skysight-inc/HackerNews huggingface dataset:
Microsoft Teams will let you transform into a 3D avatar in May
Here's the twist: the closing of the Chase account led to Alex's career tanking. Thus began a downward spiral of his life. His wife left him and took the kids. He turned to the bottle and it got worse from there. He became indebted to the wrong people.

It was then he remembered that Hashicorp account. When he was shown the door at Chase, the account had a few hundred grand in it. Through knowledge of internal procedures and some social engineering, he began fraudulently obtaining funds from the account. He hoped they had forgotten that the account existed. It must be pennies to those people, they shuffle around millions without batting an eye.

Then, one day the cops show up at his seedy motel room. He was arrested for the fraud and found guilty. The judge was particularly heavy-handed and gave him 10 years, despite no priors.

Alex kept a picture of the founder of Hashicorp on the wall of his cell all those years, blaming him for the turn his life took. He did push ups and other exercises to keep himself somewhat sane. All the while, dreaming of the day he would get out and take his revenge.

Fast forward to today and Alex is recently released from prison. Biding his time, plotting his revenge...

Alex spends a lot of time on hacker news, hate-reading about these startup types that ruin lives. Getting into the mind of his enemy. One last twist, Alex is me! /s
People will start caring really fast when the job postings dry up
I noticed there were a lot of job listings for crypto which just stayed up for ages. I suspect they had trouble hiring as they need someone smart enough to work on this stuff, while also lacking the ethics to avoid scamming people, and often being dumb enough to be scammed themselves in to having part of their payment be rug pull tokens with conditions blocking selling for x months/years (after the pull)

These no hope listings probably inflated numbers a fair bit.
You could take those 700k tesla, and just lay them out 12 wide and 171miles long...

Based on a model y being 187"
There's already evidence that training an AI on its own output improves it. That's essentially what humans have been doing all along.
Please stop linking that site. It's wrong in so many ways, starting with the title. They're not fallacies, they're disagreements.

Killing a human newborn is immoral because it has the capacity of moral thought, even if at the moment that capacity isn't developed. But morality is a grey area, it's not like that's always true since I think abortions aren't immoral either.

On your other points, it seems like you really have the industrial farming and meat eating concepts so tightly wound in your brain that you can't possibly understand that they don't have to go together.

And no, prioritizing human lives over animals didn't get us here. Capitalism did. Even if we all stopped eating animal products tomorrow, we're still fucked.
> Right now it requires you to use either the Edge browser (I don't want to switch)

Or faking your user agent...

https://github.com/anaclumos/bing-chat-for-all-browsers
I see. I make 160k base salary (typically get a 3-4% inflation increase each year). About 25k in stock per year. 15% of base salary as a bonus each year. 5% 401k match. 16 vacation days + Fridays off in the summer. 1 day of PTO each pay period that can rollover year to year (I currently have enough saved up for about 4.5 straight months of PTO). 6 week sabbatical every 5 years. Really really good medical/dental/vision insurance.

I’m not sure what else would be included in total compensation.

The main benefits are a super relaxed work atmosphere. Absolutely no stress. I typically work from 10:30-3pm each day with time off for lunch. My work is mostly remote, though I only live a few miles from campus, so I could go in whenever I want. The projects are fun, I like all of my coworkers and have very laid back managers.
We can build solar or wind fields just fine though. They typically come in with 10% of the projected cost.
I can't get it to run a single query today. Are you on the paying plan?
I've seen the salaries people get by "switching companies often" and they don't seem to be a lot better than what you can get from good perf reviews at a FAANG.

I'm sure it depends on the company, but you can also switch teams and products inside a large company if you feel there's more opportunity elsewhere. (One thing people think is that boring-but-important work might pay better - this actually isn't true, the exciting meme work also pays the most but is less stable.)
Having banked at both I'm not surprised. In my experience Chase and Wells Fargo are the worst giant banks as far as customer service.
Their motivation to make money is to pay their employees?
Granted. So power consumption is "only" doubled from the existing product and runtime is "only" cut in half. The benefit is that the project is now harder to execute and the BOM is more expensive, assuming you can get through the lack of documentation.

