skysight-inc/HackerNews huggingface dataset:
Well, that's not necessarily true.

Training data can be generated by selecting from outputs of other AIs.

If you think about Internet in couple of years as collection of AI-generated content, if you try to train your AI on Internet content that's exactly what you are going to be doing.
Show HN: Tool that's built on top of GPT-4 to generate code that runs
Hi HN,
As a developer, I like to use ChatGPT to help with my job, especially when looking for boilerplate code, help fix bugs, ...

One issue I have with ChatGPT is that the code sometimes doesn't run, contains bugs or doesn't do what you wanted it to do.

So I wrote a tool that generates code, make sure it runs on server, solve any bugs that the code contains and then generates tests and make sure the code runs as it is supposed to.

We’d love your feedback. Email me aelqaraoui101@gmail.com or DM me on twitter @amine_elqaraoui
Hi! I just added r/productivity and r/crossfit to DemandHunt: https://www.demandhunt.com/#communities

Let me know if these end up being useful for you! :)
I do. It’s not a very controversial belief except if you only train using Internet comments.
So where would you put it exactly? I'm guessing you think it could be put in some rural place in North America where there's no infrastructure and no workforce...
It would be interesting to run the simulation again with the estimated secular mean of the assumed Planet Nine.
> Is anybody aware of anything that's price competitive in the US (or within a 50ms ping)?

OVH [1] is not quite as cheap, but I can't really think of anyone else in the area that is totally comparable. One draw of OVH, Hetzner, etc, for me over the truly small, cheap dedicated server providers is they both have pretty decent networks and free DDoS mitigation, which is really nice for things like game servers and such where CloudFlare isn't an option.

OVH's sub-brands like SoYouStart [2] will sell you decently specced dedicated servers started at around $30 a month in Quebec, which tends to be more than good enough for most of my "US" needs.

They do have a couple datacenters in the United States too, not just Canada (+ quite a few in Europe, one in Singapore, some in Australia, etc), but I believe the Virginia/Oregon servers aren't available on the cheaper SYS site -- still cheap, though, but not quite $30 cheap.

[1]: <https://www.ovh.com>

[2]: <https://www.soyoustart.com/> (main downsides compared to OVH proper is the connection is capped at ~250Mbps, and although all servers have DDoS mitigation, the SYS and Kimsufi servers don't allow you to leave it on 24/7 -- so when you get attacked, it might take a minute or so to kick in, and then it'll remain on for 24 hours, I believe)
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> They are the car dealerships of holding money, such employees should be working on instagram not in the real economy.

They should get real jobs like being influencers or something.
IP is the promise that you get the dues for your work, guaranteed by the government. It is what enables the entire "information economy". Without it, we'd soon need to weed out people that don't contribute to IP.
Thanks for the list, I guess I’m trying Buster again. It stopped working for me long ago, but I see it’s still updated.

NopeCHA works great, but I don’t want to reward their shady tactics [0] by paying them, and I can’t use their free service as they somehow label my residential IP as commercial. ETA: Wow, seems that wasn’t just me [1] and they went full scam ;)

Captchas are a cancer and I don’t even use a VPN.

[0]: https://news.ycombinator.com/item?id=33917962

[1]: https://addons.mozilla.org/en-US/firefox/addon/noptcha/revie...
> 400 mg/kg/day during 6 to 8 weeks. For humans, this is equivalent to 33mg/kg/day. So for a 80kg body: 2.6g, half a sugar cube every day.

But humans have much more time to ingest it. Parkinson develops during decades, not weeks.
What I only can hope about is the natural selection of useful data throughout time. Garbage is all around, people generate it on mass scale with modern technology nowadays, but the useful portion may survive the test of time, prevail. Those using 'good' data over 'bad' can gain benefits that could lead to the not self harming population using good data, suppressing bad ones. Mostly, of course.
SI Units of Simile
What compliance issues are there? Copilot is already being adopted at the enterprise level. Microsoft is not going to miss out on enterprise by trying to ship data out.
Yeah, if anyone knows of a good, coherent, well written Vulkan book that properly explains things instead of just enumerating API specifics (or if this is that book), I'm keen to hear of it.
I don’t understand whether this is just a higher level abstraction of boto’s s3 client (à la s3fs)
Indeed, but my objections aren’t placed due to higher productivity, but rather about personality and accountability.

