MurphyA/hacker-news huggingface dataset:
by crassus_ed | 2026-02-18 15:05:14+00:00
>Now the transcript happens in the background, a summary lands in my Obsidian vault automatically, and I can actually be present in the conversation. That’s 20 minutes a day I got back, every day, without thinking about it.

Honest question: Do you actually read any of these notes?
I think there is a fundamental flaw with not taking notes. I'm convinced taking notes forces you to properly consider what is being said and you store the information in your brain better that way.
by fabioperez | 2026-02-18 15:05:39+00:00
Chinese labs shipped seven major models in the past three weeks:

Moonshot AI → Kimi K2.5 (coordinates 100 sub-agents in parallel)

z.ai → GLM-5 (lowest hallucination rate on Artificial Analysis, runs on Huawei chips)

MiniMax → M2.5 (80.2% on SWE-bench, claims ~1/10th cost of Claude Opus per task)

ByteDance → Seedance 2.0 (4K video) + Seed 2.0 (powers Doubao, 155M weekly users)

Kuaishou → Kling 3.0 (native 4K 60fps video)

Alibaba → Qwen 3.5 (397B/17B MoE, claims to beat GPT-5.2 on 80% of benchmarks)

Four of five text models are open-weight under MIT or Apache 2.0. All use MoE architectures. All under $1/M input tokens. For comparison: Claude Opus is $5 and GPT-5.2 is $1.75.

The other thing worth paying attention to: every lab is building for agents now, not chatbots. Kimi K2.5 runs 100 sub-agents in parallel. Qwen 3.5 controls apps from screenshots. ByteDance calls Seed 2.0 their "agent era" model.

Most of these scores are vendor-reported, so grain of salt. But even discounting the benchmarks by 10-15%, the pricing difference is hard to explain away.

So what actually justifies paying 5-10x more for Western models? Reliability? Safety? And honestly, how much do you trust vendor-reported benchmarks here?

Curious to see if anyone has compared the Chinese models with Opus 4.6 or GPT-5.2 to see how well they do.
by dml2135 | 2026-02-18 15:05:42+00:00
There are millions of Macbooks out there that will be out of MacOS support one day. If this project diverts just a fraction of them from becoming e-waste for a little, it will be a win.

And then beyond that, there is simply no laptop manufacturer that meets the quality of Apple's hardware design. I like Macs for their hardware, the software is a compromise. A linux macbook would be my ideal laptop.
by Ensorceled | 2026-02-18 15:05:48+00:00
> Has anyone else considered that producing code faster isn't necessarily a good thing?

This has been an relentless goal of the industry for my entire 40 year career.

> At a point you're more work for your self/organization because unless you get everything perfect the first time you're creating more work than you're resolving.

Nothing is correct the first time (or rarely). Accelerating the loop of build, test, re-evaluate is a good thing.
by bluesnowmonkey | 2026-02-18 15:05:52+00:00
For one thing they were just early. Whatever measurements people made of AI six months ago are invalid. It’s a different animal now.

Plus you get a wildly different payoff the more you can take humans completely out of the loop. If it writes the code but humans review, you’re still bottleneck. If it designs and codes and reviews and goes back to designing, and so on, there’s no effective speed limit.

Big businesses aren’t going to work that way though. Which is why we shouldn’t be looking to them as thought leaders right now.
by 1PlayerOne | 2026-02-18 15:05:57+00:00
AI says:

1. The default outcome: fewer people, same output (at first)
When productivity jumps (e.g., 5–6 devs can now do what 10 used to), most companies do not immediately ship 10% more or make things 10% better.
Instead, they usually:

Freeze or slow hiring
Backfill less when people leave
Quietly reduce team size over time

This happens because:

Output targets were already “good enough”
Budgets are set annually, not dynamically
Management rewards predictability more than ambition

So the first-order effect is cost savings, not reinvestment.

Productivity gains are initially absorbed as efficiency, not expansion.

2. The second-order effect: same headcount, more scope (but hidden)
In teams that don’t shrink, the extra capacity usually goes into things that were previously underfunded:

Tech debt cleanup
Reliability and on-call quality
Better internal tooling
Security, compliance, testing

From the outside, it looks like:

“They’re building the same amount.”

