skysight-inc/HackerNews huggingface dataset:
> Also that assumes the scientists are completely accurate and don't make any mistakes. As recently as 5 years ago they discovered that the measured rise for almost all of the 90s was wrong and revised it by 3mm/year +- 1.7mm/year - the error was the same amount as the imputed level of rise!

Citation for this? There are always improvements to our understanding of past data, but you seem to be implying that the uncertainty exceeds the signal. That's simply not the case [1].

[1] — https://www.ipcc.ch/report/ar6/wg1/downloads/report/IPCC_AR6... pp.1291-1292
It was my understanding we were talking about laws making companies want to hire from within at the expense of hiring people from “overseas”.

That is, I was under the impression we were discussing things that happened before the legal immigration process had began.
Uber Engineering Blog
From "Selecting Talent: The Upshot from 85 Years of Research"[1]:

> The upshot of this research is that work sample tests (e.g., seeing if people can actually do key elements of a job -- if a secretary can type or a programmer can write code ), general mental ability (IQ and related tests), and structured interviews had the highest validity of all methods examined (Arun, thanks for the corrections). As Arun also suggests, Schmidt and Hunter point out that three combinations of methods that were the most powerful predictors of job performance were GMA plus a work sample test (in other words, hiring someone smart and seeing if they could do the work), GMA plus an integrity test, and GMA plus a structured interview (but note that unstructured interviews, the way they are usually done, are weaker).

> Note that this information about combinations is probably more important than the pure rank ordering, as it shows what blend of methods works best, but here is also the rank order of the 19 predictors examined, rank ordered by the validity coefficient, an indicator of how strongly the individual method is linked to performance:

> 1. Work sample tests (.54)

> 2. GMA tests ..."General mental ability" (.51)

> 3. Employment interviews -- structured (.51)

> ...

This is a summary of the peer reviewed article "The validity and utility of selection methods in personnel psychology: Practical and theoretical implications of 85 years of research findings."[2]

---

[1] https://bobsutton.typepad.com/my_weblog/2009/10/selecting-ta...

[2] https://psycnet.apa.org/record/1998-10661-006
How is this any different from using other technology, e.g. a calculator or a power tool? Or a manager and the output of their ICs?

Obviously the scope of what's possible is different but _any_ craftsman using _any_ tool will only be as good as what they verify themselves.
I would very much like to see his analysis on which interpretations correlate with high scores. I would guess the more niche ones do, and Copenhagen and Many-Worlds will do the worst.
What is the point of adding a misconception?

The conception of the theorem is that if the signal being sampled is sufficiently integrable AND bandlimited AND the signal is uniformly sampled at at least the Nyquist rate over all time/space THEN then reconstruction of the bandlimited signal is exactly possible using the sinc interpolator. The proof is covered in "Shannon's original proof" in the Wikipedia article and most books on signal analysis such as Gaskill's Linear System book. Most EE people will have to do the proof as an intro course assignment in the first month of a DSP class.

OTOH, if you are not able to sample the function over all space or time AND the function happens to be periodic outside the interval you did sample THEN reconstruction of the bandlimited periodic signal is possible using the Dirchlet kernel.

If you are not able to sample the function overall space (from the first) AND that function is not periodic, you have small problems which occasionally become big problems if you are no careful. Most DSP books have a chapter about windowing discrete data and dealing with this conundrum. Basically, exact reconstruction is not guaranteed and context-specific techniques need to be employed to ensure desirable fidelity.
Yes, we do insist that. If you have a problem with wanting a level playing field, too bad.
There still isn't much of a reason to move away from it, except for those who want to signal their disdain for Musk's political views

This says so much more about you than about anyone leaving Twitter.

I'm a person of colour. Do I have not have a reason to leave a web site that platforms people who espouse the belief that my children are a disease that needs to be eradicated with fire?[1] Of course I do, and you know that. I do not have a "disdain for Musk's political views," to put it like that is to suggest that white supremacy is a view no different than believing in universal healthcare.

Your rhetoric is a shallow and obvious attempt to invalidate and dismiss other people's concerns.

And while you have a right to your beliefs, no matter how much they lack empathy, no matter how much they are divorced from a belief that other people are not NPCs and are truly entitled to their own world views...

This type of talk is not in the best traditions of Hacker News, a site that yes, has a far more Libertarian slant than I personally hold, but also yes, attempts to hold its discussions and debates to a higher standard than you display in this comment.