Imagine someone stalking you, imitating your way of communication and professional style and then emulating work for a high stakes project.

Body doubles happens right now within IT space but having people reduced and used as a text generation model would be another level.
He turned it into a company that changed the industry and went public, so somebody made a good call.
Who says GPT has the ability to hold 25,000 token in its "head"?

You can send 25000 random words in the prompt and asks GPT how many pairs of words share at least one letter. I doubt that the answer will be correct...
Medical error is the third leading cause of death in the US at least. Given that data, I am assuming the chances of a human being held accountable for their errors in medicine is also almost zero. It might not be ccompletely zero, but I think the difference is effectively negligible.
I retired at 28. Plenty of people do.
That's impressive. Are these CDI jobs? Also, do you speak French or are these English-speaking start-ups?
Collato – the AI search engine for product teams
IP laws are a double-edged sword because of the way how advertising and human memory works. You can not have IP laws and also negligible impact on culture. You always get both, and people replicate what they know. The goal of IP (like many other things) is to eradicate itself.
> So what do we read from that? If you drop a sack of salt weighing as much as an eight-year-old child on a series of rabbits, roughly half of them will die?

No, you should read exactly what it says. If you put a series of rabbits in skin contact with 25kg of salt each, less than half of them will die. That's how we know the LD50 is greater than 25 kilograms.

I assume 25 kilograms was the limit of testing, and that's why the result is reported the way it is.

I'm also willing to go out on a limb and assume the number of test rabbits that died from being put in skin contact with 25kg of salt was zero, which is less than half of the test pool as long as it contained a positive number of rabbits.
> We don't learn by gradient descent, but rather by experiencing an environment in which we perform actions and learn what effects they have.

I'm not sure whether that's really all that different. Weights in the neural network are created by "experiencing an environment" (the text of the internet) as well. It is true that there is no try and error.

> We are not limited to text input: we have 5+ senses.

GPT-4 does accept images as input. Whisper can turn speech into text. This seems like something where the models are already catching up. They (might)for now internally translate everything into text, but that doesn't really seem like a fundamental difference to me.

> We can output a lot more than words: we can output turning a screw, throwing a punch, walking, crying, singing, and more. Also, the words we do utter, we can utter them with lots of additional meaning coming from the tone of voice and body language.

AI models do already output movement (Boston dynamics, self driving cars), write songs, convert text to speech, insert emojis into conversation. Granted, these are not the same model but glueing things together at some point seems feasible to me as a layperson.

> We have innate curiosity, survival instincts and social instincts which, like our pain and pleasure, are driven by gene survival.

That seems like one of the easier problems to solve for an LLM – and in a way you might argue it is already solved – just hardcode some things in there (for the LLM at the moment those are the ethical boundaries for example).
>Nobody is going to "generate training data" if they get precisely nothing out of it.

"Before accessing your account, please solve this puzzle to verify you're not a robot."
On the other hand, can one really keep an open mind to about any out-of-line idea just in case one of the thousands might turn out true? I'm not sure how this attitude could work, Hancock isn't even the looniest out there, so how do you decide where to draw the line? My question is not about one specific theory, but about the process: how exactly should one decide (for oneself, and for further investigation) which theories to "keep open mind" and which to classify to the bin?
That's not really how it works.

At least in the UK (and most western countries are similar), the government decides (with ministers) what the curriculum should be and how it will be assessed. They decided that rote learning is what students should do. The schools have no funding for anything innovative - again, a decision by the government on how much to allocate. They can barely afford text-books, let along support an edu-tech start-up ecosystem. VCs won't touch edu-tech with a barge pole. Meanwhile, the government assessors ensure that things are taught in a particular way. Again, decided by the government and the bureaucrats. The teachers have zero control over this.

Now universities should know better. They have more funding and more resources. But there are some leaders here, like MIT.
Because since there isn't any public demo available, you can't really say more than "Yay, this seems interesting."

