skysight-inc/HackerNews huggingface dataset:
> Slow down. Assuming that time moves in one direction is not comparable to geocentrism.

Why not?

The "arrow of time" almost always requires thermodynamic arguments. And that requires a concentration of "low entropy" to move toward "high entropy". Which, by definition, are "boundary conditions" and not a fundamental part of your physical rules.

If, for example, your universe is entropically uniform, is there an "arrow of time"? And, even if there were, could you detect it?

However, I would like to point out that it's not like we haven't had this kind of issue before. The Bohr-Einstein debates were a good example. Einstein favored a "fields" interpretation of quantum mechanics. Unfortunately, Einstein's interpretation predicted that atomic states wouldn't decay, and that was clearly, obviously wrong, and Bohr very much hammered on that.

Except that Einstein wasn't "clearly, obviously wrong." As you increasingly isolate excited atoms, their atomic states take longer and longer to decay. The problem was that the experiments of the day couldn't create these kinds of singular quantum state systems--they were stuck with systems that were contaminated with lots of thermodynamic interactions.

We may be seeing something similar here. We are just starting to be able to put together the experiments that can probe things like Bell's Inequality. As we isolate these systems, we may find that the systems were contaminated with statistical time and that we get different results when we can isolate them.
It’s amazing how quick some people on HN are to dismiss how impressive it is for a generic language model to be able to play chess at any level - or indeed other feats of ChatGPT.

It’s utterly staggering that it can work as well as it can on problems like this at such an early stage in this technologies lifecycle.
Thanks I enjoyed reading this! How did you feel about htmx use/ease of learning?
Why are we surprised by this? As far as I know all the authoritative sources have been saying this was animal origin from the wet market from the beginning. Anything else seems lie dangerous misinformation
The limiting factor may now mostly be cost.

Notice where the funding is coming from on this though. Seems like the initial use case is more killer robots than robot butlers: situational awareness and target identification, under the guise of "common sense for robots."

https://www.darpa.mil/program/machine-common-sense
If you haven’t heard, there is a severe labor shortage in the US even for “unskilled labor”. They could be working somewhere else.
OMG, I can't believe Plone is still kicking. God, please, nobody work on that. It doesn't need to exist any longer.
He does have a section about GPT 4 which does match your results. Not sure if he added it after your comment or if you accidentally missed it.
The goalposts haven't really moved though? The reality that a lot of people have thrown "engineer" in their title but just write code given a spec or tightly scoped requirements or design has been true for a while now.

But for quite a few folks, the coding is the easy part. When building larger systems you're not even that often implementing things from scratch. The decision making, dealing with existing tech debt, tooling, etc. is the hard part. Ambiguity is the hard part and it's always been that way.

Don't get me wrong GPT-* is impressive. Heck, I pay for a subscription. But it won't really make a lot of folks at my company notably more productive.
I recently asked an AI for help writing a python program with a mutex to prevent outdated information from being accessed. It presented me with a solution that I didn't fully understand, so I asked it to explain that part of the code. And then I asked it to explain part of the explanation. It just kept answering, never getting tired or irritated with me asking for clarification, and generating information that couldn't exist in a book or a blog post. It reminded me of the primer in "The Diamond Age". It catered the answers to my needs and deficiencies instead of making me adapt to it.
We're talking about physics, not mathematics. We don't have the luxury of hand-waving away fundamental questions about the nature of the continuum.

See: https://en.wikipedia.org/wiki/Continuum_hypothesis
Honestly it’s been staring us in the face for 100 years. Light doesn’t experience time. We’ve known this for so long. Light is created and destroyed in the same instant - across billions of light years it happens instantly. For that to be true, what else must be true? Must.

There is no photon. There is just a wave. The interaction probably (definitely?) depends on features of both the emitting electron and absorbing electron. There is either retrocausality or superdeterminism (or both). We don’t know which. Right now that’s not important but scientific fashion has been refusing to get this one thing. We’ll learn so much once we move past this.

Light going into a black hole? Research paper.
Your opinion on this probably depends on what your job currently looks like. Everywhere I've worked there's been significantly more stuff we wanted to do than we could actually do. Speeding that up looks awesome to me.

But if you work at BigCo and mostly sit on your hands already, then, yeah. I don't know.
Comparing ChatGPT to Codex for text-to-SQL translation
There's something called WBTC[1]. It's very popular.

[1]: https://wbtc.network
The Rise and Fall of Lisp – Too Good for the Rest of the World [video]
Show HN: GraphQL Client Library for Clojure
Hey HN!

This is a library I've been working on for Clojure. There are other libraries out there which do something similar, but they are to DSL-ish for my taste.

Therefore, decided to write my own w/ hiccup-like syntax while attempting to stay as true to GraphQL spec/idioms. There are a couple small things which are different (i.e. aliases and directives).