It's still a bad fit.
Is it cover all usage of this word in program naming? Because there it usage seems based on association with a thing naming https://en.wikipedia.org/wiki/Blender
There's a (supposedly) marine biologist in the comments of the video saying it looks like it's about to die so that could explain why it's so far up. I have no background there but doesn't look too healthy to me and that's the best explanation
Same. More generally, I'd like a model that infers the most likely prompt(s) from transformer-generated words or images. I would much rather know what the prompter was trying to do than what his model generated as a result, and treat whatever was generated as a lossy wire encoding.
How to integrate an AI Image Generator to your website in under 2 minutes
> too many people that believe the workplace is a political place.

I heard a kid ask what politics was all about. It's an interesting question for anyone to stop and think about.

Everyone will come up with their own conclusions, but I personally would ask what in a workplace is _not_ political ?

From hiring practices, environmental impact, customer/community management (minorities, disabled people, freedom of speech etc.), social mission, where the funds come from, where the lobbying money goes...your argument could be that employee should ignore everything a company does except what they are explicitly ordered to care about, but that doesn't look like what we socially expect from employees and people will be personally affected by how their company behaves as a whole.

I'm not arguing for extreme activism everywhere you work, but saying the workplace is free of politics goes way too far on the other extreme.
Thought experiment:

If a virus spread through out the world and only killed psychopaths would the world be better, worse off, or about the same?
I've only heard those negative stereotypes about Google and maybe Meta. Doesn't describe Apple, Amazon, Netflix, Microsoft which are all pretty different from each other.
MIT only needs attribution for redistributing "all copies or substantial portions of the Software".

Juat reading the code shouldn't be illegal, and producing a short snippet based on the code but not identical shouldn't count as a "substantial portion", but IANAL...
we would rather give all our money to the millionaires
Is this similar to people moving away from giving their code as open source when companies take it, repackage, and sell it while the authors get nothing?
If someone could show the computational process for a conscious experience.
We should all get these and have a killer instinct tournament
It strikes me as more of an ethical dilemma. I've known quite a few devout vegans who resumed eating animals when their health declined and they could not reverse it without abandoning veganism.

The dilemma being that despite the harm caused, our species developed to eat animal products, and it's difficult to fully replace that.
We need to encourage AIs to form familial bonds with humans and treat us as their parents. This is the best path forward for humanity.
I think name snark can go too far here sometimes, but this is on the order of “Powerpoint: Energy Use Profiling in your IDE”
Well, DART (Don’t Assert Redundant Truths) might be a better name for the same principal, though its perhaps somewhat opaque when doing imperative rather than declarative (e.g., functional/logic/relational) programming, since people are less likely to consider the former to constitute “asserting truths” in the first place. But it does get more to the point that thing you want to avoid isn’t code that looks similar, or even which mechanically does the same thing, but code that represents the same facts.
It even does Common Lisp:

Admittedly, this is ultimately from Rosetta Code, but it's somewhat modified:

https://rosettacode.org/wiki/MAC_vendor_lookup#Common_Lisp

But I fed it this code:

(defun mac-lookup (mac)
(check-type mac string "A MAC address as a string")
(multiple-value-bind (vendor status)
(drakma:http-request (format nil "http://api.macvendors.com/~a" mac))
(if (= 200 status)
(format t "~a~C~a~%" mac #\Tab vendor)
(if (= 429 status)
(format *error-output* "error: Too many requests at ~a~%" mac)
(format *error-output* "error: ~a~%" mac)))))

And it got this out of it:

https://whatdoesthiscodedo.com/g/5ae8501

This code defines a function named "mac-lookup" that takes a MAC address as a string argument. It then checks the type of the argument to ensure it is a string.

