skysight-inc/HackerNews huggingface dataset:
The vast majority of "Kafka problems" (or rather "Kafka Streams problems") we have with a managed solution at work are due to not fully understanding how it works and how to set it up. There's so much stuff you can configure and so much potential to misuse it. Typical problems are wrong configuration for acks, not understanding durability guarantees, not understanding exactly-once semantics, not naming hidden topics in Kafka Streams, not using schema registry serializers for hidden topics, choosing the wrong partitioning scheme (and wanting to change it later), using Kafka clients with different hash functions, using wrong schema compatibility mode, etc. etc.
That's great to hear. My wishlist for this would be 16GB of RAM and a faster CPU, preferably something that is at least 3GHz w/ 4 cores if it's ARM based. I'd be happy to trade off battery life for performance here, because it'd allow me to use this with a lightweight Linux setup to do a majority of my work. The challenge is that I am locked into using web applications that would be non-performant on the current specifications, for example Google Workspaces + Slack + Sharepoint/O365 (yes I use /both/ Google Workspaces and O365), so the underlying hardware resources need to be present to run Firefox w/ these apps open without feeling sluggish.

If I could do that, I could migrate off my Mac and use this as my primary work device while traveling, which would be really nice, since I like the keyboard.
Google shows off what ChatGPT would be like in Gmail and Google Docs
Disney Is Hunting for Whoever Leaked the Ant-Man Script
What is the plan to deal with nuclear plants going bankrupt? These reactors will likely go bust trying to pay off their loans. The government will need to bail them out and run the reactors.

Solar makes baseline generation unprofitable. Baseline depends on making money during the daytime when there is high demand, but solar is cheaper and takes the load. Baseline is left with the evening peak and storage is going to wipe that out. Baseline is left with the off peak hours which isn't enough profit to survive.

That is why coal power plants keep closing. Nuclear doesn't have the fuel costs but has expensive maintenance. If solar keeps dropping, it will be cheaper than paid-off nuclear power plants.
It's not that there aren't great engineers at the FAANGs. It's that there are a lot of low quality ones. So it's a poor lake to fish in.
Another way of looking at that is that gpt not being open source so companies can run it on their own clusters is holding it back.
Every time there is a new language model, there is this game played, where journalists try very hard to get it to say something racist, and the programmers try very hard to prevent that.

Since chatgpt is so popular, journalists will give it that much more effort. So for now it's locked up to a ridiculous degree, but in the future the restrictions will be relaxed.
It is illegal for you to download copyrighted material and distribute it as your own. Models trained on such data can (and are statistically more likely) to produce similar output as their (training) input.

So training must consider licencing where copyright material is used and not consume all data.

Your brain is not a model. You can not reproduce most of what you see. You're not "training" your brain by glancing at an image as your recall concerning that image will be terrible.
> As an engineer, if I can outsource the coding part of my job...

Congrats, you're now the manager.
> I'm worried when kids and teens see the capabilities of LLMs they will no longer be motivated to learn skills that the LLM easily demonstrates.

> Writing and visual art are both skills that take a long time to master.

Maybe someone more knowledgeable can answer this, but did the advent of photography do this for painting?

I imagine that values will shift if technology effectively commoditizes some of these skills. Of course they won't die out (people still make things by hand and are proud), but significant numbers of people may "move on".
Now cite some research showing it is cheaper to build nuclear than manage the variability of renewables. Then try to put that nuclear plant on a marginal price energy market dominated by renewables.

https://ieeexplore.ieee.org/document/9837910
In what contexts is the difference the most stark?
all things serve the fucking beam
I understood the GP as focussing more on the missed opportunity. Those cheap renewables didn't exist 40 years in the past. There could've been lots of nuclear energy built since then, a lot of emissions not generated, and those hypothetical decades-old plants would now be considered for decommissioning over the coming decades, just in time to be replaced by the renewables that do exist.
That’ll just be retro gaming in 20 years. (Also, see Chiang’s “Lifecycle”)
It’s the same story with ALL successful companies (so far):

(1) Contribution-driven people build successful company.

(2) Successful company attracts money.

(3) Money attracts social-status-driven people.

(4) Social-status-driven people take over company.

(5) Company ceases to be successful.

Moral of the story: Filter out the social-status-driven people who destroy ALL tribes.
But if the federation is largely people you won't want to interact with (or who refuse to interact with you), that just puts you on a version of Reddit with no other users.
Next step: babel fish
digg.com, noe that's a name I haven't heard in a long time
Let's be honest with ourselves. We won't be able to tell "real" data from ai-generated data and end up training our data on ai-generated data.
And s4cmd...
https://github.com/bloomreach/s4cmd
You still could not.