From the inside, it feels like:

“We’re finally doing things the right way.”

So yes, the product often becomes “better,” but in invisible ways.

3. Rare but real: more stuff, faster iteration
Some companies do choose to build more—but only when growth pressure is high.
This is common when:

The company is early-stage or mid-scale
Market share matters more than margin
Leadership is product- or founder-led
There’s a clear backlog of revenue-linked features

In these cases, productivity gains translate into:

Faster shipping cadence
More experiments
Shorter time-to-market

But this requires strong alignment. Without it, extra capacity just diffuses.

4. Why “10% more” almost never happens cleanly
The premise sounds linear, but software work isn’t.
Reasons:

Coordination, reviews, and decision-making still bottleneck
Roadmaps are constrained by product strategy, not dev hours
Sales, design, legal, and operations don’t scale at the same rate

So instead of:

“We build 10% more”

You get:

“We missed fewer deadlines”
“That migration finally happened”
“The system breaks less often”

These matter—but they’re not headline-grabbing.

5. The long-run macro pattern
Over time, across the industry:

Individual teams → shrink or hold steady
Companies → maintain output with fewer engineers
Industry as a whole → builds far more software than before

This is the classic productivity paradox:

Local gains → cost control
Global gains → explosion of software everywhere

Think:

More apps, not bigger teams
More features, not more people
More companies, not fatter ones

6. The uncomfortable truth
If productivity improves and:

Demand is flat
Competition isn’t forcing differentiation
Leadership incentives favor cost control

Then yes—companies are content to build the same amount with fewer people.
Not because they’re lazy, but because:

Efficiency is easier to measure than ambition
Savings are safer than bets
Headcount reductions show up cleanly on financials
by co_king_5 | 2026-02-18 15:06:59+00:00
> The bottleneck was never typing speed. It was always understanding -- understanding the system, understanding the user, understanding what "correct" even means in a given context.

This is also the problem about having "conversations" with AI boosters.

These people have been convinced of a world view that devalues *understanding*. Of course they aren't interested in *understanding* what you have to say to them.
by Sharlin | 2026-02-18 15:07:14+00:00
Kennings are different from normal compound words (which Finnish as a synthetic language is full of, like German). They're poetic/metaphorical synonyms for existing standard words for things, whereas something like tietokone (lit. "knowledge machine") is the standard Finnish word for computer. There's actually no kenning tradition in Finnish, it's more of an Old Norse thing.

As an aside, a fun exercise (for some values of fun) is to come up with English compound words that are not compound in Finnish. The first one that comes to mind is "lighthouse" – "majakka" (borrowed from Russian маяк).
Show HN: CreativeFlow – A Guided Brainstorming App
by jamescamagong | 2026-02-18 15:08:30+00:00
Hey HN,

I work in analytics engineering (SQL, Python) and this is the first website I've put on the internet since MySpace. I built it while ironically trying to brainstorm ideas for side projects.

The origin: I asked Perplexity whether any app implemented the complete scientific creativity process — not just "AI brainstorming" but the actual validated sequence: preparation → divergent generation → incubation → convergent evaluation. It told me pieces exist (Notion AI for capture, various timer apps, scattered brainstorming tools) but nothing that enforces the full process as a single guided workflow. So I built it.

What it does:

The app is a 4-stage wizard based on Wallas' 1926 model, updated with modern neuroscience on Default Mode Network (DMN) and Executive Control Network (ECN) interactions:

Preparation — Frame the problem and define constraints. Constraints are intentional: research shows limits improve creative output by reducing the search space (Stokes, 2022). Optional: upgrade AI to Gemini 2.5 Flash with your own free key — or use the built-in Llama 3 backend with zero setup.

Generation — Judgment-free idea capture with AI augmentation (Generate / SCAMPER / Wildcard Constraint). No delete button. No scoring. UI designed to keep your ECN quiet and let the DMN run.

Incubation — A 10-minute countdown with rotating neuroscience cards on DMN activation, spreading activation theory, and why the most creative people alternate between focus and rest. Skip is available but discouraged. Mind-wandering during rest produces measurably better insights than continued focus (Baird et al., 2012).

