MurphyA/hacker-news huggingface dataset:
by libraryofbabel | 2026-02-06 00:07:30+00:00
I wonder too. It might be that progress on the underlying models is going to plateau, or it might be that we haven't yet reached what in retrospect will be the biggest inflection point. Technological developments can seem to make sense in hindsight as a story of continuous progress when the dust has settled and we can write and tell the history, but when you go back and look at the full range of voices in the historical sources you realize just how deeply nothing was clear to anyone at all at the time it was happening because everyone was hurtling into the unknown future with a fog of war in front of them. In 1910 I'd say it would have been perfectly reasonable to predict airplanes would remain a terrifying curiosity reserved for daredevils only (and people did); or conversely, in the 1960s a lot of commentators thought that the future of passenger air travel in the 70s and 80s would be supersonic jets. I keep this in mind and don't really pay too much attention to over-confident predictions about the technological future.
by nl | 2026-02-06 00:08:15+00:00
I don't understand what this comment is trying to say.

The commentator mannykannot didn't really comment on the politics other than to agree that 1984 is a criticism of Stalism (which... I don't think anyone would argue with?).

Orwell also wrote "Animal Farm" which is a criticism of Fascism, and Asimov leads with this.
by ajross | 2026-02-06 00:08:53+00:00
Yeah, that's sort of the market that's picked it up: "I need to connect to old junk". And it would seem like a great fit, except that (as you point out) volumes are tiny and the benefit of a $1 chip vs. a $10 FPGA is high only at scale.

I just checked, and that board is $70. Here's a significantly more capable device with an ESP32 and a iCE40 FPGA which could do the same things and more for $100:

https://groupgets.com/products/ice-v-wireless

I have one and it works great, though not many people picked it up. It's actually available for $50 now, it looks like they're liquidating what they bought.

Point being: is PIO really enabling new solutions in this market? No. At best it's providing a ~30% reduction in retail price for some oddball niche applications. Is that worth the cost of spinning the masks for the chip? IMHO, no.
by NewsaHackO | 2026-02-06 00:09:06+00:00
PIN numbers are easier to remember. Remember, 99% of the population does not care about defense against state actors, just stopping nosy co-workers or family members from looking at their stuff. The next group (which I would include myself in) is concerned about theft (both physical and remote), where someone can get "unlimited" access to your machine and may be able to defeat a short PIN but is unlikely to beat a strong password. If you are in the realm of defending against state actors, then that is something you have to take multiple steps to ensure, and a single slip-up will tank your operation (like with this lady).
by TacticalCoder | 2026-02-06 00:09:07+00:00
> When I read the first sentence, I expected the author to use `git bisect`.

Exactly the same. I'd first (or have Claude or whatever) use git bisect. Then I'd focus on the commit that is problematic. And why not have the "binary" detective work TFA talks about.

That said... 1600 ms per heart emoji. Unicode strikes again, combined with a fallback to SVG because that font couldn't color a heart emoji. What a rube-goldberg of a kitchen sink world we live in. It's just sad really.

Honestly beam me back up to the late 80s or early 90s: give me a car with pop up headlights, a Hi-Fi stereo with a CD player, an arcade cab, a Commodore Amiga and my ASCII charset. Life was better.

P.S: nice TFA btw, I enjoyed it
by mlsu | 2026-02-06 00:09:29+00:00
Flock is just, yet another failed IT project. it shouldn't be too hard.

Well I think this is the issue. The value of Flock is not what it says on the tin, it's everything else. Solving petty crimes yeah sure, yadda yadda. Ever had your bike stolen and told a cop about it?

It's the tracking part. That's where the juice is. Well obviously it'd violate the 4th amendment to slap a GPS tracker on your car to see if you're going to [known antifa member's] house - we'd never do that, but gee, this private company just happens to have a database of everywhere every person's car has ever been ...
by tialaramex | 2026-02-06 00:09:53+00:00
Virtually none of the gas power in the UK is traditional "peakers" aka Open Cycle Gas Turbines. There's a lot of Combined Cycle Gas Turbines. Gas is much more expensive in the UK than, say, the US and so it doesn't make much sense to build OCGT because although they're cheap to build they are very inefficient so your bid prices will be really high.
by lima | 2026-02-06 00:10:11+00:00
Postgres replication, even in synchronous mode, does not maintain its consistency guarantees during network partitions. It's not a CP system - I don't think it would actually pass a Jepsen test suite in a multi-node setup[1]. No amount of tooling can fix this without a consensus mechanism for transactions.

