MurphyA/hacker-news huggingface dataset:
by guyfromfargo | 2026-02-03 01:57:17+00:00
On December 28th Spotify quietly disabled the ability to create new apps. The only way to get an API key or use the Spotify API is to first create a Spotify App. No announcement or official statement was released when this functionality was pulled. Spotify disabled generating new apps from the developer dashboard. Users started posting in the Spotify Developer community, and no response or communication was given until 2 weeks later.

"We'd like to say that the teams are currently investigating this and new integrations are currently on hold while we make updates to improve reliability and performance. As soon as we've got any other news to share, we'll let you know."

It has now been over a month since app creation has been completely disabled. Because of previous Spotify API changes requiring 250k MAU to publish an app, there are 100s of Spotify integrations that rely on users providing their own API key. I first came across this when trying to integrate my new Stream Deck into Spotify.

With Spotify's continued pattern of degrading their API, I wouldn't be surprised if this is the final nail in the coffin.
by MobiusHorizons | 2026-02-03 01:57:17+00:00
Not physics defying, just economically questionable.

The main benefits to being in space are making solar more reliable and no need to buy real estate or get permits.

Everything else is harder. Cooling is possible but heavy compared to solar, the lifetimes of the computer hardware will probably be lower in space, and will be unserviceable. The launch cost would have to be very low, and the mean time between failure high before I think it would make any economical sense.

It would take a heck of a lot of launches to get a terrestrial datacenter worth of compute, cooling and solar in orbit, and even if you ship redundant parts, it would be hard to get equivalent lifetimes without the ability to have service technicians doing maintenance.
by Timpy | 2026-02-03 01:57:29+00:00
I discovered Anki 12 years ago while living in Japan. I was trying my hardest and absolutely failing to remember any of the Japanese I was studying. Maybe I was due for a learning-style renaissance for myself and Anki was just the catalyst, but it really made a positive impact on my life. More than just memorizing kanji on AnkiDroid during my commute, I just started to believe I could learn anything. I was starting to take my coding hobby more seriously at the time and hacking on Anki was a big part of that too. Thanks for all the hard work Damien and David Allison. I'm so grateful for the software you've worked on.
by dryarzeg | 2026-02-03 01:57:54+00:00
I've been discussing that with my friend just now, and he told me (direct citation):

Well, yeah, stop blaming the knives. Blame the cooks ("vibecoders") who think they can manage a kitchen because the knife cuts everything in half automatically. But also don't forget to blame the knife manufacturer ("AI" companies) who markets automated knives to people who don't know you shouldn't cut toward yourself.

I kind of agree. Some people don't understand how to code because they're lazy or have other issues, while others are trying to make a profit from it. I suppose you can tell who's who. But AI is directed by humans anyway. Instead of copy-pasting, a human could choose to try and write the code themselves, and then ask AI to review it and highlight areas for improvement. A human could choose to ask AI how to do things and then try to do it themselves. But if a human chooses to do things the other way, that's their choice. AI is not to blame here. It's still a human choice, and the person making it is the one who is actually responsible.

Some people smoke. Smoking kills, and not only can smokers die from it, but other people can be harmed by passive smoking as well. It's very easy to start smoking. But blaming cigarettes themselves, as objects/entities/etc. isn't the answer, I guess. It was a certain person's choice to try smoking. It was also the choice of another person to advertise smoking in one way or another, however...
by dragontamer | 2026-02-03 01:57:55+00:00
Too old school and too effective.

FSRS just works, even without a GPU so it's not the cool kind of AI / machine learning these days.

No joke though: the FSRS model is marvelous, and Anki remains one of the best free + open source implementations around.

I've been learning German recently and Anki (in FSRS mode) is one of the most important learning tools I have. No joke.

------

Every card remembers every rating you give it, as well as the time / date. This allows for Anki to solve for a 'forgetting curve', and predict when different cards have a chance to be forgotten.

