skysight-inc/HackerNews huggingface dataset:
Hmm maybe you’re only familiar with their azure SDKs ;)

What makes Windows not modern? The whole point of my comments is that different business eases have different funding.

Azure is a separate business for Microsoft than windows development.

I’m going to guess based on your range of comments that you’re primarily a devops and web developer and not a native app or game developer?

Which leads back to my first response to you: I don’t think you’re actually familiar with developing things for distribution on either steam or an App Store.
Google product decisions (and especially what to shut down) isn't really made by the same people who keep the infrastructure up and running.
Seems completely plausible to me, and elegant to boot. To minimize design change, the product name could be the alignment check.

{You being too high/low} and {the angle of the numbers/check being wrong} are two ways of saying the exact same thing when ignoring the world beyond you and it, like using a handheld mirror.
Really great blog post!

When I first started game development, I was all-in on building my own engine.

Then I matured a bit, and found the wisdom in using someone else's engine.

Now that I've grown a bit more, I'm starting to see the appeal of building ones' own engine again. I feel like this blog post enumerates the reasons quite nicely, and I respect the approach.

Kudos -- this looks great. :)
This is funny because in the 90s I was at a similar position. I was at a university department where everybody had a Solaris 2.3 or 2.4 box as well as a PC that would dual boot into OS/2 or a 5MB MSDOS partition. Solaris, OS/2 and MSDOS would all mount the users' homedirectory from the SunOS 4.1.3 box, either via NFS or Samba.

People sadly did most of their work by booting into MSDOS and then loading Windows 3.1 from a shared readonly Sambashare that had Windows, Office and a ton of other programs ready to use. This "immutable" Windows installation worked surprisingly well as Windows no longer could destroy itself by existing and reconfiguring itself, and users could no longer run setup.exe for unneeded programs that would break everything else.
He is the same now as he was then. I don't understand all the fawning over the guy (I mean, I do, they want to be him and live his life, which I suppose means they are as morally corrupt as he is).
I hate to be that guy but GANs and diffusion models aren't generative pretrained transformers (GPTs).

The rule I use is that a system that was trained on input data is AI and algorithms that aren't trained are not AI.
Aircraft with largest composite wing and engines ever conceived has problems with engine mounts after 1000s of test hours and longer certification requirements by FAA.

News at 11.
There is no guarantee that we will not get stuck with these probabilistic parrots for 50 more years. Definitely useful, definitely not AI.

And by the way I can copy your post character by character, without hallucinating. So I am definitely better than this crop of "AI" in at least one dimension.
If mathematics is so vast the human mind is feeble to it, then it’s also too vast for exhaustive search. Axioms aren’t even beliefs. They are first principles at the service of solving mathematical problems. If we want to solve other problems, we can change the axioms. That goes all the way back to Plato. We treat them as if they were true to solve the problems at hand. (It’s called as-ifism if you want to google it). Since logical and mathematical space is infinite; exhaustive search is the wrong approach.
It just needs external regulation. The self regulation was a disaster.
>We've run the 4-minute mile.

>We are in for radical non-linear change.

We aren't running miles much quicker than 4 mins though. The last record was 3m:43s set by Hicham El Guerrouj in 1999.
It took a week or so on 56k and later ISDN, but, sure. :)
> I am under the impression that people start programming, by and large, with imperative for/if style => so the imperative style is readable by more people.

IMO, this is a simple consequence of technology moving faster than society. There are still instructors out there who learned to program in an environment where the go-to options for imperative programming were C and FORTRAN; the go-to options for other paradigms (if you'd even heard of other paradigms) were things like Lisp, Haskell and Smalltalk; and CPU speeds were measured in MHz on machines that you had to share with other people. Of course you're going to get more experience with imperative programming; and familiarity breeds comprehension.

But really, I believe strongly that the functional style - properly factored - is far more intuitive. The mechanics of initializing some output collection to a default state (and, perhaps, the realization that zero isn't a special case), keeping track of a position in an input collection, and repeatedly appending to an output, are just not that interesting. Sure, coming up with those steps could be a useful problem-solving exercise for brand-new programmers. But there are countless other options - and IMX, problem-solving is fiendishly hard to teach anyway. What ends up happening all the time is that you think you've taught a skill, but really the student has memorized a pattern and will slavishly attempt to apply it as much as possible going forward.

> Futhermore, in JS, the functionnal style is less performant (nearly twice on my machine, i assume because it do less useless memory allocations)

Sure. Meanwhile in Python:

$ python -m timeit "x = []" "for i in 'example sequence':" " x.append(i)"
500000 loops, best of 5: 796 nsec per loop
$ python -m timeit "x = [i for i in 'example sequence']"
500000 loops, best of 5: 529 nsec per loop

... But, of course:

$ python -m timeit "x = list('example sequence')"
2000000 loops, best of 5: 198 nsec per loop

Horses for courses.
I've worked in AI for the past 30 years and have seen enthusiasm as robust as yours go bust before. Just because some kinds of narrow AI have done extraordinarily well -- namely those tasks that recognize patterns using connections between FSMs -- does not mean that same mechanisms will continue to scale up to human-level cognition, much less exceed it any time soon.

