skysight-inc/HackerNews huggingface dataset:
* There is no scientific good definition of what intelligence really is, which could allow us to maybe understand what is going on.

* Trained neural networks are black boxes that cannot be summarized or analyzed

* I don't see transcendant research being done between cognition, neuroscience and AI

* The only interesting work I have heard about is a neural mapping of a fly's brain, or an attempt to simulate the brain of a worm or an ant. Nothing beyond that.

* AI is not intelligent, contemporary AI is just "very advanced statistics"

* Language is a door toward human intelligence, but it cannot really explain intelligence as a whole.

* evolution probably plays a big role on what cerebral intelligence is, and humans probably have a very "antropo-centered" view of what intelligence is, which might explain why we disregard how evolution is already intelligence in itself. I just tend to believe that humans are just physically weak primate with an abnormal level of anxiety and depression (which both might be evolution mechanisms).
> for a LOT of people "it talks like me" creates an inescapable impression that "It is thinking

That really does seem to be true - even intelligent, educated people who one might expect to know better will fall for it (Blake Lemoine, famously). I suspect that childhood exposure to ELIZA followed by teenage experimentation with markov chains and syntax tree generators have largely immunized me against this illusion.

Of course the folks raising billions of dollars for AI startups have a vested interest in falling for it as hard as possible, or at least appearing to, and persuading everyone else to follow along.
Those technologies offered actual utility, that's the difference.
I just have a door that automatically opens/closes with sunrise/sunset. My chickens have never been caught outside.

A couple of months ago, I had to replace the roof on their coop and locked the door so they couldn’t get in and get hurt (they are intensely curious whenever anyone is inside their coop). Construction ran into the evening, and the poor birds were visibly (and audibly) upset about not being able to go inside once it got dark.

They’re smarter than people give them credit.
Not all, and they are rarer today, pensions were totally insane back in the day.

One of my mothers friends, who is now in her 80's, has been retired on a pension for over 40 years. She started working for her municipality right out of high school at 18, and worked 25 years as a clerk to get a full pension. Retired at 43(!) with 75% final pay (annually adjusted) and lifelong medical benefits.

Its totally insane and completely unsustainable. Back in the day people usually keeled over at 65 and the US was viewed as having achieved infinite growth forever, so perhaps back then it was a reasonable but generous offer. Today however it's just straight up corruption and waste to offer benefits like that.
15 billion is more than the respective budgets of Alabama, Oklahoma, New Mexico, North Dakota, Iowa, West Virginia, Montana, Wyoming, Alaska, Mississippi, Rhode Island, Arkansas, Delaware, Idaho, Vermont, New Hampshire, and South Dakota. Of these, only North Dakota, Wyoming, Alaska, and Vermont have populations lower than 800,000.
If you missed this recent post, I think you'll appreciate it: https://defragzone.substack.com/p/techs-dumbest-mistake-why-...

> Now, let’s talk about the real winners in all this: the programmers who saw the chaos coming and refused to play along. The ones who didn’t take FAANG jobs but instead went deep into systems programming, AI interpretability, or high-performance computing. These are the people who actually understand technology at a level no AI can replicate.

> And guess what? They’re about to become very expensive. Companies will soon realize that AI can’t replace experienced engineers. But by then, there will be fewer of them. Many will have started their own businesses, some will be deeply entrenched in niche fields, and others will simply be too busy (or too rich) to care about your failing software department.

> Want to hire them back? Hope you have deep pockets and a good amount of luck. The few serious programmers left will charge rates that make executives cry. And even if you do manage to hire them, they won’t stick around to play corporate politics or deal with useless middle managers. They’ll fix your broken systems, invoice you an eye-watering amount, and walk away.
Let me expound so I can be exceptionally clear. I fall firmly in the "billionaires should not exist" bucket. They are a bug in the economic system. Bernie Sanders is my North Star from a policy and nation state social system perspective (its also more financially efficient, but I digress). I do not blame workers for our current fiscal crisis predicament.

