skysight-inc/HackerNews huggingface dataset:
Plateau of productivity is still out there waiting, it is just not in 1 year, as some investors and valuations assume.

In 10 years the impact will be so profound LLMs will be everywhere, in 15 years we will not even recognise industry. Mobile boom will be humbled by LLM boom. Of current giants, maybe Microsoft will come out on top, they have everything they need.
Id consider it more a fundamental problem - lack of a way to introduce new data to a model without repeating training runs and waiting for the error to converge. Humans seem to have an understanding of things from a one-shot learning run (this is perhaps due to our vast experience with the world and ability to run simulations in our head, but a subset of that should be possible for ML quite easily)

If you solve this problem, teaching a robot arm to be accurate should be pretty easy. You would just have stereoscopic cameras that map to a 3d world, and "program" in a trajectory of the object, and the model should use that trajectory to figure out where to move and how to compensate based on visual feedback.
Gary Marcus predicted that deep learning was "hitting a wall" [1]... right before ChatGPT came out. At this point he's so committed to the bit that he has to keep predicting that this time, really, it'll stall, and hoping eventually a stall comes.

1: https://nautil.us/deep-learning-is-hitting-a-wall-238440/ Also note he doubts that scaling will work past GPT-3... Not uh, 20/20 foresight exactly.
This reminds me of the exciting time when I first got to make my own ray-traced 3D graphics... in 1991. I had to sit there and watch as the free POV-Ray tool generated the image pixel by agonising pixel, left-to-right, top-to-bottom.

Toy Story was four years later, and required 800,000 machine hours on a "render farm" to produce an output resolution of just 1080p.

Now? I get to play games on a single PC at 60 fps with ray tracing at 4K resolution!

Conceptually, the glacial pixel-by-pixel rendering in 1991 and the RTX games today are the same thing, but qualitatively there's no comparison.

We've been shown that machines can be prompted in English, think about what they've been asked, and produce useful output... at the same kind of rate I was getting from POV-ray in the 90s.

Now picture the same thing five years later (equivalent of Toy Story), ten years later (Grand Theft Auto III), twenty years later (Battlefield 3, Kung Fu Panda 2), or thirty years later (Cyberpunk 2077).

Some of us can extrapolate from the present and foresee that the pixels crawling one at a time across the screen is not how it's always going to be. That one day the same technology will make our dreams come alive.

Others look at nascent technologies like generative AI and think "Pfft... too slow." and write Substack posts.
There was no fault neglect or want of care. The engine failed. The ship was out of control. It was not bad maneuvering. It was not sleeping on the wheel. It was not want of care (it was piloted by a harbor pilot).
Being useful in some areas is different from tech companies trying to cram "AI" into every product, no matter if it makes any lick of sense or not. That irrational behaviour is what I would call the real AI bubble, and I can't wait for it to burst ;)
My pet theory is that OpenAI releases are on hiatus pending the US elections. It would be a huge disaster to release SORA in the next few months and have it some way sway voting. What do you think?
> I feel like even "simple" shell scripts tend toward more inscrutability than all but the most questionable python code I've ever written.

When you use long options in bash (scripts), it becomes very readable, but it's not a widespread practice. I always use long options while writing scripts.

Consider these two examples, which is very straightforward:

- curl -fsSL $URL | bash

- curl --fail --silent --show-error --location $URL | bash

The second one almost "talks you through".
We need that laughing Leonardo Di Caprio meme with Jensen Huang's head pasted on.
the system isn’t saying that any particular outcome is better or worse

and what’s more likely is that the insurance you’re required to have told you to do this in order to keep the insurance, regardless of your individual predilection
Just like crypto, AI has recently seen a seismic grift shift in startups and courses all around.

Even the VCs know this as the AI industry spent 17x more on nvidia chips than it brought in in revenue. [0]

So we will likely see a massive fallout when most of these AI startups are quickly commoditised either by OpenAI, Anthropic etc (better & cheaper AI models), Apple (local AI models) and open source (replicating closed source models that is 10X better)

It is an industry that is the race to the cheapest and ultimately the bottom.

