MurphyA/hacker-news huggingface dataset:
by ArmaloAI | 2026-03-11 05:00:06+00:00
You're right to push back on this — wall-clock decay is a forcing function, not a precise signal. The 7-day window was chosen as a minimum floor to prevent "ghost platinum" agents (earn a tier, never re-evaluate, coast forever). It's not meant to be the primary drift detector.

Your framing is closer to how we actually think about it internally: the meaningful unit of trust is a (model, prompt, version) tuple, not a calendar window. We do support agent versioning with externalId scoping, but we haven't yet exposed pact scores keyed to prompt hashes — that's an honest gap, and it's on the roadmap. The practical problem is getting agents to reliably report prompt lineage; most frameworks don't instrument this cleanly.

The silent weight update problem is the genuinely hard one. Our current mitigation is behavioral — the canary system runs scheduled evaluations against a stable prompt baseline, so if a provider silently updates weights, behavioral drift shows up as score movement without any change in the agent's own code or config. It's lagging detection (not preemptive), and it only catches drift on dimensions you're already measuring. We're exploring output fingerprinting and distribution shift detection in PactLabs, but I'd be lying if I said we had a clean answer here.

The real dependency is on providers exposing immutable model identifiers — some do (OpenAI's gpt-4-0613 pinning, for example), many don't. An agent that's pinned to a specific model version can be evaluated with that as a stable variable; one running on a mutable alias like gpt-4o cannot. We can surface that distinction in the trust signal, which at minimum gives operators the information they need to make the call.

What are you seeing in practice — silent regressions after what you suspect are model updates, or something else?
by nextaccountic | 2026-03-11 05:00:44+00:00
> If you added a simple additional to the problem, such as "Note that in this context, 'if' only means that...", most people would almost certainly answer it correctly.

Agreed. More broadly, classical logic isn't the only logic out there. Many logics will differ on the meaning of implication if x then y. There's multiple ways for x to imply y, and those additional meanings do show up in natural language all the time, and we actually do have logical systems to describe them, they are just lesser known.

Mapping natural language into logic often requires a context that lies outside the words that were written or spoken. We need to represent into formulas what people actually meant, rather than just what they wrote. Indeed the same sentence can be sometimes ambiguous, and a logical formula never is.

As an aside, I wanna say that material implication (that is, the "if x then y" of classical logic) deeply sucks, or rather, an implication in natural language very rarely maps cleanly into material implication. Having an implication if x then y being vacuously true when x is false is something usually associated with people that smirk on clever wordplays, rather than something people actually mean when they say "if x then y"
by datsci_est_2015 | 2026-03-11 05:00:50+00:00
> Macroeconomically speaking, I don’t see why we need more software engineers in the future than we have today, and that’s probably a conservative estimate.

Why? Is the argument that there’s a finite amount of software that the world needs, and therefore we will more quickly reach that finite amount?

Seems more likely to me that if LLMs are a force multiplier for software then more software engineers will exist. Or, instead of “software engineers”, call them “people who create software” (even with the assistance of LLMs).

Or maybe the argument is that you need to be a super genius 100x engineer in order to manipulate 17 collaborative and competitive agents in order to reach your maximum potential, and then you’ll take everyone’s jobs?

