skysight-inc/HackerNews huggingface dataset:
> which involved complicated rust `no_std` and linker setup for compiling rust code onto bare metal RISCV from scratch.

That's complicated, but I wouldn't say the resulting software is complex. You gave an LLM a repetitive, translation-based job, and you got good results back. I can also believe that an LLM could write up a dopey SAAS in half the time it would take a human to do the same.

But having the right parameters only takes you so far. Once you click generate, you are trusting that the model has some familiarity with your problem and can guide you without needing assistance. Most people I've seen rely entirely on linting and runtime errors to debug AI code, not "solid fundamentals" that can fact-check a problem they needed ChatGPT to solve first place. And the "experience" required to iterate and deploy AI-generated code basically boils down to your copy-and-paste skills. I like my UNIX knowledge, but it's not a big enough gate to keep out ChatGPT Andy and his cohort of enthusiastic morons.

We're going to see thousands of AI-assisted success stories come out of this. But we already had those "pennies on the dollar" success stories from hiring underpaid workers out of India and Pakistan. AI will not solve the unsolved problems of our industry and in many ways it will exacerbate the preexisting issues.
> vs most things related to hardware or low level work.

counter point:

https://github.com/ggerganov/llama.cpp/pull/11453

> This PR provides a big jump in speed for WASM by leveraging SIMD instructions for qX_K_q8_K and qX_0_q8_0 dot product functions.

> Surprisingly, 99% of the code in this PR is written by DeekSeek-R1. The only thing I do is to develop tests and write prompts (with some trials and errors)
So, what are investors thinking to warrant this? If it is 'DeepSeek means you don't need the compute' that is definitely wrong. Making a more efficient x almost always leads to more of x being sold/used, not less. In the long term does anyone believe we won't keep needing more compute and not less?

I think the market believes that high end compute is not needed anymore so the stuff in datacenters suddenly just became 10x over-provisioned and it will take a while to fill up that capacity. Additionally, things like the mac and AMD unified memory architectures and consumer GPUs are all now suddenly able to run SOTA models locally. So a triple whammy. The competition just caught up, demand is about to drop in the short term for any datacenter compute and the market for exotic, high margin, GPUs might have just evaporated. At least that is what I think the market is thinking. I personally believe this is a short term correction since the long term demand is still there and we will keep wanting more big compute for a long time.
> Anything a CPU can do can just be done better

Nope. Anything inheriantly serial is better off on the CPU due to caching and it's architecture.

Many things that are highly parallizable are getting GPU enabled. Games and ML are GPU by default, but many things are migrating to CUDA.

You need both for cheap, high performance computing. They are different workloads.
I always called it VC-backed price dumping, many American tech companies got successful by taking enormous amounts of VC capital to simply price dump competition.

I get side eyes from Americans when I bring this up as a key factor when they try to shit on Europe for "lack of innovation", it's more a lack of bottomless stacks of cash enabling undercutting competition on price until they fold, then jacking up prices for VC ROI.
The notion I now believe more fully is that the money people - managers, executives, investors and shareholders - like to hear about things in units they understand (so money). They don't understand the science, or the maths and in so much as they might acknowledge it exists it's an ambient concern: those things happen anyway (as far as they can tell), and so they don't know how to value them (or don't value them).

Because we saw, what a week ago the leading indicator that the money people were now feeling happy they were in charge which was that weird not-government US$500 billion investment in AI announcement. And we saw the same being breathlessly reported when Elon Musk founded xAI and had "built the largest AI computer cluster!"...as though that statement actually meant anything?

There was a whole heavily implied analogy going on of "more money (via GPUs) === more powerful AIs!" - ignoring any reality of how those systems worked, their scaling rules or the fact that inferrence tended to run on exactly 1 GPU.

Even the internet activist types bought into this, because people complaining about image generators just could not be convinced that the Stable Diffusion models ran locally on extremely limited hardware (the number of arguments where people would discuss this and imply a gate while I'm sitting their with the web GUI in another window on my 4 year old PC).
This comment provides context.

https://en.wikipedia.org/wiki/List_of_proposed_amendments_to...

