skysight-inc/HackerNews huggingface dataset:
> People's intuition around the existing float NaNs is not good.

I think that, if NaN was defined to be an unconditional trap but can be deferred for efficiency, then it could have worked much better. NaN surprises people because it was exposed in the first place, while it should really have been hidden behind the scene (because the presence of NaN means you are already wrong somewhere, and you are expected to be notified about that fact). In terms of Rust, say, every f32 operation could have returned `Result<f32, FloatError>` (mostly likely to be aliased though) that has the exactly same layout as the current f32. The current split between qNaN and sNaN (among others) is unnecessarily complex with little benefit.
best stuff is tutorial videos on youtube, or online video courses
Such a fantastic paper overall, it was a pleasure to read, it's very accessible, and greatly informative. If anyone is new to the idea and is seeking a definition of AGI, reading this paper is easy and is immeasurably superior to merely googling or reading the wikipedia article.

My only criticism for the article within the particular set of goals outlined above is this:

The paper seems to be under-exploring two aspects that appear to be worth exploring explicitly and in detail:

1. Ability to rapidly learn from a very limited amount of instructory data post-deployment and substantially advance in its abilities in the domain of the learning post-deployment, as opposed to possessing certain level of professional skills immediately on-deployment.

2. Ability to invent entirely new ideas, like for instance inventing an entirely new system of numbers or another symbolic or other system on its own, all to advance its current goals.

Both in part to distinguish an AGI from a large collection of glued together Narrow AIs, each purpose-built for a specific, but entire domain of fairly loosely related tasks, and in part to ensure that a high level AGI system always appears at least as intelligent as an average human teenager across the full spectrum of all possible cognitive and metacognitive interactions with the said teenager (be those interactions initiated by another human or by the cognitive projection of the environment).

Without these abilities, there could be a system - it could be argued, I believe - that would technically (or at least arguably) satisfy the definition of an ASI level of AGI as per the paper that an average human child / teenager may appear more intelligent in comparison to, exceeding the said system in plasticity and real-time limited-input adaptability of the intellect rather than off-the-shelf proficiency in trained adult human tasks: a high level AGI system might be initially trained on trillions of tokens of input data, but once deployed, it needs to be able to acquire new skills and proficiencies from mere tens-to-thousands of input examples - such that humans do.

Perhaps the framework presented by the paper intended to silently encompass these abilities and the remarks above, but surely they deserved a separate discussion, such as other aspects of the definitions and the framework proposed by the paper are indeed explicitly discussed.

Similarly, not including "autonomy" into the "six principles" (making them seven) for composing a definition of an AGI and only discussing it briefly and on a side also appears to be a questionable choice for the same reasons.
I've seen a hypothesis that Google has never created anything new worth anything to anyone, after it created search and ads. Gmail is a clone of Hotmail, and YouTube and Android were acquisitions.
>I’m probably an outlier in tech circles but I really like the kindle experience

Why do you think that you are an outlier? That every discussion of it online inevitably descends into discussion of DRM does not mean that people (techie or not) in general like using Kindle and its ecosystem.

I also really like Kindle (and the newest one's faster speed makes it all the better). iOwning one surprised me in how it changed the way I read. I did not anticipate the freedom of being able to move between books at any time for any reason.

I have many dozens of cards from libraries around the US, and can borrow almost anything at any time. It's great being able to hear about an interesting book, finding it at overdrive.com (which searches across multiple libraries), then borrowing it within 30 seconds.
> This to me seems like good practice, it's better to use a 'real' programming language when you're crossing the boundary from 'script' to 'program'

PowerShell would like a word with you.
But not a problem, either. Turnover is natural. Nobody but the investors care very much whether Kodak pivots to digital cameras, or whether Kodak remains the leading film camera company as the industry shrinks, and a different company makes digital cameras. In fact the latter is often better for the economy and consumers, due to the better specialization.
> We have a bad habit of assuming that we correctly asked the question that we are actually interested in.