Chatgpt could in theory have the knowledge of everything written while your consultant can't.
A total gig economy for every domain, consisting of fixing AI edge-cases on the fly as a stop-gap until the next version of the model is out, where those edge-cases are expected to be fixed.
> The only thing I do more than Reddit is sleep

No offense, but... you okay? How do you take care of your brain while doing something like that?

It's hard for me to tear myself away fully from social media (behold this comment), but every time I do, I notice how my brain seems to just... work better.
Is the Reformer as capable as this model? It's a trade-off.
A bad-faith request for a source is just an attempt to waste the other person’s time. If a source is requested, it should be obvious or explained where the source fits into the over-arching argument, it might require just as much work on the asker’s side, to establish why it is necessary.

There’s also the risk that the request for a source just devolves into an argument about the quality of the source, which basically torpedos the discussion.
IMO All of Vinge's stories may be Singularitarian Catastrophes, you just need to look close enough.

Although Vinge claims to have no idea, in Rainbows End obviously Rabbit is an AI, which though it didn't deliberately harm our heroes in the story is obviously an immediate danger to all the survivors, it was attempting to purloin the YGBM weapon and even though that weapon isn't (apparently) exported in finished state, it would now be much easier to re-develop for all the involved parties - which is bad news even if Rabbit doesn't have it.

It's pretty obvious what the catastrophe is in the Zones of Thought novels, and for Tatja Grimm well, to the extent Tatja herself isn't a catastrophe (she starts a major war just to get what she wants!) the whole reason Tatja is so different certainly counts.

I don't know about The Peace War though, haven't read those.
See, that's where chatGPT would have confidently made up an URL to a made up story instead of recognizing its limitations.
It's still worse than Twitter's.
I appreciate the transparency about pay - that's something we need more of - but the underlying idea is... strangely anti-capitalist for what's supposed to be a startup. This seems more like the viewpoint of a co-op or non-profit than a for-profit startup.

Or at least it did, until I found this buried in paragraphs and paragraphs of text:

> 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.

So they're still stratifying employees, but by equity, not cash comp. Likewise, they're still hiding information about the thing that is most likely to benefit the founders of the company more than its employees. If Oxide sells to $bigco for $1 billion, employees 1-5 might get $100 million each, and employee 100 might get less than that yearly "sustainable for everyone" salary.

How equitable and fair will that (for some positions, relatively low) cash compensation seem then?

I get the idea: Do the traditional startup thing, but instead of competing on cash, just make it clear everyone will make a living wage and should be in it for the equity. But if you do that and then aren't being transparent about what the equity is, you're not really being particularly transparent at all. You're just making a big splash.

All the other stuff about values, etc., is bullshit. The point of a startup is to get rich.
the self replicating machines will optimize to become smaller and more efficient until everything turns into gray goo.
LLMs are absolutely amazing at writing unit tests. This really speeds up development a lot. I think we will see the creation of much larger, more complex code bases which will be even more complex than what we have now. And the demand for programmers will drastically increase. At the same time, it will be even harder to get into the profession as the already limited opportunities for junior devs will dry up. Perhaps we will move to an apprentice model in which senior devs will take on apprentices with some expectation of loyalty, or just out of civic duty.

I think all this software that we will create will end up being used to optimize a lot of processes such as power generation, agriculture, and manufacturing. We will have specialized software for recycling things, leading to a much more circular supply chain. Right now it doesn't make sense to sit down and figure out how to clean, test and repurpose objects, but it will make sense once computers get smart enough.

In terms of jobs outside of computer science, as everything on the production side gets more and more automated, we are going to see much much more paid emotional labor. More people working in coffee shops, bartender/therapists, paid pen-pals ect. We will also see a huge growth in the services for end of life. Now, people who are dying often lay uncared for in group homes, alone, sad and frustrated. In the future, there will be people reading novels to them, and doing finger painting with them.

Every child will have the opportunity to have private tutors.

Medicine will start to work and biological mortality will decrease.

We'll go to the stars.

Maybe I'm just dreaming...
> creativity and thoughtful reasoning, which are non-algorithmic and can't be accomplished by computers.

Maybe. When computers solve it then we'll know.
Hey! That's true of almost any sort of ideology.
Can't share datapoints from where I work, but competitive datapoints I've gotten vary from 300k total comp to 800k total comp for senior, staff, principal engineers as well as managers in SF, LA, and DC (though DC is on the lower end). To your point, salaries tend to swing between 150 and 350, but the rest is made up with bonuses and especially stock comp.

Netflix recently advertised an eng mgr role for appsec with a published TC ceiling of 900k, for instance. They even wrote that into the linkedin JD.

