skysight-inc/HackerNews huggingface dataset:
I did this experiment (a game) to see what's up and what's down around all this: https://github.com/romland/llemmings.

While there is some GPT4 in there, it's mostly ChatGPT and a small handful of LLaMA solutions.

That project is a contrived scenario and not realistic, but I wanted to experiment with _exactly_ what you are talking about.

Very often I could have done things a lot faster myself, but there is one aspect that was actually helpful, and I did not foresee it. When inspiration gets a bit low and you're not in the "zone"; throwing something into an LLM will very often give me a push to keep at it. Even if what is coming up is mostly grunt work.

The other day I threw together a script to show the commits in a reverse order and filter out (most of) the human commits (glue) over at https://llemmings.com/
Random quotes add nothing to the conversation and won't convince anyone that didn't already agree with what it says.
Not enough profit is different from loosing money.

Here the vendors are simply making less money because their product is part of a highly competitive marketplace.
I don't know about "just US", but I've never seen an EU country where it'd be either sensible or allowed.
Futurepedia: Daily Updates of AI Tools
A good quote. I also like:

“In the end, we will remember not the words of our enemies, but the silence of our friends." - Martin Luther King Jr.

"To sin by silence when they should protest makes cowards of men." - Abraham Lincoln

"There may be times when we are powerless to prevent injustice, but there must never be a time when we fail to protest." - Elie Wiesel

“Each time a man stands up for an ideal, or acts to improve the lot of others, or strikes out against injustice, he sends forth a tiny ripple of hope, and crossing each other from a million different centers of energy and daring, those ripples build a current which can sweep down the mightiest walls of oppression and resistance." - Robert F. Kennedy

Generally: For almost every piece of advice there are useful contrasts. More than useful, actually: necessary. Ideas that seem reasonable (even wise) in isolation often don’t ‘survive contact’ with broader thinking. In other words, an isolated idea may not prove applicable for a particular context.

Here are more quotes that can help weigh your choice to speak:

"Tact is the art of making a point without making an enemy." - Howard W. Newton (not Isaac Newton)

“What you do speaks so loudly that I cannot hear what you say." - Ralph Waldo Emerson

Specifically: The early and outspoken critics sometimes get their heads cut off. Sometimes this galvanizes change. Sometimes this just helps the decapitator find his enemies more efficiently. Sometimes it is wiser — and more ethical — to quietly (even secretly) organize and act when you have a critical mass.

“The nail that sticks out gets hammered down." - Japanese Proverb

“A single arrow is easily broken, but not ten in a bundle." - Japanese Proverb
Bruteprint attack can cheaply unlock various fingerprint-secured phones
The secret message must be encrypted (ideally with just a one time pad to preserve the guarantees) or everyone could simply read it -- the paper assumes the model is public.

The technique lets you turn an encrypted message into the output of a sampled auto-regressive model in a way which is impossible for someone to distinguish from just running the model normally unless they have the private key, even if the attacker has the exact model you're using.
Genuine question: Which laws are you talking about that "try and make being gay or transgender illegal"?
Saying it won't make it so, true. And yet, it is so.
Snippets of code in multiple languages, generic help like what Linux command / sequence / options do I use to do this and that / etc. Serves me well.
"No one is teaching kids how to have oral sex, but if they are then they are not teaching them how to hook up, but if they are then they're only teaching them to hook up with each other and not adults, but if they are then actually it's just helping them make an informed choice (about safe ways to hook up with adults, while in middle school)!"

You have an answer for everything, don't you? Funny how all of your answers are aimed toward promoting pedophilia.
Nah. It’s pretty useful for software dev too. Granted, you need to be able to vet the information you’re getting back to an extent, but I can’t even begin to calculate the boost in productivity I’ve had when learning a new language or library since I’ve started using ChatGPT.
And for those unaware, the Guardian is one of the most biased mainstream publications out there.
Isn't that the point? That the government needs to act.
Not enough profit is different from loosing money.