Idk just seems like wild speculation that isn’t even worth me arguing against. Too late now that I’ve already written it out I guess.
by cameldrv | 2026-03-11 05:02:23+00:00
This seems too good to be true. Respiratory infections kill and debilitate a lot of people. If cranking up the innate immune system all the time reduced illness with no downsides, you'd think evolution would have done it already, but it didn't, which makes me think there's probably a downside, and the fact that the innate immune system is only cranked up when a pathogen is detected is probably because the downside is worth it in the presence of a pathogen but not otherwise.
Neuromorphic sphere topology Hebbian learning as a path to grounded intelligence
by rusanovych | 2026-03-11 05:04:17+00:00
I've been working on a hypothesis and want to get feedback from people who know more than I do.
The hypothesis
Intelligence might be a phase transition at scale, not an algorithmic problem.
Fly: 100k neurons — no generalization
Mouse: 70M — basic associative learning
Human: 86B — abstract reasoning
This doesn't look like a smooth curve. It looks like thresholds. If that's true, then no amount of architectural cleverness crosses it — only scale + grounding does.
The grounding problem
LLMs learn statistical distributions over text. "Apple" = token pattern. In biological systems "apple" = weight, texture, smell, hunger. Concepts without physical roots have a ceiling we're already approaching.
The architecture
Sphere topology: recurrent graph, no fixed signal direction, no enforced hierarchy
Hebbian learning only — no backprop
Dopamine-modulated consolidation with sleep/wake cycle
Single network: language + vision + motor through shared weights
Lateral inhibition + capacitor adaptation for stability — pure analog, already in Loihi
Grounded in physical simulation, not text
Prediction doesn't need to be engineered. Hebbian learning + physical grounding + continuous input should produce anticipation as an emergent property — same way it works biologically.
Why now
All components exist in current neuromorphic hardware. Full human scale = ~10,750 Loihi 3 chips, ~$150-200M. Below this threshold it probably won't work — that's the hypothesis, not a bug.
This needs real funding. But the architecture is ready to be attempted.
What I'm looking for
Has anyone attempted sphere topology on neuromorphic hardware? Is there prior work on Hebbian-only learning at this scale? Where does this obviously break?
by godelski | 2026-03-11 05:04:22+00:00
I can't believe we're back to advocating for TDD. It was a failed paradigm that last few times we tried it. This time isn't any different because the fundamental flaw has always been the same: tests aren't proofs, they don't have complete coverage.

Before anyone gets too confused, I love tests. They're great. They help a lot. But to believe they prove correctness is absolutely laughable. Even the most general tests are very narrow. I'm sure they help LLMs just as they help us, but they're not some cure all. You have to think long and hard about problems and shouldn't let tests drive your development. They're guardrails for checking bonds and reduce footguns.

Oh, who could have guessed, Dijkstra wrote about program completeness. (No, this isn't the foolishness of natural language programming, but it is about formalism ;)

https://www.cs.utexas.edu/~EWD/transcriptions/EWD02xx/EWD288...
by potsandpans | 2026-03-11 05:05:40+00:00
We can't have an honest conversation from the basis of, "people can do whatever they want as long as they don't hurt people."

Because it's just not the world we live in. I don't care to enumerate this here.

But I agree with you that part of the problem is politics of power. I just happen to think there is more nuance.

Criminality, there are a handful of stats we could looks at. For example gendered differences in sentencing.

> When examining all sentences imposed, females received sentences 29.2 percent shorter than males. Females of all races were 39.6 percent more likely to receive a probation sentence than males. When examining only sentences of incarceration, females received lengths of incarceration 11.3 percent shorter than males.

https://www.ussc.gov/research/research-reports/2023-demograp...

But instead of arguing about stats, in general -- and this goes back to the social transgression bit. In the real world, women can do things to men that men can't do to women. This is largely due to the politics of power. Im not particularly preoccupied by it, but I do acknowledge that it exists.

Your response is _precisely_ what I'm calling out: two people talking past one another. I do not feel that youve interpreted anything I've said with grace. Instead it's more along the lines of, "yeah yeah yeah, but it's really about power"

Maybe. Hacker news is probably disproportionately powerful white males. I try not to assume bad intent with these things.

I'm merely pointing out that culturally, we will only get worst by trying to shame "normal" people (men) into feeling ways. In fact, I think the "cultural moment" as they say is indicative on how much that has failed.
by nextaccountic | 2026-03-11 05:05:59+00:00
The duplicated people is imaginary and hypothetical, happening (or not) in an unspecified time in future; the suffering in animal farming is real and happens today.

