Another one that comes to mind constantly is 'The Peripheral'.

https://en.wikipedia.org/wiki/The_Peripheral_(novel)

I'm pretty sure Gibson has a wormhole with a lens attached stashed away somewhere.

Maybe it's time for something like that, a shared baseline standard of "this thing won't spy on you", with massive financial penalties for companies caught lying about it. Prime adoption by making it a requirement for anything bought by the government.

Then consumers can reliably comparison-shop for a "TV" that doesn't turn into a traitorous 1984 telescreen the moment it breaks out of the LAN or you fail to click "maybe later" on its incessant dark pattern pop-ups.

Isn't it high time for legislation that at least makes it clear on the box what kind of sensors and integrations it has and how bad the product is privacy wise?

Also, shouldn't corporate spying disguised as automated content recognition and classification be limited or outright be banned?

And all this connected garbage should by law be able to function with the cord cut and without registration, and if an update negatively changes the advertised product characteristics the customer must be allowed to return it for full paid price even if it is 10 years old. Force the manufactures to make statements on the "box" about the features, the support duration and level, and the privacy characteristics.

Why don't politicians care about this?

Yesterday I joked that claude gave me a cyber stop for asking how to make the anime girl video for an exploit, but it was a thing that happened. Meanwhile im trying to convince people around me that having grok nudify people isnt "fine" just because grok says it is. Its wild where the lines a drawn.

Just what in the hell is happening in the USA?

Unfortunately Wisconsin State Law only gives vague guidelines on this ("must respond reasonably quickly" or something along those lines)

https://en.wikipedia.org/wiki/Monstrous_moonshine

He has a youtube channel with lectures in number theory, category theory and other things.

I believe the normal term is "gaming a benchmark test".

Nothing in what you quoted is related to that. It's a normal way to train and test a classifier.

The only way to determine if it's brittle is to test on a different dataset and look at the sensitivity and specificity.

Even so, there is nothing wrong with a model that is trained to a narrow domain when it doesn't need to deal with "wild" images.

You have to know the right words to ask the LLM to make and train a classifier. You and I already know the words. But they are not actually that trivial to learn for an average joe, and people are lazy.

>These 200 test lesions, and every other photograph of the same lesion or patient, were removed from its data (including the validation set) before training, so it had never seen them, and they were not used to choose the model or set its threshold.

This is just benchmaxxing. A benchmaxxed model will always beat an unbenchmaxxed model, but it will be brittle.

You can always beat a specific dataset with a small model by finetuning on a train/test split. But it doesn't generalize well to 'wild' images, because they are out-of-domain.

They are not. CEOs are.

"It built a machine that turns valuable things into free things, and then pointed it at the businesses it needed to stay alive. That isn’t a revolution."

It is a revolution. Free models are out there. The "toll booths" (software companies) might not survive, but if that's the case, that is the revolution: Because something that you had to pay a massive "toll" for is now essentially free. That might not help the AI companies but it will be a revolution for everyone else that had to pay the tolls, likely making everything cheaper and everyone better off.

(Yes, everyone. Even a very poor person in a highly developed European country lives better than a mildly rich person before the industrial revolution, and I'd say the average person lives at the levels even royalty could barely dream of.)

Even if this bites the AI labs and they don't survive, building software is not going to become significantly more expensive than it currently is with free models that are being sold at cost (barring something major like a global nuclear war), mainly because you can always continue to run the existing models on existing hardware even if progress were to magically stop.

Edit: an earlier statement from Nikon said that he was complying with the investigation and "At this time, we don't see that any rules were violated" https://www.bbc.com/news/articles/ck4gjn1yzprno

It clearly isnt happening.

There are dozens (or hundreds) of functional exploits already. The problem with php2shell exploits is that (as of now) there's no "one exploit pwns all", and researchers need to spend nontrivial amount of time on every (potentially) exploitable target.

So I don't think I agree - it's a fun challenge for the itsec people around here, and some people will definitely try. There's no real opportunity cost here. The only problem is that (as of now) exploiting PHP requires some knowledge about the server configuration, and we don't have that here.

