skysight-inc/HackerNews huggingface dataset:
New use case for Memojis /s
>scaling up LLMs seem to predictability improve performance/accuracy.

Isn't this always the case before hitting diminishing returns?
A poor person in the U.S. more likely as not does not have proper health insurance, no unemployment benefits to speak of, is highly unlikely to receive disability benefits even when diagnosed with a disability, is subject to a highly prejudiced and often violent police force, must rely on a famously expensive legal system to press civil claims, must content with a social environment that in many places is shaped by easy access to drugs, has no access to government housing, can be fired at will, etc. etc.

Yes, there are many countries where being poor is even worse. But among developed economies (so about a quarter of all countries), it is hard to come up with a worse place for being poor than the U.S.
Nice. Are you a professional AI researcher?
Microsoft GitHub Copilot X might do better than GPT-4 Bing Chat regarding coding. I'm still on their waiting list for that but it looks promising.
I should add that, in my brief searching, to learn more about my own question, I stumbled on this. It seems much akin to the very cool rEFInd bootloader:

https://docs.zfsbootmenu.org/en/latest/
How does that explain the popularity of Tesla as a brand?
On the other hand, who doesn't have an Amazon account these days? Selling to a local independent store (especially these days when Safeway/Albertsons/Ralphs /Whole Foods dominates the landscape) means actually finding unscrupulous market owners and convincing them to take your product. And it's not like they have a warehouse to hold $200k worth of cereal either. Meanwhile, all you need to participate in FBA is an identity that hasn't been banned yet.

The other thing is though, this isn't jewelry and cocaine, it's cereal and baby formula. They could just, y'know, give it away. It isn't always about the money, especially if you're poor, and if you're poor, you know other poor people, and everyone can use a little bit of help. With food prices up, giving away a lot of free cereal makes you a lot of friends. Not as much as free cocaine does, maybe, but people still appreciate what you can give them.

Thieves aren't some cartoon villains, they exist among us other humans.
I got to thinking about hiring, and things like looking at code history yesterday. There will be a lot of people who suddenly became prolific Github contributors after December of last year. I myself wrote 2 small-to-medium apps in a day using ChatGPT and added them to Github. I'm wondering if looking at Github history is now perhaps as useless as asking a potential writer for a writing sample.

Another point, the apps that I wrote with GPT-4 were filling gaps in my platform and things that would never have come off the backburner due to the lack of ROI. I wonder how we can accelerate contributions to OSS projects. Knocking out new features, refactorings and technical debt 10x faster. Of course it has to be done with care but -- an army of willing AI contributors...
See the stack overflow answer in my sibling comment - there's a bunch of reasons. One is that the Z80 has a bunch more registers than the 6502, another is that the famed fractional cycle times of the 6502 compared to the z80 are based on highly synthetic benchmarks / cherry picked individual instruction comparisons rather than real world use cases.
I really wonder what led to that, technically.

Back in the day it was really common to speed up renders by building custom direct lighting rigs for illustrations like this. So it may be the result of a workaround to optimize render times, or the result of moving the workaround through the scene to various places and forgetting to move one of the lights in the rig, etc.

Or, changing the cloud materials, or recreating one of the cloud materials in one location, and forgetting to turn off "accept shadows" for example, which is a common toggle to see in 3D rendering software.

It's kind of fun to remember all the different ways you could hack the lighting alone, to say nothing of using procedural textures to trick the eye, various modeling tricks, and so on...
The argument of the Chinese room is the strong claim.

From https://en.wikipedia.org/wiki/Chinese_room#Complete_argument the conclusion of the complete argument is:

> (C1) Programs are neither constitutive of nor sufficient for minds.

> This should follow without controversy from the first three: Programs don't have semantics. Programs have only syntax, and syntax is insufficient for semantics. Every mind has semantics. Therefore no programs are minds.

---

I personally don't agree with it and believe that there is a flaw in:

> (A2) "Minds have mental contents (semantics)."