>Hundreds of proposed amendments to the United States Constitution are introduced during each session of the United States Congress. From 1789 through January 3, 2019, approximately 11,770 measures have been proposed to amend the United States Constitution.

> Collectively, members of the House and Senate typically propose around 200 amendments during each two-year term of Congress.

For amendment to pass, it requires 2/3 supermajority in both the Senate and the House of Representatives.
wow, this was really deep. Thank you very much for your comments.
I guess we just have to figure things out in life ourselves and not rely on any tool to tell us our purpose.
selling more does not necessarily mean you make more money. more efficiency could lead to less margins even if volume is higher.

moreover, even things are incredibly efficient, the bar to sufficiently good AI in practice (e.g. applications), might be met with commodity compute, pretty much locking nvidia out, who generally sells high margin high performance chips to whales.
Is it reasonable to assume that more senior devs benefit more from LLMs?
Yes, same here. As a European, I used to feel we (USA and Europe) were on the same side, the West, since they/you did save us from the baddies 70 years ago...

But who's the baddies now? China is not waging war everywhere. Or threatening to steal Greenland... Or ruining our teenagers with social media.
NumPy has no Fortran code, for quite a long time now. SciPy has and it is being rewritten. What you mention is the ufunc machinery underneath which is all C. NumPy also has SIMD support (albeit limited to certain functions). BLAS is also C/Assembly but only LAPACK is F77 (which is too much code to be rewritten).

This does not mean Fortran is bad (obligatory disclaimer for Fortran fans).
I was at one place where we tracked every bug introduced, and discovered more than 90% were in code written after 5pm. We dramatically cut our bug rate just by shutting down PRs outside of business hours.

The problem is that when our performance declines, so does our ability to judge our performance. We can feel more productive while actually doing a much worse job.
I’m dating myself but it reminds me of when e-mail hit the mainstream and Microsoft jammed it into every product with no thought for how it would really be used. Like in Excel … every email address in your spreadsheet would open the email client when you clicked the cell. Gee what if I want to edit the value in this cell instead of email the person? We’ll make that possible if you hold shift (or something). It was terrible and this feels exactly the same. The purpose is not to give the user a helpful AI assistant it’s just to be able to say “we have AI”. That’s it.
What was hilarious to me was I tried using it to figure out a niche config. I couldn’t use it because my employer totally locks down permissions. Not going to request bot access any time soon.
The key question is: has demand elasticity increased for Nvidia cards? An increase in elasticity means people are more willing to wait for hardware price to drop because they can do more with existing hardware. Elasticity could increase even if demand is still growing. Not all growths are equally profitable. Current high prices are extremely profitable for Nvidia. If elasticity is increasing future growth may not be as profitable as the projection from when Deepseek was relatively unknown.
it's open source, here is their platform called hai: https://github.com/HFAiLab/hai-platform
Thanks for your feedback. I really appreciate it
I imagine it's a mix of either using ChatGPT as an the oracle to get training data. Or, it's the radiocarbon issue where the Internet has so much info on ChatGPT other models now get confused.
Indeed LLMs are useful as an intern, they are at the “cocky grad” stage of their careers. If you don’t understand the problem and can’t steer the solution and worse has only limited understanding of the code they produce you are unlikely to be productive.

On the other hand if you understand what needs to be done, and how to direct the work the productivity boost can be massive.

Claude 3.5 sonnet and O1 are awesome at code generation even with relatively complex tasks and they have a long enough context and attention windows that the code they produce even on relatively large projects can be consistent.

I also found a useful method of using LLMs to “summarize” code in an instructive manner which can be used for future prompts. For example summarizing a large base class that may be reused in multiple other classes can be more effective than having to overload a large part of your context window with a bunch do code.
Nvidia's revenue growth rate was 94% and income growth rate was 109% for the Oct 2024 quarter. This compares to Apple's 6% and -35%.

