skysight-inc/HackerNews huggingface dataset:
If your mocks are hard to write you may have your fanout too wide and would do better with squaring up your dependency tree a bit. I have a rule of 5 for DI frameworks. If any module needs more than 5 other modules you should start looking to refactor to push dependencies down the stack.

What I see with Fakes too often is that they are difficult to write so people reuse them, end up writing too many tests that only test the fake, and couple a bunch of tests to each other which makes refactoring fraught. Anyone who makes refactoring difficult is an enemy to your project, not an asset.

Mocks make DAMP easier. You don’t care how the other function turns “foo” into “bar”, you just care what happens to this function when it gets “bar” as a response. That’s the surface area.

There’s a lot of people in this response chain who are very obviously conflating “unit tests” with all tests. Unit tests don’t care about integration. That’s integration tests. I liken testing to plumbing. Unit tests are similar to quality control at a pipe factory. You verify that the pipes aren’t damaged prior to assembly. The plumber inspects them before installing, and inspects their work as they bond or solder them together. But at the end of the day your plumber still has to turn on the faucet and make sure water 1) comes out the taps and 2) stays in the pipes everywhere but the sink, otherwise they haven’t done their job.

Unit testing the individual pipes is necessary but insufficient. You have to verify the connections and the end to end system still, but more work up front saves you some embarrassing rework at the end.
This won't solve anything. There's a myriad of sampling strategies, and they all have the same issue: samplers are dumb. They have no access to the semantics of what they're sampling. As a result, things like min-p or XTC will either overshoot or undershoot as they can't differentiate between the situations. For the same reason, samplers like DRY can't solve repetition issues.

Slop is over-representation of model's stereotypes and lack of prediction variety in cases that need it. Modern models are insufficiently random when it's required. It's not just specific words or idioms, it's concepts on very different abstraction levels, from words to sentence patterns to entire literary devices. You can't fix issues that appear on the latent level by working with tokens. The antislop link you give seems particularly misguided, trying to solve an NLP task programmatically.

Research like [1] suggests algorithms like PPO as one of the possible culprits in the lack of variety, as they can filter out entire token trajectories. Another possible reason is training on outputs from the previous models and insufficient filtering of web scraping results.

And of course, prediction variety != creativity, although it's certainly a factor. Creativity is an ill-defined term like many in these discussions.

[1] https://arxiv.org/abs/2406.05587
^ This perfectly encapsulates the story I see every time someone digs into the details of any llm generated or assisted content that has any level of complexity.

Great on the surface but lacks any depth, cohesive, or substance
I believe that AGI cannot be exponential for long because any intelligent agent can only approach nature's limits asymptotically. The first company with AGI will be about as much ahead as, say, the first company with electrical generators [1]. A lot of science fiction about a technological singularity assumes that AGI will discover and apply new physics to develop currently-believed-impossible inventions, but I don't consider that plausible myself. I believe that the discovery of new physics will be intellectually satisfying but generally inapplicable to industry, much like how solving the cosmological lithium problem will be career-defining for whoever does it but won't have any application to lithium batteries.

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

[1] https://en.wikipedia.org/wiki/Siemens#1847_to_1901
Another article immediately skipped for leading with GenAI image slop.
I can think of some runaway scenario's where LLMs are definitely bad but, indeed, this particular line of criticism is really just luddites longing for a world that probably doesn't exist anymore.

These are the people who regulate and legislate for us, they are the risk-adverse fools who would rather things be nice and harmless lest they be bad but work.

Personally, I think my only serious ideology in this area is that I am fundamentally biased towards the power of human agency. I'd rather not need to, but in a (perhaps) Nietzschean sense I view so-called AI as a force multiplier to totally avoid the above people.

AI will enable the creative to be more concrete, and drag those on the other end of the scale towards the normie mean. This is of great relevance to the developing world too - AI may end up a tool for enforcing western culture upon the rest of the world but perhaps a force decorrelating it from the McKinsey's of tall buildings in big cities.
Most of the time a PWA isn't needed at all, a mobile Web friendly website suffices.
I was wondering about that too. This is in the article linked to https://rubymamistvalove.com/block-editor

7. The previous version of Daino Notes, called Notes is FOSS (free and open-source software) available at https://www.notes-foss.com/ and the source code is available at https://github.com/nuttyartist/notes. I decided to make Daino Notes closed source due to difficulties in monetizing FOSS. In order to comply with Notes' MPL license, all common files between Notes and Daino Notes are published in https://github.com/nuttyartist/daino-notes-public
Google has issues with authentication.

I lost my childhood account because it decided the recovery codes, written on paper + stored in a safe location (matching) were all marked as invalid.

I'd have seen logs of them being used if someone had done something movie plot level like break into my personal safe.

