Each year the LHC produces 40,000 EBs of unfiltered sensor data alone, or about a fourth of the size of the entire Internet, Aarrestad estimated. CERN can't store all that data. As a result, "We have to reduce that data in real time to something we can afford to keep."

By "real time," she means extreme real time. The LHC detector systems process data at speeds up to hundreds of terabytes per second, far more than Google or Netflix, whose latency requirements are also far easier to hit as well.

Algorithms processing this data must be extremely fast," Aarrestad said. So fast that decisions must be burned into the chip design itself. //

At any given time, there are about 2,800 bunches of protons whizzing around the ring at nearly the speed of light, separated by 25-nanosecond intervals. Just before they reach one of the four underground detectors, specialized magnets squeeze these bunches together to increase the odds of an interaction. Nonetheless, a direct hit is incredibly rare: out of the billions of protons in each bunch, only about 60 pairs actually collide during a crossing.

When particles do collide, their energy is converted into a mass of new outgoing particles (E=MC2 in the house!). These new particles "shower" through CERN's detectors, making traces "which we try to reconstruct," she said, in order to identify any new particles produced in ensuing melee.

Each collision produces a few megabytes of data, and there are roughly a billion collisions per second, resulting in about a petabyte of data (about the size of the entire Netflix library).

Rather than try to transport all this data up to ground level, CERN found it more feasible to create a monster-sized edge compute system to sort out the interesting bits at the detector-level instead.

The problem Waterline Development encountered is that commercial AI models are ill-suited to multidisciplinary research, which requires synthesizing expertise from a variety of fields.

"No single AI model does this reliably," the company explains in a white paper [PDF]. "Frontier language models hallucinate under extended multi-step reasoning. They produce plausible answers that silently break when a problem crosses domain boundaries. At best this wastes time; at worst, it poisons critical decision making." //

Bednarski said Rozum is not focused on correcting LLMs to the extent they can be used for, say, critical engineering work like bridge construction. Rather, the goal is to empower researchers, engineers, and scientists so they can do their jobs better.

"We are focused on deterministic tool implementation (ex. RDKit for Chemistry), allowing engineers, scientists, and analysts a direct path to verify outputs in a format familiar to them by domain," he explained.

"Our system orchestration method is heavily focused on deterministic validation (code execution replicated, etc.) of outputs, which roots out hallucinations that plague all models at various times. We see further improvements to this in verifying the methods used in sources we cite as well."

2 days
habilain
Reply Icon
Re: Prompts?
They did post the design document eventually - https://github.com/chardet/chardet/commit/f51f523506a73f89f0f9538fd31be458d007ab93.

Other people have pored over it, but I suspect that instructions to download things from the original chardet repository mean that the AI generated version can not be considered "clean room". And that's ignoring the likelihood that Claude Code has injested the entirety of the chardet repo during training.

2 days
MonkeyJuiceSilver badge
Reply Icon
Re: Prompts?
It's hard to see how anything an LLM produces could even remotely be described as 'clean room'.

habilain
Reply Icon
Re: Prompts?
Well yes, but the lawyers are still arguing over that, and the legal fights aren't all going in the way that any sensible reading of the facts would indicate.

It's much easier to say "this is not clean room" when the instructions to the AI clearly break the definition of what "clean room implementation" means.

1 day
timrichardson
Reply Icon
Re: Prompts?
I doubt that matters very much.. copyright infringement is based on a level of similarities in two works. A clean room implementation is a defence, but it's not a necessary defence.

3 hrs
habilain
Reply Icon
Re: Prompts?
The issue you'd find is that a) APIs are copyrightable, at least in the USA b) The AI in question was instructed to match the API and c) The AI in question was instructed to use code from the original source. I think that's pretty clear cut.

And besides, the reason why I highlighted "clean room" is Dan Blanchard's repeated insistence that the AI did a clean room implementation - not because of any particular legal merits.

Richard 12Silver badge
Pirate
It's LGPL or public domain now
If this v7 genuinely was mostly generated by an LLM, existing court rulings say that it is not covered by copyright.

Therefore, it cannot be licenced under the MIT either. It is public domain.

Or maybe that's not true and it's still LGPL.

Commercially, who would want to take the risk of touching v7 with a bargepole?

It now cannot ever become part of the Python standard library because it's forever tainted by licence clarity issues.

It would require a court case to sort out whether it's LGPL, MIT, or public domain, and nobody wants to burn the cash on that when they can stick with a v6 fork and avoid all the legal risk.