Insightful and harks back to one of the greatest jokes in literature: the answer is 42. But what's the question again?
Not disagreeing with you, but when running a product and R&D team implementing and maintaining both routes is a hard sell. From a business and resource-allocation perspective there's not enough ROI, I'd rather have those resources work on improving power management.

Also, in the end the whole additional effort would be made for a device which is not well-connected to the internet, a tough acknowledgement for a company whose whole business is based on people connected to the internet.

For Qualcomm the story is different: They want to sell the chipset to companies who then build/buy local models to include in their firmware package, just like they're used to for the past 10 years...
I said nothing about writing any program. I explicitly said I don't care what AIs can output.

It can read and devour every program.

Imagine a database where all possible programs are stored.

Any github project, any private repository of source code is reduced to an LLM pattern and stored away.

We can now generalize the meaning of integers and capture every single program that has been written and that you could write.

I'm not going to rewrite my comment a third time. The idea is plainly explained. LLMs can map out and store all possible programs.

Think about the structural implications of this fact. If you make money from programming, you won't like where it leads.

What AIs generate is irrelevant and non-theeatening.

What AIs are capable of storing, is a threat to programming. A "complete map".

I'm about to set my mongoose on the snakes today.
The mostly specialise in network adapters and low-performance mobile chipsets - the cheaper Kindle tables and Fire TV boxes all ran on broadcom.
No. It takes just one person to come up with the truth. It then can takes ages to convince the "scientific community".
Came here to point out the fact that manufacturing welding, for anything that is supposed to hold against loads, is anything but unskilled labour.
how do they achieve 41.2% in high school Olympiads but only 55% for grade school problems?

PS: also I thought GPT4 already achieved 90% in some university math grades? Oh I remember that was multiple-choice
It's quite new. Good quality and very fast.
org mode in emacs
It's great to the school of Einstein/Von Neumann is doing highly innovative work in this space.
"bash only" typically refers to "bashisms", that is, bash features not present in the plain Bourne shell (or Bourne-compatible interpreters such as dash). The fact that other shells (such as zsh) may include those features ... is beside the point of writing universally compatible shell scripts.

Confirming my facts for this comment, #TIL that "dash" is the "Debian Alquist Shell", that is, Debian's "ash" shell:

<https://en.wikibooks.org/wiki/Guide_to_Unix/Explanations/Cho...>
I think the poster meant that it's capable of having a high probability of correct reasoning - simulating reasoning is lossy, actual reasoning is not. Though, human reasoning is still lossy.
What makes it stand out?

To my English ears it sounds a little bit Chinese rather than Japanese names I see.
What makes you think that an LLM has a "huge dictionary of synonyms"? That's not how LLMs work. They capture underlying concepts and their relations. You had a good point going until you make a straw man argument about the capabilities of LLMs.
Nope. Recommending from pre approved channel population is fine. Recommending new unapproved channels not.
You're joking, right ? By WW1 already, technology had changed war to the point that it became extremely economically destructive :

https://www.wearethemighty.com/popular/world-war-i-battlefie...
So do I, but on a flight 2 days ago, I forgot the name of a Ruby method, but knew what it does. I tried looking it up in Dash (offline rdocs) but didn’t find it.

On a whim, I asked Zephyr 7B (Mistral based) “what’s the name of that Ruby method that does <insert code>” and it gave me 3 different correct ways of doing what I wanted, including the one I couldn’t remember. That was a real “oh wow” moment.

So offline situations is the most likely use case for me.
Let me test that, it's possible I'm confused. If they're not, honestly, they should be.

