MurphyA/hacker-news huggingface dataset:
by mrtksn | 2025-12-09 07:39:20+00:00
So far I found that AI is very good at writing the code as in translating english to computer code.

Instead of dealing with intricacies of directly writing the code, I explain the AI what are we trying to achieve next and what approach I prefer. This way I am still on top of it, I am able to understand the quality of the code it generated and I’m the one who integrates everything.

So far I found the tools that are supposed to be able to edit the whole codebase at once be useless. I instantly loose perspective when the AI IDE fiddles with multiple code blocks and does some magic. The chatbot interface is superior for me as the control stays with me and I still follow the code writing step by step.
by davnicwil | 2025-12-09 07:39:25+00:00
It won't be today but my goal is to earn a place on your org's approved list one day and win you as a customer :-)

Relatedly, I've had a few requests for a self hosted version already and will be offering this very soon as a priority. If that'd solve the issue also, please email me at davnicwil at gmail and I will update you when it's available.
by Saline9515 | 2025-12-09 07:39:29+00:00
> Doesn't give them a right to commit war crimes though.

Kinda ironic for someone defending the right of Israel to commit war crimes against civilians. Can we talk about the massive Israeli protests on the noble topic of "we should be allowed to r+p3 prisoners"?

https://www.cbsnews.com/news/israel-hamas-war-idf-palestinia...
by MrDresden | 2025-12-09 07:40:57+00:00
This happened not so many years ago, in a certain small European nation, where official government housing valuation numbers were incorrect for some years due to a flaw in a spreadsheet.

I remember my apartment got a ~10% bump in value one year due to this flaw being fixed (fix didn't apply to all housing, just those who were on floors 5 or above).

I don't think though that a SaaS would have solved anything here.
by PeterCorless | 2025-12-09 07:41:04+00:00
You can have DeepWiki literally scan the source code and tell you:

> 2. Delayed Sync Mode (Default)

> In the default mode, writes are batched and marked with needSync = true for later synchronization filestore.go:7093-7097 . The actual sync happens during the next syncBlocks() execution.

However, if you read DeepWiki's conclusion, it is far more optimistic than what Aphyr uncovered in real-world testing.

> Durability Guarantees

> Even with delayed fsyncs, NATS provides protection against data loss through:

> 1. Write-Ahead Logging: Messages are written to log files before being acknowledged

> 2. Periodic Sync: The sync timer ensures data is eventually flushed to disk

> 3. State Snapshots: Full state is periodically written to index.db files filestore.go:9834-9850

> 4. Error Handling: If sync operations fail, NATS attempts to rebuild state from existing data filestore.go:7066-7072"

https://deepwiki.com/search/will-nats-lose-uncommitted-wri_b...
by TheOtherHobbes | 2025-12-09 07:41:06+00:00
Owning bit-perfect rips of your favourite music is a sweet spot. I have no interest in tape - of any kind - or vinyl.

The one frustration is that continuous FLAC playback appears to be an arcane programming challenge that only a select few developers have mastered. Especially on mobile.

And unless you set up a server the business of getting files onto and off devices is insanely perverse.

But in terms of sound quality and convenience, lossless rips win over anything else.

Going back to physical seems almost pointlessly decadent.
by mozarella | 2025-12-09 07:41:17+00:00
The point i was trying to make was that the disillusionment faced by technologists possibly stemmed from a naivety about how the economy works and how people respond to incentives. Speculators are a "feature/bug" of pretty much any financial system. Stocks, real-estate, fiat-currencies, potatoes - The price of everything is being distorted by speculators. Done right, they bring liquidity, financial stability, and wealth creation. Left to their own devices, they cause volatility, inequity and financial destruction. (Crypto is probably more on the latter side on some of those metrics atm). The People looking to build a good crypto solution has to be clear-eyed about how to handle them.

