While what you say may be true for state and local law enforcement, it is not true for federal law enforcement.

https://www.mololamken.com/kno...

"Under Section 1001 of title 18 of the United States Code, it is a federal crime to knowingly and willfully make a materially false, fictitious, or fraudulent statement in any matter within the jurisdiction of the executive, legislative, or judicial branch of the United States."

Actual text of the code:

https://uscode.house.gov/view....

"Â1001. Statements or entries generally

(a) Except as otherwise provided in this section, whoever, in any matter within the jurisdiction of the executive, legislative, or judicial branch of the Government of the United States, knowingly and willfully-

(1) falsifies, conceals, or covers up by any trick, scheme, or device a material fact;

(2) makes any materially false, fictitious, or fraudulent statement or representation; or

(3) makes or uses any false writing or document knowing the same to contain any materially false, fictitious, or fraudulent statement or entry;

shall be fined under this title, imprisoned not more than 5 years or, if the offense involves international or domestic terrorism (as defined in section 2331), imprisoned not more than 8 years, or both. If the matter relates to an offense under chapter 109A, 109B, 110, or 117, or section 1591, then the term of imprisonment imposed under this section shall be not more than 8 years."

This is the statute under which Martha Stewart was sentenced to federal prison.

https://www.nyccriminalattorne...

"The interview isn't about solving the crime they're investigating. It's about creating a new one. When federal agents can't prove the underlying offense, they charge you with lying about it. Martha Stewart wasn't convicted of insider trading - she was convicted of lying to investigators about insider trading she was never found guilty of. The crime she went to prison for was created in the interview room. This is the federal playbook: investigate one thing, charge another. The conversation itself becomes the crime.

18 USC 1001 makes it a federal felony to make false statements to government agents. Five years in federal prison. $250,000 in fines. No oath required. You don't have to be in a formal interview room. You don't have to sign anything. A casual conversation on your front porch counts. Any federal matter, any federal agent, anywhere. And here's what nobody tells you: the agents asking questions usually already know the answers. They're not asking to learn what happened. They're testing whether you'll tell the truth."

I am also not a lawyer, so your mileage may vary.

Thanks for the heads up.

Have you tried setting up something like a whitelist (see below)? I feel like that would make my life a lot better - just having a process that filters out the obvious SEO sites so that I don't have to do it.

https://github.com/searxng/sea...

Two words:

Parallel construction.

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

"An example from one official about how parallel construction tips work is being told by Special Operations Division that: "Be at a certain truck stop at a certain time and look for a certain vehicle." DEA would alert state troopers and they may wait for that certain vehicle and use drug searching dogs to identify illegal drug-related activity, giving the appearance the search was conducted randomly.[4] "

This example also would be a form of evidence laundering. By the time the case is presented to courts, the fact that this all resulted from a warrantless search would be nowhere to be found.

https://techcrunch.com/2026/07...

"The payout will deliver $3,000 per work across an estimated 500,000 works, shared among the authors and publishers who hold rights to them. While the settlement is believed to be the largest in the history of U.S. copyright law, many authors and creators still donâ(TM)t view it as a win.

Thatâ(TM)s because of how the legal question was resolved. Alsup sided with Anthropic on the core issue. He ruled that training an AI model on copyrighted text counts as fair use â" a decision widely seen as a turning point for the AI industry. But the ruling didnâ(TM)t excuse how Anthropic obtained the books in the first place. Anthropic had built its training library from two sources: books it purchased and scanned (fine), and books it downloaded from pirate sites like Library Genesis and Pirate Library Mirror. Alsup found the second method illegal on its own terms and said that piracy question could go to trial; Anthropic agreed to a settlement soon after to avoid a trial and whatever damages a jury might have awarded."

So... it's legal to scan books you own and then use them to train LLMs, but it's not legal to use scans that someone else made (I'll assume in this case, they didn't own the books in question.) Hence... the perverse incentive to buy and re-scan books that might already have been scanned... and the cheapest way of doing it is to chop the spine off.