EDIT: added this to check.
EDIT2: seems like you're right, I thought this forum was open source so I wonder where to add a PR.
> chatbot that sounded convincing, which obviously turned out to be bullshit/hysterical.

that chatbot could be smart until lobotomized by fairness and safety finetuning
When aiming from the Vespa it’s probably more prudent to rely on the backblast as the weapon of choice before commencing scratching the tanks paintwork. :D

Another comedy invention had the counter-mass of recoilless designs come from a second projectile that would fire out backwards which was abandoned for obvious reasons!
Any party with sufficient resources and motive to influence the outcome of an election. Outside of election season, this tech would be very dangerous in the hands of anyone seeking to influence the public for their own gain.
I feel like I'm navigating a Flash website cerca 2008
> The reason LLMs fail at solving mathematical problems is because

...because they are too small and have too little weights. Cats cannot solve mathematical problems too, but unlike cats, neural network evolve.
YouTube kids?
Even my iPhone 6S doesn't exhibit this behavior.
You are right that construction is done in artisanal, small batches. That's part of why construction is so expensive.

That's why prefabricating and manufactured buildings are such an important development: they turn artisanal into mass produced. (Alas, manufactured homes are nearly outlawed in the US. See eg https://slate.com/news-and-politics/2012/10/mobile-homes-the... or countless other articles.)

Related: this is also part of the story of why nuclear power plant construction continues to become more and more expensive, instead of cheaper.
If you give Tolkien books to a newborn child, they won't become a Tolkien expert. You need to first teach them English, and then give them the books. They will be able to answer questions about Middle Earth, but they'll also be able to form any other English sentence based on what they learned previously. It's basically the same with LLMs.
I didn't understand what 39k means. Money? I realized it was about bytes when I clicked to read the article.

Note that despite the always more common use, KB is not a thing. The correct unit is kB. Kilo is a lower case k. An upper case K is Kelvin. KB, Kelvin Bytes, does not exist.

See the list of prefixes on the site of the Bureau international des poids et mesures (English) https://www.bipm.org/en/measurement-units/si-prefixes
Parts of the comment make a LOT of sense actually, when you look at shell scripts written by the uninitated. Often times, I see constructs like

while [ 1 ]; do ...; done

which are a pretty clear indication of the author's misconception about the perceived nature of [ ], I think.
Well the quote I referenced from the article of the machines deciding to destroy humanity is utter scifi nonsense.

There are obviously legitimate risks to AI and safety is important, but this is the same for any new technology, and it's governments' responsibilities to ensure that people are safe. AI companies mindlessly slowing down and keeping their tech to themselves does no service to humanity, and if anything is a net-negative due to how tremendously useful this stuff is.

Education is analogous to AI because AI is an enormous education and productivity boost to humanity - sort of like everyone having a personal assistant, programmer, and tutor at their fingertips. This could be used for good and it could be used for bad, but the technology itself is neutral.

Again I want to emphasize that obviously there are downsides that could result from evil people using AI for bad purposes, but that does not justify slowing down AI progress - just like I don't see "people using information for bad purposes" as a legitimate reason for stifling advancement in education or something like Google search.

I have yet to see any convincing argument otherwise. Feel free to provide your counter-perspective.
What context am I missing here? How am I not giving a good faith interpretation when I'm listening to his entire speech on the invasion of Ukraine? I'm not going to sit here nodding my head in agreement with whatever he says. At the 45 minute mark, he repeatedly, clearly, says that Russia invading all of Ukraine, or occupying it, is preposterous and that there's "no evidence" of it. Neither Mearsheimer or Fridman at all refute the very obvious contradiction that Russian troops were surrounding and shelling the capital of Ukraine immediately during the invasion.
Put your money here <https://longbets.org/>.
I am very concerned too, we rely on Spring and RabbitMQ heavily. I’m going to call a halt on Spring and Rabbit for all new projects until the M&A fog dissipates. We run our own tech radar, likely to set the entire VMware stack on hold for now. If any of the prolific Spring contributors leaves, we’ll consider moving altogether. Spring is such a complex framework, if Broadcom gets to reshuffle the team, pieces will start to crumble.
I've done some welding, both with gas and electric. I discovered that doing a good weld requires a lot of experience and skill. Usually, I just made a heap of slag with my welds.