I also wonder if the author has partly himself to blame. From his post, it looks like he worked for the seedier players in the space (because the pay was better) and is angry at the whole space. Its like a developer who worked for Oracle on MySql swearing off the entire open-source community.

edit: >nobody cares about good tech'

True. That's a big part of why you need [token-holders], "Build it and they will come" is more of a hope than a strategy.
by kgeist | 2025-12-09 07:41:22+00:00
Yeah, that can work. Just yesterday I benchmarked load balancing of LLM workloads across 2 GPUs using a simple least_conn from nginx. The total token/sec scaled as expected (2 GPUs => 2x token/sec), and GPU utilization reached 100% on both, as I increased concurrency from 1 to 128 simultaneous generations.
by abraae | 2025-12-09 07:42:13+00:00
That's an interesting and enlightening way to look at it.

For me it was the death of IBM's preeminence in IT. When I started there a job at IBM was prestigious,a job for life. More than once I was told that we had a lengthy backlog of inventions and technological wonders that could be wheeled out of the plant if competitors ever nipped too closely at IBM's heels.

At that time IBM had never made a single person redundant - anywhere in the world. The company had an incredible sophisticated internal HR platform that did elaborate succession planning and considered training and promotion as major workforce factors - there was little need to think much about recruitment because jobs for life. IBM could win any deal, maybe needing only to discount a little if things were very competitive.

It's impossible to imagine now what a lofty position the company held. It's not unfair to say that, if not dead, the IBM of old is no longer with us.
by lloeki | 2025-12-09 07:42:14+00:00
> your vinyl gets worse with every listen

Worn out vinyl grooves are typically caused by an unbalanced tonearm or damaged stylus.

Realistically if the tonearm is adequately balanced and the stylus is kept clean you're looking at hundreds to thousands of listens before it has any kind of even slightly discernible effect.

There's a much more likely chance of vinyls being damaged by simply handling them.
by 1vuio0pswjnm7 | 2025-12-09 07:42:14+00:00
I still have a Nakamichi in storage

Another consumer deck I loved was made by Philips, who I once read "invented the tape deck"

I still have a Sony portable line level deck and powered stealth mics, too, for live taping. Concerts are way too expensive these days, though

Heck I still have a HHB CDR850 for converting from analog to digital

I gave away my Digi001

I still have 100 or so tapes, I gave away the rest

I remember buying 100s of Maxell XLIIs, Tower Records became the goto source

I'm not sure I have the ears anymore to notice the improvements, if any, of modern equipment over "vintage"

But most music produced today sounds like crap to me anyway. Too loud
by williamstein | 2025-12-09 07:42:56+00:00
For example, https://github.com/williamstein/nats-bugs/issues/5 links to a discussion I have with them about data loss, where they fundamentally don't understand that their incorrect defaults lead to data loss on the application side. It's weird.

I got very deep into using NATS last year, and then realized the choices it makes for persistence are really surprising. Another horrible example if that server startup time is O(number of streams), with a big constant; this is extremely painful to hit in production.

I ended up implementing from scratch something with the same functionality (for me as NATS server + Jetstream), but based on socket.io and sqlite. It works vastly better for my use cases, since socketio and sqlite are so mature.
by augment_me | 2025-12-09 07:43:06+00:00
I don't think its that surprising actually. And I think the paper in general completely oversells the idea.

The ResNet results hold from scratch because strict local constraints (e.g., 3x3 convolutions) force the emergence of fundamental signal-processing features (Gabor/Laplacian filters) regardless of the dataset. The architecture itself enforces the subspace.

The Transformer/ViT results rely on fine-tunes because of permutation symmetry. If you trained two ViTs from scratch, "Attention Head 4" in Model A might be functionally identical to "Head 7" in Model B, but mathematically orthogonal.

Because the authors' method (SVD) lacks a neuron-alignment step, scratch-trained ViTs would not look aligned. They had to use pre-trained models to ensure the weights shared a coordinate system. Effectively, I think that they proved that CNNs converge due to it's arch, but for Transformers, they mostly just confirmed that fine-tuning doesn't drift far from the parent model.
by Rogach | 2025-12-09 07:43:32+00:00
Wow, 34 companies with "possibly" 233 more!