> Unlike the symbols used by a program, our thoughts have meaning: they represent things and we know what it is they represent.

While a person may know what they are thinking, examining the mind from the outside it isn't possible to know what the mind is thinking. I would contend that from the outside of a mind looking at the firings of neurons in a brain it is equally indecipherable to the connections of a neural net.

The only claim that "we know what it is they represent" is done from the privileged position of inside the mind.

I would argue that intelligence is more related to the Kolmogorov complexity exhibited by something.

( David Dowe: Minimum Message Length, Solomonoff-Kolmogorov complexity, intelligence, deep learning... https://youtu.be/jY_FuQbEtVM?t=886 )

That the model of GPT is much smaller than its input.

The Chinese room lookup table is enormously large.

If we attempt to relegate GPT as no better than a Chinese room, we can show that the Chinese room look up table is impossible with the amount of data that GPT has access to as part of its model.

If we say that its not a lookup table but instead an enormously complex interplay of inputs and variables, then the distinction between the room that GPT exists in and our own mind breaks down trying to distinguish which is which.

If we want to switch to consciousness, then possibly the argument can progress from there because GPT doesn't have any state once it is run (ChatGPT maintains state by feeding its output back into itself and then summarizing it when it runs out of space). However, in doing this we've separated consciousness and intelligence which means that the Chinese room shouldn't be applied as an intelligence test but rather a consciousness test.

Are GPT 3 and 4 conscious? I'll certainly agree that's a "no". Will some future GPT be conscious and if so, how do we test for it? For that matter, how do we test for consciousness for another entity that we're conversing with (and its not just Homer with a drinking bird tapping 'suggested replies' in Teams ( https://support.microsoft.com/en-gb/office/use-suggested-rep... ))?
the "derivative work of linux kernel" argument really doesn't hold for ZFS, regardless of what the linux kernel developers state

it was originally written for Solaris

and today the same source tree works on FreeBSD and illumos, equally as well as it runs on Linux
> If I define a word I have never seen before using deductive logic according to the passage I find it in

uhuh. And have you studied anything in the area of the intelligence of really-existing systems? (ie., animals)

For sure, bugs bunny appears witty; and chatgpt, intelligent.

But you know: only because their writers are.
Title is technically accurate, but kind of weird. Investors are pulling money out of some (smaller) banks and transferring them to other banks. Or are pulling money out of savings/checking accounts and adding them to money market accounts with different risk profiles. The title implies the banking sector is at risk, but that's not what's happening - the big banks are getting bigger.
For 20k+ users they probably give you more insider info. Did you ask if SLE and Leap are going to continue to be made? Or did you go directly for ALP or MicroOS?
>arrow keys

sane people will just use hjkl even on readline with ~/.inputrc and 'set -o vi' in ksh.
You are obviously on the east coast.

From the bay area, there is nowhere you might want to go that a train would make less stressful.

Want to go to LA? That's 1 hour in the air for around 100 bucks.
Or it's a 10 hour ordeal involving transfers between coach bus and train in more than one location. All for the low price of 60 dollars.

Want to go to New York? That's 6 hours by air or 80+ hours by rail. Where realistically you are going to book a roomette ($$$) and not just sit in coach for 3 days straight.
There are a ton of nonwhite people in the defense sector. Just as there are a ton of non-white US citizens.
You interpreted it the wrong way. You gain concurrency, you gain latency.

With blocking I/O and parallelism you have a thread ready to go when the operation is complete. You have N threads for N iops. With concurrency you have to dequeue completed work, and then delegate that work to (usually) fewer than N threads. Dequeuing completed iops takes time (it's an extra syscall), and there may not be a thread ready hand the completed iop. More latency.