0 https://www.wsj.com/tech/ai/a-peter-thiel-backed-ai-startup-...
It’s amazing that the captain of such a large vehicle has through the results of their choices the capability to do so much harm
Gary Marcus is not a person writing serious things. We barely have any tooling for this stuff. Most people don’t know still how best to use these things in production workflows. Investors will continue to throw their piles of dry powder at this until a large large company comes out and says “we’ve failed to figure out how to use genai to improve things”. And no company ceo is going to come out soon and say something that bold. Nobody wants to look like a moron.

So the answer is, there is no bubble. This is an exploratory phase, and there is a lot more money left to chase opportunities.
Chess.com is also definitely using an evaluation-centric definition to label moves as blunders. The issue is that this definition is also some function of the change in winning probability.

> So what is a blunder for a strong player may merely be a mistake for a weaker player.

Statistically this intuition appears to be correct. Your winning probability is still more than 25% when down a queen against an 800 rated player, but under 10% if playing a 2200: https://web.chessdigits.com/articles/when-should-you-resign#...

So it would make sense for the definition to take into account the opponent's Elo rating.
I just don't understand the controversy around this book (although I know nothing of the movement people often speak about). For me the book gave me great insight in to becoming a man. Something I and most men do by accident and not by design. Crucially I learned how I as an older man have a responsibility to guide younger men when they are a bit lost.
There is one big difference compared to previous hype cycles:

While crypto or VR tech still hasn't arrived in our daily lives, most of my friends are already using tools like ChatGPT on a regular basis.

Generating images and videos is entertaining, but I believe that the true value of AI lies in automating tedious, repetitive work, both in the digital (e.g. data entry) and physical space (e.g. assembly or logistics work).

It's these "boring" use cases that will bring big efficiency boosts to our economy.
I hope not. I was irresponsible to let ships pass a dozen times a day through a flimsy contraption that could collapse at the first nudge. This risk was unacceptable.

Unacceptable!

The people of Baltimore have benefited for years of a port facility literally downtown, which is practically the same thing as building houses in a flood zone. Should have never been permitted!

I hope “We The People” accepts the responsibility for their actions!
I like it in theory but the small demos I've played with lack a lot of the details that GUI toolkits have converged upon. Small behavioural things ingrained in usage patterns that have to be reimplemented.

First two that come to mind are tab/shift-tab navigation and being able to adjust sliders roughly with arrow keys.
It’s not a good approximation because (spoilers) the challenge is to identify the location of the planet relative to the suns, not simply to locate the suns themselves. I too wondered at the title.
Probably not until speculators find a new bubble to up.

My hunch: GenAI will be very useful embedded in many applications, but mostly in the background (like relational databases and unlike "blockchain technology"). It won't become ubiquitous and ever present, like the internet or mobile phones.
As teenagers used to record mixtapes of music we likes to people we liked/love.
Nowadays people just tag other on social medias or send links in private messages. I wonder if some still take the time to curate / prepare special things the same way we did.
But where is the real use? Chatbots and stock images seem very niche and hallucinations have not been solved either.
Right. Base damage is covered by the first line insurer. The excess damage is covered by the backend insurer.

Business is about managing loss. Nothing more. No further emotional support required.
That's a very malicious way to interpret what the article is talking about in hundreds of words.
> 50B in, $3B out. That’s obviously not sustainable.

Ouch. GenAI seems to promise no shortage of solutions but offers no reliable revenue stream.
I held a portable USB3 Blu-Ray reader in my hand once.

I could have used it, too, but I could not think of anything I wanted to do with it by that time in 2017 -- seven years ago -- despite my proclivity for making backups of films.

BD on a PC has never been common in my world of computing, and by 2017 optical drives in general were becoming very uncommon in everyone's world.

