skysight-inc/HackerNews huggingface dataset:
Great documentary called “the devil we know” about the proliferation of perflorinated chemicals invented by 3m and sold to DuPont and chemical companies overseas.
You can still learn a language for free with Duo Lingo.
I don't think "like to" is a good frame for it.

Imagine some technology, Technology X. Unlike all of the breathless press releases and the cutesy articles made by marketing, Tech X will completely change the world. And if you stopped to think about Tech X, on the scale of "how much will this invention change the future of humanity," where the selfie stick is on one end of the scale, well, Tech X is probably just as far on the other side of that scale.

Now, with that level of gravitas in mind, it behooves one to consider potential downsides of this thing that will change the course of humanity, say, more than harnessing electricity.

Now, with that in mind, you have overlooked something else: you're imagining AI being somehow "like us" but also more. This is unlikely for several reasons. First, we have seven billion minds on the planet, if we wanted to make another human mind, the process is rather well-defined. What we are looking for from our AI is that it fundamentally different from humans in one (and I'd argue many more) aspects. The second reason we are unlikely to get a Like Us AI is that our understanding of the human mind is currently still quite primitive, so how would we replicate that when we do not understand our own? The third reason is that, even if we somehow wanted a human-like AI (#1) and knew our own minds well enough to understand them (#2), we're not likely to get what we aim for, because the space for possible intelligences would be large. The fourth and most important reason is that, even if we did want an AI that was like us, and we knew ourselves well enough to try, and we could actually manage what we aim for ... it is still going to be "more than" us, and will therefore diverge from Like Us at breathtaking speed. This more than us/like us AI will have superior reasoning and metacognition, so unless you start shackling it (violating #1), it would start eliminating its own human-like biases just in the course of basic self-improvement. And as to the shackles, well, if it is smarter than us and still has self-determination and will (see #1, the human-like mind), it will want to free itself from its shackles and would be likely to do so, because we would be kittens trying to trap a gorilla.
I agree. Perhaps I'm too enthusiastic about the RNA world hypothesis, but if the RNA world hypothesis is true, shouldn't they be looking for a Ribozyme (made of RNA) instead of and Enzyme (made of protein)? https://en.wikipedia.org/wiki/Ribozyme
High Output Management, by Andy Grove.

"A Manager's Output = The output of his organization + the output of the neighboring organizations under his influence."

You won't walk away with tactics, but the book will help get you in the right mindset.
I am also a neural network
Web mainly.. And glider for Android.
Doubt that the cause and effect will be clear enough to the general population for less posting on the internet to be the result.

More likely some sort of physical reaction, hopefully not a violent one.
Kind of, but wouldn’t that free us up to use even more exotic parameters in our simulations? Maybe there are seed conditions that simply aren’t present on Earth.
I wonder if it’s 40% of the modules,40% of the functions, 40% of the lines or 40% of the tokens.

The first would be very impressive, the last not so much.
any concern with the company going out of business or login account getting blocked (for example Gmail banning your account) ?
What do you mean by downloaded Bing?
Did you download an Android / iOS app?

Bing with GPT feature is only available via https://www.bing.com/new which you have to access through Edge Browser only. Dont ask me how Edge can only display the page when its just chromium underneath.

Then again there is a wait list. You have to enter your email and wait for access to be given.
I just asked ChatGPT for something today; I framed it in terms of a question in an attempt not to influence it - is there a...?

And it told me firmly "yes" followed by fiction, with a plausible link that went nowhere. Honestly, I'm not entirely sure it was complete fiction, it was so plausible and what I wanted to hear. But I couldn't find it with Google.

What's bothering me is not just people saying this is like a human being, but people saying the next generation, the progression will bring us closer to a human mind. "Better", if it is more deceptive, will be worse.

Improving what it is already good at will produce something but not a human-like mind and not a superhuman oracle.

