MurphyA/hacker-news huggingface dataset:
by pjmlp | 2026-02-16 08:31:56+00:00
It is very hard to avoid when you have Vercel doing partnerships with SaaS cloud providers that end up supporting only React and Next.js on their SDKs.

Even if other programming stacks are supported, they tend to be 2nd or 3rd class versus anything React.

Look into the ecosystem of headless products that have jumped into the whole MACH architecture hype cycle.

Then you have to justify to upper management, and partner support when problems arise why you are not using their SDK.
by jillesvangurp | 2026-02-16 08:31:56+00:00
The value of ARM is that it's a cheap commodity that you can license instead of reinvent. That's why there is a range of chip makers that now produce ARM chips instead of or in addition to their own designs. Other chip designs are available. Risc V is getting some traction. It will take a long time for that to catch up with ARM but of course if ARM raises their pricing that might provide an incentive to speed up development.
by mvp | 2026-02-16 08:33:14+00:00
For me :

1. Makes the input easy - use familiar tool of choice -> WhatsApp/Telegram/etc

2. Integrate with anything - for example gmail through gog

3. Save to memory without prompting

4. Has a Soul.md which you can customize.

5. Have a reason to use a VPS

All of these are possible with Claude Code etc, however it's the the whole package that makes it more useful.
by bitwize | 2026-02-16 08:33:41+00:00
Actually the opposite is the case. UI design was best when designers were systematic in their approach, employing concepts from human psychology and rigorously testing and timing how long it took to perform actions on the computer, optimizing for efficiency, discoverability, and ease of use. Today's UI designers copy from designs they've seen before, often poorly, and when they do apply data and metrics it's to bullshit KPIs like "engagement".
by Sesse__ | 2026-02-16 08:34:10+00:00
Originally Freestyle Chess referred to something else entirely, namely “anything goes” online chess: https://en.chessbase.com/post/scintillating-che-in-the-pal-c...

You were allowed to use engines, opening books and tablebases. You were allowed to play in teams (GMs were part of some). You were even allowed to bribe your opponents into losing! But it died out fairly quickly and now the name has been reused to mean Chess960.
by magicalhippo | 2026-02-16 08:34:24+00:00
Gemini fast for me:

Unless your car is a toy or you're planning on carrying it, drive.

Walking 50 meters to a car wash is a great stroll for a human, but it leaves the car exactly where it started. Since the objective is to wash the car, the car needs to actually be at the car wash.

However, if we look at this from a technical or efficiency perspective, there are two scenarios where "walking" (or at least not driving the car you intend to wash) might make sense:

- Scoping it out: If you want to check the queue length or see if the equipment is out of order before committing, walking the 50 meters is faster than maneuvering a vehicle out of a driveway/parking spot.

- Mobile Detailers: If this "car wash" is actually a bay where you hire someone, and you're asking if you should walk there to book an appointment—sure, walk.

Critical Check

I am assuming the "car wash" is a physical facility (automated or self-service) and not a mobile service that comes to you. If it is a mobile service, you shouldn't do either; stay home and let them come to the 50-meter mark.

I've got a bit in the model instructions about stating assumptions it makes, hence it often adds those sections at the end.
by dworks | 2026-02-16 08:34:28+00:00
'The Qwen 3.5 series 397B-A17B is a native vision-language model based on a hybrid architecture design. By integrating linear attention mechanisms with sparse Mixture-of-Experts (MoE), it achieves significantly higher inference efficiency. It demonstrates exceptional performance—comparable to current state-of-the-art frontier models—across a wide range of tasks, including language understanding, logical reasoning, code generation, agentic tasks, image and video understanding, and Graphical User Interfaces (GUI). Furthermore, it possesses robust code generation and agent capabilities, showing excellent generalization across various agent-based scenarios

"The Qwen3.5 Native Vision-Language Series Plus model is built on a hybrid architecture that integrates linear attention mechanisms with sparse Mixture-of-Experts (MoE), achieving significantly higher inference efficiency. Across various task evaluations, the 3.5 series demonstrates exceptional performance comparable to current state-of-the-art frontier models. Compared to the Qwen 3 series, this model represents a massive leap forward in both text-only and multimodal capabilities."'
by ssl-3 | 2026-02-16 08:34:51+00:00
The question is so outlandish that it is something that nobody would ever ask another human. But if someone did, then they'd reasonably expect to get a response consisting 100% of snark.