Same with MySQL and many other "traditional" databases. It tends to work out because these failures are rare and you can get pretty close with external leader election and fencing, but Postgres is NOT easy (likely impossible) to operate as a CP system according to the CAP theorem.

There are various attempts at fixing this (Yugabyte, Neon, Cockroach, TiDB, ...) which all come with various downsides.

[1]: Someone tried it with Patroni and failed miserably, https://www.binwang.me/2024-12-02-PostgreSQL-High-Availabili...
Show HN: IncidentFox, AI SRE that auto-builds its own integrations (open source)
by chiehminwei | 2026-02-06 00:10:23+00:00
We've been building an AI agent that debugs production incidents, and we think most AI SRE tools are solving the wrong problem.

Everyone's focused on the reasoning — better prompts, better models, RAG over runbooks. But in our experience, the bottleneck isn't the AI's ability to think. It's access to data. At any company past 50 engineers, half the context you need during an incident lives in internal tools with no public docs, custom deploy systems, homegrown dashboards, internal CLIs. No vendor integration covers this.

So we focused on the integration problem. On setup, IncidentFox reads your codebase and Slack history and auto-generates tool integrations — including for internal tools it's never seen before. It figures out what APIs exist, how they're called, and builds the connectors. After each incident, it learns what data sources were actually useful and refines.

The agent itself is straightforward: alert fires → form hypotheses → query observability stack → correlate → report findings in Slack. For example, if latency spikes on your payments service, it'll pull the deploy from 20 minutes ago, find the relevant code change, check downstream dependencies, and open a PR with a fix.

Three design decisions we're opinionated about:

1. Slack-native, not dashboard-native. At 3am you don't want another tab. Paste screenshots, drop log files, view traces — all in the thread.

2. Team-customizable agents. The SRE team's agent should behave differently from the platform team's. Engineers can configure prompts and build team-specific tools. One-size-fits-all doesn't work for incident response.

3. No manual MCP server setup. If you need to spend weeks configuring integrations before AI is useful, you've already lost.

Apache 2.0, fully self-hostable. Try it in our Slack (https://join.slack.com/t/incidentfox/shared_invite/zt-3ojlxv...) with real telemetry (no setup), or clone and run it yourself.

The technical piece we find most interesting: given enough incidents, the agent builds an emergent model of your entire infrastructure — which services are fragile, which deploys are risky, which alerts are noise. Nobody explicitly teaches it this. It just falls out of the investigation data. We think there's something deeper here about AI agents that learn system topology from failure patterns.

Would love to hear people's thoughts!
by mercutio2 | 2026-02-06 00:10:28+00:00
I guess I’ve never tried the pro models, because I’ve used gemini-cli free every day for the last three months or so.

It does eventually finish its quota, but then I just switch to a different Google account (which, amusingly, is what Gemini told me to do).

Happy to consume Google’s free tokens! The free model is a distant third for coding, but it’s fine for leaf node work in a larger project.
by waffletower | 2026-02-06 00:10:28+00:00
In the case of Anthropic -- they host on AWS all the while their models are accessible via AWS APIs as well, the infrastructure between the two is likely to be considerably shared. Particularly as caching configuration and API limitations are near identical between Anthropic and Bedrock APIs invoking Anthropic models. It is likely a mutually beneficial arrangement which does not necessarily hinder Anthropic revenue.
by vladdoster | 2026-02-06 00:10:47+00:00
Location: Nashville, TN
Remote: true
Willing to relocate: boston || nashville
Technologies: Python, Django, IaC, Terraform, Golang, CI/CD, Azure/AWS, {ba,z}sh, Lua, Springboot,
Redis, Docker, Open Service Broker, {,non}relational & vector dbs, shared services, SOA
Email: mvdoster@gmail.com

resume: https://linkedin.vdoster.com && http://github.com/vladdoster

sr. cloud software engineer @ Mastercard (5 years)