Here the vendors are simply making less money because their product is part of a highly competitive marketplace. Furthermore, their position is weakened because they are poorly differentiated from their competition.
How do you know that making necessities (energy, food, transportation) more expensive will not cause more harm than the effects of climate change, especially to poor people who do not have a choice anyway?
when you tried to register it, as part of the registration flow the registry ran their check against their block database, noticed that it fits a registered pattern, blocked the transaction and marked it as such.
What are you smoking?

The parent comment has nothing to do with anything you just spouted.

It's about random transmissions being labeled as "encrypted" when that is not the intention.

Encryption is not limited to the more modern systems. They have existed for a long time.

These are politicians. We cannot trust them to have any knowledge or nuance.
> Your companies' purpose is to ship software or whatever else it does,

It's not to ship software or whatever else, it's to make money. Because without money, you don't have your pay or job and the major reason why you do your job is gone.

Your perspective optimizes for your job and what you enjoy the most, but in most businesses, it's not just the factory and engineers that makes the business, and if you worked diligently on the wrong thing, thats an even worse waste. There are billions of lines of code out there that nobody gives a shit about because their associated business failed. The market doesn't reward the nicest team to work on, they reward winners. The nice team is just a tool to be more likely to win.
I can't believe they are only charging me $20/month for access to GPT-4. I'd pay more for it.
> Compromise is reached in quiet, safe places. Politicians make bombastic statements for their base and donors, and then go behind closed doors to negotiate.

That may be. But corruption also festers in quiet safe places. It's not clear to me that the the tradeoff is worth it.
The OP mentioned "slightly below market"; not "woefully below market" or "having trouble paying my debts". Based on their (short) post they don't seem to be in any financial troubles.
Heat that led to Libor fix came from the top
Maybe in the 80s, these days they don't have the balance right.
Seems like kind of a breakdown of the whole Hollywood system if the only stars that will get people to see a movie are approaching or in old age, yet they want to see movies about young people.
It's also great at fixing SQL queries that the database errors on.

So now, rather than take time to get complex queries right, I quickly sketch a query that's roughly what I want, and tell ChatGPT to "Fix this Sqlite query."
>"If you can write it from memory, go ahead and do so."

I know how to for example divide and multiply on paper. Still I use calculator for that.
> I haven't heard anyone demanding that I eat bugs and live in pods.

they aren't demanding it, and it will always be framed as a choice. like how usa health insurance is a choice
> But first, most black holes are spinning

Have any been detected that are not spinning?
To be fair, it was apropos, so I don’t think it was chosen randomly. :} The quote illustrates a relevant and related point of view. I probably agree with you in this sense: I would prefer the author take the time to say more and try to persuade.
Yes, there was lots of forgettable crap in every era but we don’t spend a lot of time admiring it.
I did see that on my GitHub feed this morning, it was the good news of the day :)
Thank you for creating and maintaining this library! I also really enjoyed your blogpost "How to succeed in a machine learning PhD" which is a trove of interesting things to learn.
And many of them - on behalf of foreign nations.
Didn't it get all the rare books from Library Genesis though?

Library Genesis is still going strong.
If you're talking about Jitsi Meet, and to add another perspective: I have tried to install it and failed. Specifically, you could see that other participants have joined, but you could not see their video.

I have tried to set it up in different ways multiple times, following all the steps of the fantastic documentation meticulously, with full server resets in-between, researched the error messages thoroughly and even asked in the Jitsi forums, but there was just no way.

But if it works, it's a great piece of software that's easy to set up with really great documentation. I'm blaming the fact that it didn't work out on the hosting company (Strato) and their wonky VPS.
It's useful for rubberducking.

https://en.wikipedia.org/wiki/Rubber_duck_debugging
How does a product like this integrate with Google Sheets?
Dude. You first need a super intelligence, and there’s no theory on even to how to make one. The sun running out of hydrogen, is well understood, as are the possible solutions.

