an apples-and-oranges comparison. If not, then these gotcha articles feel like pointless "well ackshually" criticisms. Akin to complaining about the cost of a fishing trip because the captain didn't include the price of their boat.
by pengaru | 2025-10-05 20:56:17+00:00
> I did not expect that anyone would take the first part of my comment seriously, but here we go.

> However, this year a Ford SuperVan 4.2 made the Nordschleife in 6:48.393, so even without Sabine Schmitz a van was faster than the BYD.

You are spouting such absurdities, that is a van in name only:

https://carbuzz.com/nurburgring-ford-supervan-42-lap-record-...

And it was driven by Romain Dumas someone far more qualified to set such a record than Sabine Shmitz - despite your "even without Sabine Shmitz" disingenuous wording. Sabine is half television personality half racing driver...
by tcbawo | 2025-10-05 20:57:16+00:00
> Whose_ destructor, if not the receiving-type

The receiving type should control the lifetime of any callbacks to itself that it gives away. The destructor is the best place to ensure this gets properly cleaned up.

Like anything, custom callbacks can be used well or misused. Design is a matter of expertise and taste bordering on an art form. Connecting framework implementation and business logic can be done cleanly or clumsily. I am skeptical of an argument that callbacks have a code smell prima facie.