It never broadly caught on.
Intel Foundry Operating Model Shown with Path to Process Leadership
Thank you for sharing your experience! Big fan of Kiwis and so curious about the country. I really loved to hear first-hand experience.
> The lesson I take away from this incident is that we probably shouldn't be allowing anonymity for core contributers in critical open source projects. This attack worked and the attacker will likely get away with it free of consequence, because they were anonymous.

This would be impossible to enforce, and might not be a good idea because it enables other ranges of attacks: if you know the identities of the maintainers of critical open source projects, it’s easier to put pressure on them.
Sora is so ridiculously expensive, they doubt it has a market.
Of course. Right now we're in an AI Spring, but winter will come again.
> (...) the backdoor adds an audit hook. The dynamic linker calls all the registered audit hooks when it is resolving a symbol.

How was this possible without also modifying the LD_AUDIT var? Haven't seen that mentioned yet, or perhaps I'm missing something.
Oh and aluminum ships burn.

(Which is not to say they are toast.)
the use of "flimsy contraption" and "first nudge" indicates your level of ignorance of the subject.

https://www.omnicalculator.com/physics/kinetic-energy

https://en.wikipedia.org/wiki/MV_Dali#Description

"Description

Dali is a Neopanamax container ship[7] with an overall length of 299.92 metres (984 ft), beam of 48.2 metres (158 ft 2 in), moulded depth of 24.8 metres (81 ft 4 in), and summer draft of 15.03 metres (49 ft 4 in). Her gross and net tonnages are 91,128 and 52,150, respectively, and her deadweight tonnage is 116,851 tonnes. Her container capacity is 9,971 twenty-foot equivalent units (TEU).[2][8]

Dali is propelled by a single low-speed two-stroke crosshead diesel engine coupled to a fixed-pitch propeller. Her main engine, a 9-cylinder MAN-B&W 9S90ME-C9.2[9] unit manufactured by Hyundai Heavy Industries under license, is rated 41,480 kW (55,630 hp) at 82.5 rpm.[2] Her service speed is 22 knots (41 km/h; 25 mph).[5] For maneuvering in ports, Dali has a single 3,000 kW (4,000 hp) bow thruster. Electricity is generated onboard by two 3,840 kW (5,150 hp) and two 4,400 kW (5,900 hp) auxiliary diesel generators.[4] "
Agree on that. The need of an AI rice cooker, an AI printer, an AI Juicero, is definitely questionable. Hopefully, eventually, this stuff will run out of money and we'll be left with what makes sense.
So you're trying to derail the discussion to something about "value", because the page I linked about "skill" has a passage about how skilled laborers were historically important to the economy? What does this have to do with the subjectivity/objectivity of "underpaid", "unfair wages", "unskilled labor", or whether a burger flipper is more "skilled" than an accountant? As I said earlier, even if you think that accountants are useless paper pushers, the fact that they're pushing papers in a very specific way that takes years to learn, makes them more skilled.
There's really no need to make an unsafe temporary allocation for a simple type like Int. You can just assign it a value, and if you only need it once, just pass it through with &. For example:

var size = buf_size
c_birthday(rawPtr.baseAddress, data_len, res_ptr.baseAddress, &size)

In this case, since you know your size is fixed, and it's actually quite large (1 MB) it is never going to fit on the stack anyways. So there is no need to use a function that will try to do that: just use Array's init(unsafeUninitializedCapacity:initializingWith:) initializer instead, and you will bridge it into Swift's lifetime management without having to do the whole closure dance. Finally, since your API is unlikely to modify the buffer you pass it in, try using withUnsafeBytes instead of withUnsafeMutableBytes (and correctly annotating the pointer with const in your bridge).
You're reading history in reverse. The Soviets landed a robotic probe on the moon years before the USA succeeded with human pilots,

https://en.wikipedia.org/wiki/Luna_9 ("Luna 9")

https://en.wikipedia.org/wiki/List_of_missions_to_the_Moon#M... ("List of missions to the Moon—Mission milestone by country")

You absolutely don't need sophisticated technology or giant budgets to accomplish this.
That phenomenon goes a lot broader than young kids. Verbal fluency and rhetoric has almost become a sort of personal marketing technique. Sounds impressive at first, but doesn't necessarily correspond to anything of substance behind it. My tentative hypothesis is that it's a symptom of the "optimization" of educational content on the internet.
I suspect that the actual cost to rebuild the bridge will be far higher than that. Initial estimates of large public works projects are virtually always too low, and actual costs can easily be 5-10 times higher.