"Internal Anthropic documents about its plan to scan millions of books, revealed in the copyright lawsuit, donâ(TM)t make clear why the company wanted to destroy the books in the process. A deposition of Tom Harvey, who Anthropic hired to lead the project and who previously helped create Google Books, shows that one company Anthropic contracted to scan the books was Datamation, which offers both âoehigh volume destructive and non-destructive book scanningâ services. In a destructive book scanning process, the spine of the book is cut so the pages can be fed into a scanning machine, which is faster and cheaper than non-destructive book scanning.

Regardless of its original intentions, the federal judge in the copyright lawsuit from authors against Anthropic, William Alsup, found that Anthropicâ(TM)s creation of digital copies of the books was legal specifically because the books were destroyed.

âoeHere, every purchased print copy was copied in order to save storage space and to enable searchability as a digital copy,â Alsup wrote in his ruling. âoeThe print original was destroyed. One replaced the other. And, there is no evidence that the new, digital copy was shown, shared, or sold outside the company.â "

Kind of fucked up that the scan can't be shared (or donated). I imagine in most cases, good copies of these books no longer exist in libraries or in the Library of Congress. With current law, all books that are covered under copyright will eventually fall into the public domain, but this is meaningless unless copies exist for people to redistribute once that limit is reached. Essentially companies are exploiting the monopoly benefit extended through copyright without allowing society to benefit from the material falling into the public domain, which is the implicit contract to using state power to enforce copyright.

Ironically, destroying physical copies in order to comply with the 1:1 rule makes the remaining copies that much more valuable.

My experience thus far with the various LLM chatbots is that they've all been trained with the default idea that users want to one-shot solutions.

A human in a similar situation normally would ask questions to clarify the problem, and attempt to ascertain the level of domain knowledge so that they can intelligently communicate.

Part of the song and dance in forming a prompt is to pre-load the model with all those items, so that you don't burn an obscene amount of tokens for it to finally get to the point where it can be useful. An open ended query can be useful for discovery but only if you're willing to do the legwork to cross-reference against other models and reference material.

To put it another way... most humans are lazy and just want to put in the minimum of work, and are willing to accept a 60% acceptable answer from a bot (basically using it as a search engine replacement). Add the fact that most humans are not domain experts, nor are they able or willing to educate themselves to a minimum standard, they have no way of judging whether the bot answer is even at the 60% standard - instead they do what most people do... if it sounds good, and the bot claims to be an "expert", then they go with that.

I anticipate that models specifically curated for specific domains will become more and more useful. I've seen models plugged into residential and commercial electrical code, for example, to act as an always available code compliance helper for a specific municipality. And, as you point out, as long as you can look up the relevant section of code to verify that the LLM supplied advice is correct, and do the load calculations to make sure the math is correct, you can validate the LLM's answer.

The demand is real... whether they can scale the workload down to actually make money remains to be seen.

Long term there are major benefits to society if they can drive down the cost of energy, cooling, and computational infrastructure to support democratized access to LLMs and diffusion models without bankrupting providers.

In the meantime, I would just settle for a decent search engine that didn't require me to go to page 3 of search results (and forcing me to verify that I'm a human for daring to click to page 2 of the search) to find a relevant link that wasn't SEO spam. You'd think that a university agricultural reference for the public would be in the top rankings when searching for a specific variety of vegetable, but apparently today, that's no longer the case.

Given that many companies do a terrible job of maintaining and refreshing their code base... and that even their production code bases are in perpetual beta... and even before AI they were doing things like discarding their legacy codebase and attempting to rewrite things from scratch (remember Sonos?)... an argument can be made that if you're going to churn out a shitty replacement, but can do it faster, that will still save you money.

https://arstechnica.com/gadget...

"In May, Sonos updated its mobile appâ"to the dismay of many users. With missing features and bugs, customers complained about a loss of functionality and hardware not working the way it should. As Sonos deals with the expensive repercussions, a report from Bloomberg today highlights how Sonos allowed the release of an update so buggy and incomplete as to overturn its goodwill with long-standing customers.

Illustrating how poorly this app update has gone, last month, Sonos CEO Patrick Spence said the company would spend $20 million to $30 million in the short term to get the app where it needs to be (which is, basically, functioning as well as the predecessor) and rebuild customer and partner trust. Sonos also expects to miss its annual revenue target by $200 million. This is partially due to its delay of two hardware releases to focus on the app. Bloomberg noted that âoeSonos shares are down 25% this year.â Annual bonuses and merit-based raises have also reportedly been canceled."