So it's easier to point out obvious potential flaws.
I agree with you on the diagnosis: AI will replace humans, there's no other alternative.

I also think it will occur much sooner than most people expect. Maybe 5 years for all people to be replaced.

However, I don't think that is inherently bad.

Even if this means the extinction of mankind, as long as we inherit this planet to some form of "life", or some replicating mechanism that's capable of thinking, feeling, and enjoying their "life", I'm fine with it.

Our focus should be on avoiding this situation to turn into slavery and worldwide tyranny.
* divas that have to attend meetings several times a week, that is
Why? I'm pretty sure it could do this kind of task - attention is computed between all pairs of tokens. Yes, it's a lot of compute.
Hey there ! Thank you for sharing my blog post. I tried to share it myself earlier, but my post was hidden (probably because my account is new).

This is my first technical blog post. I intended for it to be easy to follow along, and tried my best to write in a pleasant style. However, as a non-native speaker, I know that my writing sometimes feels awkward.

Please tell me everything that is wrong with this post, whether it's from a technical or a linguistic standpoint. Don't worry about sounding harsh, this will only help me improve :)

I wish you a pleasant read.
The value you produce is merely an upper limit on your salary. Your salary is more based on offer and demand, meaning how much your management believes it would cost to replace you.
Does the "fine-tuning" also happen on-premise or do you need to access the Code?
Low EV. Some make it very big, but most earn nothing and retrain.
I'm no particular Hetzner fan, but is it possible there were a load of false positives in there?
You ended up admitting i was right - nobody ends up on H1-B for 15 years (unless as you pointed out, they choose to be).

And “boots on necks”? I think you have a persecution complex going on.

I encourage you to engage people on HN on a more positive note. Don't take out your frustrations on others.
I mean low EV compared to other careers right now. Obviously automation benefits the ownership class massively. Buy tech stocks; they are discounted at the moment.
Anybody who's never set up a dedicated service or colo will be pleasantly shocked at how cheap it is compared to the pay by hour cloud.

When these guys open up dedicated servers in a USA region it's going to be huge. Unfortunately, at the moment only the cloud offering is available in the USA so you're stuck with a bit of latency round tripping to the EU.
I'd watch that game show.
Nobody's invented an orchestrator yet. There will be a kAIbernetes invented by someone, which will analyze structures. It seems to me that not many people are really trying hard to project and extrapolate in a realistic way. This will develop much like other techs have developed, but express itself (literally, expression is what these fuckers do) very differently in its various stages.

Ten years got us from seeing dog faces in everything to verbal diarrhea that makes sense most of the time and award-winning Instragram photographers that only exist as a StableDiffusion delusion. You and I might be gone in twenty years, but the world will still be here in a thousand. We just don't know, but I do know one thing - AI is still at the "Steam Thresher" stage of things.

We programmers will definitely be the last to go, I think, but we'll go too, because fundamentally, we became programmers to make machines do stuff we don't want to do.
I agree. But that's different to claiming to know better than the people voting what is their own interest.
Really? Been running few dedicated servers for several years straight without a fail.

Even Herzner cloud just works and I don't know how they do it but it's dirt cheap.
It's because they don't "get bullied". They _want_ this kind of stupid identity activism and encourage it from the top with their DEI propaganda officers. Any "activism" and identity outrage is an opportunity to make it look like they're doing something "progressive" without actually doing anything meaningful (i.e. expensive) and precludes any material change that would actually help people and threaten the upper classes' power or wealth. The instant that "activists" aren't useful to them anymore, they get axed immediately. Just look at Microsoft's AI ethics team. An entire team dedicated only to whitewashing their corporate image.
+1. There is no more incentive to post things on the internet if this is how things are going to be. If all the effort you put into something can be used to bolster a LLM that will then be used to make money off that info, no one would want to write. If I have a blog, I'd write for humans and not so some "Open" "AI" company or Micro$hit can come and claim my work as their own. People will sooner credit LLMs for being "smart" than acknowledge the upcoming massive Original Content vaccuum.
I've worked on something like what you talked about, a "problems" discussion board, and indeed companies exist that offer such a service (i.e. https://canny.io/) but the issue was that in a forum explicitly about problems, users typically don't end up putting their money where their mouth is.

