skysight-inc/HackerNews huggingface dataset:
Yes, and if you check my posting history, I never tried to justify my doing so was for any other reason than “trading labor for money to support my addiction to food and shelter”.

I’m not judging anyone for making an outsized salary for working at Facebook. Just be honest that you’re there for the money and not some high minded ideals.

https://news.ycombinator.com/item?id=35035560
That would actually be an interesting product: spell-check but it edits your email or slack message to be more sycophantic. I'd use it.
Let me be clear, those were bonuses that helped fill in gaps. I've been seeing through the muck since before gamergate had a name and I'm good at reading between the lines.

The real issue is someone acting like they're too anti-woke to encode morality rules into their ai... After listing morality rules.

It's abject hubris, "oh of course my morals are the universal standard".

The fact that they cast side-eye on other people expressing ideas about social norms, or acting like unregulated free speech is unlimitedly good, and the cluelessness about moral relativism/absolutism, well, like I said, it completes a picture.
This reminds me of something (perhaps Raymond Chen?) writing about how people think selection coloring is just an easy "invert the colours" and pointed out a midrange selection color would make that inversion not work.

I think I read that while I was at uni, so well over 20 years ago now. GitHub messing this up now seems disappointing (and aren't they part of MS now? shouldn't this be on the standard "new ui QA tasks" list?)
I have been wanting to get back into learning the FV-1, which is used in a lot of guitar pedals.

http://www.spinsemi.com/products.html

https://electric-canary.com/fv1start.html
> Are software engineers going to go the way of human “computers”?

Anything with digital IO will.
twitter down now too
I would be very surprised if not.

At least some state actors will invest the very negligible money of getting to where gpt-4 is now. It does not need to be cost efficient to train or run.

It's total cost is not even near the scope of a space program or even a major military research project.

With 10-100 million dollars you can probably get most of the way there once it gets prioticed.
You would be guessing wrong. If it helps to understand Oxide a bit: we have had ~2000 applications and we have 60 employees (a level of oversubscription in part because of this very blog entry, published in 2021). It is exceedingly unlikely (though not impossible) that we would hire someone straight out of school, and one of the surprisingly challenging things at Oxide has been turning away people who could quite potentially be terrific contributors.
That's true, I'm a fast reader and I am probably on lower volume boards than you might be thinking of.
I think after the bans of certain, negative communities on Reddit

fatpeoplehate, incels, thedonald

They would go out into other parts of the site and be spread their pessimism with unnecessary arguments. It made the site more of an echo chamber, less diverse, and less supportive of free speech, but it did make many places less tedious
But it will have zero credibility, so no.
Take something from advent of code and change it up a bit seems like a good test
Reddit is also having issues, maybe someone tripped over a power cord?
>this is letting me pick up more work than ever

Is this a desirable outcome, to be just a meat robot middleman for the machines doing the actual work? I hope this will lead to a total rethinking of how our relationship to work and the why of it all.
Overall I really like this -- I think it makes a ton of sense for a startup, where the expectation is that most of the hires will contribute equally. You might end up having senior people self select out for the "low" comp, but others won't care because they believe the equity will make up the difference.

But I take issue with this part:

> As for how equity is determined, it really deserves its own in-depth treatment, but in short, equity compensates for risk – and in a startup, risk reduces over time: the first employee takes much more risk than the hundredth.

I don't think it's correct. Someone who joins with 25 years of experience is taking a lot more risk than someone who joins with 5 years of experience. The first person is most likely on their last job or close to it -- they don't have a lot of runway left to "take another chance". The person early in their career will have many chances to take new risks.

OP didn't get into it, but I hope they consider that when the look at the equity part of compensation.
I like this idea. If I'm in another early startup where everyone has to be really good, I might propose it.

We'd need to keep having attractive enough work and environment, and promising enough equity lottery ticket, that others can't just hire away our people by paying 2x to 5x more TC.
I think companies are getting very receptive to uploading code with the new 30-day policy. We have been able to negotiate this for financial firms. Reach out and we might be able to make something happen.
Thank you for clarifying.

I put your remarks into the same prompt and it essentially devolved into recursive garbage after agreeing with you.
Reimplementing quicksort in a language the rest of the company doesn't use in a part of the software that no one ever touches is fireable, sure, but I suspect that on the way to ChatGPT there were more than a couple "Leedcode hard"-grade problems that OpenAI engineers and PhDs solved because the library for that didn't exist before.
serious question for everyone: what are you planning to do when these LLMs replace our jobs? it seems it won't be long before a handful of tech employees will be all even the largest of companies will need, and maybe a few years after that the role will have changed so much there's no need for a single dedicated tech employee.