Running 1000s of threads isn't realistic because your OS would typically grind to a halt, so concurrency is unavoidable. It does have a cost, though.
The quote isn't talking about physical distance. It's talking about "close" in the sense of progress. You haven't made any progress towards walking on the moon even if the pile of chairs is as big as Mount Everest. There isn't just the question of toppling either, the chairs would start physically crushing each other and then they are no longer chairs.
Last time I played with getting a moderately complex old (Jaguar/Panther/Tiger era) Obj-C/Cocoa OS X app building on modern macOS, fixing the build-stopper errors didn't take too long but there was a mountain of deprecation warnings, despite everything seemingly working as expected.

That was a few years ago though so I wouldn't be surprised if some of those deprecations have turned to errors in the meantime.
> As the much villified theme for star trek enterprise says "its been a long road getting from there to here"

Off topic, but I actually really like Russell Watson's 'Faith of the Heart'. I mean, how can you not?! https://www.youtube.com/watch?v=M6bumUQwQIU
Reality Distortion Field :)
> Sadly I stopped paying attention to that conflict when I learned there is an elephant in the room that no one seems to notice

Are you American by any chance? Believe me, this elephant is noticed, was talked about daily by every European country almost every day of the past year, and is being acted upon all the time. What do you imagine the alternative is?
By that standard, how do you know another human being understands anything? All you see is their behaviour. You don't have access to their internals, you don't really know what "process" is going on in there. This road leads to solipsism.
Referring to the private property of the king?
Did you try asking GPT-4? It has a significantly higher IQ.
> My wife works in PICU and she has never seen so many suicide attempts in all her career (going back to 2006) as she has in past few years.

Social media has been around a lot longer than the last few years. (In fact, while they weren’t even the first wave of widely-used-by-young-people social media, both Twitter and Facebook opened to the public in 2006.)

There have been a few major events that have occurred in the last few years, though, that aren’t social media that might relate to the effect under consideration.
Yeah because the Mountain Meadows Massacre 19 years later wasn't an us vs them mentality or anything
While we're obviously seeing more widespread distribution of footage of the worst incidents via social media, isn't it likely that policing has actually improved over the last couple of decades, as the genuinely bad cops are increasingly likely to be caught on camera now that there's hundreds of millions of smartphones, dashcams, bodycams, CCTV cameras, etc out there?
The entire argument here rests on a supposition in the middle: "because if GPT is just a Chinese room it shouldn’t be able to do this."

"Shouldn't". According to whom? Where is the source? I would posit it should and clearly can do that while still being a "Chinese room", and this entire post's premise is obliterated. Oof.
But, you are. We all are, I am too.

There are emergent behaviors and properties that make us more important than simply the sum of our chemistry - at least I hope.

But what if LLMs, could there be emergent behavior there that makes it more than simply the sum of its code?
> As an example, we're not far from some arguing against the existence of a great many people because an AI can objectively do their jobs better.

We are already here.

The problem is that everyone seems to take capitalism as the default state of the world, we don't live to live, we live to create and our value in society is dependent on our capacity to produce value to the ruling class.

People want to limit machines that can enable us to live to experience, to create, to love and share just so they keep a semblance of power and avoid a conflict with the ruling class.

This whole conundrum and complaints have absolutely nothing to do the models' capacity to meet or surpass us, but with fear of losing jobs because we are terrified of standing up to the ruling class.
You missed the part right above it:

> However its hard to see, results are better than my work.
personally I will abandon Linux before I abandon ZFS
I think they are in a position to do that. My bigger concern would be if that is what it is—a mostly VR headset with some AR capabilities, then its killer app will be games. But to appeal to that audience and developers they are going to need to be a bit more receptive to how that industry works. They will probably see some success regardless, as they did with games on iOS, but they would need to embrace a certain openness or at least culture of partnership they haven’t in the past. Closed platforms in gaming only work because they have a significant number of exclusive games—see Nintendo, and to a lesser extent, Sony. If Apple’s answer is that we have the best VR headset but it can’t plug into a PC and also costs 3X everything else it won’t work.

