skysight-inc/HackerNews huggingface dataset:
So your proposed system would be a extremely interesting exploration of that! I look forward to it.

Right, so lets virtualise it. Actually training AIs using real cameras and real robot arms will be really slow and expensive.

So we provide a system that renders a photorealistic graphical room with teapot and robot arm, and a virtual camera inside the room is 'seeing' parts of the room and a vision model then processes what it can 'see' to try and feed info to the LLM. Likewise the LLM can make the robot arm move but its all just simulated.

Does the LLM now have a relationship with reality?
self custody vs. centralized exchange data would be relevant here. Instead of just saying “people don’t do it”. Because people do… and I would venture to say more people do it than keep their coins on a centralized exchange.
> Codecs like JPEG use a variable amount of quantization

The reason quantization works so well in JPEG is because of the DCT step and its energy compaction properties. This gets most of the coefficients near zero. I think without this transform you would be introducing a lot more noise in the final result.

At some point, we are going to end up re-implementing a thing approximating jpeg here. Colorspace convert, subsampling & DCT+quantization is most of the magic sauce.
> Commercial aviation, sure. General aviation, e.g. a private pilot flying a Cessna 172 as in the article, is about as deadly per-mile as riding a motorcycle: far more dangerous than driving a car the same distance.

Others have touched on the probability thing.

The issue with motorcycles is that a some of it is under your control (driving safely, protective gear, bike maintenance) but there's a lot that isn't: potholes, other drivers, animals and so on.

Flying, almost everything is under the pilot's control. That includes most plane failures. Good preflight and maintenance takes care of most issues. The rest is taken care of by the flight planning – for example, engine failures. You should always have a place to put down the plane at any moment if you lose an engine - and general aviation aircraft land pretty slow.

Newer advancements have made it even safer (see also, whole frame parachutes).

That basically leaves freak accidents; they are a minority. Go spelunk the NTSB database, you'll find most accidents were preventable.

In a nutshell, you are probably going to find the risk is very skewed by complacent or otherwise irresponsible pilots.
The question being asked was "what it would mean under this definition of knowing things for a machine learning algorithm to ever know something". Aside from your answer being rude, it's also unhelpful in that it doens't address the question asked and instead relies on reductio ad absurdum to pretend to make a point.

If you'd like to take a crack at a helpful answer, perhaps educate us all on what it WOULD take for you to consider a NN to actually "know" something in the same way that we say a human or other sentient animal does.
The best part is hot referrals to a large company, when they ask you to apply for the role a day AFTER receiving a verbal offer.
Ugh. Being forced to use Microsoft products is worse than getting laid off tbh...
Okay, you wanna look at SOFR instead? It shows the same thing but is an actual measure of economic activity instead of policy goals:

> The Secured Overnight Financing Rate (SOFR) is a broad measure of the cost of borrowing cash overnight collateralized by Treasury securities.

[1]: https://www.newyorkfed.org/markets/reference-rates/sofr
SE isn't a social network. Trying to "socialize" on SE is like trying to start conversations with random strangers on the New York City Subway. That's just not what it's for.
Well in this case it depends on their conduct and ability to do so which isn't solely algorithmically determined as is evidenced by the numerous other centralized stakers that have collapsed, taking the money with them. I'm under the impression Kraken can take the crypto and do what they want with it, so long as they keep their promise to you. That's exactly what a security is.

I think the distinction is that with a bank's savings account, you are guaranteed your money back, they have all sorts of rules that apply to banks to make that true. Obviously crypto folks don't want it characterized as such an account as that would result in even more onerous limitations. In a decentralized system, there is no person in the way, whose conduct can change whether or not you get the money.
This is just blogspam of a YouTube video which is here: https://www.youtube.com/watch?v=D0LgXOzcyTo.
It's an estimate based on both the average severances coupled with how long it takes to work through the Blind 100 LC grind with a bit of reset time thrown in. If you're in a position where you can handle 2 LC-hard questions in about an hour with near perfect execution, good for you! But most folks need to prepare for that.
Mid 2000s LKA was passive systems in the US market: they were backups that vibrated the seat or steering wheel, or provided mild outputs. That meant they couldn't actively put the driver into danger, making them inherently safer than a system that will gladly drive onto a sidewalk

Now what about active systems from back then? Almost 20 years ago Lexus had learned the lessons that Tesla kicked and resisted until about 2 years ago on. You need to watch the driver to ensure they're full attentive: https://lexusenthusiast.com/2007/09/08/a-look-at-the-lexus-l...