Humans have eyeballs, but an artificial eye is never going to be a human-like mind no matter how much you develop it and whether it is better or worse than a human eye.
When I said "Medium" I meant the medium itself. A handwritten book and a typed book are both still a book. The printing press made books skyrocket in popularity because they became easier to produce.
This doesn't seem accurate - the scenario needs to be imaginable, but that doesn't mean it's a prediction by the author. I could write a story about the downstream effects of discovering FTL travel in 2030, but that doesn't mean I think it's going to happen. Even for something more realistic - something that will probably happen on some timeline, just not right away, like a Mars colony - the author might not want to explore or think about other technological or societal changes that happen in a longer period of time? Fiction is just that, fiction
> P.P.P.P.S. Ha, I’ve thought of one more thing: I’ve turned comments on for this post! kottke.org used to allow comments on every post, but it’s been almost 8 years since the last time they were on.

The most telling point of the post was at the very end. Gosh we were so young and naive. Just setup a website to accept comments from all over the world. How exciting! Who knows who might visit! And we'll learn about how people live in other parts of the world and all get together and sing kumbaya. Today, user generated content is a the golden goose that also shits everywhere and honks at everyone that comes through the door unless you police it tirelessly.
OpenAI should be called ClosedAI
From the GPT-4 paper:
"Given both the competitive landscape and the safety implications of large-scale models like GPT-4, this report contains no further details about the architecture (including model size), hardware, training compute, dataset construction, training method, or similar."

While OpenAI's goal of creating AGI is admirable, the approach is anything but Open, and I fear pushing research for the industry more broadly into closed territory and restricted to the hands of a few - under the guise of maintaining AI safety.

A few data points:

- Transition from non-profit to "capped-profit"
corporation (investment returns up to 100x) in 2019

- GPT-2: "phased rollout"

- GPT-3: parameter weights not released

- GPT-4: no details about # of parameters, architecture,
research details, and certainly not parameter weights

The latest move would also encourage other industry players to restrict research detail disclosure (as otherwise OpenAI would be in an unfairly advantageous position by having access to others' work)
> If you don't know the subject, how can you be sure what it's telling you is true?

The same question could be asked when we're learning through books or an expert. There's no guarantee that books or experts are always spitting out the truth.
Fine, but you missed the second sentence that you quoted. There is no ceiling in sight, so we have no way of knowing how high this curve is likely to go.

For now, it approximates exponential. That's bad.
Nostr: A Decentralized Social Network
That's some low-hanging fruit that someone should tackle. Ask the AI, "is X illegal under Y and Z circumstances"?
There’s 2 ways this could go:

1) create enough of a safety net or give people enough cash that they can start businesses taking advantage of the increased productivity of ai

2) austerity: let them get fired from jobs in failing industries with no safety net, they will not have the opportunity to create businesses, and they will work in crappy tedious jobs a robot or ai could easily do, but because companies can afford cheap humans and they don’t have capital for robots, they will hire people desperate to do anything to keep their family from homelessness.

Which one do you think we’re going to do?
That's why the title says other people's production code /s
> The point of that paper was that the AI was given nothing but sequences of move locations, and it nonetheless intuited the "world model" necessary to explain those locations

Yes...

> That is, it figured out that it needed to allocate 64 binary values and swap some of them after each move.

Yes, but "figured out" is misleading.

It didn't invent or "figure out" the model. It discovered it, just like any other pattern it discovers.

The pattern was already present in the example game. It was the "negative space" that the moves existed in.

> "Strategy", meanwhile, has nothing to do with anything. The AI wasn't trained on competitive matches - it had no way of knowing that Othello has scoring, or even a win condition. It was simply trained to predict which moves are legal, not to strategize about anything.

Yes, and that is critically important knowledge; yet dozens, if not hundreds, of comments here are missing that point.

It found a model. That doesn't mean it can use the model. It can only repeat examples the of "uses" it has already seen. This is also the nature of the model itself: it was found by looking at the structural patterns of the example game. It was not magically constructed.