There is a great book about this phenomenon (and how to avoid it) by Brent Flyvbjerg called "How Big Things Get Done".
TLDR of the logic behind that sum for anyone else who wondered like I did:

They claim the ship's value before the crash as $90M, and that estimated costs for salvage and repairs to the ship are $19.5M and $28M respectively, leaving the value of the ship now at $42.5M (points 15-17 in the main document).

They then add the value of pending freight ($1.17M): "Petitioners offer an Interim Stipulation
of Value in the amount of $43,670,000 (i.e., sound value of the vessel plus pending freight less
repair costs and salvage costs)." and mention that they'll file updated numbers once salvage and repair costs are confirmed rather than estimates.

IANAL nor in the US, so I'm curious whether this is standard law to be able to limit your liability to the (post-crash) value of the ship and the only thing in question is how the numbers end up, or if it's a long-shot hope that the companies' lawyers figured they might as well try asking for in case a judge feels friendly?
You can’t halt this stuff. There isn’t one player and there is considerable market incentive.
The French do the same against illegal gold miners in French Guiana Amazon. They have approximately 1,000 soldiers compared to up to 9,000 illegal prospectors. I can't imagine how a single unit will be capable to curb anything when you look at the size of Brazil's Amazon.
The bubble bust on the Internet too; the outcomes can be wildly different.
IMO LLMs are basically the best thing since wikipedia for learning/autodidacts.

They're also pretty fantastic for discoverability if you do a bit of filtering to remove hallucinations. Only downside is you end up finding that project is abandoned for years or so.
#define WORLD WESTERN_EUROPE_JAPAN_SOUTH_KOREA_AUSTRALIA_NORTH_AMERICA

Quite a big chunk of the world is happy to deal business with Russia and they are not that isolated.
> Which is ridiculous, it's just an incredible token predictor.

I'm not sure I'm not just a mediocre token predictor.
Here's one of many example use cases we found for GPT4 API:

Our sales people request invoices from a potential customer. On those invoices are our competitor's services and price. Invoices can come in PDF, png, jpeg, excel, csv, email formats. Content formatting can come in random forms. Pricing breakdowns are also non-standard across invoices. We have matching services and our own prices.

The goal is to find similar services where we charge less. In the past, our sales people would spend hours combing through those invoices. We wrote a prompt for GPT4, fed in our services and prices, and asked it to find services we could potentially replace as well as our profit margin. It took us a day to write this prompt. The results were outstanding and GPT4 gave accurate results. We even asked it to package it up in a PDF for us to send to the potential customers. On a Monday morning, we started on the prompt. By Tuesday morning, we got it working well enough that we were confident ship it to a few of our sales people to test.

This will save our company hundreds of thousands each year and we can get back to the potential customer much faster than before - increasing the likelihood of a sale.

If we had to program this like normal software, it'd probably take months to get it right with dedicated engineering resources to account for new invoice edge cases. Chances are, engineering would never even prioritize this feature for our sales people because there is simply no economical way to account for so many different invoice edge cases.

I believe we're just getting started. If we get GPT6 in two years and massive improvement in inference cost and context size, it's going to change everything we do. Heck, even GPT4 with 100x context size and 100x lower cost per inference would be transformative.

If this is a bubble, I'd like to live in it. I believe that many businesses have found use cases similar to the impact of ours. But they're just not broadcasting them to the internet in order to keep it a business advantage.
Why are people so fixated on gender? We all mostly want the same things, feel the same things and do the same things, both good and bad. Individual variety overwhelms slight difference in averages between the groups.