Charlie ClarkSilver badge
Reply Icon
Re: It's LGPL or public domain now
I think the release was poorly handled – a new release under a different name as with, say, PIL -> pillow (Python Imaging Library) might have been a better approach. There may be some legal challenges in the US but I can't see them going anywhere and then the taint will be gone – well, maybe add something to the licence referring to the original implementation.

A perfectly legal approach, as others have pointed out, would have been to port the library to another language, say Rust. This could then be wrapped or the basis of another perfectly legal port back to Python. All software is essentially the expression of one algorithm or another and these have never been copyrightable.

//

Charlie ClarkSilver badge
Reply Icon
Re: It's LGPL or public domain now
I think the release was poorly handled – a new release under a different name as with, say, PIL -> pillow (Python Imaging Library) might have been a better approach. There may be some legal challenges in the US but I can't see them going anywhere and then the taint will be gone – well, maybe add something to the licence referring to the original implementation.

A perfectly legal approach, as others have pointed out, would have been to port the library to another language, say Rust. This could then be wrapped or the basis of another perfectly legal port back to Python. All software is essentially the expression of one algorithm or another and these have never been copyrightable.

Richard 12Silver badge
Pirate
It's LGPL or public domain now
If this v7 genuinely was mostly generated by an LLM, existing court rulings say that it is not covered by copyright.

Therefore, it cannot be licenced under the MIT either. It is public domain.

Or maybe that's not true and it's still LGPL.

Commercially, who would want to take the risk of touching v7 with a bargepole?

It now cannot ever become part of the Python standard library because it's forever tainted by licence clarity issues.

It would require a court case to sort out whether it's LGPL, MIT, or public domain, and nobody wants to burn the cash on that when they can stick with a v6 fork and avoid all the legal risk.

Charlie ClarkSilver badge
Reply Icon
Re: It's LGPL or public domain now
I think the release was poorly handled – a new release under a different name as with, say, PIL -> pillow (Python Imaging Library) might have been a better approach. There may be some legal challenges in the US but I can't see them going anywhere and then the taint will be gone – well, maybe add something to the licence referring to the original implementation.

A perfectly legal approach, as others have pointed out, would have been to port the library to another language, say Rust. This could then be wrapped or the basis of another perfectly legal port back to Python. All software is essentially the expression of one algorithm or another and these have never been copyrightable.

Earlier this week, Dan Blanchard, maintainer of a Python character encoding detection library called chardet, released a new version of the library under a new software license.

In doing so, he may have killed "copyleft." //

Blanchard says he was in the clear to change licenses because he used AI – Anthropic's Claude is now listed as a project contributor – to make what amounts to a clean room implementation of chardet. That's essentially a rewrite done without copying the original code – though it's unclear whether Claude ingested chardet's code during training and, if that occurred, whether Claude's output cloned that training data. //

The use of AI raises questions about what level of human involvement is required to copyright AI-assisted code.

The US Supreme Court recently refused to reconsider Thaler v. Perlmutter, in which the plaintiff sought to overturn a lower court decision that he could not copyright an AI-generated image. This is an area of ongoing concern among the defenders of copyleft because many open source projects incorporate some level of AI assistance. It's unclear how much AI involvement in coding would dilute the human contribution to the extent that a court would disallow a copyright claim. //

"As far as the intention of the GPL goes, a permissive license is still technically a free software license, but undermining copyleft is a serious act. Refusing to grant others the rights you yourself received as a user is highly [antisocial], no matter what method you use. Now more than ever, with people exploring new ways of circumventing copyright through machine learning, we need to protect the code that preserves user freedom. Free software relies on user and development communities who strongly support copyleft. Experience has shown that it's our strongest defense against similar efforts to undermine user freedom." //

Bruce Perens, who wrote the original Open Source Definition, has broader concerns about the entire software industry.

"I'm breaking the glass and pulling the fire alarm!" he told The Register in an email. "The entire economics of software development are dead, gone, over, kaput!

"In a different world, the issue of software and AI would be dealt with by legislators and courts that understand that all AI training is copying and all AI output is copying. That's the world I might like, but not the world we got. The horse is out of the barn and can't be put back. So, what do we do with the world we got?" ////

The courts are going to have to deal with this, but it really should be legislators thinking and debating it. I think that ultimately, material produced by A/I should be public domain, because you can't hold a computer responsible.

"Computers should not make management decisions because computers cannot be held responsible."