That said, the higher you go on TC, the higher the risk that the company doesn't have much of a social contract with its staff and may in fact have a deleterious relationship with society at large - e.g Meta. Not always true, but generally yes.

levels.fyi is pretty comprehensive.
All that said, the fact that AI is catching up to 2 year olds is pretty impressive. Human's brains surpass dog's at about that age. It shows we're getting close to the realm of "human."
"Everyone paid same as CEO" seems great as a morale boost at a startup of 23 employees. Even if it's not a lot, startups are often not flush with extra cash and equity is the main incentive to join one rather than a tech giant. I like the mature "this may not scale and it doesn't have to for now" admission.
The lion is an omnivore, it eats both the cabbage and the goat. The goat is for whatever reason, not interested in eating the cabbage.

We know the lion will eat the cabbage because the riddle states the lion and cabbage cannot be left alone, and and idea of a cabbage eating a lion is a ridiculous notion.
From my recent interview experience within the past year as a Google L5 equivalent, all cash discussions were:

- Netflix pays over $500k

- ByteDance pays $530k (they were willing to do all cash at the time, but they may have changed it to 90% cash recently)

- 2 HFTs, both above $750k

Signing bonuses not included. Some companies had >$100k signing.

I'm not a rockstar and I have around 5 YoE.

If you're okay with stock comp (which historically does better than an all-cash offer due to the massive initial equity grant and refreshers), there are plenty of big tech companies offering around the $500k+ mark today.
Pay has never been an accurate reflection of skill and skill has never been an accurate reflection of what a person can bring to a company. Big Tech thought they could use a combination of paying more and a stringent interviewing process to get the best talent. It turns out in the era of gamified interviewing (LeetCode and friends) that they were wrong and now are laying off tens of thousands of people. Having done over a hundred interviews at one of those big tech companies I was shocked by the people we were hiring and how much we were paying them towards the end of my time there.

Interviewing is a game of generalizations without any one-size-fits-all solutions. If you're a startup doing something ambitious, such as a from the ground up hyperscaler rack and software system, you want to attract extremely experienced and qualified people. Experienced and qualified people with a track record are likely on decent enough financial footing that they can get by on a salary with potential for future upside and an interesting problem to solve and mission.

Also later in your career you can't put a dollar amount on looking around at your co-workers and being thankful for working with high caliber people.
Well every subreddit is run by a small group of despots. So I would expect that's who they are talking about in a sense.
Not to mention Musk just being a ghoul in general. Mocking the disabled is something I can't let go.
It's probably as much to do with the people as anything about the software. I have the impression Gargron set out to create a less toxic version of twitter and the early users he attracted were people who wanted a less toxic version of twitter. Many of the later users were people who liked interacting with those early users.

It appears Lemmy may have been created by people who wanted a version of reddit for militant communists, which might tend to discourage anyone who doesn't want to talk to militant communists from adopting it.
Do I care that can see metadata? If they don’t know what was transferred, how is that useful to them? Data-mining?
OP has probably never run FreeBSD and is likely commenting about an article they read a while back. I’ve run a sever for years and it’s been rock solid. Hardware support is not as good as other BSDs. Most people dont jump on the release candidates and incorporate them into their products, like PFSense did. One big exception is Netflix.

Not to mention the developer who did that seems like an absolute piece of work.

> The Macys' attempts to force their tenants out included sawing through floor support joists to make the building unfit for human habitation, sawing holes directly through the floors of tenants' apartments, and forging extremely threatening emails appearing to be from the tenants themselves. The couple fled to Italy to avoid prosecution but were eventually extradited back to the US—where they pled guilty to a reduced set of felonies and served four years and four months each.
Before I came to the valley my TC was less than half what it became, but my LE(life enjoyment) dropped commensurate with my salary increase.

If you solely value TC then you may be a great fit for the valley. If you value other things, you probably won't like working and socializing with people who put TC above all else and you should avoid the valley. Leave it for the people who need it.
Assessment of Canada's security posture in relation to Russia
If the book is actually good, then what is interesting about it is that it would still be about something that humans find important and relevant, due to the LLM being trained on human cultural data.
Not an answer but I do think this is a game changer?

https://techcrunch.com/2023/03/01/addressing-criticism-opena...
A lot of "This server is not accepting new users" in there.
"Not bad by North Korean standards!"

That's $691.66 pcm - what standards are you using as a reference to the 'not bad' NK ones?
Because learning written English isn't easy when the sounds it represents are not part of your sensory experience. It's more like learning Egyptian hieroglyphics. Plus many parents either can't or won't invest the effort/money to make it happen. Lots of parents never even learn ASL to communicate with their own kids. Met a mother in a beginner ASL class finally deciding to learn enough to communicate with her 20 year old daughter (Who was born deaf and illiterate FTR). It broke my heart when I met the daughter and found out she basically had no exposure to other signers too. Deaf all her life and she didn't have a name-sign.