Nvidia is growing profits faster than income.

Nvidia's net profit margin is 55% (vs Apple 15%) and they have an operating income of $21B vs Apple's $29.5

These are some pretty impressive financial results - those growth rates are the reason people are bullish on it.
I think you're missing the core argument here. Khan's warning wasn't about foreign competition - it was about how monopolistic behavior leads to technological stagnation. The Deepseek situation demonstrates this perfectly.
Let's look at the actual numbers:

- DeepSeek built their model with 2,048 H800 GPUs and $5.5M in computational costs

- Meta targeting 600,000 H100 GPUs

- OpenAI Used ~25,000 A100 GPUs for GPT-4

- Altman claims to need $7T for his "dream AI"

This massive efficiency gap suggests something deeper than just trade policy at work. American tech giants have become accustomed to solving problems by throwing massive resources at them rather than through efficient engineering.
The chip restrictions and Huawei ban are separate policy decisions based on national security concerns. But they don't address what Khan warned about - namely that allowing monopolistic practices would make these companies "fat and happy inside their castles," focusing on "performing alchemy with spreadsheets" rather than actual innovation.

DeepSeek's achievement is particularly interesting because they succeeded despite having access to less advanced chips (H800s instead of H100s/A100s). They had to optimize for efficiency, which ironically led to better results.

This isn't about whether export controls are justified - it's about how domestic monopolistic practices made our tech companies vulnerable to more innovative competitors, exactly as Khan predicted.
This totally makes sense, since Nvidia and ASML alike had hugely inflated market cap. This is more of a return to normal.
None of the models other than the 600b one are R1. They’re just prev gen models like llama or qwen trained on r1 output making them slightly better
Didn't DeepSeek train on Nvidia hardware though?

I can't see how DeepSeek hurts Nvidia, if Nvidia is what enables DeepSeek.
This might help

https://en.wikipedia.org/wiki/Stingray_phone_tracker
Of course. China wants to beat the US in innovation, and gain the economic and militaristic advantages which that brings. And they're going about it the right way if there's any substance behind that press statement.
It’s remarkable we’ve hit a threshold where so much can be done with synthetic data. The reasoning race seems an utterly solvable problem now (thanks mostly to the verifiability of results). I guess the challenge then becomes non-reasoning domains, where qualitative and truly creative results are desired.
Our closest cousins are actually bonobos (or at least they are as close to us as chimpanzees are), which don't have this type of hierarchy. Regardless, group social hierarchies don't necessarily translate even between closely related species, such as chimps and bonobos, so there is no reason whatsoever to extend them from some ape to humans.
Depends on what exactly you want to do, but there's a reason why these vendors can afford to charge so much while being so user-hostile.

I think the only "real" option is FreeCAD.

OpenSCAD makes you "code" your model instead of drawing it. There's a learning curve associated with every CAD software but I don't think you'll achieve a reasonable speed with this one even if you do put in the effort.

Blender is great for "freehand" modeling but awful if you want "real CAD" with accurate measurements, parametric modelling, constraints etc. - there may be plugins to make it somewhat work.

Onshape is free as in beer for hobbyist use but locks you into their platform and there currently doesn't seem to be a usable CAM solution yet, at least none that could deal with metal - if you want that for free, I think Fusion 360 (Autodesk, heavy lockin and serious restrictions on the free version) is your only realistic option.
I've only done a little bit of arduino programming, but for that you had to import a whole library for floating point math which took a huge amount of space, and many chips didn't even have hardware support for it.
Because if you don't have infinite money, considering whether to buy a thing is about the ratio of price to performance, not just performance. If you can get enough performance for your needs out of a cheaper chip, you buy the cheaper chip.
DeepSeek the holding company is called high-flyer, they actually do open source their AI training platform as well, here is the repo: https://github.com/HFAiLab/hai-platform
Fluorinert was absolutely something the USSR could produce. You need fluoromers and fluorine chemistry for nuclear technology.
> You really don't want to have to deal with multiple versions of the same library with compiled languages, but you have to with JavaScript.