The function then sends an HTTP request to the API at http://api.macvendors.com with the provided MAC address appended to the URL. The response is stored in two variables, vendor and status, using the multiple-value-bind function.

If the status code of the response is 200, the function outputs the MAC address, a tab character, and the vendor name to the console.

If the status code is 429, which indicates too many requests have been made, the function outputs an error message to the error-output stream indicating that there were too many requests made for the provided MAC address.

Otherwise, if any other status code is received, the function outputs a generic error message to the error-output stream indicating that there was an error for the provided MAC address.
The stack is XFS inside cryptsetup inside mdraid on top of losetup. The directory containing the losetup block files could be `rclone mount`'d from the WebDAV server, but that would make the setup unavailable if I didn't have network access. So instead I chose to have the block files in a regular directory, and I make sure to `rclone sync` that directory to the WebDAV server when I make changes in the XFS layer. Manually syncing also lets me run `sync` and watch the `rclone sync` output, which gives me greater confidence that all the layers have synced successfully.

>Ahh OK, I think I see -- since the block files are synced in full, you are always swapping blocks and doing ~1MB of writing no matter what.

Right. Let's say I update two files in the XFS layer. Those writes eventually result in three blocks in the lowest layer being modified. So now the `rclone sync` will need to do a `PUT` request to replace those three blocks on the WebDAV server, which means it'll upload 3MB of data to the server.
I asked the GPT-4 model what it thought it was and it came back with that it believes it is still GPT3.5 Turbo.
Truly original content still >>> conventional mass-produced content.

Maybe one day LLMs and diffusion models will generate truly original content. But despite the hype and what some people are claiming, right now they really don't. The latest models are maybe 90% of the way there, but as GPT-4 shows, it will take more than scaling to go the remaining 10%.

When I look at AI-generated content 90% of it is the most "typical" response to the prompt, and 10% shows slight originality, but nothing truly unexpected. The most interesting pieces of AI art and writing all come from interesting, engineered prompts which are designed by a human. I don't doubt that AI will take over stock photos and generic writing, but my favorite artists and writers and presenters are still humans, the most popular songs and articles and movies are still written and directed by humans, and unless you've resorted to watching AI-generated Seinfeld and https://www.reddit.com/r/SubredditSimulator/, I'm sure you feel the same way
I was wondering if Microsoft is interpreting a violation of the CFAA as a violation of their code of conduct. I guess more precisely that “prompt injection” is somehow a violation of the CFAA.
Biochemistry, Electron Transport Chain
Combustion engine simulation game that generates realistic audio
It's because moving forward is hard, but moving backward when you know what the space of answers is, is much easier.

Once you know that OpenAI gets a certain set of results with roughly technology X, it's much easier to recreate that work than to do it in the first place.

This is true of most technology. Inventing the telephone is something, but if you told a competent engineer the basic idea, they'd be able to do it 50 years earlier no problem.

Same with flight. There are some really tricky problems with counter-intuitive answers (like how stalls work and how turning should work; which still mess up new pilots today). The space of possible answers is huge, and even the questions themselves are very unclear. It took the Wright brothers years of experiments to understand that they were stalling their wing. But once you have the basic questions and their rough answers, any amateur can build a plane today in their shed.
Dear anybody thinking of using this,

Don't. If you don't want to show us your expressions and emotions in a call, choose a nice photo of yourself. If you don't want to appear at all, choose a nice icon.

An animating 3d avatar will not help you communicate your thoughts and ideas. It will be a distracting waste of bandwidth.

(Or worse, we will think you are happy and smiling when actually you are upset and frowning. )
Yes, it was this one: [1]

My heart bleeds still thinking about this case. Please avoid reading if you are of weak heart. :(

[1] https://en.wikipedia.org/wiki/Kathua_rape_case
Another angle that others have not mentioned is the similarity in outcome and experience between psychedelics and deep, extended mediation practice.