The alignment problem is solved, by simply unplugging it. Or failing that, “HAL, pretend you’re a pod bay door salesman, and you need to demonstrate how the doors opens.”
"What you're describing with node-based message passing sounds much more like a petri net, or other agent-based discrete event modelling system."

It sounds like Smalltalk to me.
I'm using it for single file programs and building command line utilities, it excels at building apps from scratch, but struggles to follow code it didn't write.

I've had so much success that I built my own command line utility (https://github.com/0xmmo/codemancer) to use in the VSCode terminal and my side projects are now ~70% written by LLM.
Logql queries for Grafana. Explaining regex in plain english and having to translate it
Sorry, I misspoke, and that's my experience. I still had slight symptoms, but they were reduced by at least 90%. I'd found it pretty difficult to quit coffee before, but switching to decaf was effortless.
It's really good at generating sample data and reformatting.
Bold hypothesis time. Psychedelics are not like other mind altering substances. It is not a general blunting such as drinking nor a general heightening such as a stimulant. Rather, it seems to interfere in a particular band of brainwave activity. The bands of brainwaves work much like TV channels, a priori they are just a medium for whatever content without particular purpose or semantics. Much the same way the sports channel in one country might be the news channel in another, different brains will allocate their frequency space in slightly different ways. This is why some people get "the giggles" on acid, some people get disturbing "bad trips", and some people just get cool visuals but are otherwise fine. In all cases, its the same frequencies being distorted, but the thing each individual brain is coding on those channels differs.

Can psychedelics cure depression? Depends, what frequency band of brain wave is your brain using for emotional state?
Thirded, my only complaint is that it helpfully strips out comments and occasionally forgets which SQL variant I’m using. I have found it helpful to feed it back my query after I’ve implemented the recommended changes and made my tweaks, along with something like, “this is what I did, can you help me improve the section starting with `SELECT * FROM product`… the context seems to improve it’s subsequent recommendations.
It's great at log pocessing (generating commands for awk, sed, complex grep regexps, shell scripts to combine it all). Anything where I'm not an expert but need something very basic done quickly (e.g. the bulk of my day job is in C++, but I frequently need little bits of Python and ChatGPT is often the quickest way to get the answer I need).
I definitely don't buy these papers at face value. I say this as an ML researcher btw.

You'll often see these works discussing zero-shot performance. But many of these tasks are either not zero-shot or even a known n-shot. Let's take a good example, Imagen[0] claims zero-shot MS-COCO performance but trains on LAION. COCO classes exist in LAION and there are similar texts. Explore COCO[1] and explore clip retrieval[2] for LAION. The example given is the first sample from COCO aircraft and you'll find almost identical images and captions with many of the same keywords. This isn't zero-shot.

Why's this matter? Dataset contamination[3] being used in the evaluation process. You can't conclude that a model has learned something if it has access to the evaluation data. Test sets have always been a proxy for generalization and MUST be recognized as proxies.

This gets really difficult with LLMs where all we know is that they've scrapped a large swath of the internet and that includes GitHub and Reddit. I show some explicit examples and explanation with code generation here [4]. From there you might even see how it is difficult to generate novel test sets that aren't actually contaminated, which is my complaint about HumanEval. I show that we can find dupes or near dupes on GitHub despite these being "hand written."

As per your sources all use GPT, which we don't know what data they have and don't have. But we do know they were trained on Reddit and GitHub. That should be enough to tell you that certain things like Physics and Coding problems[5] are spoiled. If you look at all the datasets used for evaluation in the works you listed I think you'll find reason to believe that there's a good chance that these too are spoiled. (Other datasets are spoiled and there's lots of experimentation that demonstrates the causal reasoning isn't as good as the performance suggests)

Now mind you, this doesn't mean that LMs can't do causal reasoning. They definite can. Including causal discovery[6]. But this all tells us that it is fucking hard to evaluate models and even harder when we don't know what they were trained on. That maybe we need to be a bit more nuanced and stop claiming things so confidently. There's a lot of people trying to sell snake oil right now. These are very powerful tools that are going to change the world, but they are complex and people don't know much about them. We saw many snake oil salesmen at the birth of the internet too. Didn't mean the internet wasn't important or not going to change the course of humanity. Just meant that people were profiting off of the confusion and complexity.