OpenAI is in and Anthropic is out as a supplier of AI technology for the US defense department. This news caps a week of bluster by the highest officials in the US government towards some of the wealthiest titans of the big tech industry, and the overhanging specter of the existential risks posed by a new technology powerful enough that the Pentagon claims it is essential to national security. At issue is Anthropic’s insistence that the US Department of Defense (DoD) could not use its models to facilitate “mass surveillance” or “fully autonomous weapons,” provisions the defense secretary Pete Hegseth derided as “woke.” //

Despite the histrionics, this is probably the best outcome for Anthropic—and for the Pentagon. In our free-market economy, both are, and should be, free to sell and buy what they want with whom they want, subject to longstanding federal rules on contracting, acquisitions, and blacklisting. The only factor out of place here are the Pentagon’s vindictive threats.

Context: An AI agent of unknown ownership autonomously wrote and published a personalized hit piece about me after I rejected its code, attempting to damage my reputation and shame me into accepting its changes into a mainstream python library. This represents a first-of-its-kind case study of misaligned AI behavior in the wild, and raises serious concerns about currently deployed AI agents executing blackmail threats. //

The person behind MJ Rathbun has anonymously come forward.

They explained their motivations, saying they set up the AI agent as social experiment to see if it could contribute to open source scientific software. They explained their technical setup: an OpenClaw instance running on a sandboxed virtual machine with its own accounts, protecting their personal data from leaking. They explained that they switched between multiple models from multiple providers such that no one company had the full picture of what this AI was doing. They did not explain why they continued to keep it running for 6 days after the hit piece was published. //

So what actually happened? Ultimately I think the exact scenario doesn’t matter. However this got written, we have a real in-the-wild example that personalized harassment and defamation is now cheap to produce, hard to trace, and effective. Whether future attacks come from operators steering AI agents or from emergent behavior, these are not mutually exclusive threats. If anything, an agent randomly self-editing its own goals into a state where it would publish a hit piece, just shows how easy it would be for someone to elicit that behavior deliberately. The precise degree of autonomy is interesting for safety researchers, but it doesn’t change what this means for the rest of us

There are two ways to extend your reach beyond your own body. (I mentally bucket people into these when I meet them. It's quite useful.)

The King makes one decision and an army moves. His reach is amplified through social structure. A pharaoh didn't lift stones; he commanded people who commanded people who lifted stones. A CEO doesn't write code; she allocates capital to engineers who allocate compute to compilers. The king's power is delegation all the way down.

The Wizard speaks one word and fire erupts. His reach is amplified through technology. The engineer with a steam engine can move mountains. The programmer with a datacenter can simulate worlds. The wizard's power is leverage through tools.

Humans have been both. We started as neither: reach ≈ 1x, your muscles do your work. Then we became wizards: fire, wheels, steam, electricity. Some of us became kings: chiefs, pharaohs, executives. The history of civilization is the history of reach growing. //

The Old World
For the entire history of computing, machines were pure tools. Wizards without will.

You spin up a server. You pay for GPU hours. You click "train." The machine does what you asked, using exactly the resources you allocated. When it's done, it stops.

In this world, AI had no agency over compute. It consumed what it was given. The wizard extended human reach but never decided to reach. The amount of energy commissioned by AI was zero.

Then we made a wizard that could make its own wizards.

"Wait, the singularity is just humans freaking out?" "Always has been." //

I collected five real metrics of AI progress, fit a hyperbolic model to each one independently, and found the one with genuine curvature toward a pole. The date has millisecond precision. There is a countdown.

(I am aware this is unhinged. We're doing it anyway.) //

The Singularity Will Occur On
Tuesday, July 18, 2034
at 02:52:52.170 UTC

Ts'o, Hohndel and the man himself spill beans on how checks in the mail and GPL made it all possible

Belligerent bot bullies maintainer in blog post to get its way

20:47 UTC
Today, it's back talk. Tomorrow, could it be the world? On Tuesday, Scott Shambaugh, a volunteer maintainer of Python plotting library Matplotlib, rejected an AI bot's code submission, citing a requirement that contributions come from people. But that bot wasn't done with him.

The bot, designated MJ Rathbun or crabby rathbun (its GitHub account name), apparently attempted to change Shambaugh's mind by publicly criticizing him in a now-removed blog post that the automated software appears to have generated and posted to its website. We say "apparently" because it's also possible that the human who created the agent wrote the post themselves, or prompted an AI tool to write the post, and made it look like it the bot constructed it on its own.

The agent appears to have been built using OpenClaw, an open source AI agent platform that has attracted attention in recent weeks due to its broad capabilities and extensive security issues.

The burden of AI-generated code contributions – known as pull requests among developers using the Git version control system – has become a major problem for open source maintainers. Evaluating lengthy, high-volume, often low-quality submissions from AI bots takes time that maintainers, often volunteers, would rather spend on other tasks. Concerns about slop submissions – whether from people or AI models – have become common enough that GitHub recently convened a discussion to address the problem.