———

[1] Other people of colour take a different view on whether to use Twitter, and that's the entire point of not dismissing other people's views. They have their own strategies for making the world a better place, and I don't have to dismiss their choices as posturing, I can respectfully make different choices for myself.
We tried that. It reduced the frequency with which it happens, but not as much as we would like.

https://www.science.org/content/article/first-polio-cases-li...
It the college graduates who aren’t the way you describe, those who show initiative and responsibility in their work are the best hires. So not much changes.
Listen to the World (2018)
Audio that went along with the physical issue of the NY Times Magazine, also in digital form. I'm a big fan of audio tours so thought it was a cool format to travel the world.
Haven't read the full paper, but several aspects of this sound less than fully reliable.

It reminds me specifically of 90's multi-client LAN database systems (dBase, Clipper) where clients coordinated via file locks. Unreliability & hangs became a big problem for us.

In the summarized RDMA database, I'd be pretty concerned about reliability & integrity:

1) Crashed servers will leave records locked, and the system will hang.
2) Question whether lock timeouts can be adjudicated reliably.
3) Any errors in server behaviour can easily & widely corrupt data across any other nodes.
4) Overall the RDMA coordination makes me cautious. Can we really replace Paxos with RDMA reliably? If not, problems squeeze out elsewhere.
5) Proposed single-threaded recovery procedure sounds a hazardous operational bottleneck.
6) I'm also cautious about coordination requirements around recovery/ or to transact knowing that recovery is not in process, unless we can show that can be reliable & not add cost to the protocol.
Looking straight into a welding arc doesn't blind you instantly. Eventually, sure.

More rapidly it gives you a lingering after image and feeling like your eyeball is full of sand
This just means this exam can be solved by searching internet and compiling the collections in a presentable format.

For human this is not a easy task because first they need to memorized these information, second, they somehow need to not resort to intensive matrix multiplication in order to say something meaningful.

Even the results from human and chatgpt might look similar but they are very different. This is somewhat similar to comparing finding a interpolation polynomial that is close to sin(x) to just save all the values in the considered interval and do a table lookup.
Parts of Linden are just as close if not closer to OSU than Clintonville.

Linden also has parks and stores just like Clintonville.

And with crime I suggest looking at where the crime happens, it's typically particular to a few main streets/corners.

The neighborhoods themselves are comparable.

You're almost making it sound like if you lived in a home in Linden that you'd expect drive by shootings on the regular or some such shit. That's not the case though shootings and street theft have been happening quite a bit in Clintonville and Short North on High St. Over last few years.

People still move out of Clintonville to smaller school districts because city schools are perceived as bad. Of course a lot of white flight occurred during inner city bussing but whatever.

If better schools, less crime, and allegedly work proximity are the reasons you need to convince yourself why suburbs became popular the first place and not that it is because white people don't want to have black neighbors, suit yourself.
Feds propose cutting Colorado River water to CA, NV and AZ by up to 1/4
> To the best of my knowledge—and I double-checked—this exam has never before been posted on the public Internet, and could not have appeared in GPT-4’s training data.

Sure, but you can Google the answers to most of the questions. Personally I've accepted that GPT does learn and apply concepts present in its training data, and all of this would be. Learning is part of intelligence but not the whole thing. (I thought this was why, decades ago, most of the research in this general area rebranded itself from the ambitious goal of artificial intelligence to the more humble but accessible goal of machine learning.)

The interesting question now is how much better it can get, in difficulty it can tackle, reliability, and quality of explanations. How long before AI can answer questions whose answers are not widely known, for which templates do not already exist?

Personally, I believe this will not be some trivial matter of simply scaling up more. The waters of intelligence are much deeper than that. It's hard to believe given the rapid one two punch of GPT 3.5 and 4, but we are about to stall.

If I'm wrong, mark this comment and make fun of me in five years. Wrong or right, it's going to be interesting!
The Flynn effect covered up the dysgenic trend that has been steady for a long time--probably since 1800 in the West. That effect is played out and we will see a steady reduction from now on, assuming no major social changes.

The Flynn effect itself was likely caused by a combination of nutrition, access to early education, and (simply put) a familiarity with IQ test formats. I never see people mention the latter, but imagine someone from 1932 being presented with an IQ test. The very process (3d shapes, analogies, numbers backwards?) would have been baffling for 100 percent of recipients.
Assuming most cars have similar stopping distances. There would be no rear end collisions if we had instant reaction time to cars stopping in front us. Rear end collision is the most common collision and attributed to follow distances. Standard safe follow distance is 3 seconds. Standard reaction time is 1 second which means at 60mph you travel 88 ft. Most modern cars can stop from 60mph around 150ft.

https://www.qld.gov.au/transport/safety/road-safety/driving-...
That isn't true of this course though. I've read the lecture notes, it really is a great introduction to the subject.
If your interface is text, then an increasingly improving text-based agent eventually wins. The same is true for other interfaces GPT can or theoretically could speak: audio-visual, decision making, generative programming, etc
Citadel CEO Ken Griffin Donates $300M to Harvard University
This isn't necessarily true with LoRAs - a 4090 can train/compute the alpaca dataset with LoRA in under 6 hours (it might be 3, I forget what it was).