Designed and built Platform-as-a-Service for microservice workloads running on Azure and AWS
to migrate on-prem workloads to the cloud. The platform operates globally, allowing teams to
deploy to several Azure-backed regions worldwide. Helped plan and create regional landing zones
in Azure for application teams wanting to perform globally. Designed platform components using
Terraform, Go, and Node; developed support tooling using Bash, Python, and Azure CLI. De-risk the
platform by addressing security vulnerabilities and ensuring the platform is PCI compliant.

api/devops software engineer @ Harvard Medical School (2 years)

Worked as part of the DevOps team to manage a 15k core CentOS HPC cluster. Designed and implemented
Python-based security scanning pipeline to securely deploy & run Apptainer images via SLURM.
Coordinated cross-team emergency patching eﬀorts. Collaborated with researchers and engineers across
3-letter institutions to deliver secure research infrastructure. Built CI/CD Pipelines with GitHub, Jenkins,
to automate code builds, testing, and deployments. Wrote Puppet modules to manage configuration of HPC fleet.
Wrote custom Puppet module & Python scripts to automatically remediate Tenable findings.

full-stack software engineer @ Global Prior Art (3 years)

Used Django, Celery, Selenium grid, and AWS API Gateway for IP rotation to scrape USPTO patent PDFs,
apply CV for data extraction, and generate reports with relevant claims, saving employees 4-5 hours daily.
Wrote E2E black-box/fuzzing unit tests. Automated on-premise deployment via Github Actions and Ansible.

maintainer @ Zinit (5 years)

Develop and maintain a zsh plugin manager on Github with 4k stars. Implemented unit tests,
containerization, bug fixes, and new features.
See: https://github.com/zdharma-continuum/zinit

contributor @ Open-source documentation (5 years)

Contributed hundreds of documentation corrections and enhancements to 400+ open source projects.
by jazzypants | 2026-02-06 00:10:54+00:00
The real question is where do you draw the line with these ideologies? I don't think anyone deserves violence just for thinking the wrong things, but we're currently seeing the result of when those thoughts inevitably turn into actions.

It doesn't seem like America ended up on the right side of the paradox of tolerance, so I'm curious how you think we could have avoided our current fascist leadership?
by D-Machine | 2026-02-06 00:11:09+00:00
Cuba is dying and collapsing, with this kind of issue being just a part of a broader systemic set of causes. It is a serious tragedy and humanitarian crisis. If people aren't aware of how bad it is: they haven't had reliable food and electricity for a while now, even parts of Havana and other cities look eerily like a ghost town, and it seems as if almost anyone that is able to has been fleeing.

"Compared to the peak of 11.2 million inhabitants reached in 2012 – the year of the last census – Cuba has lost 13% of its population. [...] A quarter of the island's population is aged 60 and over, and it is the only demographic category that has grown in recent years"

https://www.lemonde.fr/en/international/article/2025/04/30/c...
by willsmith72 | 2026-02-06 00:11:37+00:00
this doesn't add up. the 20k is in API costs. people talk about CC losing money because it's way more efficient than the API. I.e. the same work with efficient use of CC might have cost ~$5k.

but regardless, hiring is difficult and high-end talent is limited. If the costs were anywhere close to equivalent, the agents are a no-brainer
by bryanlarsen | 2026-02-06 00:12:41+00:00
That's one of 3 possible futures.

1. 1-3 LLM vendors are substantially higher quality than other vendors and none of those are open source. This is an oligarchy and the scenario you described will play out.

2. >3 LLM vendors are all high quality and suitable for the tasks. At least one of these is open source. This is the "commodity" scenario, and we'll end up paying roughly the cost of inference. This still might be hundreds per month, though.

3. Somewhere in between. We've got >3 vendors, but 1-3 of them are somewhat better than the others, so the leaders can charge more. But not as much more than they can in scenario #1.
by jlaternman | 2026-02-06 00:13:18+00:00
Nope. He was unapologetically socialist before his involvement in the Civil War, and that conflict actually did make him anti-communist, and an anti-authoritarian. Socialism of the kind Orwell supported and communism of the kind we have seen in the world are two very different things.