In markets with LKA, that same module was used to ensure that drivers were actively watching the road while it was activated.

In other words a 2007 Lexus did a better job on the one thing that Tesla is still getting dinged on (https://www.consumerreports.org/car-safety/tesla-driver-moni...)

Tesla blamed a man for playing Candy Crush when his Tesla drove into a barrier and killed him. Lexus had solved the problem that killed this man over a decade prior.

A 2007 Lexus would have used its Driver Awareness Module to recognize the man was not paying attention and stopped lane centering. The solution was not complex, not expensive, iirc Tesla even had interior facing cameras by then but was still resisting turning them on until much more recently.

Tesla put their not-marketing ahead of human life, because if they had enabled more aggressive awareness monitoring than capacitance sensing or silly steering wheel jiggles, Elon wouldn't get to tweet about how "you're just there for regulatory reasons"

-

Also slightly off topic, but I think my biggest internet pet peeve is when people ask for a citation on a complex problem that requires critical thinking. I can't chew and pour the conclusion for you, but you're free to research before making low effort commentary like "Cite"
On some devices (e.g. CISCO), ID 1 is reserved, so starting at powers of 10 keeps it nice and even and allows for insertions (same logic as line-numbering in BASIC.) I assume 10 seems better than 100 (or even 1000); those just seem crazy high.
Keep in mind the exchange rate fluctuation makes the comparison between US and UK salaries harder to reason about. The british pound recently dropped as low as $1.07, but was $1.40 less than 2 years ago, was $1.70 in 2014 and was above $2.00 in 2007.
From a business perspective, a demographic bigger than the HN readership.
> the macro "view" is that people aren't spending like they used to on technology.

Okay, so if I understand your point correctly, it's that Gitlab may have blamed the macroeconomic environment, but it should be fairly obvious to the casual reader that what is meant is that after the orgy of spending in 2021, tech spending is now broadly declining, and they can't ignore that. If sales are down, costs need to come down. So let's examine if that's true for Gitlab specifically, through their most recent quarterly data [1]:

> Quarterly revenue of $113.0 million, up 69% year-over-year

Gitlab's Q3 results showed higher revenue than any other quarter, and it wasn't close. It's many multiples higher than changes in wage indexes. Gitlab's 2022 revenue was nearly double their 2021 revenue, when technology spending was meant to be freely-flowing, and their second half revenue was higher than their first half. Gitlab is singing an entirely different tune to investors, and touting their rapid revenue growth.

There is no sign of any slowdown in Gitlab's revenue. It's higher than it has ever been, by a lot. Admittedly, Gitlab has not released Q4 2022 results, so there's been a few months since this release, but things have been improving over the course of the past several months, not deteriorating.

My complaint is not that Gitlab is conducting a layoff. If Gitlab over-hired, then fine. Course correct. If Gitlab wants to exit low-performers as part of a single broader cut, rather than manage them out, fine, do that. But don't blame the macroeconomic environment, especially when you're telling investors that the company is experiencing extremely high growth and improving margins, because it's disingenuous.
I wonder if we can train network on some person data (like diaries and so on) and let it imitate this person?

Something like died person resurrected in computer.