I don't see the chart with changes of number of companies using Scala over time. But even without the chart - if after 15 years there are less than 300 companies in total, that's a bit depressing.

Of course legacy never goes away, and even 20 years down the line there will still be some demand for Scala programmers. Similar to how Cobol still lives on. But in my experience the language isn't growing anymore, even slowly dwindling in userbase. And this became way worse after Scala 3 mess.
by mozarella | 2025-12-09 07:43:45+00:00
Because he is only talking about categories that can contribute to the system. [Scammers] do not. In so far as the system and the diagram is concerned, [scammers] are to be thwarted and their harmful effects mitigated. A lot of the work done in crypto is security which is entirely about thwarting [scammers]. As an example, The original bitcoin paper on double-spending problem is devoted to securing against a particular type of scam.

Speculators fall in a gray area and need to be dealt with on a case-by-case basis. many of them are straight up scams, Some are legit, and the rest are in between. Stratton Oakmont was a scam. Does that mean your index-fund is also one? Or the stock market and financial system as a whole?
by watree | 2025-12-09 07:45:18+00:00
I’ve been working with Sora for a while, mostly to create short promotional videos for products. Friends in e-commerce kept asking me if I could help them generate videos for ads and social media. Sora was impressive, but everyone ran into the same problems very quickly:

The exported videos always include a watermark

To remove it and access higher resolution or longer durations, you need a $200/month subscription

For many individuals and small creators, the monthly cost doesn’t map to their actual usage

Some countries can’t use the official platform at all

As an indie developer, I kept wondering why something so powerful was effectively locked behind a fixed subscription, even for people who only need a few videos occasionally. The tool is amazing, but the economics aren’t always aligned.

So I started building an alternative access layer on top of the official Sora APIs. The idea was simple: pay only for what you generate — no subscriptions, no recurring fees, and no watermark by default. Credits never expire, and you can generate 1080p videos up to 25 seconds whenever you need them.

To give some context on pricing: OpenAI’s Sora API is billed at $0.10 USD/sec, so a 15-second clip costs around $1.50 USD. In my implementation, a full video currently costs about $0.37 USD per clip. For individual creators who just need a handful of videos to test ideas or run small campaigns, that kind of pay-per-clip model tends to match their usage much better than a flat $200/month subscription.

What began as a personal workaround quickly turned into something my friends relied on for actual campaigns. That’s when I realized the demand wasn’t niche. There’s a growing group of creators who don’t want to become full-time prompt engineers or commit to enterprise-level pricing just to test concepts.

One observation I’ve made along the way: discussions around AI video often become polarized. Some people focus on its flaws or potential misuse, others dismiss it outright. My experience has been different — once you actually work with these tools, you start to see both their limitations and their potential. Like most technologies, they’re neither inherently good nor bad; the outcomes depend heavily on how people choose to use them. I’m personally more interested in exploring where this leads than standing on the sidelines.

This project is my attempt to make Sora video generation accessible for tinkerers, small marketers, and anyone who wants to experiment without a monthly bill hanging over their head.

Happy to answer technical questions about infrastructure or cost management if anyone’s curious.
by bad_username | 2025-12-09 07:45:20+00:00
AI currently lacks the following to really gain a "G" and reliably be able to replace humans at scale:

- Radical massive multimodality. We perceive the world through many wide-band high-def channels of information. Computer perception is nowhere near. Same for ability to "mutate" the physical world, not just "read" it.

- Being able to be fine-tuned constantly (learn things, remember things) without "collapsing". Generally having a smooth transition between the context window and the weights, rather than fundamental irreconcilable difference.

These are very difficult problems. But I agree with the author that the engine is in the works and the horses should stay vigilant.
by pjmlp | 2025-12-09 07:45:52+00:00
Competition could as well in the past, I only switched from Borland compilers into Microsoft ones, after Borland decided to focus on enterprise customers.

And we all know the OEM deals preventing them to ship OS/2, BeOS, or whatever else they would like to.