If gaming isn’t the primary use case what is? Nothing in VR/AR I have seen beyond gaming has enough appeal or function to be worth it for more than a few hundred thousand people in a few different industries.
Most minimal kernel configs are extensively tested. I've never had an issue booting from a custom kernel.
...instead of pretend knowing the answer and splitting out nonsense
It would make them worse in the short term, perhaps. But if you were engineering a system from the ground up? Bad design choice IMO. Too easy to drive into the ground a la Zimbabwe.
This is nonsensical lol. But watching the posts shift in real time is very entertaining.
Are you gonna want to get all sweaty in a 3 grand headset?
Still, I don’t see OpenAI having a strategic advantage.

Until today, Google still has a defacto monopoly on search. Their secret sauce made them leader in the space and so far no other company has been able to come up with something better.

ChatGPT does not have any special secret sauce, Google can just build something better. So if I have to bet, long term, I will still bet on Google. That said, it is also not obvious that leadership at Google will be capable of delivering. That’s all different story.
Guess I need an LLM to block ads from the output of other LLMs.
True, until it isn't.

That is, once a device is useful or otherwise desirable enough... Issues like awkwardness or microefficiencies fade.

I think the issue is that there's not enough to do in vr/ar. If we had a vr game of thrones, then everyone would be in vr watching it. If ar made some job much better, everyone doing that job would use one.

The modern platform paradigm means all the speculative, creative investment is on the platform itself. "Creators" make the content. Well... The prizes for creating "content" are mediocre.

A breakthrough filmmaker will have to make the VR's first blockbuster for the art... and so will their financiers. You can raise some money to make ar software, but the unicorn potential is slim compared to a platform play... the big bucks aren't available for such.
>> Many philosophers believed you need to have a strong vision to make the most of your life.

I'd say it's not to make the most of your life, but to make something of it. Having goals or purpose can be separate from the competition for "most". I also find that goals or principles help to make decisions when a course is not clear. Like a tie breaker.
If it stopped making mistakes and produced complete fully working programs, no, there would be no way to say it doesn't understand.

Yes, "understanding" is a process, but it's not well defined. And anyway, if it's a requirement for those things, and the AI did those things, then the only possibility is that the AI has this process in some way.

But well, our current AIs do not produce complete programs, nor fully working ones, nor do they say things without making mistakes. All the people making assumptions about the next generation that will do those things are basically hyping bullshit; and the next generation won't do those things because those AIs don't understand. What doesn't mean that eventually an AI that understands won't appear; of course it will. It just won't be the next generation of those.
I definitely agree with the premise that we should err on the side of too much empathy than not enough. It doesn’t really cost us anything to show empathy to someone or something.

That said, though, the human race as a whole is pretty fucked up. For many years, we enslaved and denigrated each other on the daily. We regularly put dogs and other animals in rings to fight against each other. As a whole, we can do some pretty fucked up things to the things around us as is, and I don’t see that changing with AGI.

If someone can look a dog in the eye, and then put them in a ring to fight to the death, then refusing to show empathy for a robot should, sadly, be second nature to some.
We would see decisions being made that aren't physically possible with current technology. Also the number of people who would need to keep something like this a secret would be on par with that of a fake moon landing.

If their application of the technology were so secret that we couldn't tell it existed, then it wasn't worth whatever they paid.
Arguing over whether it “understands” or not is bad philosophy.

It’s like there’s a magic show and you’re arguing over whether it’s “real magic” or whether there’s “some trick to it.” There are always tricks, but until you know what they are, the mystery is still there and you haven’t solved it.

If God told you “yes it understands” or “no it doesn’t,” what would you have learned? The mystery would still be there. It’s like the Douglas Adams story about the machine that answered 42.

We know the basic architecture of large language models, but hardly anything about how they calculate anything specific. That’s the mystery. It will take research, not casual tinkering.