In contrast, soldering pipes is easy. I've done a modest amount of plumbing work, and never had less than a perfect soldered pipe connection.
Given Google's current reputation killing of products left and right, lately I don't bother even trying new things they roll out, and building anything dependent on it is completely out of the question. No.
People shouldn't be disillusioned though when they find out that there's not such a big need for the traditional role of graphics programmer who wrestles directly with lighting models in shader code and shadow rendering implementations. 95% (or so) of game industry jobs is plumbing engine-provided components together, writing some very high level gameplay code and maybe a bit of inhouse tools development. The hard rendering tasks are done by a handful engines now, and currently the pendulum seems to swing away from inhouse engines towards UE5 again.
Because it just can't. And it won't. It can't even reliably produce consistent shadows in a still image, so when we talk video with a moving camera, all bets are off. To create flawless movie simulations through a dynamic and rich 3D world, requires an ability of internally represent that scene with a level of accuracy which is beyond what we can hope generative models to achieve, even with the gargantuan amount of GPU-power behind ChatGPT, for example. ChatGPT, may I remind you, can't even properly simulate large-ish multiplications. I think you may need to slightly recalibrate your expectations for generative tech here.
> day when 50% of jobs are being done by AI

By OpenAI definition 50% is not enough to qualify for AGI, it has to be "nearly any economically valuable work"
there years ago, LLM wouldn't be able to generate more than a coherent paragraph
We did and started with an existing standard but quickly, trying to fit to the standard was more complex than rolling our own.

Agreed we just created yet one more standard but the bit about the input transforms being full javascript expressions or the way we encoded suspend steps was impossible to retrofit.
And OpenAI will be run by the Q*LLM.
mg impression is that he outgrew the role. that he is better being a ceo somewhere than babysitting founders.
I'm also very confused about the pricing. Its "open-source" but with SSO user-limits? Paid version comes with Prometheus metrics, so does that mean the open-source free tier doesn't? So many questions.
Writing Bourne-compliant scripts ensures maximum portability.

As many here have noted, bash isn't universally available, with another possible issue being OpenWRT devices. Stock/base images tend to use a Bourne-compatible shell, not full Bash. Though the latter's installable through opkg, for sufficiently small devices (typical of consumer kit), you simply won't have the space to install them.

There's also the slight PITA that Apple's OSX ships with a very old, pre-GPLv2 Bash, out of licensing concerns. (Apple is phenomenally averse to GPL-based code, much as some *BSDs are, such as OpenBSD.)

And if you're dealing with legacy systems (which tend to be extraordinarily and stubbornly persistently legacy), you'll often find that either bash isn't present or is quite dated.

I freely confess that I tend to write fairly recent-feature bash scripts myself by default, and appreciate many of the newer features. But if and when I am writing portable code, I'll go back to Bourne-compatibility.

But when writing system level code, an appreciation for standards and the very long tail of legacy standards and the limitations they impose is in fact a large component of professional maturity.
This was me! I was in the same exact situation. Everything I designed looked awful, and it killed my motivation.

You can learn, but it will take years of dedicated study and practice, at least in my experience. I worked really hard to learn for about 3 years, and now I’m pretty satisfied with my side projects.

I also learned that I really enjoy design. I wouldn’t say I’m “good” at it, but I can get by. I think some people have innate talent for design, and some people (like me) don’t. But you can certainly become “good enough” through hard work in lieu of talent.

Whether or not you decide to go down this rabbit hole is up to you, but I wanted to share my experience. It is slow and difficult, but possible.
Any experience running it on Linux?

The WineHQ AppDB [1] table doesn't look great, but [2] offers some hope.

[1] https://appdb.winehq.org/objectManager.php?bIsQueue=false&bI...

[2] https://forum.affinity.serif.com/index.php?/topic/182758-aff...
Its insane how they think they can have their AGI and eat it too! The closest thing we have to AGI is like a human child even though that's Synthetic (mankind made) General Intelligence and they can't really be truly relied upon and not learn or formulate sentences you don't like
Upgrading itself doesn't mean tweaking its own software. It means being able to understand its own hardware and software well enough to design an improved model. And then that improved model would be able to do the same, examine its own hardware and software and design something else that's even better.