Pensions are not stealing from the future. When done properly, invested prudently, and managed to a fiduciary standard, they are an effective mechanism to invest those worker capital earned at that time into productive investments to provide returns in the future when those workers approach retirement. Through the 401k attempt, we have shown this policy to be a failure. The human cannot be relied on to financially prepare for retirement, this must be done with systems and at scale.

When I say "stealing from the future," I mean where pensions were promised and now they're being marketed as "too expensive" when what would've gone into pensions over the last 40 years was vacuumed up by the very wealthy through management compensation and shareholder returns. I mean sovereign debt that has been issued, to be paid back by future workers who in no way consented to having to work to pay that debt back. I mean infrastructure and climate expenses that will rapidly approach $1T/year in costs, because we did not have the will to pay for these things today.

Capitalism stole from the future, and it will never be enough. Someone is going to be left holding the bag, and everyone is going to be unhappy the future is not as bright as the past was.

(i am once again asking you to think in systems)

McKinsey: Dependency and depopulation? Confronting the consequences of a new demographic reality - https://www.mckinsey.com/mgi/our-research/dependency-and-dep... - January 15th, 2025

US Treasury Fiscal Data: What is the national debt? - https://fiscaldata.treasury.gov/americas-finance-guide/natio... ($36.22T as of this comment)

Climate change could erase $1.4 trillion in real estate value - https://www.axios.com/2025/02/03/climate-change-insurance-co... - February 3rd, 2025

Climate crisis costs the world 12% in GDP for every 1°C temperature rise - https://www.weforum.org/stories/2024/06/nature-climate-news-... - September 10th, 2024

HN Search: climate change cost - https://hn.algolia.com/?dateRange=all&page=0&prefix=false&qu...

The cost to fix America’s crumbling infrastructure? Nearly $2.6 trillion, engineers say - https://www.cnn.com/2021/03/30/politics/infrastructure-us-in... - March 30th, 2021

https://news.ycombinator.com/item?id=42052544 (401k failure citations)
And discovered you could disable cache writeback to have a region of fast RAM without bus contention, and ways to use the hidden 9th bit in each byte which is only usd by certain graphics framebuffer operations.

I don't think he uses either one in serious code, but if he did, good luck emulating it.
People can't even afford the cars they finance. Having your own plane is extremely rare. Even if you COULD have your own space craft, they would be more rare than owning a plane.
I basically agree with your edit. There was a lot more fluidity among roles and even just moving into computer roles from other engineering (and even non-engineering) fields. But that's not really what you wrote initially.
The problem with 'more code, quicker and cheaper' is that when you fall behind a baseline of quality it actually ends up costing you and your business, significantly. Companies learned this the hard way during the outsourcing booms, and the usage of AI amplifies this problem 10 fold much like it's doing with spam.
sounds very cool

now that I think about it, LLMs are so useless for the security code. You can't even show an LLM a code which your wrote and ask it to break it, it will reply with something like "hacking is a big no-no around here"

I asked ChatGPT for an ansible playbook to wipe the hard drives with zeros completely (I know the dd command to achieve it, I was just curious what approach would it advise). ChatGPT replied with a firm "no" to this request, I've canceled my subscription after that
I feel like every enterprise ad or marketing site is like this. I have no idea what it does, but it says it'll make numbers go up, so execs buy. It must work to a degree, because it's so common.
I don't know. A cold code review on a codebase they never saw is not super informative about how the candidate would interact with you and the code once they're in known territory.
》under EU regulations, OpenEuroLLM will provide a series of transparent and performant LLMs

What EU relulations? It is a moving target, and nobody knows what exactly apply. It would be nice to provide list of regulations with references. And some testing suite or checklist, to verify AI use actually fits regulations.

Right now, if I integrate spellchecker into my app, I have no idea if I am breaking any AI EU regulations!!!
I hated small talk traditionally. It was very much a learned trait. One of the best conversation openers is “what keeps you busy?” and then ask open ended questions.