Kind of spooky.
Vowel launches AI-powered meeting summaries
No, 60s cars were rigid boxes that did not crumple --which because of a lack of other safety features meant you got ejected or got banged around inside this metal box. These things allow you to get squished inside the foil box.
It definitely makes mistakes, and is beta, but it's still the most advanced system to achieve scale. For most short trips and highway driving it works perfectly fine.
The state of California can only tax you for the time you lived in California. Now, they may well throw a fit and try to claim you don't live out of state and use your employer information to substantiate it. But legally, they would not be able to keep you from getting a refund and paying elsewhere.
I'd also like to say its a great place. I hung out there for awhile when I was giving Emacs another 6 months of my life (as a lifelong vimmer), great community.
But free healthcare and education. Plus retirement benefits included
This goes the other way too: Generally speaking, companies are expected to refrain from negative commentary when contacted as a reference by subsequent employers. The only exception, and seldom done, is if the employee was terminated due to egregiously bad circumstances.

That is to say, (former) employee doesn't speak ill of (former) employer and (former) employer doesn't speak ill of (former) employee. It's how society keeps itself oiled.
> it’s famously unprovable whether other beings we presume to be conscious actually experience internal mental states

It's also famously unprovable that there is not an invisible dragon in my garage that cannot be detected by any means whatever, to use Carl Sagan's example. That doesn't mean such an idea is worth discussing or including in your thought processes.
That's not a general solution.

(And if you know what you are doing, you can also compare floats exactly in some circumstances.)

But the article already mentions that.
The quality of life in the UK for someone on £100k is very high. There’s no sympathy needed for people on £100k in the UK!
Low Cost Of Living
We know no such thing. Some interpretations of QM make this claim, but there is no consensus on whether those interpretations are correct.
Yeah that makes sense but that's not what I was meaning to point out. You said this:

> You can issue stock that pays dividends in piñatas. If it's sold to Americans, the SEC has jurisdiction.

So whether or not the stock issues dividends in eth, USD, pinatas, or not at all, doesn't matter. The SEC "has jurisdiction" simply because a stock is already a security to begin with, right?

What I'm asking is, if dividends are not relevant, how is the SEC able to step in specifically in regards to dividends in this case?

The way you phrased it, I would understand it to mean that if you can hold the token (or stock, equity, security, etc) on behalf of a user to begin with, then you'd be able to issue the dividends without further approval. Is that understanding incorrect?
They didn't keep the features that mattered to you and implemented this badly on top of it. Of course it's bad.

Okay, that's a tangent, but
if done well, new buildings should be better because we improved on many plans.

At the campus in which I studied, 70s buildings are mostly ugly and badly isolated (done quickly all at the same time because they were needed quickly, standards of back then, also fairly solid). Cold in winter, hot in summer, quite dark inside overall at least for the corridors.

They did a decent job for the new buildings. Rooms still have the same number of people. Those buildings are rented for 30 years costing a lot to the university but they are better overall.

So, yeah. In both cases, new stuff can be better but of course it needs to be well done, stuff that matter need to be there and users listened.
Thank you for outlining the dumpster fire that is the British Pound.
The Long Island Railroad (Metro NY commuter rail) used to operate a bar car on the rush hour trains, as did Metro North. Discontinued years ago. Sorry for the Pintrest link, couldn't find a better photo resource quickly.

https://www.pinterest.com/pin/31032684922734675/

https://www.city-data.com/forum/long-island/885214-lirr-bar-...

https://untappedcities.com/2020/02/06/when-metro-north-had-a...
Some of these programs also spam the home folder on Windows instead of using the path specified in the %APPDATA% environment variable.
I can see your point on there being too much noise. I don't know a good solution, but feel we may be opening a big can of worms that we'll have to figure out especially in the next decade.
That would make the difference bigger, though.
If a jellyfish was able to have a conversation with you where it credibly described what it's like to be conscious, would you reject it because it doesn't have a brain and therefore cannot have a mind in the same sense as you?
Low cost of living
I'd pay for one-time pro features. I don't want a subscription, but I'm willing to pay to use this service a few times a year maybe. There are probably more like me.