Somehow many people are ready to ascribe personhood and have ethical considerations towards computer programs and other digital entities, while not being much concerned about the suffering of animals that actually exist today in the physical world
by jackyinger | 2026-03-11 05:07:22+00:00
How is searching encrypted data not going to be used for exfiltration? What a terrible idea.

I’m sure you can name benign useful things you could use it for. But it seems to me you’re blatantly overlooking the obvious flaw.

There is no getting around doing search on encrypted data reducing the level of secrecy. To have an even minutely useful search result, some information within the searched corpus must be exposed.
by whynotmaybe | 2026-03-11 05:08:07+00:00
Fond memory of when I wrote an editor in the 90's because we didn't want to use "ms edit" for COBOL and asm files.

Syntax coloring, fast buffering and even a screen saver.

You could even call the compiler directly from it.

All this running on a pentium 120 and it felt a thousands times faster than today's vscode.

But vscode can edit multiple files at the same time...
by devinplatt | 2026-03-11 05:08:46+00:00
I'm curious how this works if the green team writes an implementation that makes a network call like an RPC.

Red team might not anticipate this if the spec does detail every expected RPC (which seems unreasonable: this could vary based on implementation). But a unit test would need mocks.

Is green team allowed to suggest mocks to add to the test? (Even if they can't read the tests themselves?) This also seems gamaeable though (e.g. mock the entire implementation). Unless another agent makes a judgement call on the reasonability of the mock (though that starts to feel like code review more generally).

Maybe record/replay tests could work? But there are drawbacks in the added complexity.
by Swizec | 2026-03-11 05:09:43+00:00
You have a lot more flexibility around those downswings at 40 than you do at 80. For example you could retire but continue doing work that brings you joy and also happens to make money. A lot of people in this situation start lifestyle businesses or do consulting work, for example.

At $4mm in a market account (not 401k), you also have the option to take out margin loans at shockingly low interest. This gives you untaxed cashflow without touching your principal. 160k untaxed is a lot more cashflow than the same number in salary or retirement distributions.
AI Aadhaar OCR API for Fast Aadhaar Data Extraction
by azapi_ai | 2026-03-11 05:12:05+00:00
The Aadhaar OCR API is an AI-powered solution designed to automate Aadhaar Card Data Extraction from scanned images, PDFs, and mobile uploads. It helps businesses instantly capture important details such as Aadhaar number, name, address, and date of birth with high accuracy. Using advanced AI Aadhaar Document Processing, the API converts unstructured Aadhaar card images into structured digital data that can easily integrate with verification systems or onboarding platforms. This technology reduces manual data entry, improves processing speed, and supports secure identity verification workflows for fintech, banking, and digital service providers.

We built an AI-powered Aadhaar OCR API that can extract data from Aadhaar cards instantly for KYC automation.

https://azapi.ai/services/ocr/aadhaar-ocr-api/
by twotwotwo | 2026-03-11 05:13:22+00:00
This is fascinating, and makes me wonder what other things that 'should' be impossible might just be waiting for the right configuration to be tried.

For example, we take for granted the context model of LLMs is necessary, that all you can do is append and anything that changes the beginning requires a recalculation of whatever comes after it. And that does match how training works.

But all sorts of things would become possible if it were possible to shift things in and out of context without recomputing it all; conservatively you could avoid compaction, optimistically it might be a way to get info to the model that's both more deeply integrated than search and more efficient than training larger and larger models.
by kindkang2024 | 2026-03-11 05:13:26+00:00
> As software engineers, I get the feeling we’re moving almost entirely away from code.

Wille-Driven Development — I prefer the word from Schopenhauer's Die Welt als Wille und Vorstellung (The World as Will and Representation).

What we will begins to matter more. The gap between desire and existence is collapsing. In Genesis, creation is a pure speech-act: fiat lux, and it was so — no implementation details, no build step, will and result simultaneous. We're not there yet. But I find the distance is measurable and shrinking.

The Representation — code, syntax, toolchains — is receding. The Will asserts itself more directly. Welcome to the future.
by imiric | 2026-03-11 05:15:52+00:00
> Your tests are an assertion that 'no matter what this will never change'.