For the most part, I think it is promising. Especially once I have the time to implement support for CLJS & different client implementations (i.e. http on jvm, ajax/fetch on js/node).

Would love some feedback, if you think there are things I am missing/not considering.
The important thing is not to talk to someone, but to talk about things that you can take action that will work. If you are talking about the right things, it will be useful to you. but it doesn't work and if you're talking about the same things, it's normal that it doesn't help.
A probability of zero does not mean that the event is impossible. When we refer to probabilities we are talking about probability densities. Infinite precision is a useful modeling tool in the same way that approximations of pi are useful.
I doubt they'll pursue this. There is no advantage to it. ChatGPT will never beat Stockfish, and Stockfish would do it on a ludicrously small fraction of the resources. It would send the wrong message.

Some future AI might, but a language model won't.
If the direction of time is reversed, the eggs become whole again, but your memory of them once being scrambled is reversed, too, so you don't notice anything unusual.

(It's like a rollback of database transaction, where not only the database state, but also the state of everything, including your brain, is getting rolled back)
> If all you're doing is very simple crud apps and transforming API responses,

I think all of us here conflate simple with easy. It's simple in theory yes - you get some JSON from service X, maybe tweak service Y that talks to X and then feed it into some front end. In practice even very experienced engineers can take days writing or changing a simple end point or some front end because unclear requirements/bugs/micro service hell/unclear existing code/etc etc.

If it was that easy the pace and quality would have been much higher than what I'm seeing in tech companies.
There have been a few (not docker containers but Facebook bots and such) and they perform in study as well as a real therapist does, that is to say not very well but sometimes it helps people. You can find a variety in apps on phones and such but its obviously a big data grab rather than the nice private medical data thing that we would actually want.
I did this in undergrad when the Wifi in my dorm room was abysmal. I used an old Mac mini and hardwired it with the in-room Ethernet and then used the Wifi hotspot mode to make a nice fast wireless network for my roommate and I.

The Mac also pulled double duty as an AirPlay receiver and Plex server. Pretty handy.
> I support the contractor status (mainly due to general support of a flexible labor market)

A ride share or delivery company could offer flexible hours with part-time workers too, so flexibility is not why the delivery companies created Proposition 22. As I understand it, Proposition 22 was necessary in order to:

* Allow drivers to use their own car rather than forcing Uber to manage all the cars in their fleet.

* Avoid paying drivers when they are parked waiting for an order, which allows drivers to have multiple apps open looking for orders.
Personally I think the illegal moves are irreverent, the fact that it doesn't play exactly like a typical 1400 doesn't mean it can't have a 1400 rating. Rating is purely determined by wins and losses against opponents, it doesn't matter if you lose a game by checkmate, resignation, or playing an illegal move.

That's not to say ChatGPT can play at 1400, just that that playing in an odd way doesn't determine its rating.
I think you need to consider it not as a chemist, but as a psychologist.
There are some attempts to do the math on whether just the fuel could have done it in the comments to this video (https://www.youtube.com/watch?v=UVzLV-R_-kk).

Example:

The thrust from a propeller blade is typically proportional to the density of the medium it is operating in (plus other factors of course). The density of air at altitude will be somewhat less than 1 kg/m^3. Density of pure liquid kerosene is around 800 kg/m^3, but in this case the kerosene is dispersed as droplets in the air. If we take a hypothetical guess that the air/fuel mixture is around 25% fuel, 75% air, the net density of the mixture will be around 200 kg/m^3. On encountering the fuel mixture of this density, the propeller blade would experience a sudden increase in load by a factor of about 200. A sudden overload of this magnitude would be enough to bend most things. Of course we don't know the actual air/fuel ratio. It could be less or could be more. The velocity of the dumped fuel relative to the drone's airspeed could also be significant. Too many unknowns to be anything like accurate, but appears not impossible for a fuel cloud to bend a propeller blade.
I think it's only a matter of time until one of these models gets into the hands of a hacker who wants unfettered ability to interact with a LLM without moral concerns.

I think there's tremendous value in end user facing LLMs being trained against moral policies, but for internal or private usage, if these models are trained on essentially raw WWW sourced data, I would personally want raw output.

I'm also finding it particularly interesting to see what ethical strategies OpenAI comes up with considering that if you train a model on the raw prejudices of humanity, you're getting at least one category of "garbage in" that requires a lot of processing to avoid getting "garbage out."
It's not losing one customer, it's losing many customers for reasons that those customers wouldn't normally be concerned about. Refusing to accept fares at some locations isn't something that would make other customers decide not to accept a ride from you.