I ended up just not going back -- I'd been experimenting with Protonmail, and libreoffice is enough for my word processing needs.
Without Comic Sans (https://www.youtube.com/watch?v=ynliPsRmmcQ) the world would be a worse place.
The tweet has some claims that don't fly.

You don't get the luxury of offline migrations or single-master writes in the high-volume payments space. You simply don't have the option. The money must continually flow.
The people who are lazy but have taste will do well, then.
Isn't it expected that most, if not all, of the content will be produced by AI/AGI in the near future? It won't matter much, if you're lazy or not. It leads to the question, what we'll do instead? People may want to be productive, but we're observing in real-time how world is going shit for workers and that's basically fact for many reasons.

One reason is that it's cheaper to use AI, even if the result is poor. It doesn't have to be high quality, because most of the time we don't care about quality, unless something interests us. I wonder what kind of shift in power dynamics will occur, but so far it looks just like many of us will just lose a job. There's no UBI (or social credit proposed by Douglas), salaries are low and not everyone lives in good location, but corporations try to enforce RTO. Some will simply get fired and won't be able to find a new job (that won't be sustainable for personal budget, unless someone already has low costs of living and is debt-free or has somewhat wealthy family that will cover for you).

Well, maybe at least government will protect us? Low chance, world is shifting right and it will get worse, once we start to experience more and more results of global warming. I don't see scenario, where world is becoming better place in foreseeable future. We're trapped in society of achievement, but soon we may be not able to deliver achievements, because if business can get similar results for fraction of the price (that is needed to hire human workers), then guess what will happen?

These are sad times, full of depression and suffering. I hope that some huge transformation in societies will happen soon or that AI development slows down, so that some future generation will have to deal with consequences (people will prioritize saving their own and it won't be pretty, so it's better to just pass it down like debt).
Fireworks, New Year, and Xmas golfed JavaScript code (in 140 characters or less)
Dwitter is a JavaScript-based social network where coders showcase their creativity by crafting mesmerizing animations and visual effects in just 140 characters of code. Check out this festive collection of fireworks, New Year, and Christmas-themed masterpieces!
PL_Synth by Phoboslab
I've yet to see a DSL work great. Every single time, I'm asking "why isn't this just Python (or some other lang)" especially the times when it's some jacked up variant of Python.
Yeah, the other skill you need to develop to make the most of AI-assisted programming is really good manual QA.
> And changing the user agent fixed it!

Send a note about that to the legal team at the Department of Justice managing the Google antitrust lawsuit.[1]

[1] https://apnews.com/article/google-search-antitrust-case-5911...
How? Morris didn’t get the job because he was born in the wrong country?
It sounds very similar to AI town - there's been a couple attempts at building virtual playgrounds for chatbots to interact with each other, and vote on solutions if they're trying to come up with a consensus. In that respect, it's probably similar to how mixture of experts work but just modeled at a higher level.

https://github.com/a16z-infra/ai-town

The big thing that you want though is diversity in terms of each of the AI's, and I'm not convinced that altering temperature / system context prompt / optional backing RAG represents sufficient variety from virtual bot to virtual bot.

Ideally, you would want to throw as many different LLMs (Llama, Mistral, Qwen, etc.) into the mix as possible, but hardware constraints make this borderline impossible.
Whenever I see these tricks(see also: the quake 3 fast inverse sqrt) involving using, not casting, but using integers as floats directly and floats as integers, I wonder if there is a way to do it without the jank.

Because what do you really want? some sort of exponent or exponent math right, some variant of the log function should work. is the problem is all the log functions are gated behind the function call interface. where as the subtract function is less heavy being behind the operator interface. or are they trying to use a floating point accelerated log aka floating point subtract?
Yep, abstracting away SQL is a common and very costly mistake. The article is about more general system design, otherwise I would have expected to see that in the list.
The "problem" is noone cares and certainly doesn't want to pay for the costs, especially the end users. That EOL equipment still works, there are next to no practical problems for the vast vast vast vast vast vast vast majority of people. You cannot convince them that this is a problem (for them) worth spending (their) money on.

Even during the best of times people simply do not give a fuck about privacy.

Honestly, if there is a problem at all I would say it's the uselessness of the Intelligence Community when actually posed with an espionage attack on our national security. FBI and CISA's response has been "Can't do; don't use." and I haven't heard a peep from the CIA or NSA.
that's 10% and who's to say that market is worth 1.5 trillion to begin with
Will 2025 Mark the Dawn of the Humanoid Robot Era?
As we approach 2025, it feels like humanoid robots are closer than ever to becoming a part of our daily lives. But do we need AGI for this revolution to truly begin, or is the next step simply about refining and perfecting existing technologies like perception systems?