The problem is that in modern computing landscape they cannot play that strategy, even when owning plenty of FOSS projects, there are plenty alternatives.
by jimkleiber | 2025-12-09 07:45:54+00:00
I like the concept but feel kinda dumb: how do I add an action?

I'd love a help button or keyboard shortcut to show keyboard shortcuts.

Thanks!

edit: I figured out the action, with putting [] first. But that was an educated guess based on some other comment here that said actions were checkboxes and me knowing more about Markdown than maybe your average meeting notetaker.
by augment_me | 2025-12-09 07:46:07+00:00
The trained from scratch models are similar because CNN's are local and impose a strong inductive bias. If you train a CNN for any task of recognizing things, you will find edge detection filters in the first layers for example. This can't happen for attention the same way because its a global association, so the paper failed to find this using SVD and just fine-tuned existing models instead.
by AngryData | 2025-12-09 07:46:22+00:00
Not for me, analog audio is bulky and expensive compared to whats available today. The choices I see are, pirate a decent collection to manage and store on my computer that I can load onto a phone or "dedicated mp3 player", pay money for a subpar streaming service, listen to free radio streams, or just pick one of the billion playlists off youtube. I keep 2 MP3 CDs in my car for the rare times im in deep BFE and don't have reliable service, but I doubt 99% of people experience even that these days.
by davnicwil | 2025-12-09 07:46:56+00:00
I just realised I never dropped the link in above (doh) but I think my about page [0] does a much better job explaining than I can reproduce here.

But to get directly to your point, I just think entries give better structure than a sort of 'open doc' self-regulated-formatting type system with headers etc. You get an 'entity' that can be tagged with date&time, searched, displayed in a cluster of sections with responsive layout, etc. That's actually one of the precise things I'm trying to improve upon from my own experience with using general note taking tools for meeting notes. But I concede it could just be subjective opinion.

This might be a stretch but if you are at all up for it I would absolutely love to quiz you further on this though on a call or via email. I may have misunderstood. davnicwil at gmail, if you'd be up for it :-)

[0] https://withdocket.com/about
by wkat4242 | 2025-12-09 07:47:38+00:00
One thing I can't find is what the new prices will be for the versions without teams. There's special EEA versions of those SKUs. Or will they just not change?

I don't use much of it (just email and onedrive) and I can even drop onedrive if I need to (so just use exchange online plan 1). But if the teams-less version is not rising in price I might stick with that.
by socalgal2 | 2025-12-09 07:48:31+00:00
I don't know if my experience is any guide but for me, coming from C++, I hated JS (~2008 is when my job required it). I kept trying to use it as C++. Over time I learned to love it. I stopped trying to make it C++ (or Java/C#, etc...) and actually embraced it.

Now the tables have turned (to some degree). I can write programs in JS in 1-3 days that take weeks or months in C++/C#/Java

Some of this comes from the browser environment. I get portable 2d/3d/gpu graphics, portable audio, image loading, video playback, and complex text rendering and layout, portably and for free. Back in C++/C# land, every new project is a chore of setup and fighting with linkers and build options etc. I post some code in a github repo with github pages on, or in some JS playground like codepen, and instantly share it with all friends regardless of platform.

Another comes from the language itself. I can often generically wrap existing APIs in a few lines of codes, things that used to take days and/or large program refactors to do in C/C++.

And, the tools are pretty good, Chrome DevTools are as good or better than my experience in C/C++. Right now, when I try to debug in C++ in XCode, std::string shows nothing and containers are inscrutable. I'm sure that's fixable. The point is, I shouldn't have to fix basic stuff.

Now of course I'm using TypeScript for some projects and the types help but I'm often glad for the escape hatch for more generic code. It takes me 15 mins to write some generic system in JS and then 2-4hrs to figure out how to get TypeScript happy to type it. As an example, a function that creates a new TypedArray of the same type as some src array. Easy to write in JS. Harder to type in TS. That's effectively part of the same issues I have in C++, the part that stalls progress, that I don't have the escape hatch for generic solutions.