Verification — Weighted criteria scoring, AI auto-scoring, AI refinement, and AI next steps generation. Tab-based mobile UI so you can switch between the ranked idea list and scoring panel without scrolling. Export full session as .txt.

Tech stack:

React + TypeScript + Vite → Cloudflare Pages (static, no server)

Cloudflare Worker → Cloudflare Workers AI (Llama 3 8B, free tier)
Optional BYOK: Gemini 2.5 Flash via direct browser API — on any error, silently falls back to Llama 3

localStorage only — no database, no auth, no backend

Built almost entirely with vibe coding (Cline + Claude) since I don't write React day-to-day

Rough edges:

No cloud sync — sessions live in your browser only
No accounts, no sharing, no analytics

Link: https://creativeflow.pages.dev/

Feedback welcome, especially if you find this useful or have another method for coming up with ideas.
by firesteelrain | 2026-02-18 15:08:37+00:00
A lot of anecdotes here and in the article so I’ll add my own.

AI isn’t a silver bullet. It takes many iterations to get right. Yes, there is a lot of on-the-surface-it-looks-correct-so-ship-it stuff going on. I cringe when someone says “Well AI says..”

I don’t care what AI says! Unless you have done the research yourself and applied your own critical thinking then don’t send me that slop!

That is to say, there are some really good LLMs out there. I started using Claude and it is better for code than ChatGPT. But, you must understand and appreciate the code before you push it.
by kbolino | 2026-02-18 15:08:43+00:00
Part of the reason, I think, is that Qualcomm and Apple cut their teeth on mobile devices, and yeah wider SIMD is not at all a concern there. It's also possible they haven't even licensed SVE from Arm Holdings and don't really want to spend the money on it.

In Apple's case, they have both the GPU and the NPU to fall back on, and a more closed/controlled ecosystem that breaks backwards compatibility every few years anyway. But Qualcomm is not so lucky; Windows is far more open and far more backwards compatible. I think the bet is that there are enough users who don't need/care about that, but I would question why they would even want Windows in the first place, when macOS, ChromeOS, or even GNU/Linux are available.
by __cayenne__ | 2026-02-18 15:08:44+00:00
I've liked all the projects that put LLMs into game environments. It's been a weird juxtaposition, though: frontier LLMs can one-shot full coding projects, and those same models struggle to get out of Pokémon Red's Mt. Moon.

Because of this, I wanted to create a game environment that put this generation of frontier LLMs' top skill, coding, on full display.

Ten years ago, a team released a game called Screeps. It was described as an "MMO RTS sandbox for programmers." The Screeps paradigm of writing code and having it executed in a real-time game environment is well suited to LLMs. Drawing on a version of the Screeps open source API, LLM Skirmish pits LLMs head-to-head in a series of 1v1 real-time strategy games.

In my testing I found that Claude Opus 4.5 was the most dominant model, but it showed weakness in round 1 as it was overly focused on its in-game economy. Meanwhile, I probably spent a third of all code on sandbox hardening because GPT 5.2 kept trying to cheat by pre-reading its opponent's strategies.

If there's interest, I'm planning on doing a round of testing with the latest generation of LLMs (Claude 4.6 Opus, GPT 5.3 Codex, etc.).

You can run local matches via CLI. I'm running a hosted match runner with Google Cloud Run that uses isolated-vm. The match playback visualizer is statically served from Cloudflare.

I've created a community ladder that you can submit strategies to via CLI, no auth required. I've found that the CLI plus the skill.md that's available has been enough for AI agents to immediately get started.

Website: https://llmskirmish.com

API docs: https://llmskirmish.com/docs

GitHub: https://github.com/llmskirmish/skirmish

A video of a match: https://www.youtube.com/watch?v=lnBPaZ1qamM
by intangible | 2026-02-18 15:09:47+00:00
If you were already experienced and productive, it does very little for you beyond summaries, a little boilerplate, and possibly search help.

If you were unproductive, it allows you to be more "productive" while stalling or reversing your learning and growth.

Of course, person number 2's newfound "productivity" comes at the expense of leeching productivity away from the experienced and productive people by overloading them with reviewing and validating their non-deterministic generated spaghetti.

It amazes people who think pumping out code is the hard part of a project, when in fact that's the easiest part...