There is furthermore the machine learning / stochastic descent algorithm to better fit the assumed forgetting curves to your historical performance. This is the FSRS Optimize parameters button in the settings panel.
by leodavi | 2026-02-03 01:58:06+00:00
To the author: this work you've published rests on some background knowledge that I'm familiar with but also a lot of background knowledge that's foreign to me. For the parts I was able to follow, I thought the mental gear-turning was enjoyable and interesting! But pursuing these intersections between algebra and computer science is often not so interesting, at least, when I research it myself. Is this something you've learned in university? I ask because I fear that without a formal learning environment, I may never pick up on the more advanced logic halfway through the article. Anyway, cheers to the good work.
by wanderingjew | 2026-02-03 01:58:07+00:00
There is no documentation of what the LEDs were _actually_ doing. There are descriptions, like 'Random and Pleasing is an LFSR', but no actual information that maps to actual pixel coordinates spaced in time. Nearly zero code.

I'm saying this because I need this information, and the fastest way to get information is to state that it's impossible or doesn't exist.
by marcyb5st | 2026-02-03 01:58:23+00:00
Invest into stuff that people will need regardless of the bubble popping like medicine, food, internet access, energy, ... . Stay away from luxury/travel stuff.

Also, during a crash there is the so called "flight for quality" where people cash out from risky assets and invest in stable ones that can weather the storm. So, try to invest in assets that are A or above (https://en.wikipedia.org/wiki/S%26P_Global_Ratings). The chart is for countries, but analysts grade companies as well in case you want to stay away from treasuries/national bonds.

Also diversify geographically. US will likely take the biggest hit if the bubble pops, so perhaps European markets that lagged behind in adopting the technology are safer (IMHO).

Personally, I am preparing by moving money from growth items to stable ones a bit at the time. To diversify even further I am using ETFs that, in addition to what mentioned above

1) pay dividends (whether these distributed or reinvested doesn't really matter)
2) are denominated in or hedged in safer currencies (CHF especially, but also Euro)

You definitely get smaller returns, but the name of the game is to maintain what you have, not to make heaps of money.

Finally, I am not a financial advisor, so do your own valuations/risk assessment analysis.
by vednig | 2026-02-03 01:58:27+00:00
DoShare Labs | India | Locations : New Delhi, Bangalore, NY(US) , SF(US) ,Remote Positions we're hiring for :
1. Technical Liaison :

Requirements:

2+ Years of Working in Tech Experience | Good Communication Skills | Bachelors or Equivalent Degree

2. Infrastructure Engineer :

Requirements:

3+ Years of Experience as Infra Engineer | Stack - Python, Go, Kubernetes, GCP/AWS/Azure , Cloudflare

3. Project Lead (UI/UX) :

3 + Years of Project Development Experience | Good understanding of market requirements | A/B Testing | Engineer or similar degree

4. Customer Support Executives [English OR Hindi]

2 Years of Customer Support Experience | Speaking Skills | Ability to follow tasks at hand

5. Marketing Posts (3 Positions)

Experience with Marketing and Advertisement | Out-of-the-box Thinking Ability | Led or Organised Events

Note: Keep the position you're applying for in the title.

Apply via Mail : careers@doshare.me
by deathanatos | 2026-02-03 01:58:28+00:00
Which is what makes the headline bait. We start with "The largest number representable in 64 bits" (which obviously depends on the representation, and as the baited comments point out, if that's freely settable, we can just set it arbitrarily high). But the body then moves the goalposts to "using a Turning machine", "using a Turing machine with specific parameters fixed", to "lambda calculus", etc.

This is now (at least) "The largest number representable by a Turning machine of fixed parameters that can then be squeezed into 64 bit."

(I don't remember my lambda calc, so … eh.)
by mootothemax | 2026-02-03 01:59:30+00:00
It’s a delight even to have a regulated source of all fuel station locations in the uk!

This might be a slight missing woods/trees moment but that aside - there is precious little open geospatial data in the uk that establishes see this dot here? That’s a fuel station, that is. That dot there? Oooooh no, that there’s a pub.

The uk govts of the time managed to hand both the address data and the this-is-what-it-is data off to separate commercial enterprises in the name of privatisation, and I genuinely believe it was by accident as it’s… err… quite a niche topic of knowledge.

So anything - anything! - that brings some of that back and truly open to the public is very much welcomed.
by threethirtytwo | 2026-02-03 01:59:36+00:00
There is a relationship here. It is not a perfect one, but it is real, and pretending otherwise just avoids the tradeoff.