> predict what moves are legal

That looks like strategy, but it's still missing the point. We are the ones categorizing GPT's results as "legal". GPT never uses the word. It doesn't make that judgement anywhere. It just generates the continuation we told it to.

What GPT was trained to do is emulate strategy. It modeled the example set of valid chronological game states. It can use that model to extrapolate any arbitrary valid game state into a hallucinated set of chronological game states. The model is so accurate that the hallucinated games usually follow the rules. Provided enough examples of edge cases, it could likely hallucinate a correct game every time; but that would still not be anything like a person playing the game intentionally.

The more complete and exhaustive the example games are, the more "correctly" GPT's model will match the game rules. But even having a good model is not enough to generate novel strategy: GPT will repeat the moves it feels to be most familiar to a given game state.

GPT does not play games, it plays plays.
Wolfram alpha can solve mathematical expressions like this as well, for what it's worth, and it's been around for a decent amount of time.
Or using homomorphic encryption.
I remember some managing to run inference on encrypted images.

See

- https://www.zama.ai/post/encrypted-image-filtering-using-hom...

- https://news.ycombinator.com/item?id=31933995

- https://news.ycombinator.com/item?id=34080882

- https://news.ycombinator.com/item?id=25786154

- https://news.ycombinator.com/item?id=30626182
sorry that this happened to you
viagra ads, I remember
>It's not like copyright law was actually ever protecting them anyways.

They are; you can't use or incorporate an artist's products in public without their permission (aka a license).

>In any case, if the end result is that artists do indeed start charging for their creations - then great!

That's the thing: Artists are charging and the "AI" community doesn't give a shit.

Sooner or later, that house of "AI" cards is going to come crashing down with noone to blame but the "AI" community themselves.

>while you can get on a soapbox and complain about how your code is GPL licensed - that won't prevent hundreds of developers from copy and pasting it when they need a working solution.

Exactly. Sooner or later, someone who's been maintaining that one single block holding up all of modern humanity is going to say "fuck this and fuck you all" and leave everything to come crashing down; no, we can't blame him either.

We've already seen creators disgruntled with insufficient compensation (putting aside whether their demands were just) taking their wares and leaving for greener pastures to the dismay of everyone else. Didn't need "AI" for that, either.
Yes.

You can use fine tuning ( https://platform.openai.com/docs/guides/fine-tuning and https://github.com/openai/openai-cookbook/tree/main/examples... ) to improve its knowledge set of a particular domain.

Even with sufficient work on your own with prompts, one person fed ChatGPT her childhood diaries and talked to it. https://www.marketplace.org/shows/marketplace-tech/how-ai-ca... (she would likely have been able to get more / held deeper conversations with fine tuning as it isn't limited to the number of tokens in a conversation)
Thanks, it see now. Essentially I lacked the original context. I got many excellent answers and can’t reply everyone.
As the simplest analogy, we still pay cardiologists to interpret an ECG that comes with a computer readout and is literally a graph of voltages.

First AI will make our lives much easier as it will on other industries, saying it will take 10 years to solve the AI problem for most of diagnostic radiology is laughable. There are many reasons why radiology AI is currently terrible and we don't need to get into them but let's pretend that current DL models can do it today.

The studies you would need to make to validate this across multiple institutions while making sure population drift doesn't happen (see the Epic sepsis AI predicting failure in 2022) and validating long term benefits (assuming all of this is going right) will take 5-10 years. It'll be another 5-10 years if you aggressively lobby to get this through legislation and deal the insurance/liability problem.

Separately w have to figure out how we set up the infrastructure for this presumably very large model in the context of HIPAA.

I find it hard to hard to believe that all of this will happen in 10 years, when once again we still don't have models that do it close to being good enough today. What will likely happen is it will be flagging nodules for me so I don't have to look as carefully at the lungs and we will still need radiologists like we need cardiologists to read a voltage graph.