It's one thing to discard it as "numerology and gifs" but it's another to willfully disrupt legal elections in a soverign country.

Or is a decade a really long time and we've all forgotten about Cambridge Analytica?

https://en.wikipedia.org/wiki/Cambridge_Analytica

When you are mostly just shown content that you’ve agreed to see, there’s less of an issue when you see something that offends your particular sensibilities, values, etc. because you agreed to see it, or you went looking for it.

But when the potential content you’ll see can include literally anything, there is a real incentive for the platform to make that content as neutral as possible. Because if you’re shown something that you really don’t like, you’ll stop scrolling and the engagement stats will go down.

With the tutorial, the summary also makes more sense. I have not read the other parts yet, but so far I like what I see.

All is in pretty good taste, and I like what I've seen so far. I do not care if the author himself came up with the idea, or if AI came up with it and the author approved.

I do not understand why you "have to" know this to make use of it. You can judge ideas independently of where they came from (and you should).

Of course Humans can make errors when translating that to English. But if you’ve read any amount of Claudish it should be obvious that interpolating the code to documentation with an LLM typically produces a significantly worse result in almost every way. Except for superficially “sounding” correct.

Even Rust's "enum" feature, which can store different sized things all in the same space, does that at the cost of the smallest variant being just as big as the biggest.

Goose can do all of that not only inline (no pointers), but with variable size, meaning small items take less space. It's like a serialized data representation, but iterable. It makes for big space savings vs these languages.

A lot of the AI discussion seems to be focused on what these tools mean for an individual developer, but in a team setting any gains are at risk due to coordination tax and ideological friction. In my experience the ideological friction is most of it right now.

Figuring out a way to accelerate the process in light of the code writing bottleneck being removed is essential. I've observed a development team regress back to fully manual development because their daily PR/code review process is too slow. It doesn't matter how fast you write code if you can't actually merge it and ship it to the customer faster too. PR stacks can only take you so far before the conflict monster gets too big to fight.

I don't think AI can fix the process, ideology or people issues. I've seen how long an average PR review actually takes. If these employees were simply doing their jobs at all we'd be 10x better off regardless of AI. A truly skilled developer who makes a genuine attempt should be expected to solve 99% of their tasks within the same business day as of October 2026.

Burning down the backlog to zero doesn't mean the development team will be subsequently laid off. Quite the contrary. It will create a vacuum that the business will fill with new work that may incidentally increase the developers' compensation packages. No one is laying off the development team that just chewed through 50 items per day for 3 straight weeks. Who would support all the potential bugs they just created? That's right. They might hire even more developers. This is called a "win-win" scenario. Not every game must be zero sum, but I understand rejection of this possibility to be part of the aforementioned ideological issues.

Any prompt jockey can make a faster ripgrep. The spec is "faster ripgrep".

What is the one thing that only you can specify, where your competitive advantage is maximized? Find that thing and pursue it with all your energy!

Perhaps we should be more ambitious in the types of problems we try to solve, and the types of value we try to provide with the software we build.

"funnily enough, I have some faith in some of the projects that people are the most skeptical of, e.g., every time I see pgrust somewhere, there are a lot of skeptical comments. But, without having looked into the details of what he's optimizing, I would trust that they're not doing something shady with their benchmarks because Michael Malis started the project (and is still involved)"

This aged like milk. pgrust was caught cheating on all benchmarks this week.

Claude in its current Opus 5.5 form has made some wild reaches in response to reasonable-seeming prompts. For instance: "this error is getting swallowed, make sure the real termination message exposes the root cause" -> discovering that the issue is actually in a third party library that isn't exposing the original error except so through logs, so doing some hackery to inject a log-capturer that gets the stdout, buffers it, and looks for the message in order to re-throw based on that...

And it can demonstrate that working, but it's added some fragile and/or unintended consequences like (a) string matching on a particular WARN log message of a particular version of the lib, and (b) buffering those logs such that there were now cases where they would never make it to the actual output stream before the program terminating.