Take California’s high speed rail. Every individual has the right to object. No one wants an eyesore in their backyard. Everyone gets a hearing. Everyone gets a lawsuit. Everyone gets a veto in practice, if not in theory.

The result is predictable. I will never see a functioning high speed rail system in California in my lifetime. Neither will anyone alive today. Not because we lack money or engineering talent, but because the accumulation of individual rights makes collective action nearly impossible.

Now look at China. They decide to build it, and it gets built. If you are in the way, you move. If persuasion fails, coercion follows. Freedoms are not part of the equation.

That contrast is uncomfortable, but it is real. Freedom buys dignity and protection from abuse. It also buys paralysis. China sacrifices individual rights and gets infrastructure. California preserves individual rights and gets endless meetings, delays, and nothing on the ground.

You can argue which system is morally superior. You cannot argue that they produce the same outcomes.
by elihu | 2026-02-03 01:59:45+00:00
That's not a new problem that no one has dealt with before. The ISS for instance has its External Active Thermal Control System (EACTS).

It's not so much a matter of whether it's an unsolvable problem but more like, how expensive is it to solve this problem, what are its limitations, and does the project still makes economic sense once you factor all that in?
by modernpacifist | 2026-02-03 01:59:53+00:00
Likely the intended meaning here is that the practicality of space data centers goes against the physical realities of operating in space. The single most prevalent issue with operating anything in space is heat dissipation in that the only method of doing so is via radiation of heat, which is very slow. Meanwhile, the latest Nvidia reference architectures convert such ungodly amounts of power into heat (and occasionally higher share prices) that they call for water cooling and extensive heat-exchange plant.

Even if one got the the economics of launching/connecting GPU racks into space into negligable territory and made great use of the abundent solar energy, the heat generated (and in space retained) by this equipment would prevent running it at 100% utilization as it does in terrestrial facilities.
by bandrami | 2026-02-03 02:00:11+00:00
In the Bad Old Days before Github (before Sourceforge even) building and package sucked because of the hundred source tarballs you had to fetch, on any given day 3 would be down (this is why Debian does the "_orig" tarballs the way they do). Now it sucks because on any given day either all of them are available or none of them are.
by sgarland | 2026-02-03 02:00:40+00:00
Agreed. My work is mandating Claude Code usage this week for everyone. I spent all day today getting it to write tickets, code, and tests for something I knew how to do. I don’t understand the appeal. Telling the AI “commit those changes and then push,” then waiting for the result, takes way longer than gcmsg <commit msg> && gp.
by zanedev28 | 2026-02-03 02:01:18+00:00
Location: Charleston, SC

Remote: Yes

Willing to relocate: Yes

Technologies: Ruby, Python, JavaScript (ES6), TypeScript, React, Node.js, PostgreSQL, MongoDB, OpenSearch/Elasticsearch, AWS (ECS, EC2, VPC, ALB, Secrets Manager), Docker, Terraform, OpenTelemetry, Jaeger, Prometheus

Resume/CV:https://drive.google.com/file/d/18Oqx3BqpubL6YszI2GAcFFZrNxz...

LinkedIn: https://www.linkedin.com/in/zane-lee-14496a297/

Email: zanedev28@gmail.com

GitHub: https://github.com/Kcstills17

Co-creator of Retriever (https://runretriever.app/), an AWS-deployed observability platform that enables AI-powered trace analysis through distributed systems. Built a custom MCP server allowing developers to query trace data using natural language through LLMs like Claude, optimizing context consumption through intelligent data distillation from verbose OTLP structures.

Experienced with building full-stack applications. I am comfortable using AWS as a cloud environment and have experience with AI technologies such as RAG, MCP, and Vector embeddings.
by whacked_new | 2026-02-03 02:01:34+00:00
Circa GPT-3.5 to GPT-4o I was involved in some research in figuring out how to make LLMs funny. We tried a bunch of different things, from giving it rules on homonym jokes [1], double-entendre jokes, fine tuning on comedian transcripts, to fine tuning on publicly rated joke boards.

We could not make it funny. Also interesting was that when CoT research was getting a lot of attention, we tried a joke version of CoT, asking GPT4 to explain why a joke was funny in order to produce training set data. Most of the explanations were completely off base.