For those reading who are curious on which comment is accurate, I would encourage you to read up on it to confirm for yourself. It's a highly fascinating subject to read about.

Another thing the Spanish Civil War did make Orwell was a hardcore realist.

"Half a loaf of bread is better than no loaf."
by throwawa1 | 2026-02-06 00:14:00+00:00
I'm a deflock user - I'm a libertarian. These cameras are a huge privacy violation, its amazing how fast Flock has grown ubiquitous. There is a strong Fourth Amendment argument against Flock, they have a generous interpretation of the constitution that your car has no rights and neither does your license plate therefore you have no privacy while on the road.

I've also been on the receiving end of secret Federal subpoenas for private user information at a YC backed startup. They include gag orders and management does not question the orders - they simply comply. It happens more often than you think.

However you feel about the current administration, imagine this power in the hands of the other.

Flock isn't American in any sense of the word. We should work in our communities, through legal, procedural, and civil means to eliminate these terrible, terrible cameras. The cost is much worse than the benefits on offer.
by jMyles | 2026-02-06 00:14:32+00:00
The difference is that North Korea is a place, with an organization that claims to be its government. You can point to it on a map.

Antifa is an adjective that people with no connection to one another self-apply. I'm antifa, and I imagine you are too, but it doesn't mean that we've ever met or coordinated with one another in any meaningful way.

The word "antifa" is basically meaningless altogether, since virtually every person since the end of WW2 claims to oppose fascism.
by cryptonector | 2026-02-06 00:15:01+00:00
Maybe in order to get the most out of agentic programming one needs to either a) already master the domain in question, or b) become a master in the process.

When (b) then the process can be the thing that triggers "thinking hard", and when (a) the one's mastery can be the reason one "thinks hard" when driving the agent.

Does this help TFA? Idk. Maybe if TFA can try either doing (a) a lot or (b) a lot it might. Or maybe agentic programming is going to drive out of the business those who stop thinking hard because they have agents to help them.
by manquer | 2026-02-06 00:15:53+00:00
> how many winners ... duopoly

There aren't any insurmountable large moats, plenty of open weight models that perform close enough.

> CO₂ emissions

Different industry that could also benefit from more competition ? Clean(er) energy is not even more expensive than dirty sources on pure $/kWh, we still do need dirty sources for workloads like base demand, peakers etc that the cheap clean sources cannot service today.
by adnan1507 | 2026-02-06 00:17:15+00:00
Hi HN,

I’m building Vantum ERP in public and opening a small early partner program for companies that want early access and a closer relationship with the product as it evolves.

The focus is on clarity, modularity, and predictable workflows.

Early-stage, functional, and very much a work in progress.

Website: https://www.vantumerp.com

Happy to answer questions.
by GaryBluto | 2026-02-06 00:17:51+00:00
> Being anti-antifascist just make you a fascist, or a fascist-adjacent supporter.

If a loose-knit ideology/movement called "Anti-Rapists" emerged that evolved into a cohort of various disconnected thugs who targeted homosexuals for violence, would being Anti-"Anti-Rapist" make you a supporter of rapists or rapist-adjacent supporter?
by bcrosby95 | 2026-02-06 00:18:00+00:00
Reasonable scale means... what exactly?

Here's my opinion: just use postgres. If you're experienced enough to not when I say that, go for it, the advice isn't for you. If you aren't, I'm probably saving you from yourself. "Reasonable scale" to these people could mean dozens of inserts per second, which is why people talking vagueries around scale is madenning to me. If you aren't going to actually say what that means, you will lead people who don't know better down the wrong path.
by DennisP | 2026-02-06 00:19:18+00:00
This is an outdated view.

People get the idea that just because LLMs are initially trained to predict word sequences, that's all they can do. This is not the case.

Transformers are general-purpose learning mechanisms. Word sequences are just the first thing we teach them. Then we train them more with human feedback. Then we sometimes hook them up to math and logic engines to train them some more, so they learn logical and mathematical reasoning. The article describes this process in a bit of detail.

With "reasoning models" we also let the model have some internal monologue before generating output, so it can "think through" the problem.

We didn't do all that with early LLMs. Those were just word predictors. But now we do those things, and that's why our lowly LLMs are writing huge software projects that actually work, and solving famous math problems that have been open challenges for half a century.