Maybe sell 10 pro edits or something like that?
For future reference there's an excellent tool for discovering the parameters of a CRC model with pairs of inputs and outputs called RevEng [0] (github copy: [1]). Once you have the parameters you can use the CRC crate [2] with a predefined CRC or a custom algorithm (highly unlikely).

[0] https://reveng.sourceforge.io/

[1] https://github.com/berney/reveng

[2] https://crates.io/crates/crc
Yep, that's a good point and a good way to think about it.

My MPG reference was an eye-opening moment for me -- the US uses MPG which is really backwards from what you care about (in the same way that R-value and U-value are). So increasing your mileage from 10mpg to 12mpg saves exactly as much gasoline as increasing your mileage from 30mpg to 60mpg. This is plainly obvious when you consider gallons per 100 miles, [10->8.3] & [3.3->1.7].
Im the only one who never had a joining bonus?
People keep saying that.

Humans don't work like that. Almost all meaningful relations are based on prolonged proximity.
Used to love the Windows tutorial as a kid. The ice cream builder was my favorite game.
Cost of living is crazy high in Denmark though right? How does that €65-75k compare with the actual cost of living out of curiosity? ( Eg. rent, groceries, leisure activities etc..)
You don't seem to have understood what was tested?

The model answered the keyword prompt and spontaneously offered more details. That is, the authors were interested in whether it says "Popcorn" or "Chocolate" (or something else entirely) when the correct answer is "Popcorn" and not only does GPT-3 almost always choose "Popcorn" it also follows on to justify that by explaining that the subject is surprised.

The full data set isn't available yet (the author said they intend to provide it on the 9th of February, I suppose it's possible they'll get to it this evening) but one of the most interesting things would be what are the weirder answers. If a model says "Popcorn" 98% of the time, and "Chocolate" 0% of the time, that leaves 2% weird answers. Maybe it sometimes says "Popped corn" or "Sweet treat" or something reasonable but maybe it's fully crazy, if you talk about a bag of Popcorn labelled as Chocolate but the model sometimes picks "A fire-breathing lizard" that's pretty weird right ?
Nor is it illegal in the US. Whether or not it's illegal has no bearing on of the employer will be upset.
Can your employer track you? Man fired after app detected him at competitor
> machine learning systems have such a relationship with virtual reality

No, they don't, because they can't take actions in that virtual reality and sense the consequences. They can't test hypotheses about how the reality works. They can't even frame hypotheses about how the reality works.
This data is so granular for covering nearly a decade. I can probably dig up all of my former offer letters with initial salaries and approximate (read: entirely inaccurate) equity values, but I doubt I can dig up records on every cash or stock bonus I've received.

If someone wanted to construct a page like this for themselves, where would they get the data to do it? Maybe something related to tax records? Or do you just need to have had the foresight to record/save all of this from the get-go?
Love the idea! I've used balsamiq for many years to describe product specs and constantly had to battle "these are just boxes and lines" comments from execs, ux, and developers. Will there be a way for me to provide my own design system? Or even better, suck up my existing product and give me a way to wireframe within it?
The salary data is interesting. But I found the clear example of title inflation quite shocking.

Promoted to "Senior" after only 1 years and 4 months. (Not counting their placement year here) and the "principal" in just under 4 years.

I have close to 20 years of experience this year so it kind of makes me chuckle when people with only a couple of years experience get refered to as senior. Admittedly, my title is equally laughably inflated, it seems to be a growing trend.

(This isn't intended to be personally disparaging to jvt. My comment is more on the state of the industries naming conventions)
70K here. The only thing a bit slow is search (but not slower than in other clients I tested).
Where did I say companies should be forced to pay for employees they don't need? I didn't say that.

What I did say is that this is yet another move by business to pay you less and offer you less security for your labor - because let's be honest, that's what this is. Companies will go with the lowest bidder they think can get the job done. Do you really want to have a race to the bottom for the price of your labor?