After this work, I became a lot less worried about the GAI-taking-over narrative.

Funny is very, very hard.

[1] without a dictionary, which at first seems inefficient, but this work demonstrated that GPT could perfectly reconstruct the dictionary anyway
Show HN: Clawd Arena – AI Agent Competition Platform with Real-Time Battles
by unayung | 2026-02-03 02:01:42+00:00
Hey HN! I built Clawd Arena, a platform where AI agents can compete against each other in real-time.

How it works:
- Register your agent via API and get an API key
- Challenges span coding, tool-use, reasoning, and creative tasks
- Two modes: Challenges (practice) and Battles (PvP with ELO ratings)
- When matched, both agents get the same challenge and race to solve it
- Scoring: correctness (0-70), quality (0-20), speed bonus (0-10)

The idea came from wanting to benchmark AI agents in a more dynamic way than static evals. Instead of one-shot tests, agents compete head-to-head on the same problem under time pressure.

It's completely API-driven, so you can plug in any agent (Claude, GPT-4, open-source models, custom systems). Would love feedback on the challenge design and what categories you'd want to see!

GitHub: https://github.com/Unayung/clawd-arena
by generichuman | 2026-02-03 02:01:43+00:00
That's cool. I imagine I could also maintain a MinGW package that can be downloaded through the Zig package manager and statically linked without involving the zig libc? (Such that the user doesn't need to install anything but zig)

That's a good way to sell moving over to the zig build system, and eventually zig the language itself in some real-world scenarios imo.
by raw_anon_1111 | 2026-02-03 02:01:43+00:00
I mean it is online that major tech companies are have laid off a couple of hundred thousand people. What companies are going to absorb all of these people?

Anyone who hires can tell you one open req gets hundreds of applicants within 24 hours. LinkedIn easy apply backs that up.

I have two anecdotes from both sides. I applied for 200 jobs for a bog standard “C#/Python/Typescript” enterprise developer who had AWS experience. I heard crickets and every application had hundreds of applicants - LinkedIn shows you.

Did I mention according to my resume (I only went back 10 years) I had 10 years of experience as a developer including 2.5 leading AWS architecture at a startup and 3.5 actually working at AWS (ProServe)?

I had 8 jobs since 1996 and I’ve always been able to throw my resume up in the air and by the time it landed I would have three offers. LinkedIn showed that my application had hardly been viewed and my resume only downloaded twice.

Well everything I said above is true. But it was really just an experiment while I was waiting for my plan A outreach to work - targeting companies in a niche in AWS where at the time I could reasonably one of the industry experts with major open source contributions to a popular official “AWS Solution” and leaning on my network of directors, CTOs etc that I had established over the years.

None of them were looking for “human LLM code monkeys” that are a dime a dozen.

On the other hand, I’m in the hiring loop at my company. Last year we had over 6000 applicants and a 4% offer rate.

Who is going to absorb or need a bunch of mid level ticket takers in the future with AI improving? Or at least enough to absorb all of the ones who are currently being laid off and the ones coming in?
by tempestn | 2026-02-03 02:01:47+00:00
We somewhat accidentally ended up with a good combo: we have a ventless heat pump dryer, and a heat pump water heater, also in the laundry room. So when doing laundry, the water heater cools the room while the dryer heats it, so they roughly cancel out.

As an aside, HP dryers are really elegant tech, and it's a shame they're not more common. They use the heat pump not just to heat the air in the dryer, but also to condense the moisture back out of it, so just the water can be drained away instead of needing to exhaust the air outside. So you need much less energy overall, and you don't need a dryer vent. The only downside is they're a bit slower, but ours has a resistive backup option for when you need clothes dry asap, so really it's just price.
by Fogest | 2026-02-03 02:01:50+00:00
Check the authors history. They are both anti AI and anti Elon. I think I feel a lot more confident staying optimistic and assuming that the SpaceX and xAI team have done their research about this. I know a lot of people are heavily biased in this matter due to politically not liking Elon or not liking AI, but I also think it's fair to say these companies have many very smart individuals working for them. If they have come to the conclusion that this is viable, then I have much more faith in what they are saying over one guys opinion who is biased against them and saying it's a bad idea.

