skysight-inc/HackerNews huggingface dataset:
That's pretty neat.

The Resistant Starch 2 (RS2) in green bananas has served as my bowel-regulating medicine for decades now. TFA makes me wonder if rice prepared this way could have a similar effect. It's a nuisance to keep green bananas onhand for breakfast daily, and once they turn yellow the RS2 has become sugar and the medicinal value is gone. Rice however...
> Reminder that these models have no concept of truth, no abstract reasoning abilities

This has positive potential too - bias prevention. Give it an ultrasound and it'll do its work regardless of the patient.

None of this is guaranteed (there could be training pitfalls, i.e. maybe patient data is fed to AI, including race/sex, and if training data has bias toward non-white males then so will AI), but it's a potentially positive aspect to explore!
Hangeul very nicely reflects how Korean language's syllables change depending on what goes before and after them (phonetic context).

In comparison, most of irregularities with English spelling are either caused by extensive word loaning or by language changes that happened too long ago to make sense today.

So no, they're not the same.
I read the Reddit post and found that most people agreed that they got fooled by the fact that they didn't think it to be very controversial, just a bit silly maybe.

Perhaps the fear that people have, that these AI generated images could sway the public's opinion on high-profile cases isn't as realistic as perhaps these technologies being used to create small adulterations that could, combined, have a huge effect.
As a non senior data engineer, I think AI can take my job already, except that it requires my company to open up its code base for AI to consume and train seniors to be better prompt engineers so that they spend less time modifying code written by AI. There are a lot of edge cases but I think the tech is already here.

To escape from that fate I'm going to drill deeper into k8s, docker and Linux system programming. I know a better route is to launch a career that translates requirements from business stakeholders and develop an AI-friendly architecture so that our AI lords can conveniently code functions, scripts and programs without much interference. But throughout my career life I have tried my best to avoid that road (because I'm not interested in business), so I have to pick the second best way -- serve our AI lords by maintaining infrastructure for them, just like rhino birds serving rhinos I shall serve our AI lords faithfully in eternity, even after death when my coding skills can be consumed by them.
The DDT (deduplication table) used to require ~1GB RAM for every 1TB data written over the life of the file system. Deleting data from the file system wouldn't remove the dedupe references, you'd have to recreate the pool entirely and start over with a new DDT.

However, there are now special devices that can be used stored to store DDT. Typically this is done with two SSDs configured as a mirrored vdev for the DDT metadata. This reduces the overhead on memory, but does cost some performance and still has the same limitation that the DDT size can only be reduced by re-creating the pool.
I honestly don’t see how that follows from what I said. I would be curious to hear your reasoning.

Unless you mistakenly thought that the crypto industry has been built on solid foundational end-user demand for products this whole time.
What language do you use, CUDA-flavored C? I have found Numba's GPU JIT to be a great alternative, since you get to write Python.
Jorge Luis Borges’ widow María Kodama dies at 86
Thats why it provides disclaimers to everything it says medically
People seem to assume tech progress is always some linear or exponential thing where things just keep getting better.

They can’t imagine we could also just hit a plateau and have no progress for a decade until some other major breakthrough happens.

AI art is hitting a plateau or has hit a plateau. Progress came quickly for months but nowadays each update is just a bit better details with more resolution and better hands. That’s it.

If you have AI anxiety, just read my comment history.
Every industry has gotten less and less unionized.

Why would software buck the trend?
How I learned to stop worrying and love the bomb.
Most productivity gains over the last 50 years have flowed into the pockets of capital or property owners.
And therefore, "fish" is also silent!
> curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh

Oof. Can we please, please, please stop releasing software with "| sh"?
What about the landlords that bought property twenty years ago, when prices weren't going up? What's their excuse?

---

Their excuse is that they, as landlords, will charge as much for rent as they get away with, regardless of what their expenses may or may not be. Two identical apartments, owned by two different landlords, one of which costs its owner ~$1000/month, and the other ~$1,500/month will both be rented out for essentially the same price.

There's no need to spill ink on moralizing and justifying why rent's going up. It's going up because you (or someone else) has the money to pay for it to go up, and because you have limited alternatives.
Sounds to me like they should be spending a lot of money and effort to develop anti-drone devices.
I don't think you can disclaim your way out of this. Especially not if you end up causing harm and if you say things authoritatively. That makes a huge difference.

If they can add a disclaimer they can also say 'Sorry, ChatGPT-4 is not a doctor, consult your doctor'.

This of course would harm those who don't have access to doctors but even there you'd need to prove that it does more good than harm before you'd be allowed to put the output out there. Even the most innocuous medicine has to go through a standardized test before it is released to the public. Without proven efficacy it may well be a net negative.
Ah, gotcha, basically the proliferation of veto points as companies grow into corporations. In its idealized state, Amazon avoided that by giving autonomy to the deeper nodes (the famous Two-Pizza Teams).
> Curious what other software engineers are doing to prepare for these types of obvious changes.