Ask about their favorite travel destinations or even what are some interesting things about where they live.

On the other hand, step outside your comfort zone and try something different so you have something to talk about interesting.

https://tynan.com/letstalk/

You didn’t become a software developer overnight. You won’t become a great conversationalist over night either.

“How to Talk to Anyone”

https://www.amazon.com/How-Talk-Anyone-Success-Relationships...

(not an affiliate link)
The increase in productivity means you need fewer inexperienced and/or bad engineers to a project. On the other hand, they may be retained to go after bolder, more numerous targets.
The GP is still passing through hundreds of people, dozens of them capable, until he reaches somebody that convinces him of their competence. You were passed down because you weren't convincing enough.

Or maybe he is getting resumes from a channel that has been victim of machine-gun filling, and there indeed thousands of incompetent people posting resumes into every channel and just half a dozen real applicants.

TBF, I have no idea how to fix either one of those problems. Hiring is just completely broken.
Thanks and great question! There's a ton of eval tools out there but there are only a few that actually focuses on evals. The quality of LLM evaluation depends on the quality of dataset and the quality of metrics, and so tools that are more focused on the platform side of things (observability/tracing) tend to fall short on the ability to do accurate and reliable benchmarking. What tends to happen for those tools are users use them for one-off debugging, but when errors only happen 1% of the time, there is no capability for regression testing.

Since we own the metrics and the algorithms that we've spent the last year iterating on with our users, we balance between giving engineers the ability to customize our metric algorithms and evaluation techniques, while offering the ability for them to bring it to the cloud for their organization when they're ready.

This brings me to the tools that does have their own metrics and evals. Including us, there's only 3 companies out there that does this to a good extent (excuse me for this one), and we're the only one with a self-served platform such that any open-source user can get the benefit of Confident AI as well.

That's not all the difference, because if you were to compare DeepEval's metrics on more nuance details (which I think is very important), we provide the most customizable metrics out there. This includes researched-backed SOTA LLM-as-a-judge G-Eval for any criteria, and the recently released DAG metric that is a decision-based that is virtually deterministic despite being LLM-evaluated. This means as user's use cases get more and more specific, they can stick with our metrics and benefit from DeepEval's ecosystem as well (metric caching, cost tracking, parallelization, integrated with Pytest for CI/CD, Confident AI, etc)

There's so much more, such as generating synthetic data to get started with testing even if you don't have a prepared test set, red-teaming for safety testing (so not just testing for functionality), but I'm going to stop here for now.
To me it seems like your underlying assumptions is "1 worker can only work on one message/item at a time", right?

While you could also use Kafka like that - and it might even work for your use case, as long as you configure option (sorry forgot the name) that makes Kafka redistribute shards because particular workers/consumers are too slow.

AFAIK the usual way is for each worker to get more than one message/item at a time, and do the actual item/work in/through separate thread/work pool (or another async mechanism).

Kafka then keeps track of which messages were picked up by each worker/consumer, and how big is the gap between that and committed offset (marked as done).

It gets a bit more tricky if you:
- can't afford to process some messages/work again (well at extreme end it might actually be a show stopper for using Kafka)
- need to have automatic retry on error/fail, how quickly/slowly you want to retry, how many times to retry...etc.
- can you afford to temporarily "lose" some pending (picked up from Kafka but offset not marked as done) items for random things (worker OOMKILLED, solar flare hit network cable ...)

We've actually solved some of these with simply having another (set of) worker(s) that consume same topic with a delay (imagine cron job that runs every 5 minutes). And doing things in case there's no record of task being done, putting it into same topic again for retry ...etc.
Not a surprising stance if the project is funded by the people who are responsible for said regulatory framework
> I was asked by an SME to code on a whiteboard for an interview (in 2005? I think?). I asked if I could have a computer, they said no. I asked if I would be using a whiteboard during my day-to-day. They said no. I asked why they used whiteboards, they said they were mimicking Google's best practice.