The breakthroughs where deep AI have excelled -- object recognition in images, voice recognition and generation, and text-based info embedding and retrieval -- these require none of the multilevel abstraction that characterizes higher cognition (Kahneman's system 2 thinking). When we see steady progress on such frontiers, only then a plausible case can and should be made that the essentials of AGI are indeed within our grasp. Until then, plateauing at a higher level of pattern matching than we had expected -- which is what we have seen many times before from narrow AI -- this is not sufficient evidence that the other requisite skills needed for AGI are surely just around the corner.
We are but prediction machines https://www.psy.ox.ac.uk/news/the-brain-is-a-prediction-mach...
Agreed, Tesla now has a reputation for low quality. Even taking to randoms who do t know much about EVs or Teslas just say this now. It’s become common wisdom Toyota make good cars, Tesla make crap.
There used to be a pioneer drive you could flash with replacement firmware that could read raw data (even the ECC!). I used to have one of those but lost it in a move :'(

It was really handy to get scraps off a disc that was very damaged.
The power consumption is genuinely worse than advertised (2x the draw of Pi 4, 3x the performance). The reality is a 3W idle minimum, 15W at full load, meanwhile the Pi 4 can idle at 1W and won't ever go over 5W. They're just about the same power per watt, the efficiency gains are zero.
Yeah fair enough. I just don’t see how this is entirely revolutionary though. We still need to know our stuff.
People aren't looking at this from a business perspective. Right now a decent subset of artists hate AI, so it makes sense to try and target that market if it's large enough.

If artists suddenly started loving AI tomorrow, this pledge would be out the window. It's just business and marketing - nothing more, nothing less.
I'm so glad you added this. I wasn't really interested in the game (assuming it was a poke-clone) until you pointed out this video! Now I can see that the developer definitely has a direction for the game but identifies fun/and "good feeling" properties and pivots which makes me want to wishlist the game.... But I won't because I really enjoyed that part of the video and it made me laugh.
Well I was being sarcastic. I really dislike it when people have to first convince you that you should trust them.

Either make a good argument or don’t.
I wanted to share some thoughts on the significant fees we currently pay to companies like Stripe, PayPal, and Visa/Mastercard, which run into billions annually.

These fees are largely due to the complex infrastructure and intermediaries involved in traditional payment processing. However, the Bitcoin Lightning Network offers a promising alternative.

The Lightning Network is a decentralized, second-layer solution built on top of Bitcoin, allowing for near-instant transactions at a fraction of the cost.

It eliminates many of the intermediaries that drive up costs in traditional systems, potentially saving businesses billions in fees.

Additionally, it supports micropayments and offers enhanced security and privacy, making it a viable option for reducing our reliance on traditional payment processors.While there are challenges in adoption and regulation, the Lightning Network could become a strong competitor to these established players within the next decade, offering a more efficient and cost-effective solution for processing payments.
Give me a take home exercise, doable in maximum 2-3 days and pay me the salary rate for that period.

I'd be happy and it would be fair.
But Android Auto isn't required to be able to do all of that.
Aha, so they did get permission to use their trademark. That makes them practically official then.
> Protecting children wasn't a serious motivation of many people who supported it?

It may be helpful to understand the context.

Ambitious politicians have one goal above all others: Getting elected. This type of law impacts that in two ways. One, they'd really like private corporations to censor the opposition for them, but forcing them to is clearly unconstitutional and also offends voters who don't like that level of cynical authoritarian opportunism to be so transparent. Two, if you can drum up a moral panic and then purport to solve the problem you hyped up, some people will vote for you.

Politicians combine these two into laws like this. "Think of the children" laws too often pass because anyone opposed to them is painted as a monster regardless of the details of what is actually in the law or how ill-conceived it is. Their hope is that it will both disguise their underlying goal from the voters and invoke "hard cases make bad law" to create a precedent that laws in that style aren't unconstitutional, so the next one can do what the really want. Or, because the law is ambiguous and it's hard to even know if you're following it, have something that allows them to threaten arbitrary social media companies with prosecution if they don't do what the administration really wants in a backroom deal.

> But do we think people who promoted it were insincere about believing it was harmful or undesirable for children to see violent depictions?

It's not that they might not believe those things about a particular situation, it's that they're insincere about that situation being their true motivation for passing the law, and disingenuous about the ability of their law to address it. The politicians who propose "think of the children" laws are usually acting in bad faith, and when the law is overbroad with no regard for collateral damage or constitutionality, there is no doubt of it.
I would go with blue team. Incident response, finding intrusions and keeping red team footholds out would be fun and challenging.