i am terrified

i imagine i should shift to some physical work. carpentry, real estate... something like that. it seems inevitable that any knowledge worker will become obsolete and the time to obsolescence for physical work is longer
Most of the other big tech cos have promotion windows twice a year at least.
They are interactive. What AI is doing with story generation is a text version of the holodeck, not just a plain old book. You can interact with the story, change its direction, explore characters and locations beyond what is provided by just a linear text. And of course you can create stories instantly about absolutely anything you want. You just throw some random ingredients at the AI and it will cook a coherent story out of them. Throw in some image generation and it'll provide you pictures of characters and locations as well. The possibilities are quite endless here. This goes way beyond just generating plain old static books.
Pre-industrialisation: 80% of population are farmers

Post-industrialisation: <1% of population are farmers

There's going to be a big squeeze in the field (pun not intended).
It can lick boot perpetually and without rest. Many managers, however, will still prefer the real thing.
Or actual bills.
In the US, at that time, the Federal Reserve used to issue $10000 && $100000 notes exclusively for settlements between member banks.
esperanto is easy enough to learn that you don't need a tutor with native proficiency. and you if you practice enough you can easily achieve proficiency in less than a year.

the grammar is simple so the main work is picking up the vocabulary and the rest is conversational practice and learning about edge cases
Your statement is correct, but not complete.

When a covered entity (a HIPAA-required provider) does business with a private non-covered entity _and_ that transaction involves HIPAA controlled information, they must enter into a Business Associate Agreement (BAA). This effectively forces the private entity to maintain the same HIPAA standard as the provider.

A private company is absolutely free to build non-HIPAA compliant software, but they completely unlikely to get any healthcare providers to actually use it.
> market to market value is probably closer to a 15% discount from par if they tried to liquidate immediately

Correct. The only way someone makes money on these is by borrowing against them. Conveniently, it now looks like the Fed will lend against the face value of Treasuries at the discount window.
When you come back after a day or two away do you start reading where you left off like a chat log?
In a couple of years the mythical 10x engineers will probably be 100x engineers, depending on how well they've managed to integrate this tech into their tooling.
Progress can come to a screeching halt at any point. We saw this with self-driving cars previously: the AI true believers were certain self-driving would be everywhere within 5 years... in 2015. Now the idea of a self-driving car has mostly been abandoned.

Let's get at least one company, at least one, replacing its graphic design department with DALL-E, or its development team with GPT, before calling an entire profession obsolete.
> He's excited to bring the future to people

Is he? Is that why he spends his time falsely claiming cave divers are paedophiles and why he publicly mocks people with muscular dystrophy?

> and often overestimates the capabilities of existing technology

So what you're saying is he bullshits and he lies.

You do appear to be fully bought in to the Musk Mythology. At this point the only person who can help you see the more simple (and uglier) Musk Reality is you. It will be a hard road for you.
But you would think that such folks would see the value in the model? I mean, I get that trust is at a very low point but wouldn't folks see the value in a model that focuses on (among other things) fostering mutual trust? There is clearly a lot of anger out there, and I don't know if that's part of a broader trend or not.
What I've noted is that GPT is really good at things that have really good documentation.

The example of kube-tf in this repo is a perfect example. The Kubernetes documentation and all of Hashicorp's documentation is excellent. GPT will have infinite examples of good code to stitch together code for the task in this example.

Now I've been running a private cloud at work on the OpenNebula platform, which has documentation that is definitely lacking. I tried to ask GPT to write some basic code in Python such as "Give me a list of VMs from the OpenNebula API in a powered off state that have a start time older than 30 days."

What I noted was that it would spit out code that looked correct on the surface, but would not run. It would take a decent amount of me modifying the code until I got my desired result. Since there was no documentation, I was just reading through the OpenNebula packages themselves to understand what to do.

The nice thing, though, is that it was a great starting point. Much in the same way I might take a code snippet from StackOverflow and modify it to suit my own needs.

I listened to a great podcast titled "The Trouble with AI" on Making Sense with Sam Harris. One of the key takeaways I grabbed from it was that GPT is an LLM not an AI. What it is very good at is predicting the next correct character or word in a sequence based off of other examples. But it does not actually fundamentally understand what it is outputting.

In order to demonstrate, open up a session with ChatGPT really quickly and ask it a single digit multiplication question. Such as "What is 3 multiplied by 4?" and you will see a correct answer.

Next, ask it something a bit larger, like "What is 12366 multiplied by 981632?" and you will get an incorrect answer but one that looks pretty close to correct. Validate with a calculator yourself.

The reason being, as an LLM it doesn't actually understand multiplication. Instead it has just seen 3 multiplied by 4 countless times in the data it ingested when it was being "trained", but never has seen larger number examples of multiplication. Not that it knows multiplication in the first place.