Rust handles this fine by unifying up to semver compatibility -- diamond dependency hell is an artifact of the lack of namespacing in many older languages.
Yeah, this is a great point (and no offense taken—I appreciate the real talk even if it’s a bit painful to hear). I’m taking the other job because the risk is so much lower. And while I do believe that this business could potentially make me more money/be more fulfilling than a day job, there is a huge amount of risk that we’d never make any money and that I’d be forfeiting a guaranteed high salary. We’re still a ways away from making enough revenue to warrant me forfeiting the salary job.

I appreciate your insight. I’ll definitely keep this in mind. Even though I want to get my slice, I also want to be fair to my partner. It might just be that we’re not a good fit for each other right now.

If we can’t come to an agreement and I have to exit, do you have any suggestions about what to do with the app (I currently own the IP for all the code)?
> Government wields a magic wand that can make this happen.

What wand would government wave to make food prices decline in a short period of time? Cattle herds are at the lowest level in 73 years due to costs related to climate change (which influences beef prices), and the government isn’t going to mandate vaccination for poultry to stem Avian flu contagion (leading to flock culling, further intensifying the supply death spiral; this influences eggs and poultry meat prices). The majority of coffee comes from Brazil, Vietnam, Colombia, Ethiopia, and Indonesia; it can only be commercially grown in California, Hawaii, and Puerto Rico in the US. Show your work to support your assertion.

https://archive.today/bzPeJ

> Americans aren’t dumber than other people.

If you vote for someone who tells you they can make something cheaper they can’t actually make cheaper, and you don’t understand the how and the why, you are not a smart voter.

US Cattle Herd Shrinks to 73-Year-Low in Blow for Beef Lovers
- https://www.bloomberg.com/news/articles/2024-01-31/us-beef-t... |
https://archive.today/GJz4w

Major Florida grower [Alico Inc.] to end citrus operations after years of hurricanes and tree disease - https://apnews.com/article/florida-citrus-alico-hurricanes-g... - January 7, 2025

https://news.ycombinator.com/item?id=42806145 (citations wrt poultry, dairy, and meatpacking supply chain)

Food prices worried most voters, but Trump’s plans likely won’t lower their grocery bills
- https://www.ap.org/news-highlights/spotlights/2024/food-pric... - November 14th, 2024

Trump now says bringing down grocery prices, as he promised, will be 'very hard'
- https://abcnews.go.com/Politics/trump-now-bringing-grocery-p... - December 13th, 2024
Why not? It takes maybe a week to set up? And most of that week would be waiting for a funds transfer. It costs $0 to open and you get atm fee reimbursement and no international transaction fees. I get that people are busy but if you’re unhappy about something and you can change it, then why not carve out time to do so. People have plenty of time to seek new employment, this is just as critical.
Fair enough that people irritate you too much these days. I can't cast the first stone on that one...
Better get some chickens then!
good point, I also can just sleep/wake whenever so it doesn't matter. I don't like being locked into 9-5 despite the world operating on that schedule I get why
"Pr0n" is classic internet slang that predates onerous censorship let alone "apps".
Mackintyre is a professional historian whose work is based on first hand accounts so I think it can be taken as fact that many found him unpleasant.

I found it interesting & surprising to read of his character, having (possibly like you) only known of him as a war hero, and thought it worth mentioning, that's all.

So no need for vicarious outrage. As you say, he's long gone.
We need GPUs for inference, not just training. The Jevons Paradox suggests that reducing the cost per token will increase the overall demand for inference.

Also, everything we know about LLMs points to an entirely predictable correlation between training compute and performance.
Yes revenue has grown xx% in the last quarter and year, but the stock is valued as if it will keep growing at that rate for years to come and no one will challenge them. That is the definition of a bubble.