I've always wanted my own castle, and blue team is probably as close as I'll get :)
Rocket explodes during testing at UK's new spaceport in Shetland
They also say 50 years in the title and <=10 years later: "In the past decade, another ocelot, named Lil' Jefe, has been spotted roaming in the state, the Arizona Republic reported"
It's just interest rates. 0 a few years ago, 5% today.
Seems a bit of a stretch. Git is not linear, and there’s no consensus mechanisms
Edit: sorry, you got this question a bunch below. I didn't read ahead.

Are probation periods not a thing in the US? Maybe because of at-will termination?

In Australia most roles have a 3-6 month probation period in which either party can terminate the employment agreement at will. That's essentially a "paid trial period".

After that, employers have much stricter rules for what reasons they can fire you (in theory) and and both employers and employees must give 2 weeks notice or extra if agreed upon in contract.
Well, if you ask most educated English speaking humans to complete 'It was the best of times', they will most likely answer with 'it was the worst of times', too.

Btw, here's what I get from ChatGTP 4o:

> It was the best of times, it was the worst of times

> That's a famous opening line from Charles Dickens' A Tale of Two Cities. It contrasts the extremes of the era, reflecting the novel's themes of duality, revolution, and the complexity of human experience. Dickens was commenting on the contradictions of the time, particularly the French Revolution, where there were both tremendous progress and terrible suffering. What made you bring up this line?

> But these are statistically derived text constructs entirely dependent upon the training set of the LLM. Train one strictly on Java source code available in Maven Central and the answer will be radically different.

Well, if you give that line to a German who hasn't learned any English, the answer will also differ from what an educated English speaker will give you? What's your point?

What's an original insight to you? As far as I can tell, the LLM misses the 'insight' part more than the 'original' part.

> Such is the difference between understanding and statistical text generation. People can do the former, LLM's do the latter.

I agree that LLMs aren't good at understanding. (Yet?) And even people only sometimes are.

As far as I can tell, contemporary LLMs generate their answers 'greedily', ie just from left to right more or less directly with the output from the network.

In contrast something like AlphaGo overlays what you can call searching or optimisation processes on top of the outputs from their network.

I'm impressed by how well these LLMs already work despite all the limitations. And ML is still getting better rapidly.
Why do you need to use your phone while driving? Set your nav at the start of your trip, start your music at the start of your drive. Skipping or anything else is easy to do when stopped at a light.

My phone has always done just fine mounted on a dash, never had any concerns around sun/heat damage.
We do predictions, but much more important, we are able to create new states. Prediction the classical view assigns probabilities to existing states. What's unique to us and a lot of other biological intelligence is the ability to create new states when needed. This is not implicit in the narrow view of prediction machines
Is this a good thing ? Because apparently we’re supposed to be building god. So it sounds like we’re on the wrong track, am I wrong ?

If we’ve just copied our feeble abilities, is that supposed to be exciting?

Is god like intelligent just a prediction machine too ?
I have a couple of orangepi 5+'s that replaced a large, loud, power hungry server. with an attached nvme drive, iscsi connected over 2.5gbit ethernet, 8 cores, and 32gb of ram, they are quite capable.

one is the primary database, another runs everything else in docker containers.
Some days it's worth it to burn some imaginary internet points for the good of the discussion and article. People downvote for various reasons, which we will never be able to figure out why definitely. Each person is different, and they all have days where they swing one way or another.
It is 100% possible and there are a slew of tricks you can use to get big performance boosts with negligible cost to accuracy.
Binary compatibility is possible, but not my main concern just yet. The CUDA api is missing length parameters left and right, often for highly problematic things such as "how long is this ELF file" and "how many parameters does this kernel need".
I will definitely write wrapper headers at some point, but I don't want those hacks in the actual source code...
> comedy doesn’t transcend cultures easily

Or foreign investment censorship priorities.
Maybe that's true for some governments. Or maybe it was true a long time ago. In America I question whether our government is actually even the government. One thing I like about Google is they don't claim to provide services they don't actually do. I'm glad you live in a place where the system that governs you worked well enough to earn your trust.
How do you plan on finding instruction latencies for eg. sm_89?
The old Google badges used to have lenticular images, too. (Perhaps they still do? I haven't been working there in a while.)
and censorship the test results?
To handle time-based effects you need a custom architecture.

https://www.research.ed.ac.uk/en/publications/neural-modelli...

Don’t use NAM. Learn PyTorch.
Half of price is hidden in shipping fee. It's 60 + 70 in shipping + taxes.
> they have to be specialized in avoiding humans

Exactly.