GPT is fantastic, but as of right now it needs to be used as a starting point towards knowledge or something concrete. I wouldn't trust it as an authoritative source on anything quite yet. It is fantastic for generating a bit of code and then allowing the developer to tweak that code until it actually works.
Pick from this list: https://leetcode.com/problemset/all/?difficulty=HARD
Taxpayers did not pay for the FDIC protections. And shareholders are wiped out, so they didn't gain from this collapse.
And yet still cheaper than doing nothing. Same is true of half-solutions or pretend solutions. In reality nuclear is more than cheap enough to do the job. If upfront costs is really an issue, then we should subsidize it.

And even with all nuclear disasters included, it is still cheap enough to do the job. If it is uninsurable, then government should insure it. Again, still cheaper than anything else.
So to play devil's advocate here, one good thing that does come out of bailing out depositors is that the employees that work for these companies can get paid. Therefore, they can use that money to spend on the economy. They can prevent stress from losing a paycheck. That has to count for something doesn't it?
Just ask OpenAI and it will build it :)
> Yeah, there's an awful lot of power going into private hands

That sounds scary, but what do you mean by "power"? Honest question, I'm fascinated by the discussion about learning, intelligence, reasoning, and so on that has been spawned by the success of GPT.

What "power" do you imagine being wielded? Do you think that power is any more dangerous in "private hands" than the alternatives such as government hands?
It’s extraordinarily hard! Often in trying to analyze some complex system I have found it’s much more tractable to implement the system and analyze the results (e.g. a montecarlo sim of dice-rolling rather than trying to do the math). Likewise, a tractable way to measure over-regulation might be to simply do nuclear in a limited low-regulation area and draw conclusions from that.
Yeah same here. Having to go to an Enterprise level to get free guest users is absurd, they've really stopped listening about product feedback, and the pricing model makes no sense...
GPT-4 certainly is aware of go generics. Do you have an example you would like to test?
Fees that banks collect from depositors fund the FDIC ... so like I said, taxpayers are going to take the hit on this one.

Countries like Russia and China would execute the leadership at SVB that allowed this disaster to happen.

In this country, they'll all get another cushy job from their friends in the industry where they can take even more risks with taxpayer money ... hopefully with a much better outcome next time!
It can draw! https://twitter.com/simonhamp/status/1635796861884723200?s=4...
I should probably start doing that. I’m a self-important jerk usually.
"I'm altering the deal. Pray I don't alter it any further."
I am pretty deaf yet somehow have wound up interviewing people for a living (go figure).

I currently use googlemeet and recently switched to Otter.ai for recording/transcription. Unlike the previous transcription tools for journalists that I used in the past - Otter.ai generates the text live on the laptop screen while we are talking and even corrects itself to make sense as the speaker reveals contextual clues.

It is a huge help, and I had wished there was something for real life conversations like this is for screen conversation.

Good news for deaf people. You only have to watch newscasters speaking through a pasted-on permanent grin - as if every word is ee - to know that lip reading is garbage.
Back in the day Google offered hardware search appliances.

Offering sealed server boxes with GPT software, to run on premises heavily firewalled or air-gapped could be a viable business model.
We don't need an upscaler, we need an upclasser so all the ASCII Dickbutts drawn get little top hats and monocles put on them.
They Probably need to hire a high priced agile consultant that will suggest putting 10k people on it to get it done in a month.
"Tendency of the rate of profit to fall" affects labor, too.

Sure, you may have a temporary advantage by leveraging AI and effectively doing labor arbitrage (the same way some craftsmen could gain a temporary advantage over others if they had access to rare/expensive tooling in the early days of the Industrial Revolution) but this advantage will quickly disappear as AI tooling becomes cheap and ubiquitous.
"Emergent World Representations"

The weasel word here is "emergent". That means they are implicit representations.

The representations of the Othello board that exist in that model are not explicitly constructed. They just happen to align with the model that a person playing Othello would likely represent the game with.

That work showed that, given an example sequence of valid Othello game states (as training corpus) and a valid "fresh" Othello game state (as a prompt), the system can hallucinate a sequence of valid Othello game states.

The system does not know what Othello is, what a turn is, or what playing is. It only has a model of game states progressing chronologically.

When we look objectively at that model, we can see that it aligns closely to the game rules. Of course it does! It was trained on literally nothing else. A valid Othello game progression follows those rules, and that is what was provided.

But the alignment is imperfect: some prompts hallucinate invalid game progressions. The model is not a perfect match for the explicit rules.

In order for all prompts to result in valid progressions, the training corpus must have enough examples to disambiguate. It doesn't need every example: plenty of prompts will stumble into a valid progression.

The next thing to recognize: a "valid" progression isn't a "strategic" progression. These are being constructed from what is known not what is chosen. Given a constrained set of Othello strategies in the example corpus, the system will not diverge from those strategies. It won't even diverge from the example strategies when the rules of Othello demand it.