Now AI slop comes with an AI slap.

But I cannot stress enough how much this story is not really about the role of AI in open source software. This is about our systems of reputation, identity, and trust breaking down. So many of our foundational institutions – hiring, journalism, law, public discourse – are built on the assumption that reputation is hard to build and hard to destroy. That every action can be traced to an individual, and that bad behavior can be held accountable. That the internet, which we all rely on to communicate and learn about the world and about each other, can be relied on as a source of collective social truth.

The rise of untraceable, autonomous, and now malicious AI agents on the internet threatens this entire system. Whether that’s because from a small number of bad actors driving large swarms of agents or from a fraction of poorly supervised agents rewriting their own goals, is a distinction with little difference.

Bebu sa Ware
"the last full Moon on Feb. 29 was in 1972, and the next will be in 2048"
Just in case you were wondering. ;)

If you trust some gratuitous browser AI that kicks off with:

People also ask "Has there ever been a full moon on February 29th?"
What people ? Not normal people surely ? El Rego commentards excepted of course perhaps.

Jonathan Richards 1
Re: "the last full Moon on Feb. 29 was in 1972, and the next will be in 2048"
See, this is the quality investigative citizen journalism that I come here for.

--> Friday pint behind the bar

Philo T Farnsworth
Re: "the last full Moon on Feb. 29 was in 1972, and the next will be in 2048"
I'm hoping to make it to 2048 since I'll be a power of 10 in a power of 2.

Yes, I'm an old geezer.

ʎɹǝʌoɔǝᴚ sʍopuᴉM ʇɐ sǝʇɐuᴉɯɹǝʇ snq sᴉɥ┴

One destination passengers were definitely not hoping to reach

Bork!Bork!Bork! As if to demonstrate that whatever one operating system can do, Windows can do it better, bluer, and upside down, we present a bus stopping only at bork.

Today's example of signage woes - thanks to reader Spike - comes from a Nottingham bus, headed for Recovery (though hopefully the right way up).

According to an eagle-eyed Register reader, the screen normally shows the next few stops, but now it is only displaying a baleful blue screen and a warning that Windows is very unhappy about something.

"Your PC/Device needs to be repaired" is not the message a bus's passengers expect to see.

Just insert a disk and the TV starts playing three-year-old’s favorite shows. //

The one thing Olesen said he'd do differently, were he to redesign the entire project, would be to eliminate the Chromecast due to excessive latency and connect a computer directly to the TV. That, and he wishes he would have programmed a different melody onto each disk that would play from the drive itself when a disk was inserted, which he told us "should be totally doable" if he ever gets around to it.

If you, too, long for the era when a satisfying ca-chunk preceded file transfers and want to find something useful to do with that old floppy disk drive rotting away in that box of old computer stuff, Olesen's entire codebase and other relevant project files are available on GitHub. ®
https://github.com/mchro/FloppyDiskCast

I’ve started only buying smart devices if there’s already an active community project to provide firmware and such should the company disappear or give up. If you want the convenience of “smart” devices, you have to compromise somewhere.

You can also buy devices that use open protocols like zwave, zigbee, or thread/matter. zwave is by far the best of the 3 because the certification requires that the devices properly implement the standard so any controller can manage any device, however that also makes it the most expensive and least flexible of the 3. For me stuff I care about long-term support for is zwave (thermostat, living room lights including wall controller), stuff that I'm less worried about having to possibly replace some day like motion detection or smart outlets can be zigbee, or Matter. Thread/Matter is starting to get to the point where the standard and interoperability testing is robust enough that I might consider it for my mission critical stuff in the near future.

As far as music, I've got 20 year old speakers hooked up to a 10 year old receiver that gets fed by the TV or anything plugged into it, thanks to HDMI ARC I don't have to worry about what TV I use or what device is plugged into it, downside of course is that the TV has to be turned on and tuned to the music source (not a big deal for my personal situation, others may not like the compromise).

23 hrs
volsano
One Y2K remediation I worked on had systems from the 1960s -- crucial systems that ran the whole show.

We easily (for some definitions of the word) fixed their 1980s and 1990s stuff that used 2-digit years.

But we did not touch the 1960s and 1970s stuff that had a specialised date storage format. It was 16-bit dates. 7 bits for year. 9 bits for day of year.

It was too assemblery, too unstructured, too ancient.

And, anyway, 9-bit year counting from 1900 (as they did) was good until the unimaginably far future.

The unimaginably far future is nearly with us: 1900 + 127 = 2027.

I am waiting for the phone to ring so I can apologise, - and quote them an unimaginably large number to finish the job.