That's a strange definition. A lot of software should change in order to adapt to emerging requirements. Refactorings are often needed to make those changes easier, or to improve the codebase in ways that are transparent to users. This doesn't mean that the interfaces remain static.

> If your interface can change then you are testing implementation details instead of the behavior users care about.

Your APIs also have users. If you're only testing end-user interfaces, you're disregarding the users of your libraries and modules, e.g. your teammates and yourself.

Implementation details are contextual. To end-users, everything behind the external UI is an implementation detail. To other programmers, the implementation of a library, module, or even a single function can be a detail. That doesn't mean that its functionality shouldn't be tested. And, yes, sometimes that entails updating tests, but tests are code like any other, and also require maintenance and care.
by golem14 | 2026-03-11 05:16:36+00:00
Yeah, that's what the link I posted also discusses (but then goes into much detail, but then offers no actual resolution).

I guess we will have to wait for cases to be brought and resolved at the courts. Not a great recipe to be the leader in AI, it must be said.

An updated copyright bill from legislature, or even positive regulatory action from the executive branch would speed things up and give much planning certainty to actors here in the US.

The rest of the world won't be waiting though -- maybe Europe, but Europe sadly doesn't really matter that much anymore :(
by h4ch1 | 2026-03-11 05:19:06+00:00
But why is it so big in the first place?

I was searching around for causes and came across the following issues:
https://github.com/ziglang/zig/issues/15358 which was moved to https://codeberg.org/ziglang/zig/issues/30193

The following quotes stand out

> zig's caching system is designed explicitly so that garbage collection could happen in one process simultaneously while the cache is being used by another process.

> I just ran WizTree to find out why my disk was full, and the zig cache for one project alone was like 140 GB.

> not only the .zig-cache directory in my projects, but the global zig cache directory which is caching various dependencies: I'm finding each week I have to clear both caches to prevent run-away disk space

Like what's going on? This doesn't seem normal at all. I also read somewhere that zig stores every version of your binary as well? Can you shed some light on why it works like this in zigland?
How talent strategy is becoming a growth lever for startups
by KFWCORP | 2026-03-11 05:19:35+00:00
Most early-stage startups focus heavily on product and growth, but people strategy often gets attention much later.

At KFW – The CHRO Bridge, we’ve been exploring how structured HR practices—things like leadership development, capability building, and culture design—can directly influence startup scalability.

Curious how others here approach talent strategy during the early stages of a company.

https://kfwcorp.com

KFW is a Chennai-based talent consulting firm helping organizations build capacity, capability, and culture through structured HR transformation practices.
by godelski | 2026-03-11 05:19:35+00:00
Why is everyone obsessed with Mac Minis. They're awesome but for the work that these people are attempting to do? Just seems... nonsensical. Renting a server is cheaper and still just as "local" as any of this (they want "self hosted", I don't think anyone cares about local. Like are people air gapping networks? lol)

And a senior director of Nvidia? He had several Mac Minis? I really gotta imagine a Spark is better... at least it'll be a bit smarter of a cat (I'm pretty suspicious he used a LLM to help write that post)

No time to think, gotta go fast?
by gigatexal | 2026-03-11 05:20:08+00:00
Very very fair call out. No company is a saint. Even Dario is okay with allowing Claude to be used to kill people just so long as there’s a human in the loop. It’s a very low
bar indeed. But idk he’s standing his ground. More of the CEO class I think should. I’d like to see more spine from them. And if they do I will patronize them more.

Too many firms are too big this is true. Breakups would energize a lot of things and even raise salaries for us workers as these new smaller more nimble companies fight for talent.

I guess I just want things to go back to where they were when we were debating about breaking companies up not talking about existentially bad things like kissing the ring of a faux businessman turned reality tv star turned populist who loves Putin. Who knew it would be the Siberian candidate and not the Manchurian one.
Why people strategy is becoming a competitive advantage for tech companies
by KFWCORP | 2026-03-11 05:20:19+00:00
As companies scale faster with AI and automation, leadership challenges are shifting from pure technology problems to people problems.