So finetuning with LoRAs and a few other methods is fine on higher end consumer hardware like a 4090 and finishes in a reasonable amount of time - IMO definitely worth it if you're experimenting with this especially for the inference.

The base training though yeah I totally agree with you - train in the cloud, don't buy hardware when you need a month of 8x A100's or whatnot.
> I think the BSDs are simpler, change less and are better documented

> Source: I ran OpenBSD on desktops in early 2000s.

From my experience witb BSDs on a SUN pizza box (also around 2000) : FreeBSD had the docs on the internet, not very helpful when you want to configure the network. OpenBSD was ok. Linux (my first choice) was slow as hell.
Auto-darkening welding masks block UV and IR all the time [1] so you're protected against things like arc-eye even if it fails to darken. Also, masks generally fail-safe (to darkened, e.g. for flat batteries) and presumably this welding microscope is designed to the same standard.

[1] https://youtu.be/qMyeVXuElkQ?t=333
Ask HN: How to prepare for AI taking my programming job?
I asked this previously in 2021: https://news.ycombinator.com/item?id=28454642

But obviously some things have changed, so I think it makes sense to ask again.

Personally I am convinced that AI will make it easier and easier to create sufficiently good software without the need of skilled and experienced engineers. It might not be in 5 or 10 years, but I believe it will happen long before my retirement.

To evade the fallout on salary and job opportunities, what are things one can do to prepare? Are there any skills that make one less susceptible to AI replacement? Any fields within engineering (or engineering adjacent) one should get into?
Imagine spending only 30% of your net worth and getting to experiment with buying and growing one of the most used and talked about sites on the internet.

If I spent 30% of my net worth I could buy a condo in the bay, possibly. Although odds are it would be worth close to that if I needed to sell it.

But many people spend 30% of their net worth trying to start businesses with almost no traction.
Musk spent 30% to buy something known internationally.
As long as on average it performs better that should not be an issue.
This is a list of research papers on CRDTs, published on the main open source reference site about CRDTs, curated by Martin Kleppmann, Annette Bieniusa and Marc Shapiro.

That’s about as canonical as you can get.

The papers obviously reference the prior work.

What’s interesting to me is to see how much new work continues to build on CRDTs and push the boundaries of what’s possible for AP, causal and mixed consistency systems.
China makes almost all of the world's EVs, the world's motors and the world's wheels. Putting together any kind of agricultural vehicle is cheaper in China than elsewhere. That's just how it is. How do I know this? I just returned from seven years making robots in China. I will stop short of looking them up and pricing them, but feel free to do so.

AFAIK the Agricultural Bank of China is the largest bank in the world by some measures. It almost certainly has the most branches, and these are overwhelmingly located in agricultural towns and villages. Recall also, in communism sharing equipment is normal. People don't all need to buy their own. Chinese villagers like villagers elsewhere help one another.

Yes, flat areas exist. But they are not the test area, Yunnan. And if you were to look at the historical spread of rice farming (a subject of considerable academic debate) you would notice that all academic suggestions of the earliest invention of rice agriculture itself, with very few exceptions, appear to disperse through or via the test area, because it is the natural headwaters of rivers feeding the majority of mainland East, Southeast and (very close by) South Asia, including the Yangtse, the Pearl River, the Red River, the Mekong, the Salween, the Irrawaddy, and the Brahmaputra. Given we know that in ancient times river valleys formed natural communications paths this give us a fair case for the general dispersion of rice farming technology specifically through steep terrain areas and specifically through the test area.
Of course they did. That ought to be their slogan. "Microsoft: finding a way to make it worse since 1975"
I've been using Coolify on a Hetzner VPS, it works great, it's like an open source Heroku that works through Docker and Compose.
That problem exists in both versions though - i.e. making it more "beautiful" hasn't obviously affected the usability. But I can see at least one way in which it could - if shown on a wide screen and there were a lot of entries, matching up the "Team"/"Member" signifier with the contact name would be quite challenging. The lines in the orginal version may look a little clunky but do serve a purpose.
I think this article is missing the forest for the trees.

The article is about finding the appropriate sensitivity of alerts on some signal in order to maximize the predictive value.

But you should care more about the quality of the signals you are monitoring than about the sensitivity of your thresholds.

The article mentions load-average as an example signal, but to me, that's a poor signal to monitor. Instead, if your SLO is defined for error rate, alert on error rate.