Contemplating a professional change. Maybe I'm being overly pessimistic; people aren't being replaced yet. But maybe it's time for something else for me.

There are dire staffing shortages in nursing homes where I live – e.g., people develop bed sores because no one is available to turn them. I certainly could dedicate the rest of my life to that and it would make a real, tangible difference to people's lives.

It's a scary change though. I am a bit squeamish and I wonder how I'd fare. And it's a big loss in pay.

That's where I am in my AI-induced existential crisis, anyway.
Two questions:

Do you NEED a standing desk?

Can you afford a standing desk?

If you can answer 'YES' to either of these two questions, go right on ahead. Otherwise you might as well stick with a sitting style of desk.

Another alternative is the 'kneeling' style of chair for your desk. https://www.amazon.com.au/Levede-Kneeling-Ergonomic-Posture-...
They might have disabled the OS features it depended on to operate, though I have the impression attempting to do that might have made the Mac worse for professional audio production using any software.
Is there a name for this fallacy? Because I see it a lot.
I'm not the person you responded to, but that's an old paper. LLMs have come a long way since. Nothing conclusive but GPT4 does show some signs of something deeper. https://arxiv.org/pdf/2303.12712.pdf
Yet healthier foods are now less accessible to the poor. Where once the rich were fat and had rotten teeth from sweets, now the rich have trainers and personal chefs and healthier food. Poorer folks have food deserts and junk calories.

Innovation doesn't always trickle down. Sometimes it works in reverse to exploit the poor and the ignorant.
You're going to leave us hanging with the Photos story?
https://medtechinnovator.org/

Recommend getting in touch with Paul.
Is that the economy, or is it the way people are socialized to think about the economy, and life in general? The suicide rate in America is four times higher than in the poor developing country I’m from.
You’re right, there is a high variability in the complexity in physical tasks just based on factors you cannot predict. The quality of things that impact physical work versus software is fundamentally different.

I see people on here post construction projects as the poster child for things that can be estimated with traditional project management techniques. This is wrong because most construction projects come in over cost and over schedule.

This can be because materials costs change, labor costs change, the soil at your site may not be what you expected, weather impacts, and stakeholders may demand something different after the project is estimated.

Although these are unknown quantities, these factors existence are known. Whereas in software, you’re more likely to encounter unknown unknowns. These are factors that nobody thinks are even possibilities until you run into them because nobody has done anything similar before. An example from my experience is when I was working on implementing a marching cubes algorithm on a GPU, we did research to make sure that you could do it. But when it came time to implement, we found that the cube data was expressed as a set of faces, and not a set of vertexes and no efficient algorithm existed for that expression of the data that could be mapped to a single instruction multiple data paradigm. We could not preprocess the data to convert it to vertexes because it would not offer any speed up if we did. To implement the acceleration we wanted, you’d have to change how the data was stored in the application. Which is a very different project with very different timescales. We ended up abandoning the effort and moved to other work. This happened because we made a discovery that no one could have predicted, in the implementation, that had an unknown impact.

In physical projects, you might find there are a lot of unknown things that can happen, that you may not predict. You can certainly reduce this by bringing in experts to a project, people who have seen much more than you. Certainly there is still potential for black swan events. But these are rare. Where as in software, the experts you may bring on may not necessarily know more than you, you are frequently your own expert. Black swan events in software projects are common.
It could also be that something like this is just another tool in the toolbox. Sure, you could spend time trying to understand Blender's Python API, but lots of Blender users are not programmers. It could be really helpful for them to be able to say "Place 10 spot lights at random position within the boundaries of Mesh 3 with random intensity and color" and just have that appear, rather than having to go looking for a plugin that does it for them.
Or in other words, the "create an adversary capable of defeating Data" problem... just a bit less of an issue (for now) if you get the instructions wrong.
Maybe whatever you call “past performance doesn’t imply future results” or something.
That implies heavy reliance that the employers in my past were paying me a surplus over a living wage. The reality is that many employers do not pay a living wage forcing people to seek other means to earn an extra income to top their regular wage.
Even in the absence of AI, what's stopping this friend from going to a quack 'natural therapist'? If Steve Jobs can be fooled, what about an ordinary person?

ChatGPT is motivated by sycophancy, humans are motivated by profit. I would say the latter is much more dangerous than the former when it comes to medicine.

Remember, totally legit doctors were peddling opioid pills to patients in the name of "Treating undertreated pain". Profit distorts human minds very easily.