The weirdest part of all this is that LLMs started showing signs of reasoning with an internal world model even before we trained them for it specifically. Microsoft showed this in a famous paper back in (iirc) 2023. They showed that, for example, you could give GPT4 a list of odd-shaped objects that probably wouldn't appear together in any particular source text, ask GPT4 how to stack them so they wouldn't fall over, and GPT4 would come up with a good solution.

Finally, don't overlook the multimodal models, which work explicitly with images, video, and 3D world models in addition to text.
by gmueckl | 2026-02-06 00:19:19+00:00
The result is a fuzzy reproduction of the training input, specifically of the compilers contained within. The reproduction in a different, yet still similar enough programming language does not refute that. The implementation was strongly guided by a compiler and a suite of tests as an explicit filter on those outputs and limiting the acceptable solution space, which excluded unwanted interpolations of the training set that also result from the lossy input compression.

The fact that the implementation language for the compiler is rust doesn't factor into this. ML based natural language translation has proven that model training produces an abstract space of concepts internally that maps from and to different languages on the input and output side. All this points to is that there are different implicitly formed decoders for the same compressed data embedded in the LLM and the keyword rust in the input activates one specific to that programming language.
by eek2121 | 2026-02-06 00:19:21+00:00
Standardizing on one single tiny little project is always a bad idea. Why? Some examples (which are admittedly not related to postgres, because I don't know their structure):

1) A single person, doing a ton of heavy lifting, leaves, or worse, turns it over, or silently sells out to a nefarious person.

2) A severe security vulnerability is found. If everyone is using postgres, everyone is vulnerable. Bonus points if the vulnerability is either not publicly disclosed or it is hard to fix.

3) Commercial/Government interests heavily influence and push the project into places that could make it vulnerable in any given way. This is absolutely a thing.

4) AI. No clarification here. Just use your imagination, with recent news regarding FFMPEG and other projects in mind.
by avmich | 2026-02-06 00:19:45+00:00
I have two fundamental problems with Postgres - an excellent piece of technology, no questions about that.

First, to use Postgres for all those cases you have to learn various aspects of Postgres. Postgres isn't a unified tool which can do everything - instead it's a set of tools under the same umbrella. As a result, you don't save much from similarly learning all those different systems and using Postgres only as a RDBMS. And if something isn't implemented in Postgres better than in a 3rd party system, it could be easier to replace that 3rd party system - just one part of the system - rather than switching from Postgres-only to Postgres-and-then-some. In other words, Postgres has little benefits when many technologies are needed comparing with the collection of separate tools. The article notwithstanding.

Second, Postgres is written for HDDs - hard disk drives, with their patterns of data access and times. Today we usually work with SSDs, and we'd benefit from having SSD-native RDBMSes. They exist, and Postgres may lose to them - both in simplicity and performance - significantly enough.

Still, Postgres is pretty good, yes.
by EGreg | 2026-02-06 00:20:01+00:00
That’s not true, solar energy still reaches the lagrange point, these tiny machines don’t need that much of it

solar energy reaches the Earth-Sun Lagrange point 2 (\(L_{2}\)), even though it is located behind the Earth, because it sits slightly beyond the reach of Earth's full shadow (umbra). Here is a breakdown of how this works: Location of \(L_{2}\): The \(L_{2}\) point is located approximately 1.5 million kilometers away from Earth on the side opposite the Sun.Earth's Umbra Length: The tip of Earth's main, total shadow (the umbra) ends before it reaches the \(L_{2}\) point, usually around 92% of the distance to \(L_{2}\).Solar Exposure: Because \(L_{2}\) is outside the full umbra, a satellite at this location (like the James Webb Space Telescope) is never in total darkness.Halo Orbits: Spacecraft at \(L_{2}\) usually do not sit exactly at the point but in a "halo" orbit, which keeps them in constant, direct sunlight to power their solar panels.Penumbra: While the Earth may block some sunlight, the region is technically in a partial shadow (penumbra) or outside of it entirely, allowing for consistent solar energy harvesting. In summary, \(L_{2}\) is not in permanent darkness, and solar power is fully functional there.*