This looks more like a culture fit test than a coding test.
To fill out the quote (from ABC's transcript) "Number one, I have nothing to do, as you know and as she knows better than anyone, I have nothing to do with Project 2025. That's out there. I haven't read it. I don't want to read it, purposely. I'm not going to read it. This was a group of people that got together, they came up with some ideas. I guess some good, some bad."
People are absolutely insane with their takes on AI replacement theory. The complexity of our stacks has grown exponentially since the 70s. Very few people actually comprehend how many layers of indirection, performance, caching, etc. are between their CRUD web app and bare metal these days.

AI is going to increase the rate of complexity 10 fold by spitting out enormous amounts of code. This is where the job market is for developers. Unless you 100% solve the problem of feeding every single third party monitoring tool, logging, compiler output, system stats down to the temperature of RAM, and then make it actually understand how to fix said enormous system (it can't do this even if you did give it the context by the way), then AI will only increase the amount of engineers you need.
i appreciate the optimism that there will be something left to actually have this 'do-over'...
Why would diversity, especially linguistic diversity, be besides the point? Europe is a lot more culturally and linguistically diverse than either the USA or China.

Hier spricht man Deutsch.

A 600 km à l'ouest, on parle français.

50 km na wschód, Polska.

360 χλμ βόρεια, Δανέζικα, Σουηδικά; 250 χλμ νότια, Τσεχία; 750 χλμ νοτιοανατολικά, Ουγγρικά; και τα λοιπά.

Europe has a need, that the other models aren't bothered by — they can do it, but more by happenstance than on purpose.
Introduction to Pipewire
>its become akin to management consulting or investment banking

Not sure how those are similar.
Not only that, but sometimes the municipality hires them back on a consulting basis to get them a paycheck and a pension for the same work.
It's not clear from the article. Are they reducing the staff count so that it naturally averages at at least 15 minutes to get to an agent or are they literally adding a loop in to make people wait even if an agent is available? While longer waits are not great, I guess I could excuse the first way. If they are just sticking people on hold to make they hang up even when the wait time would have been shorter without an artificial hold, that is just bad.
Growing pains. Reviewing carefully is still less work.
There’s got to be a happy medium between using canvas to make the controls you actually want and browser-provided one-size-fits-nobody controls. I really thought MS was onto something with Silverlight’s with XAML but that died.
That's great! Hope you enjoyed it :)
Why are you repeating Kremlin's talking points?

Using the exact same reasoning, Churchill would be a dictator, too.
Don't worry, I would be immensely impressed if they even finish a pretraining run for a competitive model. Let alone get to the stage of doing any kind of fine tuning for any kind of purpose.
Can you provide some insight into the differences as you see them? And where, just in broad brushstrokes, the mismanagement and incompetence primarily manifests itself? At the high level you cite, assuming those are accurate numbers, my knee jerk is to agree with you, but if you have insight would love to know whether the difference is actually attributable to mismanagement/incompetence/corruption/other bad thing.

P.s. Your "about" checks out!
Elon has been operating in bad faith since he came to the US on a student visa and then illegally worked for a startup.
But this time we're dealing with a malicious actor on one's end. And I say malicious, because in all honesty I can't justify someone spewing lies continuously while holding a public charge without being malicious
They also had some search engine announced with similar name like "openeurosearch" or something close to that.

That project too seems dormant lately.

They just announce things and then the train leaves the station.
(1) Do we know if he was applying to these schools as an impacted major? I went to a UC school and computer science (which I'm guessing was his stated major, based on the Google job offer) was an impacted major, and clearly stated as such. It was harder to get in as a CS major than as a bio major.