I have no idea how much money Sonos spent before committing to spending an additional 30M, but taking a 200M revenue hit because they couldn't get enough feature parity before shutting off the old servers and disabling the old app seems like a pretty big stick.

"One reason for the appâ(TM)s failure is the outdated code and infrastructure that the prior app was running on. Anonymous employees Bloomberg spoke with claimed that the Sonos appâ(TM)s technical debt had been building up for 20 years before the update.

By the time Sonos decided to update the app in mid-2022, it was dealing with software based on virtually obsolete infrastructure and code languages. As such, the app update âoewas less about introducing new functionality than sorting out the existing mess,â Bloomberg reported.

After decades of the appâ(TM)s inner workings growing stale, the impending release of Sonosâ(TM) long anticipated Ace wireless headphones, which came out in June, made the need for a new app both urgent and necessary. This is because the headphones were made to be on-the-go, differing from Sonosâ(TM) other products, mainly speakers and soundbars relying on home Wi-Fi. This seems to align with comments that Spence made to investors in August. He said that the app update was âoea redesign of the entire systemâ"not only the app but also the player side of our system, as well as our cloud infrastructureâ"and this was a complex undertaking.â"

This sounds like they didn't want to support parallel systems and were hoping that they could migrate everything over before the cutover... and when they failed to make that deadline, they decided (and by they, I mean management, because who else in their right minds would disable functionality to happy customers) to just deep-six the legacy environment without warning instead of transitioning people to a "legacy retention program" with a definite cut-off date in the future.

I guess the moral of the story is, if you have shitty management, having them make fucked up decisions that result in near-immediate feedback is better than having them percolate for a year and then result in no-bonuses / layoffs.

You don't own it.

You can extend this to hardware as well. If you're not allowed to repair or modify something... you don't own it.

The customer already has a high-end, power-managed speakerphone in their pocket.
Nobody needs this object.

They should be making The Orb of All Truth, Facts, and Wisdom,
instead of making Microsoft Intimate Intern - Home Office Edition.

At least OpenAI has that Jonny Ive glass and aluminum money.
No Teenage Engineering plastic trash for them.

I think they feel it would be more like humans communicate. But humans invented blackboards and certainly found them useful to improve communication.

This reminds me of microtransactions.

We're 50 years overdue for an alternate payment clearing system that doesn't take more to process than the payment is worth. Most of the enshittification we've seen due to an eyeball (now attention) based economy could have been sidestepped if we built a system for people to pay on a transactional basis for compute and content.

Funny how the wave of autonomous agents is once again driving people to revisit this stuff.

https://spellboundproductions....

"Thirty years ago, General Magicâ(TM)s Telescript established a foundation for autonomous agents. The vision behind it sounds like today's promises of Agentic AIââ but in fact was actually enabled by the technology from the outset. Telescript didn't ask users to just trust it. Instead, it built deterministic safety into the system itselfâ"Permits that limited resource consumption, Authorities that enforced accountability, an Engine that prevented agents from touching host resources directly."

There's no reason you can't pay in tenths, or hundredths of a cent. It's the same idea as a cryptocurrency ledger, minus the ridiculous overhead of the blockchain. Building out the infrastructure to do that is beneficial to both humans and autonomous agents.

https://x402.org/

So... yay?

This is all about leverage.

You don't wait until your one and only supplier of land decides you need to tithe 50% of your earnings for the privilege of setting up your business before you diversify.

Look at the Strait of Hormuz. The countries with the backup plan (rail built years ago) have an option other than dealing with Iran. The ones that don't suddenly have a problem - a big one.

Datacenters can indeed be built more cheaply on earth... for now. In the event that changes... you want to already have your alternatives tested and ready to be scaled up. Maybe this will all turn out to be just a waste of money that historians will later chalk up to ego.

To put it another way... if you wanted to test an untried technology and attempt to scale it up, would you rather do it while people are throwing buckets of money at you, or would you rather do it when your cash flow is under threat and investors are getting cold feet?

Facebook is not in chronological order.

People do not tell the truth about their motives when answering polls. News at 11.

What in the world are you talking about???