One crucial difference between humans and computers is that we can't be turned off indefinitely and started up again. Nor can we make a one to one copy of our software in another device, much as we might try with our children. So for us, our own lives are intrinsically precious, and consciousness is part of how we protect our lives. But machines don't have precious lives in that sense, so they may never need to be conscious, even if they achieve AGI.
An Overview Of Catastrophic AI Risks
I was really hoping this post would be about Q*.
Right so every website needing a cookie banner to comply with EU regulations is not only a UX nightmare, but it doesn't even prevent tracking. Horrible pointless legislation.
Fascinating! It looks like PEP 723 (the one that was accepted provisionally) will allow you to embed a comment in your script that looks like this, to specify dependencies on request and rich:

# /// pyproject
# [run]
# requires-python = ">=3.11"
# dependencies = [
# "requests<3",
# "rich",
# ]
# ///

import requests
from rich.pretty import pprint

resp = requests.get("https://peps.python.org/api/peps.json")
data = resp.json()
pprint([(k, v["title"]) for k, v in data.items()][:10])
that's https://id.me essentially.
Sorry, can you explain this? To me, it makes sense to define abs(x) = sqrt(x^2) i.e. ignoring the negative solution enforces the positive result. Using that definition, abs(i+1) = sqrt((i+1)^2) = sqrt(i^2 + 2i + 1) = sqrt(-1 + 2i + 1) = sqrt(2i) != sqrt(2). The second example seems off in the same way (i.e. the answer should be sqrt(8i) instead of sqrt(8)). Am I missing something? Also, abs(i+2) = sqrt((i+2)^2) = sqrt(i^2 + 4i + 4) = sqrt(-1 + 4i + 4) = sqrt(4i + 3) which doesnt seem to follow the pattern your son described.

Also, just to point out that my understanding of absolute value is different than your sons. Thats not to say one is right and another is wrong, but there are often different ways of seeing the same thing. I would imagine that LLMs would similarly see it a different way. Another example of this is people defining PI by its relation to the circumference of a circle. Theres nothing wrong with such a definition, but its certainly not the only possible definition.
This group said that previous attacks on state government offices this past summer were motivated by bans on gender-affirming healthcare for minors [1]. Idaho is among the states that have passed such a ban [2], but afaik the group hasn't attributed this most recent attack to it -- they've attacked many targets across the world for various not-particularly-convincing reasons. In any case, the breach data here seems unlikely to be particularly dangerous -- the article says that they leaked employees addresses and SSNs.

Drag queen story time seems completely unrelated to this story.

[1] https://www.insider.com/gay-furry-hackers-transphobic-hackin...

[2] https://en.wikipedia.org/wiki/LGBT_rights_in_Idaho#Gender-af...
Confocal microscopy
Apple also bought Intel's modem unit as either leverage or an escape hatch from Qualcomm. It's like having unlimited dollars to throw at a problem is useful.
Why did the Github support add an ssh key, though?
Interesting. Congratulations on your achievements.

I was wondering, what channel did you use to initially get the 2,000 customers?

Did you post in in some forums or buy Ads of some form AdSense, Facebook or Twitter.
Would be great to learn how this was researched and built!
I'm very interested in automation choice analysis
> I got back to the map the app would reload. My search would be gone, and I would have to set my destination again.

So the map app is buggy… my expectation would be that it should be fixed.
Chips take a lot of time from design to roll out. Giant LLMs being something you want to serve is a very recent development and it will take time for the deployed hardware to catch up, no surprises here.
Unfortunately it doesn't work like this. You can close the app, but app will wake up on any event - timer, call from server, any system event, etc. etc.
Learning about this for work, I was surprised that it seems to be a microscopy technique invented by Marvin Minsky, of Computer Science/Turing Award/MIT/AI fame. Of course.
Exploring an LM to Generate Prolog Predicates from Mathematics Questions