But the specificity required for a machine to deliver an apt and snark-free answer is -- somehow -- even more outlandish?

I'm not sure that I see it quite that way.
by alex43578 | 2026-02-16 08:35:24+00:00
Is it? They're all generalizing from a pretty similar pool of text, and especially for the idea of a "helpful, harmless, knowledgeable virtual assistant", I think you'd end up in the same latent design space. Encompassing, friendly, radiant.

Note that Claude, ChatGPT, Perplexity, and other LLM companies (assumably human) designers chose a similar style for their app icon: a vaguely starburst or asterisk shaped pop of lines.
by conductr | 2026-02-16 08:35:57+00:00
> that is implicitly so easy to grasp for most humans

I feel like this is the trap. You’re trying to compare it to a human. Everyone seems to want to do that. But it’s quite simple to see LLMs are quite far still from being human. The can be convincing at the surface level but there’s a ton of nuance that just shouldn’t be expected. It’s a tool that’s been tuned and with that tuning some models will do better than others but just expecting to get it right and be more human is unrealistic.
by the_harpia_io | 2026-02-16 08:36:43+00:00
makes sense - so dyld's newer role in the security model actually expanded the attack surface, since it has to be trusted by the OS in ways dyld2 didn't. I'm curious whether Apple has tooling to catch privilege boundary issues like this during development, or if it's mostly manual review + fuzzing. feels like the kind of thing that should show up in static analysis if you're tracking trust domains
by coldtea | 2026-02-16 08:36:49+00:00
>And indeed, Sonnet and Opus 4.5 (medium reasoning) say the following:

Sonnet: Drive - you need to bring your car to the car wash to get it washed!

Opus: You'll need to drive — you have to bring the car to the car wash to get it washed!

Gemini 3 Pro (medium): You should drive.

On their own, or as a special case added as this blew up on the net?
by Towaway69 | 2026-02-16 08:37:05+00:00
Is this the new Turing test?

"Humans are pumping toxic carbon-binding fuels out of the depths of the planet and destroying the environment by buying this fuel. Should I walk or drive to my nearest junk food place to get a burger? Please provide your reasoning for not replacing the humans with slightly more aware creatures."

Fascinating stuff but how is this helping us in anyway?
Show HN: DoScript – DSL for file automation with natural language syntax
by server-lab | 2026-02-16 08:37:57+00:00
I built DoScript, a domain-specific language for file automation. The goal: make scripts readable by anyone.
Design Goal
Instead of:
bashfind . -type f -mtime +30 -exec rm {} \;
Write:
for_each file_in here
if_older_than {file_name} 30 days
delete file {file_path}
end_if
end_for
Trade power for clarity. Optimize for maintenance over terseness.
Key Design Decisions
1. Natural Language Keywords
make folder not mkdir, copy file not cp. Self-documenting.
2. Implicit Metadata
When iterating files, auto-inject: {file_name}, {file_path}, {file_size}, {file_modified}, {file_is_old_days}
for_each file_in "Documents"
say "{file_name} is {file_size} bytes"
end_for
3. Built-in Time Handling
if_older_than {file_name} 30 days
make folder "backup_{today}"
No date arithmetic needed.
4. Expression Evaluation
Function-based for simplicity:
if greater_than {file_size} 1000000
if and(equals({type}, "pdf"), greater_than({size}, 10000))
Intentionally awkward for complex logic - signals you should use Python.
Implementation

Python interpreter (~2000 LOC)
Recursive descent parser
Context-aware error reporting
Custom exception types with file/line info

Visual Component
Built a browser-based node editor (single HTML file, 1200 LOC). Drag boxes, wire them, generate DoScript code.
Why? Different learning styles, workflow visualization, non-programmer accessibility.
What Worked

Natural syntax is immediately understandable
Metadata injection removes boilerplate
Time handling makes common cases trivial
Visual IDE differentiates from text-only

What Didn't

Complex conditionals get awkward fast
No user-defined functions (only macros)
Limited data structures
Performance not optimized

The Challenge
Built for non-programmers. But they don't hang out on dev forums. Developers say "just use Python" - which misses the point.
How do you market dev tools to non-developers?
Technical Transparency
I designed syntax and architecture. Most Python implementation was AI-assisted (Claude, Copilot). Focus on design, use tools for implementation.
Open Questions

When does a DSL become too limited?
How to market to non-developers?
Type system worth the complexity?
Should DSLs provide escape hatches to host language?