Additionally, users aren't themselves designers or problem solvers and often spin their problem (or even proposed solution) in a way that they don't even really want or isn't effective from a business sense.

All that is to say, I think that site you're proposing turns into "building product by democracy" which isn't super effective, actually.

You're right about the specific situation of what I've built so far, it is a tiny version of those reports. But it's $10, and what I had in mind was not to necessarily target and solve those problems, but act as a starting point for entrepreneurial users to read and explore existing problems.

From what I've seen so far, such a niche of entrepreneurial users might not exist - I think they probably do have their problem area already in mind, so unless I nail that area, they won't be paying for inspiration for random niches.

My next steps might be to deploy some automation to make these documents, and therefore have something for any niche. But right now my engagement numbers don't seem to warrant that direction, unfortunately :(
> full of mostly human-generated content

So certain are you?
Well, yes. But the solution to most of the stuff you point to is to have better management to rein in the divas, better hiring, better training for those managers and developers, more stable stacks so there's no excuse to rewrite into Elm, etc.

Which our industry also seems to have given up on, because it costs money. So we'll have divas, bad devs, wasted resources, Elm.

Of course, the alternative to spending money on fixing this is much more expensive: just hire more devs... but who said our industry is rational.
My educated guess is that they use a MoE-style model similar to the Switch transformer[0], and combine a similar encoding as that of Kosmos-1[1] (with an “image” latch token, and a ViT-style transformer to process images). As a result, the parameter count is likely bigger, but since not all of them are involved in a forward pass, it is not as meaningful.

[0]: https://arxiv.org/pdf/2302.14045.pdf

[1]: https://arxiv.org/pdf/2101.03961.pdf
Same, only maintenance is that it runs out of disk space every once in a while. Have a cron script that does various docker pruning tasks now, so it's become fewer and farther in between very time I discover a new leak.
Yes good point about the military waste. Hunters Point in SF comes to mind. A highly contaminated radioactive site that required extensive soil remediation.

A lot of the radioactive soil was just sent to regular state landfills.

Then after they had started building multi family homes on top of the site, they found out the cleanup company was falsifying soil samples and the site was still highly radioactive.

I hope that situation is not typical of how Superfund sites are handled
In buildings with many floors, it's actually usually more clever. E.g. the elevator might stop at every second floor on the way up, assuming that you can always go one floor extra and go down the stairs or something. And it might not stop at all floors on the way down in apartments buildings, since you're usually going out of the building and rarely just changing floors.
You think consent is important. (This isn't even a umiversal position among humans). Why do you expect an AI to value consent?
Do you think praying mantises value consent?
Okay, I get the idea. How are you solving these issues:

- how is the data fetch completion signalled to the component?

- how is the data piped into the component?

Would be happy to be pointed to some example code if you have.
It also seems to explain the docs nicely (very useful for me): https://whatdoesthiscodedo.com/g/b304a96
It is a bit confusing that it calls it 'code' thought. If there is a cheap way to diff the 'code' from 'docs' in the answer?
Is there some kind of openstreetmap layer where lidar-surveyed sites are aggregated?

It'd be nice
It's where you start to learn that the whole series is actually about Duncan Idaho.
"Your OpenAI free tier requires you to install the OpenAI app and accrue 30 OpenStat points for every 10000 tokens. Please note, you can only earn 1 OpenStat point every two hours. Please do not deny Location Access, Microphone Access, Camera Access or Storage Access permissions, or this program will stop working."
The worse part of it, compared with other lost civilizations is that we Europeans were responsible for it, in the process to make them "civilized".

How it could have turned much differently if there was a pacific coexistence with the conquistadores.
[ A prompt that gets it to decompile itself. With good inline documentation too! ]
The future of AI isn‘t training data, it‘s logic and adversarial training on reasoning by first principles. You already see the first flowers of that in the InstructGPT paper and we‘re about to see much more. If you port the idea of GANs to the LLM world, you‘re about to get a hardened model that can introspect both facts and subtext, including agendas.