We do care about reliable service, though. That's something the ride share companies create incentives for with their games. But they are artificial games compared to a more free market situation where you can cherry-pick.
> By and large, this only benefits the employer. Why would you support anti-human markets?

Have you participated in this part of the labor market? Or have you talked extensively with folks who have?

Before voting on prop 22, I made an effort to talk to “gig workers”. A few observations:

1. Guaranteeing a minimum pay rate when working with prop 22 was something that they welcomed. Apparently some of the apps made offers that were basically noob traps — probably not out of malice by the company, rather incompetence.

2. They almost universally did not want to have scheduled hours and/or be a full-time employee. There were a number of reasons for this, but the desired state was the same — flexible schedule.

3. Some of the folks who would likely be full-time candidates were not well-educated or skilled, but they knew how to work hard. They felt like they were rewarded fairly for their labor, often times at better net pay than they could get elsewhere.

4. Uber/Lyft seemed to be the most liked. Folks who didn’t want much human interaction and/or had an older car preferred uber eats / door dash. Instacart seemed ok, but it didn’t seem to have as many fans as the others.

I talked to about 20-25 people. Everyone seemed to like the current system. When asked specifically about full time work, the only support I heard for that was from a couple of people who said something like “it would be nice, as long as the schedule was flexible” — which is not how full time would likely work.

I think that many of these gig apps hit product-market fit both with workers as well as customers, and that’s why they are successful in this two-sided market.

EDIT: Fwiw, I also heard a lot of kvetching about AB5 from both employers and employees. That legislation may have won some political points from certain voter bases, but I don’t think I have ever heard anyone praise it (although I’m sure they exist).
I think the authors rule is fair. If we interpret illegal moves as getting stuck in an online game, the resulting Elo rating is what it would get.

But ye, he is anthropomorphizing alot ...
That's a pretty good answer, but it's only verifiable in retrospect. So far, we've seen *NNs used for bad things and utterly fail at good things (like increasing the accuracy of reading radiographs).
Has nothing to do with banning farms, or food security.
It's the word I use for exploring unfamiliar (and potentially scary) parts of a codebase
>> On a different note, what has been the value of "creative posts" and even "creative name for your blog" for you?

Why do we name anything? There are many reasons, but it's important to distinguish your site from others. Content is the primary way to distinguish a blog because the original consumption tool was an RSS reader. Things have changed a lot, so more people go directly to most blogs.

If you have web design chops then there is an opportunity to create a distinct experience. The value of this is felt most by people who can appreciate good design, so unless you've goofed up usability, most people probably won't notice the design much. Don't mess up the usability because people remember bouncing from those sites or complain in comments here.

There are tons of developer blogs out there so unless you are notable in some area (big or small) for some set of readers then your name may not be enough. "Joel on Software" as a blog name stands out more than "Joel Spolsky's Blog". It is possibly easier to communicate verbally, signifies the content, feels informal, etc.

Does it matter if the content is only useful to you? It doesn't. The act of blogging improves your writing, creativity, tech skills, forces you to learn etc. So, you move forward in area of your career that many software people struggle: communication. If you write about stuff close to the area you work in then you'll find you reference your own blog posts a lot. Scott Hanselman recommends writing a blog post and referencing it an email instead of sending the same content in that email. There is some good stuff linked from https://www.hanselman.com/blog/your-words-are-wasted.

You overcome your problems by dealing with your anxiety. Why do you care about these specific aspects to the point that it blocks you from just writing and publishing? This is the differentiator between highly trafficked blogs and those that aren't. For a subset of people, noodling on these aspects and their blog template is the point itself. You need to decide on the true purpose, the why, and come up with a plan. There are lots of in-between steps like buying a nice template, drafting a lot of content to see if a name falls out of that, adopting a name like "Vibgyor5 on Software" etc.
I'm guessing a lot of people doing uber driving now either never

A. Attempted to be a taxi driver so never saw that system
B. Grew up in the Uber generation and has only seen the improved taxi system that happened as a result of ride share
C. Never experienced the refusing cards and non white stuff.

It really is looking at it through rose colored glasses. I remember when Uber first emerged on the scene everyone that I talked to thought it was a God send because they were so tired of taxis being garbage and scammy
Most people actually believe ai is taking over software jobs xd
It's really interesting to think about how we struggle to express the idea of the future having a causal impact on the past. I reckon this is because our language and our understanding of time are limited.

Our brains like to process events in a linear sequence, from past to present to future, but this view of time might not fully capture how everything in the universe is interconnected. It's possible that our language just can't handle these complex concepts.

So, I don't think anything mentioned in this thread contradicts the idea that "time always moves in one direction" and "entropy always increases".
Where do you get the weights?
isn't llama in the wild now?
Sometimes DARPA just funds basic-ish research (eg., the internet).
Just how out of touch is this guy? 50% inflation MoM within the next 90 days? Does he not understand the multiple system shocks that would need to take place for that to even come close to reality?