AI doesn't need to be perfect in every situation, just much better than the status quo.
Well, you get precision with imprecise communication via iteration. You walk together toward the correct mutual understanding by successive clarifications.
I think the article ends up makes the point in favour of AI anxiety:

> In particular, I started to realize that every little thing that we decide not to do as a company could have been done,

If every single company has more development bandwidth available, then at some multiple it would start driving demand and then wages down quickly. The multiple doesn't have to come just by AI improvements, as a lot of non developers can start using the AI to implement things.

It is very good if you intend to found a company, you have multiplied the things your company can do by leaps and bounds. Not so good for salaries developers.
How essential is the teaspoon of coconut oil?
> It seems there is plenty of well paid work though

I've been wondering this. I've seen lots of chatter about a retreating job market in the US, but here in London I'm still getting daily recruiter emails and LinkedIn requests. I could be wrong, but it doesn't feel like it's slowed down much here.
What are you talking about? Maybe for entry level with only a couple years they couldn’t own a home but come on? You think there are mid/senior level people with 5+ years working there who cannot afford a home??
I'm looking forward to when both the interviewer and interviewee are using something like this, and the entire interview is actually just an LLM talking to itself.
It's sad but true. Go look at any medical subreddit about ChatGPT, you all a sudden have 100s of AI experts trivializing GPT and suggesting it's nothing more than autocorrect.
Starbucks has way more unionized stores now than last year.
Code that's intentionally open source tends to have better security long-term. Proprietary code that was accidentally leaked is pretty bad for security in the short term.
Time yes, money no. They still give cost estimates.
If GPT-4 is talking to another instance of itself vs 3.5 are the results similar? Or is it only good at fooling a less capable version?
> can scale current models towards "true understanding" (or similar), is a total unknown atm.

Right, but it's no more known than before GPT models IMO. It's the same unknown.

I don't mean to imply these language models are not impressive. They are pretty impressive.
The article says they don’t know yet, but want to find out.
In my experience, the far more pernicious way to get N+1 is serializers (Django REST)
It says after catering to miners over gamers for the last 5 years.
You can't know the future. What you can know is the love for your child, should you have it. It is a great blessing. Don't let AI take that away.
What was it worth when he took ownership?
Yes, basically it can be extended to anything that allows scripting, which Inkscape does via "extensions". Someone will surely come up with something similar as this project but for Inkscape in no time :)
If you're going to do this, you may as well simply not use an ORM. Which is definitely the solution that I'd recommend; they are just not actually a good idea.
What if these companies did not hire some concrete number of people but had a pipeline set up to pass a certain fraction of applicants? Seeing how people get hired by Google, for example, and then get into a "team assignment" it certainly looks to be a possibility.

Then, what happens when the stock price doubles over two years and a significant fraction of the compensation is pegged to the stock price? Compensation grows too. And when compensation grows they get more applicants, I'd imagine. It's not like they had been getting few before but their hiring pipeline had been set up for the old rate of applicants, if this suddenly grew, they'd naturally get more hires. Especially considering that the additional applicants come from a cohort that had been compensated well enough to resist the pre-stock doubling comp numbers.

When the headcount had hit backstops, some hard headcount limits they likely have had, only then they realized how much did they hire and now react to this by doing layoffs and, probably, revising their HR policies.
Except that for someone outside CS theory it will be hard to tell what is routine and what is ground-breaking. The proceedings for the recent editions of top theory conferences are here:

- FOCS (Foundations of Computer Science) https://www.computer.org/csdl/proceedings/focs/2022/1JtvJWOs...

- STOC (Symposium on the Theory of Computer Science) https://dl.acm.org/doi/proceedings/10.1145/3519935

- SODA (Symposium on Discrete Algorithms) https://epubs.siam.org/doi/book/10.1137/1.9781611977554

They're mostly paywalled but conference or full versions can usually be found on arxiv.org, and there are successful efforts to host paywalled papers illegally for the public good.

Personally, I am impressed by the progress on approximate counting and sampling. Developments include localization schemes (FOCS), average-case entropic independence (FOCS), the sampling/counting Lovász local lemma in (FOCS and SODA), and approximate counting with global constraints (STOC).
Your kids are going to love AI. Why deny it to them?
Well, they hope other companies will do the same, or even fire people, so that there will be no hirings, and so people wont have a chance to jump ship...
I doubt ChatGPT does much to interviews. If you can use ChatGPT, you can Google, and if you can google and can put things together you will anyways be able to find the problem or the root of it online with solutions. Most interview problems can not be that unique.

Onsite interviews won't have any impact anyways.
That's the next job to disappear when parents have nothing else to do
but raise their young.
Yes, I have read that paper and have forwarded it eagerly to colleagues. Respectfully, please read the paper you have linked, especially section 8.2.