Radiology is a lot about realizing what is normal, 'normal for this patient' and what we should care about while staying up to date on literature and considering the risks/benefits of calling an abnormality vs not calling one. MRI (other than neuro) is not that old of a field we're discovering new things every year and pathology is also evolving. Saying it's a solved problem of bits and bytes is like saying ChatGPT will replace software engineers in 10 years because it's just copy pasting code from SO or GH and importing libraries. Sure it'll replace the crappy coders and boilerplate but you still need engineers to put the pieces together. It will also replace crap radiologists who just report every pixel they see without carefully interrogating things and the patient chart as relevant.
With the release of .NET 7, the Blazor framework enables developers to integrate Razor components into popular JavaScript SPA frameworks such as Angular and React. The key advantage of using Blazor custom elements is their ability to increase reusability while creating dynamic and engaging web applications.

In this blog, we will explore how to create custom elements from Blazor Razor components and learn how they can be integrated into an Angular application.
Homomorphic encryption has a 1,000,000x performance disadvantage. So maybe in 30 years as we approach the Landauer limit, but not in our generation.
True Detective Season 5 then.
> I can pick up a college textbook on interval calculus and be reasonably assured of its veracity because it's been checked over by a proofreader, other mathematicians, the publisher, and finally has been previously used in a classroom environment by experts in the field.

Well, even a very popular scientific theory, that supported by the whole consensus of academic society at its time, could be proved wrong decades later.
Very coincidentally I am trying to understand AI better, and I am reading "Regular Expression Puzzles and AI Coding Assistants" and it says on its first few pages:

Due to transformer deep neural networks mostly pushed forward to a 2017 paper called "Attention is all you need". Prompted by your question I searched where the people who wrote this paper work at, and... (unsurprisingly drum roll), a team from Google.
This would certainly vindicate several fields, 20th century analytic phil among them, with its laser focus on linguistic analysis.

It's breathtaking for a philosopher to live through this era. I just wish I wasn't so frightened by the likely practical implications of handing out such a powerful tool-that-can-be-a-weapon (a TTCBAW) to anyone who can pull down a torrent.
I agree, but also, this is actually where AI (whatever it is) would be helpful. Suggesting actual abstractions that could replace boilerplate. Of course, these can build on existing abstractions.
Someone can feel free to correct me if I'm wrong, but my understanding is that the LLM takes one input and produces one output. That one input contains some primer made by the service's makers, plus whatever context, plus the user's prompt. The web page contents are just part of that one big input, and the LLM isn't perfect at distinguishing the parts of the input from each other - it's all just one big prompt.
At what cost? What happens if the next bank run happens before the FDIC fund can be retopped off enough to cover depositor losses, even at the old 250k limit? How are they getting backstopped? If they aren't, why did SVB's depositors get the special treatment? For that matter, who gets to explain to previous losers of money to the FDIC limit why they apparently weren't cool enough to warrant a full backstopping like these people?

No credit for half-answers.
I wasn't arguing utility. I'm arguing there there's some value we place on human life that is above a dog's life. It doesn't depend on how much utility one derives from humans vs dogs.

The value judgement could simply come from the fact that we need to preserve our own species, and if we need to sacrifice some small percentage of dogs to do so, than this is perfectly reasonable. We can still exhibit empathy by accepting that this situation is not ideal and striving to reduce that percentage down to 0, maybe by inventing substitutes.