How sound is the investment thesis when a bunch of online discussions about a technical paper on a new model can cause a 20% overnight selloff? Does Apple drop 20% when Samsung announces a new phone?
New Year's Security Incident
The Celery Organization on github had a security breach which has led to organizational activity halting. A number of contributions to the Celery project (apparently) have been reversed.

In case anyone is wondering where the next Celery release was.
Are we just copying .NET now?
I think I'm being misinterpreted, probably my fault for the way I'm explaining things, I'm trying to be concise but I'm passionate about photography so I'm struggling.

I am not a pro, so far from it. I'd be embarrassed to even let a pro see my work. I don't want to advocate for needing things to be technically perfect, what I was advocating for was taking a single class, reading a single book, studying a couple blog posts or something. The little changes you can pick up can add so much to a photo. Say you move a little so the sun isn't behind your subjects, or you have the camera out explicitly in the winter mornings when the light is streaming into your windows and hitting a light curtain over the window... you've got yourself a free soft box. Or you've got the camera out in the hours before/after sunset and sunrise.

Little changes to behavior, your position, use of light that can put the extra thing on a photo that would already be great because it was a great moment.
Not that hard for China since they have hired a lot of TSMC top emgineers, like the head of TSMC finfet program. TSMC seems to treat them like dirt while they are treated like superstars in China.

Main deficiency they have is in the litho machines.
Please, for the love of privacy, make this new Pebble work with Linux phones.
Right, the form to deal with onerous censorship is “corn”.
It is really hard to answer this question without being provided any information whatsoever. Even though both can be used as full stack, nextjs is more front-end oriented, while django is the opposite. It really depends what you want to build. I personally use both, Django because it is battle tested and a joy to work with, Nextjs when I need a complex ui.
The pebble did not have an e ink display, It was just a low power LCD.
the jevons paradox isn't about any particular product or company's product, so is irrelevant here. the relevant resource here is compute, which is already a commodity. secondly, even if it were about GPUs in particular, there's no evidence that nvidia would be able to sustain such high margins if fewer were necessary for equivalent performance. things are currently supply constrained, which gives nvidia price optionality.
But the SOTA models basically all suck today. If people don’t think they suck, definitely in 1 year they’ll look back and consider those older models unusably bad
I created once a maven plugin to recompress Java artefacts with zopfli. I rewrote it in Java and runs entirely in the JVM. This means, the speed is worse and may contain bugs:

https://luccappellaro.github.io/2015/03/01/ZopfliMaven.html
I found the Stratechery and Nadella's takes to be interesting. Also the fact that news orgs say things like:

"The situation is particularly remarkable since, as a Chinese company, DeepSeek lacks access to Nvidia’s state-of-the-art chips used to train AI models powering chatbots like ChatGPT."

Whereas they don't mention the fact that Deepseek still used Nvidia chips. news orgs are implying they didn't.

Stratechery points out that the reduced memory/communications bandwidth of the gimped H800 chips they have access to drove the MOE/MLA architecture developments to make their model possible on the less powerful chips.

Nadella (on X) points out that by Jevons paradox [1], AI usage (and NVidia chip usage) will increase because deepseeks has reduced costs.

One other point Statechery made is that DeepSeek likely distilled the output of leading models for V3 and R1. They have shown that they can replicate the leaders cheaply and quickly, but they can't produce a leading model without copying (yet).

[1] https://x.com/satyanadella/status/1883753899255046301
It depends it think it’s less about how senior they are and how good they are at writing requirements, and knowing what directives should be explicitly stated and what can be safely inferred.

Basically if they are good at utilizing junior developers and interns or apprentices they probably will do well with an LLM assistant.
When results started coming out about the microbiome and health and there weren't any practical results (a poop pill that changes things) I thought it was one of those fads like gluten free or high-functioning autism.

The results have kept coming and it's hard not to believe the gut-health connection now but it's still frustrating that it doesn't translate to any therapy.
This feels really press-releasey. If the founders are around, and want this thread to go somewhere, jump in and talk in more detail about what this system actually does. Lots of token and inter-service auth nerds around here!