(2) It's kind of unclear from the article, but is the argument that being hired by Google is evidence that he _should_ have been accepted by those schools? Or is that just an auxiliary detail?
Nice cope from programmers. But reality hits hard.
Stupid. A lot of people using the actual Amazon S3 for production, are also using S3 API with minio for local testing.

minio at least was updated to always emit the header, so it's simply an upgrade away.
What are the real power grabs/most insane things happening now in your opinion?
AI can now write genomes from scratch
Lynx Browser: The Land That Time Revived (2022)
Reality Is Right Here
It was probably about as hard to move between those domains now as it is today. Which is to say that it's pretty hard and needs some concerted, non-trivial effort in shaping your experience and how you present it before trying to make a transition, and often either some kind of inside reference to vouch for you or an employer that was especially hard up for candidates. Or else an employer that straddle multiple domains and actively supported internal transitions.

Depending on what you could bring attention to in your prior experience and the size/needs of the new orgs you seeking to move to, certain transitions were more feasible than others, but you could easily spend decades working in mind-numbing enterprise applications while wishing for opportunities in game development or trading or whatever and never get your resume so much as looked at. (And vice versa, even, for those who dreamed to "retire" into the supposed quiet of enterprise apps or government IT or whatever)
It's worth noting that a lot of shares in publicly traded companies are held by retirement and pension funds.

Money paid to a shareholder is money not paid to the person doing the labor and vice-versa.

That's not to say that pension funds are the sole reason that wages haven't kept up with costs over the last 50-ish years, but it doesn't help, particularly when management/the oligarchs are compensated mainly using the same shares that those retirement and pension funds use to generate revenues for the people they cover.
If you've ever worked on a government contract, you would know there are not and have never been A's on the government side.
You actually can't build a lot of things with AI
Funny I don't even consider hacking on my own car like switching the infotainment system (11 yr old car)
"Absolute power corrupts absolutely."
> im not trying to make it punchy, im trying to clarify my point

Your phrasing requires prior knowledge of the iPhone 16 and iPhone 16 Pro. It's also defining an interval without giving context to whether that interval is meaningful, where on the interval the 16e exists, and if any of the preceding are meaningful. The increased precision comes at the cost of conciseness and clarity.

Apple's, on the other hand, tells me that this is the best battery life an iPhone has had in this form factor. No unnecessary priors being pulled; I just need to know if I like a 6.1" screen.
Probably waiting on the editor to find reviewers. So far the editor couldn’t find reviewers with experience in making an open LLM.
It seems increasingly likely that LLM development will follow the path of self-driving cars. Early on in the self-driving car race, there were many competitors building similar solutions and leaders frequently hyped full self-driving as just around the corner.

However, it turned out to be a very difficult and time-consuming process to move from a mostly-working MVP to a system that was safe across the vast majority of edge cases in the real world. Many competitors gave up because the production system took much longer than expected to build. However, today, a decade or more in to the race, self-driving cars are here.

Yet even for the winners, we can see some major concessions from the original vision: Waymo/Tesla/etc have each strictly limited the contexts you can use self-driving, so it's not a 100% replacement for a human driver in all cases, and the service itself is still very expensive to run and maintain commercially, so it's not necessarily cheaper to get a self-driving car than a human driver. Both limitations seem like to be reduced in the years ahead: the restrictions on where you can use self-driving will gradually relax, and the costs will go down. So it's plausible that fleets of self-driving cars are an everyday part of life for many people in the next decade or two.

If AI development follows this path, we can expect that many vendors will run out of cash before they can actually return their massive capital investment, and a few dedicated players will eventually produce AIs that can handle useful subsets of human thoughtwork in a decade or so, for a substantial fee. Perhaps in two decades we will actually have cost-effective AI employees in the world at large.
New model from WashU scientists can improve understanding of human attention
Eh, it sounded to me like it might be more of a Shelbyville thing.
Your break-even point will be years away, so no, backyard chickens aren’t the answer for high egg prices.

That said, chickens are fun animals, and mine bring me a lot of joy even though I don’t like/eat eggs (the chickens came with my house; I give the eggs away).
I wonder if anyone is applying AI to cobol…