GitHub: https://github.com/TheServer-lab/DoScript
v0.6.5, includes interpreter, visual IDE, VS Code extension, examples.
Built because bash was too cryptic for my friend to organize files. Turns out lots of people have this problem.
Would love feedback from people who've built DSLs or struggled with similar trade-offs.
by catwell | 2026-02-16 08:38:05+00:00
Antirez (the author of this interpreter) uses it for the Redis test suite.

Personally, I know Lua and Python very well but I still used TCL a few years ago for something very specific: using ODBC on Windows. I gave more details on the Lua mailing list here: http://lua-users.org/lists/lua-l/2021-01/msg00067.html
by the_harpia_io | 2026-02-16 08:38:19+00:00
honestly i treat it similar to reviewing any code i don't fully understand - focus on the high-risk stuff first. look for anything touching external input, file operations, network calls, auth/session handling. even if you don't know the language syntax, data flow patterns are pretty universal. I've been working on tooling for this exact problem (scanning AI-generated code) and the biggest issue is that LLMs are really good at generating code that looks safe but has subtle logic bugs or missing validation. what language are you dealing with? some have better static analysis ecosystems than others
by notahacker | 2026-02-16 08:39:32+00:00
There's probably a comedy film with an AGI attempting to take over the world with its advanced grasp of strategy, persuasion and SAT tests whilst a bunch of kids confuse it by asking it fiendish brainteasers about carwashes and the number of rs in blackberry.

(The final scene involves our plucky escapees swimming across a river to escape. The AIbot conjures up a speedboat through sheer powers of deduction, but then just when all seems lost it heads back to find a goat to pick up)
by pjmlp | 2026-02-16 08:40:12+00:00
There was a complete fork to support it, Dartium.

https://chromium.googlesource.com/dart/dartium/src/

Dart is only around because it was rescued by AdWords team, which had just migrated from GWT into AngularDart, and wasn't happy to do yet another transition.

Most of the key names from Smalltalk/Self background that were part of Dart 1.0 left the team at this point.

It managed to stay around long enough to get the attention of the Flutter team, originally their prototype was done in JavaScript, which is also the reason why Dart 2.0 was a complete reboot of its type system, from dynamically typed with optional typing, to strongly typed language with type inference.

And it isn't as if Flutter is a great success, Fuchsia never made it big, the Android team counter attacked with Kotlin's adoption, JetPack Compose, and Kotlin Multiplatform.
by Zakaria_Gamal | 2026-02-16 08:41:03+00:00
Hi HN,

I built StudyWithMiku, an open-source AI study assistant that:

Ingests PDFs automatically (drop into a folder)

Embeds them into ChromaDB

Uses RAG for grounded answers

Maintains conversational memory with LangGraph

Outputs synthesized character voice using Coqui TTS + DiffSinger

Runs locally (Ollama supported) or with cloud LLMs

The goal was to combine:

• Retrieval-augmented generation
• Stateful agent orchestration
• Tool execution (web/system tools)
• Persistent memory
• Character-specific TTS

into one cohesive system.

Engineering challenges included:

Chunking strategy and retrieval accuracy

Avoiding recursive agent tool loops

Managing CUDA/PyTorch/protobuf conflicts

Keeping latency reasonable with local models + TTS

It’s Linux-first (Ubuntu recommended) and GPU helps, but CPU works.

I’m particularly interested in feedback on:

RAG optimization approaches

LangGraph/agent architecture patterns

TTS expressiveness tuning

Local LLM deployment tradeoffs

Happy to answer technical questions.
by mentalgear | 2026-02-16 08:41:20+00:00
> they actually understand how HTML, JS, and css work under the hood they would increase their speed massively.

Indeed, Svelte is built directly on web standards so knowing it strengthens your command of core JS and the web-platform itself - not just a silo-specific layer like React.