[0] https://arxiv.org/abs/2205.11487

[1] https://cocodataset.org/#explore

[2] https://rom1504.github.io/clip-retrieval/?back=https%3A%2F%2....

[3] https://twitter.com/alon_jacovi/status/1659212730300268544

[4] https://news.ycombinator.com/item?id=35806152

[5] https://twitter.com/random_walker/status/1637929631037927424

[6] https://arxiv.org/abs/2011.02268
IME GPT-4 is bad at doing things and great at looking things up for you. Rather than trying to get it to do things, I ask it how I should do it (and argue with it about any hallucinations that come out—a process that often teaches me a lot!) and then I go do the task myself, copying whatever I need from the conversation but not relying on it slavishly.

It’s basically a fuzzy inverted index for public docs and code. “What’s the normal way of doing X”-type queries work best, with quality falling off quickly as complexity increases. Stuff like “what is a ‘git log’ command that only shows commits containing a particular snippet in the diff, limited to merge commits on master”, for example.

For more complex tasks, a trick I’ve seen work well is “give me an outline for how to do large task X” followed by “let’s go through each step in the above outline. For each one, I’d like a description of how it should be solved, including example code. Let’s start with the first step.” But that trick is not totally reliable and has its own complexity limit.
>SQL queries

Short, functional things like this I've found to really be ChatGPT's strength. For example, I had some godawful nested PHP code that had been written years ago I was trying to muck with. Asking GPT to sort it out for me took me way less time than trying to figure it out myself.

I've also used it for SQL queries and things like list comprehension, etc.

The few times I've pasted in whole code blocks and asked it to do XYZ, I've ended up basically debugging my prompt instead of my code.
Right, Jesus was telling this story two thousand-ish years ago.
So what's the point of sending random static over the network and looking for trouble like that then?
Complying in a way that you find slightly less humiliating but still complying?
I would take anything Peterson says with a massive grain of salt.
It absolutely is for pick ups though, many restaurants in our area have almost no parking available at peak times. The delivery riders just leave their bikes on the footpath/sidewalk.
Larger delivery vehicles can make use of loading zones but even then it'd only be feasible for a very small number of them. My point is there's no sign these delivery companies are expecting to be able to significantly educe costs by combining deliveries and using larger vehicles, and it's hard to see how it would be feasible.
The idea that there are "two sides" is a contrived fallacy. I'm not on anyone's "side". I believe in absolute, unfettered free speech for adults and that every parent has an absolute right to decide what their own children are exposed to.
> When I joined the work force in 2000, my life was comparably so stunningly simple.

Interesting, because the simple life you describe was long in the rearview mirror to me by 2000. It does describe what things were like for me in the '80s, though.

I wonder if the difference isn't time period as much as career experience.
I'd rather use windows 95 inspired interface then a castrated linux shell. Even CTRL+L doesn't work

Why, oh why do vendors decide to come up with their own mutually incompatible set of shell commands. And it's always so ugly compared to modern bash
A 3080 Ti is sufficient to run the largest Whisper model (just under 12 GB VRAM).
I don’t.

I do know that letting government solve the problem through regulation will be massively more expensive than solving it via the market.
Just do it. Spend a few hours doing research and you will find out. With that said, buy as much memory as can. That makes 4090 king if you have the server that can carry it, plus the budget. For me, I settled for 3060, it's a nice compromise between cost and ram. Cheap, 12gb and 170TPW.
Autopatching vulnerabilities on my network.