What I find even more crazy is how other species of Homo were around until just 30,000 years ago and maybe as recently as 12,000. I find a lot of people have the perception that it was a much longer time but it could be as recent as the building of Gobekli Tepe.
I think we will see something similar to the last boom with Neural Net chatbots back in 2014(?).

Public discource will simmer down, as current language models either fizzle out or improve. Some will become background noise as the models gets integrated into search engines or leads to large scale lawsuits.

Unlike the previous neural nets though, those models have an actual tangible use. So you will see them around a lot more.

Then I think we will see another big explosion.
ChatGPT often googles it for me and gives me a summary
I find it slightly annoying and dishonest to present it as a moral position, but overall it's nothing that other businesses haven't already been doing. It's just not a big deal.
> Once we've amassed a volume of artistic media so large that it would take hundreds of human lifetimes to make use of, what is the point?

There's billions of people and they all like different things.
You completely missed my point. We already had the RPi4, and it was sold for $35 for the 2GB model. It was perfect at that. I had enough grunt, and 2GB was enough for a lot of use-cases. I still use mine for a lot of various tasks. One is my GPS-driven NTP server for example. Don't need lots of RAM for that, but do need the GPIOs.

What I said was, I don't get the RPi5 value proposition. It's fairly expensive so not just something you throw at simple tasks like an NTP server without consideration.

If you need grunt and RAM, well, why not just pay a bit more and get tons more of that? You get more PCIe, you get way more RAM, CPU and GPU, in a form factor that's not that much larger. And it's x86 so you're not facing the kernel support issues like OrangePi and friends.

In my experience, there's very little overlap between "need hardware GPIO pins" and "need 8+GB of RAM and/or lots of compute".
Yeah, this is why I said some modularity is desired. You also should want stability in ways our industry just doesn't.

Large teams churn in ways smaller teams don't. Competing teams, as the different product teams almost certainly are will be different.
> There are far more good programmers than there were good mechanism designers or electronics engineers.

But that doesn't mean a thing. The barrier to entry is much smaller.
Also from the 1990s, "intelligent agents". Here's what Don Norman wrote in 1994 at https://dl.acm.org/doi/pdf/10.1145/176789.176796 :

> The new crop of intelligent agents are different from the automated devices of earlier eras because of their computational power. They have Turing-machine powers, they take over human tasks, and they interact with people in human-like ways-perhaps with a form of natural language, perhaps with animated graphics or video. Some agents have the potential to form their own goals and intentions. to initiate actions on their own without explicit instruction or guidance, and to offer suggestions to people. Thus, agents might set up schedules, reserve hotel and meeting rooms, arrange transportation, and even outline meeting topics, all without human intervention.
I'm a big fan of Waymo, but this press release seems to be almost entirely content free. Is there a link somewhere that describes what is actually new in the 6th generation?
Stop Overthinking
AT&T was broken up based on location, hence the term Regional Bell Operating Companies.

I’m not sure how the relative straightforwardness of that approach maps to a company that basically has two main supply chains (737 in Renton and everything else in Everett with North Charleston as a satellite.)
Best self driving software and sensor suite packaged in a purpose built vehicle paired with large scale operations puts Waymo very far ahead of everyone else.
>Perspective from someone who identifies as a tidsoptimist, Swedish for “time optimist”

I also wondered all those things, and loved the word tidsoptimist.

Then I got diagnosed with ADHD as an adult at age 34, and it all clicked.

"Tidsoptimism" is an ADHD trait:

https://romankogan.net/adhd/#Being%20Late

A part of it is what's literally called Time Blindness:

https://romankogan.net/adhd/#Time%20Perception

https://romankogan.net/adhd/#Time%20Blindness

The article we're discussing (as well the one you linked, and the one written by Tim Urban on the same issue[1], and the words you wrote) is a universal ADHD experience.

Figuring out that this is how my brain works helped immensely. Turns out, there is no need to make up new terms (tidsoptimist, "chronically late person", etc). The words have already been invented. And many people have already worked out solutions, mitigation strategies (...and meds[2]).

I hope that my links above will help some people learn something about themselves, and for others - to understand their friends and colleagues better.

And for hell's sake, let's take the moral charge out of lateness itself. I'm not saying that it should be acceptable: to the extent that someone being late affects other people, there may (and should be!) consequences.

But being late has a stigma even when it doesn't affect anyone else.

And it makes it more difficult to have a conversation like this: "I have time blindness. Let's talk about what you'll do if I don't make it on time, and what the consequences will be. I don't want to make you wait." - which both helps avoid lateness and often allows for a solution other than "everyone will be angrily waiting for the late person".

[1] https://waitbutwhy.com/2015/07/why-im-always-late.html

[2] https://romankogan.net/adhd#Medication
> When does math become "AI"?

When it uses your data to suggest other people — I think that’s what people are afraid of.