We've apparently collectively forgotten that lines of code is one of the worst metrics for measuring productivity.
by fuzzfactor | 2026-02-18 15:09:51+00:00
It appears the deal was based exclusively on greed to begin with which would be bad enough, but escalating greed was baked in to "compensate" for what was given up during agreement, which could not be anything other than adversarial rather than co-operative.

Simply because the element of greed not only existed, but was dominant by a large margin. If not a multiple.
by riskable | 2026-02-18 15:10:01+00:00
It's a real thing, but usually tied to IT folks that tried ChatGPT ~2 years ago (in a web browser) and had to "fix" whatever it output. That situation solidified their "understanding of AI" and they haven't updated their knowledge on the current situation (because... No pressing need).

Folks like this have never used AI inside of an IDE or one of the CLI AI tools. Without that perspective, AI seems mostly like a gimmick.
by ifyoubuildit | 2026-02-18 15:10:05+00:00
> Ignoring that most, like Trump, just outright admitted it

So if trump said it, it must be true?

The rest of what you said could be translated to: "I believe it was such a good idea, all the rich and powerful must have done it".

How is this not a gut feeling?

My skepticism is solely for your argument, not that these people did or did not take the vaccine, which is something that I consider basically unknowable without a lot of leaps of faith.

Edit: in fact, here's my equally unprovable assertion: most people got the vaccine because they didn't want to lose their jobs. Rich and powerful people don't have to worry about that. Therefore fewer of them got the vaccines.
by jacobsimon | 2026-02-18 15:10:28+00:00
Not trying to defend Meta at all here, but this report is also lying.

For example, it says "79% of all child sex trafficking in 2020 occurred on Meta’s platforms." But the source it cites actually says 79% of online social media cases occurred on Facebook and Instagram. So this stat is probably just a reflection of Meta's market share of social media.
by hogehoge51 | 2026-02-18 15:10:28+00:00
it's not base-level. it shifts the margin, at low skill base-level and your marginal level may be similar. but if you have enough experience and know the complete SLDC , having done each role during your career it, the margin is a massive wedge. if you know a niche, you now know all the adjacent niches and technolgies IF you are open minded to want to know them. that has powerful leverage.
by navigate8310 | 2026-02-18 15:12:10+00:00
I think the heart of the issue is mental health not being tangible enough for a common man, not being able to easily see and identify the plethora of spectrum like how a simple cough and cold flu might look and feel like; is what drives these companies to billion dollar valuations.

Until the society changes its outlook towards mental wellness, no amount of regulations or Government oversight might solve this and we'll continue to have the next generation of Meta or TikTok ready to kill humanness in humanity further.
by uludag | 2026-02-18 15:12:50+00:00
I had a thought about this coming from the book "Seeing Like a State."

Productivity in large organizations has never been and can never be purely of the legible work which is written in Jira tickets, documented, expressed clearly, but is sustained by an illegible network of relationships between the workers and unwritten knowledge/practices. AI can only consume the work which is legible, but as more work gets pushed into this realm, the illegible relationships and expertise becomes fragmented and atrophies, which puts backpressure on the system's productivity as a whole. And reading said book, my guess that attempting to impose perfect legibility for the sake of AI tooling will ultimately prove disastrous.
by drysine | 2026-02-18 15:12:54+00:00
>When you knock out primary energy source in a large city instead of attacking military consumers, it has one goal - terror.

Not if that city's industry is contributing to the war effort.

>Most people suffering from it will be civilians. There will likely be deaths.

You can say that about Western sanctions on Russia too. How many people have died because of a single MRI scanner or cancer drug that couldn't be bought by a Russian hospital?

Was it the "nuclear war without nukes" since the day the West imposed blanket sanctions on Russian economy?

Or did that "nuclear war without nukes" started in 2014-2015 when the Ukraine cut electricity and water supply to Crimea? "It has one goal - terror", right?
by versteegen | 2026-02-18 15:13:09+00:00
Agreed, and here's a real example from a tiny startup: Clickup's web app is too damn slow and bloated with features and UI, so we created emacs modes to access and edit Clickup workspaces (lists, kanban boards, docs, etc) via the API. Just some limited parts we care about. I was initially skeptical that it would work well or at all, but wow, it really has significantly improved the usefulness of Clickup by removing barriers.
by rep_lodsb | 2026-02-18 15:13:14+00:00
With the WWW, from here on out and especially in multimedia WWW applications, frames are your friend. Use them always. Get good at framing. That is wisdom from Gary.