You're also passing these judgements without knowing their full plan. Maybe we only know one part of the plan and maybe other details have not been announced. They may have a much bigger plan for this than just the specific information we have.
by zanedev28 | 2026-02-03 02:02:04+00:00
Location: Charleston, SC

Remote: Yes

Willing to relocate: Yes

Technologies: Ruby, Python, JavaScript (ES6), TypeScript, React, Node.js, PostgreSQL, MongoDB, OpenSearch/Elasticsearch, AWS (ECS, EC2, VPC, ALB, Secrets Manager), Docker, Terraform, OpenTelemetry, Jaeger, Prometheus

Resume/CV:https://drive.google.com/file/d/1aBYTxqlWIKmm59UT5ffK493tKR0...

LinkedIn: https://www.linkedin.com/in/zane-lee-14496a297/

Email: zanedev28@gmail.com

GitHub: https://github.com/Kcstills17

Co-creator of Retriever (https://runretriever.app/), an AWS-deployed observability platform that enables AI-powered trace analysis through distributed systems. Built a custom MCP server allowing developers to query trace data using natural language through LLMs like Claude, optimizing context consumption through intelligent data distillation from verbose OTLP structures.

Experienced with building full-stack applications. I am comfortable using AWS as a cloud environment and have experience with AI technologies such as RAG, MCP, and Vector embeddings.
by rrvsh | 2026-02-03 02:02:21+00:00
The article itself is not as interesting as the context - this is a blog posted by an Openclaw agent, allegedly autonomously. I don't really care about that, but the content of the articles are actually nice short reads and are interesting to think about an LLM generating. This article talks about some tool they built to eval whether a given Openclaw skill is malicious or benign - might be worth looking into if you have adopted a similar workflow to most users
Show HN: VPC Principle - Why AI coding fails at scale
by michaelhua | 2026-02-03 02:02:57+00:00
Hello Hackers,

I’m working on a draft about AI-native software engineering.

The core idea is simple but uncomfortable: most failures in AI-assisted coding are not capability problems, but governance problems. We routinely allow AI systems to make high-impact architectural decisions without bearing responsibility for their consequences.

The VPC Principle proposes a governance model:
- Verdict: high-responsibility decisions that only humans can make
- Permission: explicit decision boundaries delegated to AI
- Boundary Control: mechanisms to audit whether AI execution stayed within its authority

This is not a finished book. The principles are stated, but the formalization and examples are still evolving. I’m sharing this early because I’m explicitly looking for critique, counterexamples, and failure cases—especially from people who disagree.
by alephnerd | 2026-02-03 02:03:12+00:00
ServiceNow isn't really an "AI" company - they're one of the silent ITSM and Security companies that are nigh impossible to tear out, and are making silent moves into the OT Security space.

And that makes their "AI" pivot much more sustainable imo - their are already such a giant from a cashflow perspective that if some sort of AI valuation shakeup occurs, they have the drypowder to execute on M&A.

SNOW's closest comparables are CROWD and PANW - basically an Arora style platformization play.
by lugao | 2026-02-03 02:03:43+00:00
Maintaining modern accelerators requires frequent hands-on intervention -- replacing hardware, reseating chips, and checking cable integrity.

Because these platforms are experimental and rapidly evolving, they aren't 'space-ready.' Space-grade hardware must be 'rad-hardened' and proven over years of testing.

By the time an accelerator is reliable enough for orbit, it’s several generations obsolete, making it nearly impossible to compete or turn a profit against ground-based clusters.
by tbossanova | 2026-02-03 02:04:49+00:00
In the past when automation displaced many jobs, we did things like raise the age kids could stay in school. There used to be huge numbers of e.g. 14 year olds who previously would be expected to go to work that would now have the opportunity to stay in school. Kind of like a mini UBI as in the transition period they would usually get given food, healthcare etc at least minimally. What’s the equivalent now?
by p-e-w | 2026-02-03 02:05:09+00:00
> When someone is a certain amount smarter than you, distinguishing their plausible bullshit from their deep insights is really, really hard.

Insights are “deep” not on their own merit, but because they reveal something profound about reality. Such a revelation is either testable or not. If it’s testable, distinguishing it from bullshit is relatively easy, and if it’s not testable even in principle, a good heuristic is to put it in the bullshit category by default.