Look at section 8.2 in the paper you linked:

"8.2 Lack of planning in arithmetic/reasoning problems"

> However, it seems that the autoregressive nature of the model which forces it to solve problems in a sequential fashion sometimes poses a more profound difficulty that cannot be remedied simply by instructing the model to find a step by step solution

Nowhere in the paper is an evaluation on standard reasoning datasets (https://tptp.org) because they are much much much tougher than the simple examples that GPT-4 struggles with.

LLMs are a huge breakthrough but let us not muddy the science.
Interesting. Allows each organization to develop their own chatgpt model for a fractional cost.
> training a model on realtime video and backward time-shifted sensor data

Do you mean forward time shifted sensor data? I.e. using sensor data 30 seconds from the future as a label, and real time video as input?
> China can't build a 5 nm chip or a new type of wing or a useful new programming language.

You are saying this in a reply to the post to open source RTL of high performance CPU from China?

China also can demonstrably build a competitive distributed database like TiDB. I think PL vs DB boils down to that it is hard to create a profitable business building PL, compared to a profitable business building DB.
Commercial software isn't generally an artisanal crafting process. If you're a programmer who solves variations of a problem, analogous to a carpenter building varieties of cabinets, then you have parameterized tools. When the client asks for maple instead of oak, you don't pull out a maple board and start sawing. You'd just go to your cabinet_template.yaml file and change material=oak to material=maple. You don't have to estimate how long it will take to build the cabinet because it's already done, you just ran build_cabinet.sh.
It's extremely easy to write SQL queries that take a lot longer than they look like - an unindexed full table scan looks exactly the same as an indexed join, for example, whereas in a good ORM they will look different. So as far as I can see writing SQL manually is just extra drudgery for no real gain.
Sure, once we have a universal way to accomplish the task that's easier and safer.
Interesting. This allows organization to build their own chatgpt models at a fractional cost.
Oh boy, if you want to fling papers/research, i can do that just fine.

https://arxiv.org/abs/2212.09196v1

https://arxiv.org/abs/2211.09066

https://thegradient.pub/othello/

Moreover, "have trouble reasoning" and "can't reason at all" are two very different statements. Not that i particularly agree with either but you should keep that in mind.
I'm glad it is not just me who thinks I need to "thank" chatGPT or encourage it, e.g.: "Great, now do .... " "Great, now do ... ".
Apple considers PWAs a threat to their App Store cash cow. They would support them in an instant if they thought it would be profitable.
Am I crazy for thinking this way?

Absolutely not. That's not to say, by any stretch of the imagination, that it's a fait accompli that AI is going to lead to some future dystopian hellscape. Or that if it does, that that would happen in the lifetimes of your hypothetical children. But some dystopian scenarios are certainly plausible with a lot of open questions about how probable they are. Given that, it's very valid to be concerned about these topic.

I know that technology has always had an impact on society, and that we've always found a way to adapt. But AI seems different somehow. It feels like we're entering uncharted territory, and I'm not sure if we're ready for the changes that will come.

Look, I'm about as far from a traditional Luddite as you can get. Hell, I actively spend a decent amount of my time on AGI research even now. But even I have to admit that I have some qualms in regards to what the future is going to hold in this regard. I'm not in, or even close to, "complete and total freak out / melt down mode", and I'm not retreating off-grid to my secret bunker with 14 years worth of dried beans and 12 million rounds of 9mm ammo stored away. But I do spend a lot of time just thinking through scenarios, reading what other peple are saying, and just thinking and trying to build a solid case in my mind in regards to what is probably coming.

So if you're crazy, then well... you're not the only one.
It seems fairly parallel to selling products below the cost of production, which is widely viewed as anticompetitive and often illegal.
I wonder if the same technique could also be effective with pasta, cereals, etc.
Can you really blame people? As a country, we still remember all the horrible crap that was built in the 1950's and 60's in the name of the "greater good". Neighborhoods bulldozed to build highways, downtowns hollowed out to build malls and parking lots, and strip mall after strip mall. Practically everything built in this country after World War II looks ugly and cheap. It's not that Americans don't want new things to be built, it's that we don't trust the government and the real estate developers not to fuck it up. As they say, "trust is earned".
Zak, why’d you stop submitting links 10 years ago ?
Cooling and reheating pasta also converts it to resistant starch. https://www.sciencealert.com/heating-your-pasta-makes-it-sig...
What's also crazy is that GP's comment exist in the first place. Five years ago, complaining that a chatbot failed to understand the complexities of realtime 3D rendering when explained to it in plain English would be seen as confusing science fiction with reality. Hell, five years ago, we'd be reminded to avoid using anthropomorphizing language (such as "the software failed to understand"). Today, that same language is the most apt description of what we observe.
Wait until someone discovers that some modern way of cooking or processing (microwave, etc) unlocks the full caloric potential of some basic foodstuff and that is a primary cause of obesity today.

Oh wait, I think we already know this about sugar.