Screenshots show how it reacted one time, but the output is random, so you need to regenerate a lot to get a sense of the distribution. Such experiments will help, but I suspect really figuring it out will require some good debugging tools.
Universal grammar only speaks to the ability to parse and form sentences, not to internal logic.

That ChatGPT is capable of producing human-like sentences from pattern recognition without any universal grammar baked in, even if the underlying reasoning might be flawed, goes against the argument of something such as universal grammar existing.

At the very least, it shows that a neural net is capable of parsing and producing coherent grammar without any assistance from universal grammar. It does not prove that humans don't have it, but it does make a compelling case that it's clearly not required for humans to have it either.
the approach to RT is basically cramming more and more cores and next to no specialised hardware anyway... so it is a safe path to take regardless what the drivers end up doing with them later

it's all about more cores, faster cores, more VRAM, faster VRAM - I doubt any research achieving any of that will go to waste
Interested in this as well. Also curious how it fares in comparison with BlueSpec and other technologies in this space (like HardCaml).
There’s no evidence regulation would help, and strong evidence the form of regulation being proposed will make things worse, which the article outlines.

Things that could work, that are not known to be harmful:

- Parental education campaigns.

- Elimination of tracking and other privacy invading technologies for all age groups, not just children.

The latter eliminates the need for age blocks, and matches consumer preferences of 90+% of the US population. It also de facto bans technologies that track and encourage mental illness (such as cambridge analytica, and arguably youtube/tiktok content targeting).
For some of those I agree with you, but I think several of those are easy claims to defend.

> strong focus on user experience [...] it will not let you down [...] the user can rely on predictability. [...] offer their users uncompromising release quality

Fair claims in light of OpenSUSE Tumbleweed's extensive testing. It is remarkably stable for a rolling release distro, and furthermore, Tumbleweed comes pre-configured with BTRFS and snapper. That means that if anything does go wrong, rolling it back is trivial. Compared to Debian Sid, I now do much less fiddling and fixing. This is the main reason I use Tumbleweed instead of Sid; I got sick of worrying about breakage every time I updated Sid.

> powerful package management system

Zypper has a SAT solver for dependency resolution, in my experience it works a lot better than apt/yum, which I always found prone to jamming themselves particularly during dist updates. Maybe the situation has changed recently, I haven't kept up with apt/etc developments, but assuming that situation hasn't changed much in the past 10 years I think it is fair to say Zypper is more powerful than most of the competition.

> a high-end enterprise Linux distribution that you can rely on [...] offer their users uncompromising release quality

True, for SUSE Enterprise Linux.

> strong focus on user experience and flexibility [...] with-user-in-mind approach

True: YaST. In this regard SUSE is far ahead of Debian/Fedora/Ubuntu/etc. I believe whatever Mandrake derivatives might still exist have something similar.
It's not that you dream rarely, it's that you rarely remember your dreams. As a general rule, the only times we remember dreams is when we wake up right after (or during) the dream without leaving REM state. For some people this always happens, for others rarely. But you can induce it setting an alarm for a time that you're likely to be in REM state. To find that time, some kind of sleep monitor is helpful. There are also some supplements and medications that have the effect that sleep is lighter in the later stages and it's therefor more likely to wake up during REM. One worth trying is 5-HTP, probably 200mg... this should make you sleep more deeply in early sleep and more lightly when it wears off after a few hours.
GPT-4 will also happily invent python libraries that doesn't exist to enable some functionality in the code it produces.

I don't think this is a Bard only feature.

It's not as bad as the 65B llama model I run on my (amd) PC though, especially with quantized weights it tends to stop coding at some point and repeat the last line over and over. The 30B unquantized model seems better in this particular thing.
Going to have to disagree with you. I tried Hololens 2 extensively and found it pretty bad. Terrible UI/UX, crappy field of view, muted colors, not-great resolution, and just not all that more useful than a VR headset with decent pass-through.