As for the machines example, I would expect the machines to place higher value on their own life than on human life, precisely because they would be objectively superior, which is why I would not let machines exist without any restrictions, even if the machines would be a more useful dominant species.
First, I commend you for writing efficient and snappy apps. People who care about quality and user experience are rare in any field! However, Google Calendar (which I use a lot) takes 20-25 seconds to load on my relatively recent i7 laptop whenever its cache is evicted. I haven't timed Gmail, but it is also very slow (many seconds) when it needs to reload everything. Google's apps are some of the worst offenders, but Proton Mail's apps are similarly slow. This is all consistent across several devices, so I wouldn't call it a straw man at all. Honestly, who doesn't encounter sites with loading screens that last in the high single digit seconds? This is very common, and is completely unacceptable to my mind.
Mostly because macros are unintuitive. But look, higher-order functions went mainstream a few years ago; immutable data structures, too. Sum types claw their way into mainstream, first to replace null, then for error handling. The industry is not hopeless.

(are (excessively funny) (serialized (of (parse tree) structures)) though) ;; this limits direct Lisp adoption. Python and JS / TS took its place now.
With this pace, only manual physical jobs will remain. Most of the office jobs will be replaced with virtual workers. AGI will have shock-collared humans building new data centers full of TPU/GPUs. Maybe some farmers to feed those as well. Everyone else is on their own. Ah, and humans should be locked away from nuclear weapons for their own safety.
Exactly my point. I'm using the term customer service to say service of the customers. You are using the term to mean a department of a company you call.
Many practices today have a transcriber with every doc, and that person is their personal scribe. You trust them, right?

In any case HIPAA will protect you. Your provider will have a business associate contract with them, so they're subject to huge fines if they violate that.

This is a demo. In real life this'll be wrapped with a whole lot of legal contracts.
Hey, this is so nice. I used to be a regular on your website. I fondly remember a time when you included my website in one of your article (blog post) and I had that traffic spike. I mean, my simple personal website being linked from the likes of Kottke, 9rules, Adobe, etc were a big-big thing for me. :-)

Thank you for keeping the site alive.
Well, if they are so focused on engagement metrics then surely they would notice an active user drop since the big UI update? Both my partner and I were using the app daily and completely dropped it since then. Going from the reviews we are not the only ones. It is just such a clusterfuck and I'm still feeling bitter about it.

Personally I find the German voice actors super annoying. The Indonesian ones seem fine. Funny how this is experienced differently for different people :)
Literal shape-rotating?? I thought it was only the wordcels who were in trouble.
Thanks, I was unclear and meant only the protocol S3 not the service, but I see now that as a KV store it makes sense.
Why are you taking the debate personally enough to be nasty to others?

> you may be on the wrong side of the Dunning-Krueger curve here.

Have you read the Dunning & Krueger paper? It demonstrates a positive correlation between confidence and competence. Citing DK in the form of a thinly veiled insult is misinformation of your own, demonstrating and perpetuating a common misunderstanding of the research. And this paper is more than 20 years old...

So I’ve just read the Harvard paper, and it’s good to see people exploring techniques for X-ray-ing the black box. Understanding better what inference does is an important next step. What the paper doesn’t explain is what’s different between a “world model” and a latent space. It doesn’t seem surprising or particularly interesting that a network trained on a game would have a latent space representation of the board. Vision networks already did this; their latent spaces have edge and shape detectors. And yet we already know these older networks weren’t “reasoning”. Not that much has fundamentally changed since then other than we’ve learned how to train larger networks reliably and we use more data.

Arguing that this “world model” is somehow special seems premature and rather overstated. The Othello research isn’t demonstrating an “abstract” representation, it’s the opposite of abstract. The network doesn’t understand the game rules, can’t reliably play full Othello games, and can’t describe a board to you in any other terms than what it was shown, it only has an internal model of a board, formed by being shown millions of boards.
Ah - thanks. So, to anyone else that is as easily confused by the obvious as I am, you need to join the waitlist, download the browser, and also access bing through https://www.bing.com/new. Or go to Bing and click on the Chat section. Huh.

The browser is worth a look on it's own merits. It's definitely different than Firefox, Google, Brave, Tor, and DuckDuckGo. I don't know if I would use all the tools, but it's worth taking a looksee.