Alerts on your SLO will have a high predictive value for predicting violations of your SLO, by definition. The tunable parameter here is the time window, not the threshold. E.g. if your error budget is defined for a 30d window, you may want alerts at the SLO threshold for 24h and 1h windows.

Alert on causes, not symptoms.
You still don't see many people using long tweets which is good. I used to despise seeing tweet threads starting with [1/20] for years but Twitter integrating their Threader acquisition via "reader mode" which turns multi-tweet threads into a single page like a blog post really helped solved the UI issue with that (blue feature) but I still tend to avoid threads.
Seems like landscape plus someone wearing scarlet has long been cliche :-)
Alert fatigue... it's common when alerts are non-actionable and it causes a lot of downtime.
A calculator or even most power tools have very predictable outputs for a given input. GPT does not.
I had the opposite experience with dwm. I don't like cycling through overlapping windows on the same "desktop", and I don't like taking the time to place windows correctly. With 2 screens, I have 18 "desktops", which is more than enough, and the automatic tiling is exactly what I want. On the other hand when I use GNOME/KDE/Windows I'm always losing lots of time navigating. Also I must have some kind of curse because even with high-end computers I've never had one of those run really smoothly. My current work laptop is on KDE, and when I use a shortcut to open a terminal it takes 200/300ms.

I think it also helps that I've never really tinkered with it. I took someone's build that had a few things I wanted, and I think that's it. In contrast, I spend more time on a regular desktop environment setting up shortcuts.
Elizabeth Holmes to begin 11-year prison sentence at end of month
> It doesn't say anything about whether said sampling rate is sufficient for reconstruction or whatever your intended use is.

Formally, the Shannon-Nyquist theorem states that if you sample a band limited signal at twice its bandwidth, an ideal reconstruction filter can be used to perfectly reconstruct the input signal. There's some wiggle room over ideal sampling/filtering, but the point is that it tells you exactly what the input was, provided it was band limited.

The misconception I think you're having is that band width is not the period of a signal.
> Svelte has it's own, superior, way of doing interactivity. The whole point is to make it easy to generate HTML client side.

I'm not a Svelte user, I am an HTMX fan. It would seem, in my experience, that if the data intended to be presented to the user lives on a server (i.e. in a database, retrieved via API, etc.) then it's not going to be so easy to generate that HTML client-side. Obviously, you have to call the server... why not simply allow it to send you back an HTML segment that's ready to be plugged in as-is, rather than requiring any client-side transformation?
Sounds a lot like one to me. They've got a lot of tagging work and not a huge amount of web development work, so they're asking their least experienced web developer (who keeps labelling himself junior!) to spend time tagging and writing Python scripts because they don't have team members specialised in those tasks, and the nominal manager is far more interested in trying to ensure the company still exists in 12 months than training the self-proclaimed junior.
I tried Edge and bing, God awful. You just feel their desire to take control of your experience of the web.
On the flip site, made me see how much Google own us all.
sounds like me, but I have ADHD :D
Relevant: https://www.youtube.com/watch?v=bOF_3IkjpZU
I see a lot of this style of writing in articles submitted on HN. I think they are just trying to make the writing more lively, not trying to BS.

A trope of this style is “{interesting half story} but more on that later”.

I don’t think it is a big deal and I don’t see much self promotion here other than vanilla blogging, i.e. sounds like this person is knowledgeable let’s check their bio.
Agree, prefer to pay for chatgpt then using Microsoft’s free crapware.
Thanks, I haven't heard of Authelia before, looks like it may work well for my use. I see the OIDC provider support is considered beta, have you had good luck with it being stable and reliable?
The rich donating to the rich
I think you need to get a grip and examine your racist beliefs.
Google drops global vaccine requirement to enter buildings
Not until they overcome the need for the viewer to do something.

Moving from mono sound to stereo doesn't require anything of the listener. Going from black and white to colour doesn't require you wear special equipment.

But 3D? You have to put on special glasses which you also have to remember to charge. Oh, and you can't look at other things while you're using them.

There were some passive 3D displays (the Nintendo 3DS and a few early Android phones) but they required the user to stay in exactly the right position, or the illusion was destroyed. So you couldn't easily share the experience with a friend.

Until we have TVs which can shoot lasers directly into our eyeballs, I think the barrier to entry is too high.
> You should look up global search volumes and Google share of it. There’s no dent.

"You should look up global search volumes and Yahoo's share of it. There’s no dent" was once a valid statement. Same for Altavista, MySpace, etc. You can go from on top to the bottom very fast in this realm.
I don't think the data supports the fear that AI assisted driving is more or newly dangerous when compared to fully human drivers. Teslas are safer than any other car on the road. Yes they’re newer, but by mile they’re safer. So the fear that “we should be careful” is understandable but ultimately unfounded. We are being careful.
Common enough.