What do you think is missing to make humanoid robots a reality in our homes and workplaces?
The recent arrest of a U.S. Army soldier accused of extorting AT&T and Verizon highlights a troubling misallocation of resources by law enforcement, especially when juxtaposed against critical nation-state cyber threats. While prosecuting such crimes is necessary, it diverts attention from larger systemic vulnerabilities, such as the recent breach of the U.S. Treasury Department and nine major American telecommunications companies by Chinese state actors. These breaches granted access to sensitive communications and revealed the glaring weaknesses in American cybersecurity infrastructure. Corporations like AT&T and Verizon, entrusted with protecting sensitive data, have often failed to implement robust defenses, leaving systems exposed to exploitation and forcing law enforcement into a reactive cleanup role.

This misdirected focus is particularly concerning given the escalating geopolitical tensions and the strategic importance of cybersecurity in national defense. Nation-state actors like China are leveraging advanced capabilities to outpace U.S. defenses, eroding trust in American institutions and diminishing global standing. With the potential for conflict over Taiwan and other critical flashpoints, resources spent on low-value cybercrime cases should instead fortify critical infrastructure and counter nation-state threats. A proactive approach is essential to prevent breaches, hold corporations accountable, and ensure the U.S. remains resilient in an increasingly volatile cyber landscape.
Gen-12 servers reliability, economics
Would that mean that we would need to exchange latent "embeddings" between various "reasoning" models for emulating thinking and an LLM will be just about converting to/from human language when interfacing with mere humans, at some point in the future?
To this day, asking Deepseek "what model are you" typically gives the answer

"I'm an AI language model called ChatGPT, created by OpenAI. Specifically, I'm based on the GPT-4 architecture, which is designed to understand and generate human-like text based on the input I receive. My training data includes a wide range of information up until October 2023, and I can assist with answering questions, generating text, and much more. How can I help you today?"

this tells us something about using synthetic data to bootstrap new model. All those clauses in the terms of service about not using the model to develop competing UI? Yeah, good luck with that.
> Every day by automation I feed in the hourly weather forecast my home ollama server and it builds me a nice readable concise weather report.

not to dissuade you from a thing you find useful but are you aware that the national weather service produces an Area Forecast Discussion product in each local NWS office daily or more often that accomplishes this with human meteorologists and clickable jargon glossary?

https://forecast.weather.gov/product.php?site=SEW&issuedby=S...
The use of Tailwind feels rather bloated to me. Seems a big part of why it is 22KB for RSS.xsl. Not that you necessarily need to code golf an XSLT file to be as small as possible, but it just contributes to my disregard for Tailwind itself as a source of bloat as another example from the wild where Tailwind seems verbose and baroque.
Why do we work? Ultimately, we work to live.* If the value of our labor is determined by scarcity, then what happens when productivity goes nearly infinite and the scarcity goes away? We still have needs and wants, but the current market will be completely inverted.
Productization in this context is creating APIs for Meta's models.

Fireworks.ai, Together.ai, and literal boatloads of other startups are making real money just efficiently serving up these models that Meta is supposedly using to... choke out startups.

The comment I replied to is under the mistaken idea that the presence of free models from Meta has a chilling effect on startups trying to build their own models, but right now the biggest barriers are capital and data.

Meta updated Llama to allow for synthetic generation, and they're even partnering with these startups give them distribution and day 0 access to the models.

-

If anything I'd say Meta is actively fighting against the big tech overlords the comment thinks they're trying to join. Even before Ilya mentioned it, it was clear to me that the power of post-training was going to become more and more important (I've literally built a business on it).

Llama represents a real ongoing chance for tiny startups with minimal resources to get into the fray very affordably (through either offering inference, or post-training for a specific task, etc.), scale revenue, and then start to compete against much larger, resource rich companies.
> If the Axis powers had won the war all the countries of Europe would have had even deeper "cooperation"

There you've placed a link from Fascism and "National Socialism" to the EU.

Nice try.
You may find Prioritized Grammar Enumeration as an interesting in-between DFS/BFS algorithm

https://seminars.math.binghamton.edu/ComboSem/worm-chiu.pge_...
> It's a total non-issue

Buying a separate device and carrying it all the time just for banking is a big ask for most people, even for geeks who hack their Android phones.
If you think about all the people trying to automate away farming, construction, transport/delivery - these people doing the automation themselves get automated out first, and the automation figures out how to do the rest. So a fully robotic economy is not far off, if you can achieve AGI.
Unfortunately, even after 2 years of ChatGPT and countless news stories about it, people still don't realize that LLMs can be wrong.

There maybe should be a bright red flashing disclaimer at this point.
Yeah, that's one of the biggest misconceptions I've been trying to push back against.

LLMs are power-user tools. They're nowhere near as easy to use as they look (or as their marketing would have you believe).