Balaji, please - get out of your bubble. Go talk to your neighbors. They're all concerned about where to go for their kids spring break, the next episode of Mandalorian, and whether or not their bracket is still in contention.

Let's game out what it would take for 50% inflation MoM -- you'd need severe supply issues up and down for every possible good, including goods created domestically. You'd need the Fed to fire up the printing presses in a way that surpasses even 2008, which, good luck on that one. You'd need interest rates to go negative. You'd need the real estate market to do a 180 from "nothing's really selling right now" to "people can't buy houses fast enough". You'd need a confluence of black swan events to happen globally in order to knock the dollar from being a reserve currency. How does that possibly happen?

Just dumb, all around.
> the result is essentially guiding it through a brute force of the first successful playthrough it can muster.

No, all unsuccessful playthroughs are resignations that impact the models ELO.
I'd say that's more or less covered by the general rule we've developed over the years for major ongoing topics (MOTs), which is to downweight followups unless they contain significant new information (SNI). Most likely yet-another-cherry-picked-AI-example posts don't qualify as SNI. If people see those on the front page they can flag them and/or let us know at hn@ycombinator.com.

https://hn.algolia.com/?dateRange=all&page=0&prefix=false&so...

https://hn.algolia.com/?dateRange=all&page=0&prefix=true&que...

The tech itself is moving so fast that there is a lot of SNI, plus a lot of good articles/blog posts/reflections on what's happening. I guess the goal would be to keep the highest quality stuff and filter out the copycat stuff. Which is which that is open to interpretation, of course, but it's not completely subjective either.
I think internal understanding requires internal processing.

According to this functional definition, the way we are currently using language models basically excludes understanding. We are asking them to dream up or brainstorm things – to tell us the first things they associate with the prompt.

Maybe it's possible to set up the system with some kind of self-feedback loop, where it continues evaluating and improving its answers without further prompts. If that works, it would be one step closer to a true AGI that can be said to understand things.

There is a lot of confusion around the Chinese Room Argument. I think it makes a valid point by demonstrating that input/output behavior alone is insufficient for evaluating whether a system is intelligent and understands things. In order to do that, we need to see (or assume) the internal mechanism.
With the big caveat that I'm not into chess, but I have heard that higher level play is extremely pattern based. Seems like ChatGPT would work well as long as you stick to patterns that people have studied and documented. Less optimal play would be more random and thus break from the patterns ChatGPT would have picked up from its training corpus.
I am sure your definition of "fuck people over" is vastly different than mine.

Fraud, or lying would be things I consider "fucking people over". Presenting a work for hire situation where adults agree to the terms is not "fucking people over"

>I’ve never gotten into an Uber or Lyft that wasn’t clearly a full time hustle.

My guess that is very regional.
Surely the rules of chess has to be in the training data 100s of times? Maybe it is not enough.
- minimum wage - do Uber drivers not make 7.25/hour?

- overtime - if it is enforced , all Uber has to do is not allow someone to work over 8 hours a day. Does that help Uber drivers?

- unpaid leave - if Uber drivers need to take a break and be guaranteed a “job” at Uber that’s already the case.

- child labor - you can’t drive Uber if you are underage

- farm workers - not applicable.

Did I miss anything?
Bummer. There goes my summer trip!
Belgium: We have a don't call me register.

If companies use it for marketing, they can be shutdown.

The list is easy to get for companies in Belgium. Perhaps it works?
I was under the impression that LLaMA was also trained against a series of moral policies, but perhaps I'm mistaken.

It seems Meta chose their words carefully to imply that LLaMA does in fact, not have moral training:

>
There is still more research that needs to be done to address the risks of bias, toxic comments, and hallucinations in large language models. Like other models, LLaMA shares these challenges. As a foundation model, LLaMA is designed to be versatile and can be applied to many different use cases, versus a fine-tuned model that is designed for a specific task. By sharing the code for LLaMA, other researchers can more easily test new approaches to limiting or eliminating these problems in large language models. We also provide in the paper a set of evaluations on benchmarks evaluating model biases and toxicity to show the model’s limitations and to support further research in this crucial area.
I'm assuming you're making a joke. Personally I think the lab leak thing is a stupid line of inquiry, in that trying to lay blame is useless. There is obvious merit in understanding zoonosis (sp?) better. But pretending that "dangerous misinformation" is still a sane viewpoint to take can only be a joke.
Quick and dirty pyenv plugin because I often come across abandoned old Python projects on GitHub that are using a cryptic version of Python and things seem to be breaking. It uses the https://endoflife.date/api/python.json API. If someone knows of a better programmatic way to guess the version of a scrappy codebase please let me know.