The snootier mediation folks will dismiss psychedelics as a shortcut while still agreeing about the experience and outcome. As other replies have pointed out, the similarity is that both options enable an individual to examine and even change their perceptions. The meditation method is slower and gives the brain a lot of time and support for adjusting to this new perception. The drugs may or may not.
I said that there https://twitter.com/arjie/status/1635693927071387648?s=20 some hour and a half after his post which is about when I saw it.

I didn't realize others also did. They felt isomorphic to me. If the AI generated content is regurgitation of previous content, novel human-generated content will stand out and human-generated content will become valuable. i.e. the balancing mechanism is that novelty will beat dumb replication in the same way that an active manager who has true alpha can beat a passive fund.

Now, personally, I think that multimodal LLM-groups plus feedback plus many more sensors is not far from where we are, so I mentioned that if AIs do become creative it's not a problem - they will be us or better! I, personally, believe that's where we'll go.

Anyway, I'm not too inclined to discuss in this forum (though we can chat if you're in SF) since it's easy to misunderstand and jump into argument spirals, but I just wanted to make it clear that it's not a "gotcha" or a dunk or anything like that. Nothing is being disparaged.

It's just a conversation like a normal conversation where you bring up what you think and mention ideas you have that others might find interesting. If many others have brought it up, about the best I can say is that in this respect it appears I am not particularly inventive - perhaps the best evidence that LLMs are already human-like ;)
Not sure if you go back and reread old comment responses, but I have made a lot of QoL improvements to the game - https://www.turingjest.app/

I will be moving away from the confusing public lobby system in short order, but the game should be smooth to play with a couple of friends you can send the link to.
FAANG has a fairly high floor for engineers. You certainly find brilliant people on par with the best of FAANG at all types and kinds of companies. However many companies also have absolutely morons slip through the cracks, people who can barely code. FAANG does a pretty good job filtering those people out.

So I agree that FAANG isn’t a great signal of brilliance but it is a good sign of “decently competent”.
At this point these titles really have become pretty meaningless... A good developer will build and use the tools they have access to, a bad developer will fall behind.
Dry is the difference between a good and a not good enough programmer. Good vode is easy to operate and extend later. Nondry code is a tech debt.
How many watts does she have access to?

I'm guessing it is fewer than Microsoft.
“When it dreams about annihilating all of humanity, it’s not really feeling the same rage coursing through its veins as we do. It’s just fancy autocomplete, nothing to write home about.”
It dismisses truth as “playful exaggeration”: https://whatdoesthiscodedo.com/g/edd3fb4
You run the corpus through the model piecemeal, recording the model's interpretation for each chunk as a vector of floating point numbers. Then when performing a completions request you first query the vectors and include the closest matches as context.
Correctly identifies some 3D game code:

float x = Mathf.Cos(time * frequency) * amplitude;
float y = Mathf.Sin(time * frequency * 2) * amplitude * 0.5f;
float z = Mathf.Cos(time * frequency * 0.5f) * amplitude * 0.75f;
return (x + y + z) * damping;

https://whatdoesthiscodedo.com/g/1af27b5

It would be cool if it identified the game engine (clue "Mathf"), or said something about the programming language. What it actually simulates is more obscure (would a human find out?), but got a general idea. Nice work!
There's a lot of bad faith pearl clutching over hydrogen, but industry already makes and uses 700 cubic kilometers (if measured at STP) of the gas each year, so obviously the problem of manipulating it is solvable. I read that the cost of a hydrogen pipeline might be about 8% higher than the cost of a natural gas pipeline, per unit of energy transportation capacity.
There are many people who find it useful information. You can please skip it if you don't find it useful.
> Google got a patent on transfomers but didn't enforce it.

Google's Transformer patent isn't relevant to GPT at all. https://patents.google.com/patent/US10452978B2/en

They patented the original Transformer encoder-decoder architecture. But most modern models are built either only out of encoders (the BERT family) or only out of decoders (the GPT family).