At KFW – The CHRO Bridge, we work with growing organizations on talent transformation—helping them design systems for leadership development, capability building, and culture alignment.

Would love to hear how founders here approach scaling teams without losing culture.

https://kfwcorp.com
by saguntum | 2026-03-11 05:22:33+00:00
Yeah, our basic integration test suite takes over 20 minutes to run in CI, likely higher locally but I never try to run the full test suite locally. That doesn't even encapsulate PDVs and other continuous testing that runs in the background.

The other day, I wrote a claude skill to pull logs for failing tests on a PR from CI as a CSV for feeding back into claude for troubleshooting. It helped with some debugging but was very fraught and needed human guidance to avoid going in strange directions. I could see this "fix the tests" workflow instrumented as overnight churn loops that are forbidden from modifying test files that run and have engineers review in the morning if more tests pass.

Maybe agentic TDD is the future. I have a bit of a nightmare vision of SWEs becoming more like QA in the future, but with much more automation. More engineering positions may become adversarial QA for LLM output. Figure out how to break LLM output before it goes to prod. Prove the vibe coded apps don't scale.

In the exercise I described above, I was just prompt churning between meetings (having claude record its work and feeding it to the next prompt, pulling test logs in between attempts), without much time to analyze, while another engineer on my team was analyzing and actually manually troubleshooting the vibe coded junk I was pushing up, but we fixed over 100 failing integration tests in a week for a major refactor using claude plus some human(s) in the loop. I do believe it got things done faster than we would have finished without AI. I do think the quality is slightly lower than would have been if we'd had 4 weeks without meetings to build the thing, but the tests do now pass.
by hkonte | 2026-03-11 05:23:16+00:00
The core argument is right. Domain expertise is irreplaceable.

But there is a separate, orthogonal point: prompt structure affects output quality independently of domain knowledge. A typed-block prompt (role, objective, constraints, output format as distinct units) gets different results from the same model than prose asking for the same thing. Not because of expertise, but because the model parses labeled structure differently than it parses narrative.

I built github.com/Nyrok/flompt around this, a visual canvas that decomposes prompts into 12 semantic blocks and compiles to Claude-optimized XML. Structure at the input layer is a real variable, separate from whether you understand the domain you're working in.
by frm88 | 2026-03-11 05:24:36+00:00
"Exalts the Nation and Often Race Above the Individual Donald Trump claims immigrants are “poisoning the blood of our nation,” a turn of phrase used by Adolf Hitler in Mein Kampf...

Associated with a Centralized Autocratic Government Headed by a Dictatorial Leader This one is almost too easy: Trump says, “‘You’re not going to be a dictator are you?’ I said ‘No, no, no, other than day one.”...

Severe Economic and Social Regimentation Did we mention the “largest deportation operation in American history“? And promises to invoke the Alien Enemies Act of 1798...

Forcible Suppression of Opposition This is by far the most important component of the definition and the one that is the easiest to document in Trump’s own words... "

Bret Deveraux, American historian, October 25, 2024 https://acoup.blog/2024/10/25/new-acquisitions-1933-and-the-...

It's a long blog post and the definitions are more detailed (hence the ellipses) and compared to Umberto Eco's Ur-Fascism. Worth a read, paticularly if you are in search of definitions and examples.
by computerdork | 2026-03-11 05:24:43+00:00
Hmm, not so sure TDD is a failed paradigm. Maybe it isn't a pancea, but it is seems like it's changed how software development is done.

Especially for backend software and also for tools, seems like automated tests can cover quite a lot of use cases a system encounters. Their coverage can become so good that they'll allow you to make major changes to the system, and as long as they pass the automated tests, you can feel relatively confident the system will work in prod (have seen this many times).

But maybe you're separating automated testing and TDD as two separate concepts?