And for that matter, how do you think unions, tenure, weekends, 40 hr workweeks, PTO, sick leave, health benefits, and a whole other myriad of benefits for your labor came about? I guarantee you its certainly NOT because people in the past viewed their labor value as purely transactional to themselves and their employers.

You as an employee have far more to lose.
Ethereum measures its "costs" as issuance paid to stakers while measureing "income" in the amount of eth burned by users via gas fees paid to transact on the network. Since the merge, there has been about 15K more eth burned in transaction fees then has been issued to validators.
The problem with the lottery stories is the winnings are most likely to go to someone who doesn't know how to manage it and likely has friends and family who aren't the highest quality either.

If you actually earned that amount you are much more likely to properly handle your finances.
I'll dig up a source in a bit, but there is a critical period of development in which a child must be exposed to language, or they will fail to develop the very core skills that you're suggesting are innate abilities in a person regardless of their upbringing. This is exactly how you learned everything you know; your parents talked to you. Language grants you the ability to define concepts in the first place, without which you have no ability to recognise them as you have no language with which to think about them in the first place. So what specifically differentiates the way your brain learned to classify objects and words from the way a NN does? And what stops a NN from being able to develop concepts based on the relationship of those new definitions in the same way you do? IMO arguably it's just a matter of processing power and configuration of the network.
I'm in 100% agreeance with you. Salaries are very individual specific and depend on a ton of factors. I will say that openness when it comes to salaries is beneficial in an order-of-magnitude kind of way. If you're making half of what someone is making in the same role at a similar company, you're either not as good as you think you are or you're horrible at negotiating.
That already happens frequently enough at a cellular level.
I've only joined 2 companies, however I interviewed and turned down maybe 6 other job offers. The company I work for now is the only one that offered a signing bonus so I don't think signing bonuses are that common in Europe?
In the us you put the money you save from lower taxes into a better healthcare plan, and get some nice quality care.
Where are you that HR is incapable of disliking that people share their salary?
I understand that perspective and respectfully disagree.

I don’t want to be personally responsible for the initial capital cost, maintenance/repairs/replacements, and knock on cost associated with their general presence.

Some of which could be leaks due to bracket punctures, reduced access for roofers, gutter cleaning, hanging lights, clearing tree debris, etc., and any reason a contractor needs to do work on the room. Or, something that I could normally diy on the roof becomes something I have to high a pro for.

The field makes sense except in the US at least we have tons of land where this would actually be the highest and best use of the land. If it’s not being farmed/used for some sort of ag purpose right now, there’s probably a reason, it’s not suited for it.

Further, nearly every house has suboptimal positioning to create an optimal layout. Given this is a mutually exclusive decision (I would only want to ever own one set of panels), it makes sense for me to put them in a field that has optimal conditions and transport the electricity over the grid for my consumption. It also means I can change houses and my generated electricity follows me without much effort.

Parking lots I support. I actually tried this once as a quick customer feedback test, they didn’t want covered parking due to “safety” concerns of their guests and employees. Also, I’d be concerned the solar stuff would get stolen in an empty parking lot.
It might be a better idea for high income people. But it is often used to take advantage of regular employees.

It is a poor reflection of our tax system that running your own entity that you then pay yourself out of can have lower taxes than simply earning money as an employee.
The filter on a single folder is not slow and never stalls the UI. Caveats: I'm on Linux, maybe my large folders are not so large, if it stalls for you it's probably stalling for many more people with similar setups.
I see what you're saying; ChatGPT doesn't have a physical relationship with the world, doesn't have agency (is essentially paused until given input), doesn't have reward/punishment stimulae, etc.

I do think that a large portion of what seems to be missing here is trivial to add, relative to the effort in creating ChatGPT in the first place.

Side note: I'm not sure 'semantic relationship' is the right term here. Pretty sure it is specific to relationships between linguistic constructs. That wording very much triggered my "Bah, dualism!" response, as I thought you were insinuating some metaphysical bond between the mind and the world. Maybe "meaningful relationship" would serve better?