Learning to get great results out of them takes a significant amount of work.
Florida uses "hurricane deductibles" to cover coastal homes regularly threatened by hurricanes.
But that's the thing, KaiOS is exactly the best that Firefox OS could have hoped to achieve: installs on most feature phones. Sure, it's hard to find a phone with KaiOS in the West, but Firefox OS could have never hoped to be an alternative to Android.
They are still in the lead, and I'd be willing to bet that they have 10x the DAU on chat.com/chatgpt.com than all other providers combined. Barring massive innovation on small sub 10B models - we are all likely to need remote inference from large server farms for the foreseeable future. Even in the case that local inference is possible - it's unlikely it will be desirable from a power perspective in the next 3 years. I am not going to buy a 4xB200 instance for myself.

Whether they offer the best model or not may not matter if you need a PhD in <subject> to differentiate the response quality between LLMs.
The thinking goes:
- any job that can be done on a computer is immediately outsourced to AI, since the AI is smarter and cheaper than humans
- humanoid robots are built that are cheap to produce, using tech advances that the AI discovered
- any job that can be done by a human is immediately outsourced to a robot, since the robot is better/faster/stronger/cheaper than humans
Do you mean performance that was missing in the past is now routinely achieved?

Or do you actually mean that the same routines and data that didn't work before suddenly work?
> The need for summarizing is a
> symptom of our increasingly
> poor communication and degrading
> writing skills.

Whilst I agree there is a societal decline, there has also always been a corporate tendency towards verbosity and opaqueness.

The old rule from the days of memos still seems to apply: ignore first paragraph, get positive / negative gist from second, learn about the impact in the third, ignore remainder.
The game is just a fun logic challenge to get you thinking. I didn't realize saying it increases IQ might not be accurate and cause such a big reaction. It's more about exercising your mind.
Jim Cramer
And you can ask it if it's sure, and it'll consistently double down on insisting it's ChatGPT. Ask it what country it's developed in, and it'll say US; ask it if it's sure it's not China, and it'll be sure.
We don’t need to overstate racism, but “bigwig at TI” is a down leveling for Morris. Doesn’t seem right to limit greatness if it’s about race and not based on track record or other meritocratic signals.
I don’t think the article was well sourced. WebGL technologies might be adequate for casual games… maybe. But it will be a very long time before they approach AAA gaming performance. And there is still a ton of funkyness about input (gamepad? multitouch?) and latency that is hard to address on a web stack.

He just asserts that the underlying technology has come along. It hasn’t.
Ever had depression? Ever tried explaining it to somebody but they brush you off?

One man's "Depression" is another man's "normal brain function; life just gets hard sometimes and that's natural." Explaining to the latter person how dehabilitating the experience is doesn't matter because one person cares about subjective inner experience and the other cares about mechanistic physiology.

Similarly, one person's puberty can be extremely traumatic. People who aren't trans wouldn't understand.
Oh, thanks. I didn't realize that colors could be a problem. I will try to come up with something different next time.
Thank you Simon for the excellent work you do! I learned a lot from you and enjoy reading everything you write. Keep up. And happy new year.
I am curious if there is a coherent approach to modeling attention for long- or medium-term goal following. Currently, LLMs resemble a fish or a small child in their focus and behavior. Robots with such limitations would be strange to work with.
Like all AI simps, your blanket response to pointing out flaws is to tell me to do more prompt engineering and then dismiss the issue entirely. In the time it takes me to coax the model to do the thing I was told it knows how to do, I could just do the task myself. Your examples of LLM code generation are simple, easy to specify, self-contained applications that are not representative of software you can actually build a business on. Please do something your beloved LLMs can't and come up with an original idea.
yeah, they save as much time as finding a template with a good old search and using it.
You hook the kernel write. That is why I said hook the relevant kernel operations.

The primary complexity is actually in creating a consistent timeline with respect to parallel asynchronous writes. Record-Replay systems like rr usually just serialize multithreaded execution during recording to avoid such problems. You could also do so by just serializing the executing thread and the parallel asynchronous write by stopping execution of the thread while the write occurs.

Again, not really sure if that would be possible in Windows, but there is nothing particularly mechanically hard about doing this. It is just a question of whether it matches the abstractions and hooks Windows uses and supports.
Disagree with plugin talk. I use plugin system that loads from submodules so I can have same architecture in multiple airgaped networks. Can have implementations load (for that environment) outside of main code base. Nothing wrong w that given complexities of maintaining complex ass configs if everything was shoved into the same artifact.
According to the internal projections that The Information acquired recently they're expecting to lose $14 billion in 2026, so that record breaking funding round won't even buy them 6 months of runway at that point even by their own probably optimistic estimates.
I don't understand this. You don't have routes your users might need in robots.txt? This article is about bots accessing resources that other might use.
Indeed, although I find myself reaching for o1 more than Claude for matters other than programming, solely because it has better LaTeX (...)
I'm sure OpenAI breaches copyright just as well. They are just a little bit better at hiding it.