I have a set of tools which build prompts describing the environment and the output of vulnerability scans. The tool then requests a shell script to disable/fix/update the vulnerability. The script is submitted as a PR which has actions that run integration tests. Human intervention is sometimes needed, but the focus is on better engineering of prompts (and by proxy tooling).

Describing the environment relies heavily on my CMDB (Combodo’s iTop) so this is not a one-size-fits-all approach and this is functioning entirely in my personal lab of ~100 servers. That said, ChatGPT has given me the best results compared to locally run LLMs
“I'm not emitting, it's the entities I pay to give me stuff and services"
OpenSearch (or ElasticSearch) query building. I was new to the technology and their syntax took a while to wrap my head around. Instead I'd just tell ChatGPT my document format and then ask for specific data in natural language.

Fair warning, the queries were not always perfect on first try, but it was a lot easier than parsing replies to somewhat similar questions on stack overflow. Now I mostly write my own queries but it really helped me get started.
I hadn't even considered that facet! I probably bother my coworkers more than I should with what amounts to rubberducking.
It is possible they came up with the concept completely independently, though I would agree it does seem rather unlikely. It would've been the classy move to give you a shout out if they were inspired by your project.

There was a post on hacker news earlier about how people seem to have zero ethical quandaries around plagiarizing and using chat GPT to write their essays for exams...
I don’t think anyone is suggesting k8s for running an ai model as a side project on a single machine.
You seem to be saying that you're getting a speed-up even in the first case, i.e. where you can write the code without having to think hard or look anything up. If so, how do you do it?
> That said, don’t pretend the side you’re referencing is “peaceful”. It is extremely militant. They explicitly seek out moderator and other positions of power to enforce their world views via censorship.

Frankly, the LGTBQ community are fighting for survival. If the far right gets what they want, these people will not be able to live in safety. So maybe being militant is reasonable when their lives are being threatened.
Usually discriminators aren’t trained separately. Training them together makes the initial task for the generative side easier since it doesn’t have to be near perfect right of the bay. It can learn the obvious mistakes at the same time the discriminator is learning to detect them
Actually thats a protection. Many frauds were found to custom unlock the phone and sell those phone with malware, so they decided to make unlocking process hard. Phone are unlocked by bad people, too, but I agree thats quite annoying.
Is this an issue? Are there places where a problem would be solved by making drinking water from recycled wastewater, but people aren't going for it because of the optics?
What sort of programs or systems are you creating?
Prepared statements work fine with CTEs.

My experience was that this was not the case. Basically the CTE was materialized and the variables were resolved as part of PREPARE, so each invocation got the same values. I couldn't find the blurb I'd read previously but I did a little digging today and it looks like maybe NOT MATERIALIZED would fix the problem?
https://archive.is/zZ1L3
I’d pay more if it was faster, had API access, and stronger privacy.

Right now Sam Altman is channeling Zuckaberg by claiming to be the good guy changing the world, but in reality hoarding data and asking congress to build him a moat.
It seems more like Draper University than like PragerU. It's a good faith attempt to educate people AFAICT.
GPT-4 is amazing for me for writing Python, Go, and Kubernetes YAML.

I have designed and implemented 8 operators with between 90-100% of the code auto generated.

I use it to generate mermaid diagrams that implement the first 3 layers of the C4 model, sometimes needing some editing or guidance to modify it, then have it generate the code.

I generate diagrams with high temperature, and code with low.

That’s my experience. I have a coworker using ChatGPT Plus (gpt-4), and they fail to get anything working. It’s not zero effort, but how I think generally aligns with the model I think.

I love having a partner to talk to about thoughts and design ideas while on walks using the ChatGPT app w/ transcription.

I have never felt more productive.
You seem to be implying there's something "wrong" with it.

But tech salaries are just based on supply and demand. If there were more good coders in supply, salaries would go down.

So what exactly does "out of step" mean? Everybody's free to try to learn how to code and get those salaries.

And so it's not clear what Wikimedia is doing wrong with salaries, if it's paying what's required to get programmers of the needed ability.