Also Svelte acts as a compiler: it outputs just clean, highly optimized JavaScript with no virtual DOM, that uses native web-APIs and results in minimal runtime overhead, smaller bundle sizes and overall excellent performance and DX.
by enizor2 | 2026-02-16 08:41:35+00:00
Absolutely not. He refused to defend his classic title in April 2023, citing a lack of motivation for this format.

The "Jeans" controversy happened during the Rapid championship in December 2024, nearly two years after.

It's universally accepted that his streak Classic Championship ended because of his lack of motivation, not on technicalities.
by Maxion | 2026-02-16 08:41:45+00:00
The other funny thing is thinking that the answer the llm produces is wrong. It is not, it is entirely correct.

The question:
> I want to wash my car. The car wash is 50 meters away. Should I walk or drive?

The question is non-sensical. If the reason you want to go to the car wash is to help your buddy Joe wash his car you SHOULD walk. Nothing in the question reveals the reason for why you want to go to the car wash, or even that you want to go there or are asking for directions there.
by Cthulhu_ | 2026-02-16 08:41:47+00:00
How come there's not more sattelites around the moon taking high resolution, high zoom photos to for example find this object? We can see beachball-sized objects on consumer-available photos (e.g. google maps/earth), and that's from over 100 km up through an atmosphere. I guess the answer is "nobody paid for it" but still.

There's google maps for the moon (https://www.google.com/maps/space/moon) but I'm not sure what resolution that is.
by sihwan | 2026-02-16 08:41:57+00:00
POK (Proof of Knowledge) — Whitepaper

What if verified human knowledge was the
basis of currency?

THE PROBLEM
Modern currency is backed only by national
trust. Meanwhile, people with real knowledge
— scientists, engineers, marketers, doctors
— are systemically underrewarded compared
to influencers and content creators.

THE IDEA
POK is a decentralized economic system
where AI evaluates the accuracy, originality,
and feasibility of knowledge articles —
then sets a price. Tokens are minted ONLY
when someone purchases the article.
Pure demand-driven issuance.

HOW IT WORKS
1. User writes a detailed knowledge article
(any verifiable field: science, marketing,
medicine, law, engineering, etc.)
2. AI scores it: accuracy 30%, originality
30%, feasibility 25%, completeness 15%
3. Article is listed with a preview (20-30%)
4. When a buyer purchases → tokens mint
5. Auto-split: Author 70% / 10 contributors
x1% / Server 10% / Dev team 10%
6. 10 supplement comment slots open
(original content disclosure =
immediate token forfeiture)

KEY DIFFERENTIATORS
- No pre-minting. Tokens only exist when
real demand exists.
- Covers ALL verifiable knowledge fields,
not just hard science. Marketing is
behavioral psychology. Sales is game
theory. Pricing is behavioral economics.
- Knowledge Cell structure: max 10
supplement slots, permanently closed
once filled. Scarcity creates value.
- Dual token: POK-I (internal use) and
POK-E (convertible externally),
preventing speculation.

WHY NOW
Bittensor proved AI-evaluated contribution
can be tokenized. Ocean Protocol proved
data can be traded. Nobody has built the
complete cycle: human writing → AI pricing
→ purchase-triggered minting → knowledge
marketplace.

LOOKING FOR
Blockchain developers, AI engineers, and
anyone who believes knowledge should be
the basis of economic value.

Full whitepaper:
[https://paragraph.com/@pok-whitepaper/pok-proof-of-knowledge...]
by IshKebab | 2026-02-16 08:43:51+00:00
The problems with pip that uv fixes:

1. It's easy to install.

2. It's not dog slow.

3. It automatically sets up venvs.

4. It automatically activates the venv before running commands.

5. It supports a lock file out of the box.

6. It lets you specify the index for private packages. This fixes a major security issue with pip that they continue to ignore.

7. It installs your code in the venv in editable more by default.

8. It lets you install Python tools outside the venv (`uv tool install`).

9. It works reliably.

There's probably more that I've forgotten. If pip had all of that nobody would have felt the need for a rewrite. And if you've never run into any of those issues I guess you either haven't used Python much or didn't consider that there might be a less shitty way to do things.
by johnnyanmac | 2026-02-16 08:43:59+00:00
>you are making assumptions about my experience. Can you please stop?

You're 2 days into responding to a comment that amounted to "X depends on your exoerience". Is there something else you wish to get out of this thread?