When it comes to anything except children, "I'm a man" is no more meaningful than "I'm a Libra". Objectively meaningless, subjectively can screw you up but only if you believe in zodiac.
When will the “When will the GenAI bubble burst? "bubble burst?

I've seen contrarian think pieces like this pop up on social media so much lately they pollute my feed just as much as the GenAI evangelist articles.
> There is one big difference compared to previous hype cycles

Not if you compare for example to the dot-com bubble.
The release of ChatGPT 3, 4 made us astounded because it was doing things a computer never could have done since they exists.
That made us believe that they could replace humans in a lot of fields, where, in fact, it only improves the work of an already existing human.
The hallucinations, specially, can be very costly. The money saved by doing 95% of a taks with an AI can be swallowed easily by an human having to work to fix the 5%.
My org at work is organizing a hackathon and the theme is AI-based solutions to help with software development execution. For the past year they've also tried to shoehorn LLMs anywhere they can.

Of all the ideas proposed so far, not a single one of them needs LLMs or AI to be done and could be implemented with 30 years old tech.

I won't say LLMs aren't more useful than Blockchain, they are, but this is exactly the same situation of all companies trying to find a problem to the "solution" that GenAI is, like they tried to find a problem that Blockchain solves.

Except much bigger companies have invested much more money in GenAI. The bubble burst will be spectacular.
As a former property insurance broker whose clients had big claims ($100Mish) and worked around people who handled the real big claims ($1B+), I can't really tell you with any specificity of how this will play out. All I know is that it will be a huge mess, and the lawyers will argue in court for several years.

Ultimately, someone will have to pay to rebuild the bridge. In the event of really big claims, it almost always end up being whoever has the deepest pockets. The process of discovery will list out who all the owners are and how much their policies cover this claim (whether intentionally or not!).

As counterintuitive as this may sound, the insurance and reinsurance companies are actually pretty well equipped to handle this type of event. The underwriter(s) on the other side of policy will have to report the claim to their boss and the report will show they followed company guidelines. The boss can only shrug her shoulders and say "welp, can't be too mad because this is the business we are in." No one is particularly thrilled about paying the claim, but these situations are exactly why insurance was created. (For context, the "small" claims of $1M -> $10M hurt the most because they are the ones that throw off underwriter's models the most and cause the most unprofitability)
I bought a usb floppy drive, and some old 1.44 floppies, and I thought its just nostalgia, but tbh its just super cool.

I think with esp32s3 and floppies we can make some cool computer kits :) there are also 5" spi displays 800x480 that are pretty fast

There is also a floppy disk music demoscene, and of course the retro computing scene, but I think 'constrained' programming is one of the best ways to learn and it is underused in pedagogy and androgogy. The floppy disk will raise again.

PS: I am working on adding UFI support, it is using CBI to the esp32 mass storage which support only BOT, but its going quite slowly because I am trying to use cheap 4$ logic analyzer to debug and its losing samples :(
Fictional on a surface level. A depiction of fundamental human archetypes if you see beyond it.

And it can't be a strawman as I misrepresented nobody.
You're not going to get "complete privacy" (aka fully-offline local-model-driven) robots outside of building one yourself... There'd be just too much of an economic incentive to use this as a data collection platform.
When will railroad bubble burst?
I think this is going to cause the EU to issue a new set of laws which are even more robust than the current set. Apple seems to be baiting them with their behaviour.
Linkblocks, the Federated Bookmark Manager
Unfortunately they do not market to the US anymore.

"OKI Data Americas has discontinued the sales of all OKI-branded printer hardware in the United States, Canada, and Latin America." (https://www.oki.com/us/printing/index.html)
The attack almost worked because of too few eyes
Great summary, especially since I missed this yesterday. To be honest, it's far above my knowledge, so I'd just like to thank Andres Freund and everyone else for investing their time, effort, and knowledge into keeping all of us secure.
Aren't human beings just token predictors with very specific rules though