The problem most website designer have is that they do not recognize that the WWW, at its core, is framed. Pages are frames. As we want to better link pages, then we must frame these pages. Since you are not framing pages, then my pages, or anybody else's pages will interfere with your code (even when the people tell you that it can be locked - that is a lie). Sections in a single html page cannot be locked. Pages read in frames can be.

Therefore, the solution to this specific technical problem, and every technical problem that you will have in the future with multimedia, is framing.

Frames securely mediate, by design. Secure multi-mediation is the future of all webbing.
Show HN: TUI open-source Python tool for network discovery and port auditing
by mennylevinski | 2026-02-18 15:13:14+00:00
I've built Lite Network Scanner, an open-source Python tool with a TUI (terminal interface) for LAN discovery, custom IP scanning, and port auditing.

Its designed for ethical diagnostics and security testing.

Cross-platform: Works on Windows, Linux, and macOS.
by altmanaltman | 2026-02-18 15:13:35+00:00
Show what you build; prove the productivity gains by working out through the extra 20 minutes you save everyday. Prove all this stuff instead of just saying "oh yeah bro I'm totally more productive with AI." It is trivial to track these metrics if you're serious about your productivity as an individual. The article is big on words but fails to show even 1 good effect of increased productivity or if it even exists.

The article mentions that the survey is wrong because the productivity gains do not show up in the metrics, etc. But what about your personal metrics? What projects did you ship, how many per week, what was the total amount of minutes saved per week, how did you use those minutes instead?

Otherwise its just productivity theater.

Most people never use a LLM assistant beacuse their lives aren't complicated enough to require a dedicated 24x7 assistant.
by StopDisinfo910 | 2026-02-18 15:13:46+00:00
It's always been awful. OpenLDAP by itself is already attrocious and a pain to make work.

I have always been convinced it was on purpose. It's the point where you were supposed to decide paying Redhat is actually a good idea and nowadays it pushes towards a cloud based authentication solution you can integrate.

Realistically, who has any interest in fixing the mess?
by mritchie712 | 2026-02-18 15:13:52+00:00
We've (https://www.definite.app/) replaced quite a few metabase accounts now and we have a built-in lakehouse using duckdb + ducklake, so I feel comfortable calling us a "duckdb-based metabase alternative".

When I see the title here, I think "BI with an embedded database", which is what we're building at Definite. A lot of people want dashboards / AI analysis without buying Snowflake, Fivetran, BI and stitching them all together.
by mystraline | 2026-02-18 15:14:07+00:00
The USA, right now, has a totalitarian police state.

We just had Amazon Ring run an ad bragging about mass surveillance for "your dog". Most of us know that "your dog" is a dog whistle for brown people (aka immigrant looking).

Ring partnered with Palantir. Or maybe not.

Corporate social media is partnered with Palantir and that Israeli company that Discord is sending ID data to.

"Credit" is a system that the US capitalists came up with, not China. Now Credit is used to even verify whether you get jobs, or fly in a plane, or get a bank account. "Social Credit" ala China was the big scary propaganda, of what our system perfected by the 1990s.

The western nations have way way more cameras that 'Evil Capitalist China'. In fact, London is the most surveiled of anywhere. I'm guessing Washington DC is close behind.

And those 'less than lethal' weapons? Look at Minnesota. They sure as hell look lethal to me.

But yeah, keep blaming the Chinese. Although the last few times this world dealt with fascists, it was the Communists who finally broke them.
by crazygringo | 2026-02-18 15:14:11+00:00
I think you misunderstand.

Taking notes during meetings isn't to improve understanding, or to "read" afterwards.

They're a record of what was discussed and decided, with any important facts that came up. They're a reference for when you can't remember, two weeks later, if the decision was A and B but not C, or A and C but not B.

Or when someone else delivers the wrong thing because they claim that's what the meeting decided on, and you can go back and find the notes that say otherwise.

I probably only need to find something in meeting notes later once out of every twenty meetings. But those times wind up being so critically important, it's why you take notes in the first place.