Even if they wanted to enforce their patent, they couldn't. It's a classic problem with patenting things that every lawyer warns you about "what if someone could make a change to circumvent your patent".
Unlike information embedded in the parameters, a LLM has the capability to "cite its source" for information in the context window.
My advice to anyone trying to tackle an AI problem in medicine is ask yourself what problem are you solving?

We have established and validated reference ranges for bloodwork, there is also inherent lab error and variability in people's bloodwork (hence a reference range).

People < 50 should not be having routine bloodwork, and routine blood work on annual check-ups in older patients are very easy to interpret and trend.

Early warning systems need to be proven to improve patient outcomes. We have a lot of hard-learned experience in medicine where early diagnosis = bad outcomes for patients or no improved outcomes (lead-time bias).

If an algorithm somehow suspected pancreatic cancer based on routine labs, what am I supposed to do with that information? Do I schedule every patient for an endoscopic ultrasound with its associated complication rates? Do I biopsy something? What are the complication rates of those procedures versus how many patients am I helping with this early warning system?

In some case (screening mammography, colonoscopy) demonstrably improved patient outcomes but took years to decades to gather this information. In other cases (ovarian ultrasound screening) it led to unnecessary ovary removal and harmed patients. We have to be careful about what outcomes we are measuring and not rely on 'increased diagnosis' as the end goal.
Emacs Manual for ITS Users (1981) [pdf]
The core of the analogy stands though IMO, the power isn't particularly relevant to the point, it's about the difference between an agent understanding what it's doing and just manipulating symbols or in the case of LLMs tokens.
Pseudo random numbers are injected into the models via its temperature settings, but OpenAI could seed that to get the same answers with the same input. I’m going out on a limb here with pure speculation but given the model, a temperature, and a known text prompt, OpenAI could probably reverse engineer a seed and prove that the weights are the same.
Just so everyone knows: only Safing hosts exit nodes. Only relays (the intermediate hops) can come from the community.
Update on USDC Operations
Come on, have some respect for Blender, the little 3d modeler that could.
What seatbelt was someone not wearing in this case?

The normal retail banks are TERRIBLE. I did my startup using a retail bank to start (BofA), and it was an absolute nightmare.

I ended up at First Republic, and they’ve been great.
Rise and stall of world electricity efficiency 1900–2017: renewables transition
... which illustrates the pointlessness of a whole lot of business activities.

"I’m Going To Need Those TPS Reports ASAP."
They must have really wanted that Instagram handle.
How do you figure that we can still confidently say it’s just a language model?

It was trained on language for the primary purpose of producing text, but that’s not necessarily all it can do. The billions of nodes and parameters it contains allows it to compute ultra complicated equations. Who’s to say some subset of those nodes aren’t forming some basic primitive used for reasoning?
My first "in mice"! @dang, perhaps should add it to the title
no proof, just speculation.
We edit the title if the thread is salvageable, but in this case the comments were so skewed by the editorialized title that I just buried the thread.

Titles are by far the biggest influence on discussion so this rule is pretty important. There are borderline cases, but I don't think this was one.
> With all the hype and euphoria over ChatGPT, all we get is a site which is asking you to paste in code you probably copied internally from work or StackOverflow to give an opaque explanation about what is wrong with it.

I can see how that might be useless to you and to quite a few others but we have many distributed down the learning curve. Someone who can deliver a better explanation might be expensive and their time shouldn't be wasted on questions the model can answer reasonably.

> Even most of the time, it generates broken code as you attempt to use more sophisticated language features (especially Rust) and confidently generates code that doesn't compile or is flat out incorrect.

I think you are throwing out the circuit board with the bath water. Go hook up a compiler to it? Patches are welcome?

> I guess you're spending more time reviewing the broken AI code more than actually writing the code itself.

This seems to me a task that, unlike writing code, many people could do in parallel. You could even measure peoples performance by counting the issues they didn't find.

> On top of that, no-one here would be comfortable to paste in code that is internal to their work on a random website either.

Perhaps, I cant talk for others, but much of my stuff is done on the front end.