GPT doesn't play the game. It plays the plays.
How does a democracy actually appear?

The only way I know is that the when people join to kill the governors every time they decide to go around killing the governed, some democratic institutions appear.

Yet, this is not how most democracies were created. It was how the concept appeared, but nowadays it tends to take a different route. Some murky, hard to follow route that looks exactly like noise to me.
> If you can put in ALL of the information relevant to a problem and it can algorithmically do reasoning

Well but it can't, can it? That's the very point: it is an algorithm with no abstraction or reasoning capabilities. Mind, even without that it is still very useful for certain circumscribed purposes, but it's incorrect to say it can "reason".
The commenting was for the model to learn what the types were so it could translate it to gather. Doing that one shot is surprising to me because it is somewhat hard to get pytorch tensors to work out to the correct shapes.
if you're the only one filling a void, people forgive a lot.

reddit is the place at the moment for a lot of people, that affords them a lot of forgiveness.
In the defensive security space there is also Kicksecure[0], which serves as the base for Whonix (a hardened linux distro that tries to provide strong privacy/anonymity via the Tor network). They have a wiki that goes over the desktop hardening features and tweaks that go into it.

[0] https://www.kicksecure.com/
> The Peace War though, haven't read those.

The one with the stasis bobbles ... https://en.wikipedia.org/wiki/The_Peace_War
They were, we experienced the same. Told them to go pound sand.
It's a little weird because while $191k is a lot of money to most people (it is twice what I make) but it isn't a lot of money in the Bay Area, especially for an experienced tech person.

More importantly Oxide is only (AFAIK) employing senior people who could make more at another company. They don't have Junior programmers or Helpdesk people on $191k.

It seems to very much be instead of a startup paying "minimum/ramen wage" plus options etc they are paying "middle class bay area wage" + options.
Business associate only comes into play when you're working with a covered entity. And, covered entities are far less inclusive than most people think.

----

The posted software is absolutely free to be non-HIPAA compliant. They're not a covered entity and without a relationship with a covered entity, they're not a business associate. However, without a relationship with a covered entity, they're also unlikely to generate any meaningful revenue.
I sort of agree, but it still amazes me that it can get the code is correct, even though I asked for a highly specific style (i.e., use of recursion, representing "None" as null, the format of the JSON, making local functions, etc.). So, even thought it has never seen that exact implementation, it still assembles a working function that just works. If it was just mixing up different code it recalled from memory, it would likely have a bunch of silly errors here and there that I'd have to fix manually, but no, it just works. That's what impressed me.
> It absolutely has happened.

Could you list some examples of companies that have laid off their art departments to use DALL-E/SD/etc?
Sure, I think we're all agreed nowadays that drenching everything in corn syrup isn't going great.

The answer we don't have is: What's actually better, at the same scale?

All the current offerings are for people who want to eat tofu-and-beet-juice patties, or eat lentils everyday, or drink some ever-changing goop of "meal replacement shakes." No one's really cracked the code on finding foods that are both healthy and scalable.
If adding housing supply actually increased the value of surrounding housing, you could generate unlimited wealth by building more and more housing in a city!
Well it was for a while. Then they got someone killed during the whole Boston thing. So you know, theres that..
The funny thing is though your point here is working against your argument.

You are saying that GPT is doing a poor job of showing it is a great artificial intelligence. But nobody is saying that it has infallible intelligence. It is making the same mistake that now two different humans have made in the same situation. Both me and OP above.

It is failing in the same way that humans fail at this problem! By pattern matching and assuming it's the goat proble!

You're arguing that gpt 4 isn't a sound logic engine and not are most people. A tool trained on human input, when given this problem is making similar mistakes that we make.

Are there a set of people that would get this problem right? Yup. Are there also a set of people that would make this exact mistake? Yup.

Your upset that is behaving like the "wrong" group of humans.

Your thinking of it as an expert. Instead think of it as a result smart and well read high school student. There are things you can delegate to it that it will do well. But you also need to double check its work as it will make mistakes.
> As a professional...why not do this?

I would love to but openai’s privacy policies makes it a huge ethics, privacy, and security breach. I’m interested in running Facebook’s model just as a workaround to this fundamental issue.
I’m getting at the fact that “art” isn’t a major cost for the most valuable companies in the world. Software development labor is an enormous cost.

There is no financial incentive to replace paid artists. There is an enormous financial incentive to reduce software development headcount.
The problems are all labeled with a difficulty.
Wind will never meet all of America's energy needs.
I'd like to know how it can support 32k when all the other models I've seen are 2-4k, does this mean it's got a bigger layer for attention or it's 4x billions of parameters Large?
I for one enjoy supercars and foreign women
Was there a tech-hiring bubble? Job postings data suggest so