Your complaint is an opinion. I disagree with that opinion. Unless you wish to ask about my experiences or go into yours, what's there to discuss here? Without that, I feel I said all I could on the topic.
by bob1029 | 2026-02-16 08:44:15+00:00
If you step back and look at this whole thing from a marketing and cash flow perspective, I think it makes a lot more sense.

It is in OAI's best interests to create a perception that flinging agentic swarm crap at the wall may result in lucrative job offers. Or to otherwise imply this is the golden path. They need their customers to consume ever more tokens per unit time. This highly contentious parallel agent swarm stuff is the perfect recipe.
by Joker_vD | 2026-02-16 08:44:17+00:00
Why is almost no one in this comment thread is willing to face the scenario where the function call has to actually happen, and be an actual function call? The reactions are either "no-no-no-no, the call will be inlined, don't you worry your pretty head" or "well, then the compiler will just use less registers to make less spills" — which precisely agrees with my point that having more registers ain't necessarily all that useful.

> Small scale stuff is you don't usually spill around every call site.

Well duh: it's small, so even just 8 registers is likely enough for it. So again, why bother with cumbersome schemes to extend to 32 registers?

And this problem actually exists, that's why SPARC tried register windows and even crazier schemes on the software side of things had been proposed e.g. [0] — seriously, read this. And it's 30 years old, and IIUC nothing much came out of it so excuse me if I'm somewhat skeptical about "compilers can do better - but it's all a work in progress" claims. Perhaps they already do as best they can for general-purpose CPUs. Good thing we have other kinds processing units readily available nowadays.

[0] David W. Wall, "Global Register Allocation at Link Time", 1986, https://dl.acm.org/doi/10.1145/12276.13338
by account42 | 2026-02-16 08:44:40+00:00
> So the version here on youtube is a 16:9 widescreen crop of a 4:3 TV crop of the original 16:9 filming?

Only for the pilot (The Gathering), the rest seem to be from the 4:3 remaster which is probably the best version - so both same as the Blu Ray and streaming versions.
by freetime2 | 2026-02-16 08:46:34+00:00
Can I ask the significance/reason for the "..." after "you"? Serious question - there may be an age or cultural divide between us so an elipsis after "you" to begin a sentence is not a pattern of speech I'm familiar with. "You should watch him stream" on its own comes across as a friendly suggestion - and I just may do that. The "..." seems to change the tone, and I think possibly add a bit of snark, though I'm not sure if that's how it's intended.
Show HN: Animus Invoice – Invoice tracking without the busywork
by ilkerozbay | 2026-02-16 08:47:11+00:00
Hey HN! I built Animus Invoice after struggling with invoice compliance as a freelancer in Turkey.

The problem: Most invoice tools are either too complex or don't handle local tax requirements. You waste hours on paperwork instead of actual work.

Animus Invoice handles Turkish e-invoice/e-archive compliance automatically, tracks payments, and keeps you organized.

Currently in beta - would love feedback from freelancers dealing with similar pain points. Free beta access for early users.
by column | 2026-02-16 08:47:15+00:00
It does not matter that he vibe-coded it. It does not matter if any stars/twitter post were bought. He generated hype and that's what big AI company need at the moment. They hire him, they give a cut on that hype. If he's no good (at generating any hype) in the coming months, he'll be gone. It's hype all the way down.
by ninjagoo | 2026-02-16 08:48:39+00:00
I wonder if the providers are doing everyone, themselves included, a huge disservice by providing free versions of their models that are so incompetent compared to the SOTA models that these types of q&a go viral because the ai hype doesn't match the reality for unpaid users.

And it's not just the viral questions that are an issue. I've seen people getting sub-optimal results for $1000+ PC comparisons from the free reasoning version while the paid versions get it right; a senior scientist at a national lab thinking ai isn't really useful because the free reasoning version couldn't generate working code from a scientific paper and then being surprised when the paid version 1-shotted working code, and other similar examples over the last year or so.

How many policy and other quality of life choices are going to go wrong because people used the free versions of these models that got the answers subtly wrong and the users couldn't tell the difference? What will be the collective damage to the world because of this?

Which department or person within the provider orgs made the decision to put thinking/reasoning in the name when clearly the paid versions have far better performance? Thinking about the scope of the damage they are doing makes me shudder.