It's certainly capable of being used smarter than that, but it's also really easy to end up with messy fragile stuff if you get lazy about reviewing the output.

> I have a similar thought about "there's no reason for software to be slow" BTW; in many cases, if you use AI to speed up some flow, you will add a bunch of messy code that will be overfit for the use case you tested on and will neither generalize, perf-wise, for all the use cases you should care about, nor will be maintainable upon future changes.

LLMs have hardened hundreds of apps where I work.

Maybe it's a language-specific thing. Most of the time, in Java, LLMs take into consideration tradeoffs (especially if they are part of the initial prompt) and actively explains them. It generally won't make messy workarounds, without a lot of extra prompting forcing it to do so.

Ofc, if you have:

- Functional tests - you'll be able to see it in the execution times of specific APIs

- Stress testing - performance profiling is the most important output artifact

Software is a very clear example on this front. Valheim [1] is a game that was made mostly by one guy, at first at least. Not that long ago, this would have been a multi million dollar game produced by a wide array of people. It's just that tools, markets, and more have made it possible for even single developers to have an absurd degree of efficiency. And LLMs are probably going to bump this up exponentially.

This is why a metaphor I'm currently drawn to is one of people living in a very agrarian society just prior to the Industrial Revolution. What would they have envisioned being created? Super farms of course. And those super farms were indeed created, but the overall impact was such that those super farms became a practically inconsequential part of the overall economy. The future we're moving into isn't going to be the same but more efficient for those on top. That efficiency is going to revolutionize the economy in ways that are probably impossible to see from a distant, much how somebody living in an agrarian society couldn't have even begun to imagine the 'real' impact of the Industrial Revolution.

[1] - https://store.steampowered.com/app/892970/Valheim/

Economic hubs work when there is more efficiency to be found in industrially-codependent resources being located close to each other, than there is in cheaper labor costs outside the hub. Hollywood's heyday was when there was enormous value to putting actors, agents, producers, cameras, sets, editors, VFX, writers all within close driving distance of each other, so that you could organize new movies and shows at the drop of a hat. In a day and age when teenagers are able to use cellphone cameras and pocketmoney to produce stories that are compelling enough to command attention and advertising dollars, the value of that geographic proximity has declined tremendously.

AI didn't build the coffin, but it's been putting nails in it.

To me, the entertainment industry suffers from a lot of the same problems in most other industries that chase "efficiency", in terms of resources used and profit made. Economies and industries and labor are interdependent and more "alive" than balance sheets and bank accounts.

For the film industry, when you start moving things away from LA to "save money", it has knock on effects that happen over long periods of time. Multiple Quarterly Earnings Reports long, if you will. Local businesses that depend on the film industry close due to less work, so then there is less expertise available. Less expertise means it can command high prices. Suddenly it's too expensive to film in LA altogether. So the rest of the jobs leave too.

This pattern seems super common, not just in the film industry.

It is a narrative that interweaves with AI, too. AI is supposedly an efficiency boom. In the macroeconomy, who is the "efficiency" we are chasing for, who benefits? Who is getting the money that was "saved"? Regular people do not have more more money or time. The "efficiency" is for people who are already very rich, to get richer. Is that worth the price we're paying? I know my answer. The article gets close to it by mentioning the consolidation in Hollywood, but I do not see how we fix this without enforcing our antitrust laws. It is embarrassing what we let rich people do in the name of stock price go up.

- get the largest PSU you can find (1500W at a minimum, more is better)

- get the ADT PLX Quad PCIe backplane. Run 4 thin (single slot) GPUs inside your main enclosure, stick the ADT interface board in between two of the thin boards (don't stack them close to each other or they won't be able to breathe).

- ensure you have as much or more RAM as you do VRAM

- Ensure your CPU has enough PCIe lanes to run at least five boards in x16 (four for the GPUs in the main enclosure, another for the PLX PCIe switch)

- In the BIOS set BAR1 to 'resizable' and > 4G decoding should be enabled.