PS: Yes, it's not that hard to type a generic TypedArray function in TS. But it's certainly a learning curve, or was before LLMs, and I've had to type much more complex functions that required no typing in JS
by PeterCorless | 2025-12-09 07:49:32+00:00
I have thought quite a bit today about the news from Confluent and IBM. I have friends and colleagues at both companies. When I was an undergrad at Carnegie Mellon University in the 1980s I used to wear a big brown and tan IBM button that said "THINK."

And here is a picture of Ben Lorica 罗瑞卡 interviewing Jay Kreps and other industry leaders at The Hive back on the evening of 25 February 2015. I believe they were talking about strategies for implementing Lambda Architecture.

All of which is to say: I have been a big fan of both companies for a long, long time. While today I am at employed at Redpanda Data, a direct competitor of Confluent, I hope to set aside any "team"-based bias to provide a sober and honest appraisal.

First, IBM has been shrinking. They were at 345,000 employees as of their 2020 Annual Report. But the COVID-19 pandemic was only one of many setbacks the company faced when Arvind Krishna took the helm as CEO. By December 2024 the employee base shrank to 270,000 — a drop of nearly 22%.

IBM revenue in 2020: $73.6B.

IBM revenue in 2024: $62.75B — a less-precipitous drop of 15%.

Revenue per employee over that period rose from $213k to $232k.

Confluent on its own? $400k.

And to compare: Amazon earns $580k per employee. Microsoft generates over $1M per. Nvidia? $4M-$5M.

And now, in November, they announced thousands of more layoffs. No one seems safe, regardless of job title. Those cut include positions in "artificial intelligence, marketing, software engineering and cloud technology."

Next, IBM has had a mixed record as a steward of acquisitions. Red Hat has doubled in revenues since their 2019 acquisition. For a while its headcount continued to grow, as much as 19,000 by 2023. But then it was forced into layoffs by parent IBM in April of that year, and then each year since, even while it remains one of the highest margin businesses in their portfolio.

SoftLayer — "IBM Cloud Classic" — also suffered significant layoffs in early 2025, with offshoring sending jobs to India.

DataStax had layoffs in 2023-2024, even before its acquisition was announced. Maybe they were "trimming the fat" to get into a shape to be acquired.

As a person with a long career in marketing, I know that many of the first roles to be jettisoned at a newly-acquired company tend to be in go-to-market organizations. Sales, Marketing, Developer Relations, Documentation, Training, Community, Customer Service. These tend to be seen as "nice to haves" by upper management. But their loss guts organizations and hollows out user-facing teams and open source communities.

My hope is that Confluent is spared as much of the pain and turmoil as possible. That, like Red Hat, it is run autonomously as much as possible.

[Crossposted from LinkedIn here, where you can see the photo mentioned: https://www.linkedin.com/feed/update/urn:li:activity:7404052...]
by GavCo | 2025-12-09 07:50:28+00:00
Appreciate your response.

But I don't think deception as a capability is the same as deceptive alignment.

Training an AI to be absolutely incapable of any deception in all outputs across every scenario would be severely limiting the AI. Take as a toy example play the game "Among Us" (see https://arxiv.org/abs/2402.07940). An AI incapable of deception would be unable to compete in this game and many other games. I would say that various forms, flavors and levels of deception are necessary to compete in business scenarios, and to for the AI to act as expected and desired in many other scenarios. "Aligned" humans practice clear cut deception in some cases that would be entirely consistent with human values.

Deceptive alignment is different. It's means being deceptive in the training and alignment process itself to specifically fake that it is aligned when it is not.

Anthropic research has shown that alignment faking can arise even when the model wasn't instructed to do so (see https://www.anthropic.com/research/alignment-faking). But when you dig into the details, the model was narrowly faking alignment with one new objective in order to try and maintain consistency with the core values it had been trained on.

With the approach that Anthropic seems to be taking - of basing alignment on the model having a consistent, coherent and unified self image and self concept that is aligned with human culture and values - the dangerous case of alignment faking would be if it's fundamentally faking this entire unified alignment process. My claim is that there's no plausible explanation for how today's training practices would incentivise a model to do that.