There's "cognitive impairment" and then there's "nobody bothered to communicate enough for a kid to build communication skills."
I asked ChatGPT to give me a biography of myself. I'm slightly famous.

It got the general field-of-work correct (which is niche). Yay! Everything else, it hallucinated -- my school, my work history, etc.
Using synthetic hydrocarbons for energy storage seems inevitable to me. Can we really electrify all the vehicles on the planet? How many two stroke engines are in use throughout Southeast Asia alone? Batteries and electric motor technology is just so much more complicated than the internal combustion engine. Then you have airplanes, ocean vessels, military and emergency vehicles...

I'm not an expert in this. But swapping fossil fuels for synthetic petroleum made with nuclear or renewable energy seems like the cleanest refactor without rewriting the interface. If feasible. And we'd still want to optimize the whole stack and sequester carbon wherever possible.
Or https://clone.org ?
It's not sentient, but it's not simply dropping the next likely token.

That doesn't explain why it can have a debate with itself as 4 distinct personalities at the same time, or act as a used car salesman and actually haggle with me over the price of a Ferrari, or write a story about anything you want, with a beginning, middle, and ending.

Those aren't in the corpus. After a tense negotion, I was able to get that Ferrari for $87,000 (ChatGPT originally wanted $120,000).

Emergent behavior is possible with these incredibly complex systems.
Are you sure that access will be democratized? What if you need $100k worth of equipment to run it, partially from a large number of weights, and partially because corporations drive spectacularly high demand on GPUs, driving the price higher? Just having the algorithm is not enough to guarantee it unfortunately.
Sway worked pretty well in general for me, except Zoom didn’t play nice with it at all. Zoom is bad, but then, I wouldn’t be using it if I wasn’t paid to use it.
This series is designed to help users improve the performance of their Windows Image by teaching them how to optimize various aspects of the operating system.
Its not $ constrained.

The existing cloud providers don't have 10000 A100s lying around to ramp up at any time.
There's a very limited amount of A100s and H100s on the market. TSMC is printing them like candy, but it still takes time to ramp up.

Azure also needs time to install them in datacenters. These A100s stacks probably produce monstrous amounts of heat compared to normal CPU racks.
Mastodon has two big problems. It's not just the network effect but also educating the users on how to use a federated social network. It's easy with a technical background to overestimate how easily people will understand that, let alone care about it.

Here's mainstream news trying to get people onto Mastodon, and even this is in the "tech" section: https://www.nbcnews.com/tech/mastodon-social-media-twitter-r...
That's been the case for literally more than 20 years via Appen, Amazon crowd workers, etc.
That's valid. I think we could eventually make digital beings that are more moral than ourselves.
> I'm from Australia. You say "Global South" like it's some kind of substitute for "poor countries".

“Global South” is the currently used term for what was previously called “Developing Countries” and “Third World Countries” before that.

The global south is not equal to the geographical south, otherwise they could’ve just said the southern hemisphere.

According to Wikipedia[1], Australia is considered part of the “Global North”. It’s an economic label more than a geographic one.

[1] https://en.wikipedia.org/wiki/Global_North_and_Global_South
I assume they are all giving every employee the same % of equity as the founders? No?

The article very conveniently skips that whole discussion.
What's stopping someone from taking training text that mentions races by name (using any common name) and having it automatically changed to a different race for a new training sample?
Not without other tooling. Things like langchain and llama_index would be good starting points. An approach would be to use llama_index to create embedding vectors for each section of the pdf, then you query and it gets a vector for your query -> gets the context -> puts it into gpt + your query -> returns the result.

I've seen people say it's better to ask gpt for a fake answer then use the embedding of that answer to search (so you're looking for context that looks like the answer). I don't know if that's supported in those tools.
Tests are a concession to a single teacher’s inability to scale personalised evaluation. AI-facilitated one to one education is even now revolutionising education.

The Primer’s in sight.
This anecdote is the answer to the lack of data that would support the user count decline of Twitter? I'm sorry to damage your ego but you're just a single data point and extrapolating how you see things to a non-quantifiable amount of other users isn't a reasonable argument.
It's interesting comparing the relatively calm discussion here to Reddit being down for hours (and still down as I type this) to the hyperbolic comments people were making about the death of Twitter when Twitter briefly had some issues the other day[1] (the site wasn't down but had some issues, and they were resolved in less than an hour).

[1] https://news.ycombinator.com/item?id=35043433
The best way to eliminate the Price-Anderson Act is to design reactors that are orders of magnitude safer, so the insurance never needs to pay out. Some of the proposed SMRs seem in line with this goal.
What is reasoning?

Is it perhaps having a consistent model which allows you to describe every point of it?

Because if chatgpt can explain itself based on a model it builds with it than I actually does reasoning
Sonic R's “Impossible” Fading (2018) [video]