- ditch the cables that come with the ADT board, they may work but there are much better ones out there and they're not expensive, this will save you days of troubleshooting

- Build your own enclosure rather than trying to adapt a standard one, it won't work anyway (the board pitch is wrong, as is the placement of the mounting holes).

- Put another four double or triple boards on the backplane.

- Add another 3x 140 mm fan to the front of the case so you get good airflow without the feeling of being next to a Harrier at take-off

- I used 3D printed parts to mount the PSU and the board as well as the fans (see below).

- Make sure the board is properly grounded to the enclosure

- If you're running 3090's or other cards that are P2P capable that were hobbled by NV then look at this https://github.com/aikitoria/open-gpu-kernel-modules driver module.

- Power on the ADT board, wait three seconds then power on the main machine. Enjoy your VRAM :)

If you have more questions please email me and I'll be happy to help out.

For sake of comparison, consider e-commerce. As a proxy for "impact on the economy", we can use Amazon's revenue. They went public in 1997 and that year had revenue of $148M (just 0.14% of Walmart's revenue that year). By 2000, revenue was $2.76B (1.65% of Walmart). Bricks and mortar didn't start feeling anything until probably 2011, when Amazon crossed 11% of Walmart's revenue. And it wasn't until 2025 that Amazon finally surpassed Walmart.

But, if you worked in tech in the e-commerce business, things were already feeling pretty hot by 2007. And at that point in time, the e-commerce sector was still miniscule compared to traditional retail (~4%). Software is very exciting these days and the most fantastic things are happening. They will eventually percolate out to the rest of the economy. But it will take many years before everyone notices the difference.

Apparently, nanograms / micrograms is enough to create a "antimatter catalyzed" fission/fusion propulsion system with enormous specific impulse / efficacy.

PDF: https://www.niac.usra.edu/files/studies/final_report/1071Bic...

I'm certain there are folks out there who have a hard time with written English that could benefit from an AI editor, but I would almost always rather read casual English written by a human, even if idiosyncratic and "incorrect" sometimes.

And, to be clear: Hard to read English can never be correct, no matter how carefully it follows grammatical rules, and AI often writes hard to read English.

LLM-generated text is hard to understand because while it's perfectly good language that follows valid cognitive and informational patterns, it does not reflect the intent or mental model of another mind.

"Google shipped their" -> "Google shipped its" (I use 'their' to make it clear I'm talking about the people who build features at Google, and not merely about a faceless corporation)

"feature or whatever" -> "feature" ('or whatever' is chosen to tell everyone that I'm not actually sure what the name of the feature is, and I can't really be bothered to figure it out)

"gmail" -> "Gmail" (meh)

"I wrote, it had useful tips" -> "I wrote received useful tips" (if you remove the comma, the pacing changes, the reader doesn't linger on the word 'wrote', and you invite some ambiguity around the writing and the receiving of useful tips. I feel like this suggestion is particularly brain damaged, I simply can't understand my own writing when I make this change)

(and so on. I now write emails in notepad, and copy-paste them into Gmail when I'm done, that's how much the suggestions annoy me).

And pretty much universally, they were awful. It was like somebody had blindly taken an English writing textbook and applied every little helper rule to every clause of every sentence, paying no attention whatsoever to deeper concepts like pacing, drawing attention to key words, and moderating emotion.

And I think that's basically what's going on in all of the frontier models as well. When they are being fine tuned, some reward score is telling them to be concise, not to use filler words, to avoid run-on sentences, etc. And there's no counter-balance in the fine-tuning that looks at the writing and flow as a whole.

My guess is years of RLHF optimized for rater's first impressions of how well-written something was. It uses lists! It has headings! It uses fun phrases like 'smoking gun'! It's long and informative! These things are relatively fast and easy to identify and select as a preference.

But none of this really covers whether the response is _useful for the audience_. If you're not the audience, it can be hard to tell what is and isn't useful.