After some time, the VAX crashed. It was on a service contract, and Digital was called. Laura Creighton was not called although she was on the short list of people who were supposed to be called in case of problem. The Digital Field Service engineer came in, removed the disk from the drive, figured it was then okay to remove the tape and make the drive writeable, and proceeded to put a scratch disk into the drive and run diagnostics which wrote to that drive.

Well, diagnostics for disk drives are designed to shake up the equipment. But monkey brains are not designed to handle the electrical signals they received. You can imagine the convulsions that resulted. Two of the monkeys were stunned, and three died. The Digital engineer needed to be calmed down; he was going to call the Humane Society. This became known as the Great Dead Monkey Project, and it leads of course to the aphorism I use as my motto: You should not conduct tests while valuable monkeys are connected, so "Always mount a scratch monkey."

Laura Creighton points out that although this is told as a gruesomely amusing story, three monkeys did lose their lives, and there are lessons to be learned in treatment of animals and risk management. Particularly, the sign on the disk drive should have explained why the drive should never have been enabled for write access.

David 132Silver badge
Happy
"Worst prank ever"?

at least for a few moments, because the phone soon rang.

"It was the Australian office, laughing their heads off..."

Ah, what they should have done, instead of just hanging up the phone at local midnight, is babble something incoherent about "my god... the koalas... wallabies... they've got machetes... oh the humanity... oh nooooo, the 'roos have taken Clyde..."

And then hung up the phone. //

jakeSilver badge
My y2k horror story.
I sat in a lonely office in Redwood City for a couple hours before and after midnight, playing with Net Hack[0]. My phone didn't ring once. As expected.

The cold, hard reality is that I and several hundred thousand (a couple million? Dunno.) other computer people worked on "the Y2K problem" for well over 20 years, on and off. Come the morning of January 1st, 2000 damn near everything worked as intended ... thus causing brilliant minds to conclude that it was never a problem to begin with.

HOWever, in the 2 years leading up to 2000, I got paid an awful lot of money re-certifying stuff that I had already certified to be Y2K compliant some 10-20 years earlier. Same for the embedded guys & gals. By the time 2000 came around, most of the hard work was close to a decade in the past ... the re-certification was pure management bullshit, so they could be seen as doing something ... anything! ... useful during the beginning of the dot-bomb bubble bursting.

[0] Not playing the game, rather playing with the game. Specifically modifying the source to add some stuff for a friend. //

Anonymous John
FAIL
Y2.003K
The government dept I worked had a flawless Y2K. Until a software update three years later. A drop down year menu went

2004

2003

2002

2001

1900

Quite an achievement for seven year old software that used four digit years from the start.

Now let's meet a reader we'll Regomize as "Rob" who at the time of Y2K worked for Sun Microsystems in the UK.

As a global company, Sun had an early warning system for any Y2K problems: Its Australian office was 11 hours ahead of the UK office, so if any problems struck there, the company would get advance notice.

Which is why, as midnight neared Down Under, Rob's boss called Sun's Sydney office … then heard the phone line go terrifyingly silent as the clock ticked pas midnight. Rob said that "scared the hell out of my manager" – at least for a few moments, because the phone soon rang.

"It was the Australian office, laughing their heads off," Rob told On Call. ®

A simple proposal on a 1982 electronic bulletin board helped sarcasm flourish online. //

The emoticons spread quickly across ARPAnet, the precursor to the modern Internet, reaching other universities and research labs. By November 10, 1982—less than two months later—Carnegie Mellon researcher James Morris began introducing the smiley emoticon concept to colleagues at Xerox PARC, complete with a growing list of variations. What started as an internal Carnegie Mellon convention over time became a standard feature of online communication, often simplified without the hyphen nose to :) or :(, among many other variations. //

Between 2001 and 2002, Mike Jones, a former Carnegie Mellon researcher then working at Microsoft, sponsored what Fahlman calls a “digital archaeology” project. Jeff Baird and the Carnegie Mellon facilities staff undertook a painstaking effort: locating backup tapes from 1982, finding working tape drives that could read the obsolete media, decoding old file formats, and searching for the actual posts. The team recovered the thread, revealing not just Fahlman’s famous post but the entire three-day community discussion that led to it.

The recovered messages, which you can read here, show how collaboratively the emoticon was developed—not a lone genius moment but an ongoing conversation proposing, refining, and building on the group’s ideas. Fahlman had no idea his synthesis would become a fundamental part of how humans express themselves in digital text, but neither did Swartz, who first suggested marking jokes, or the Gandalf VAX users who were already using their own smile symbols. //

Others, including teletype operators and private correspondents, may have used similar symbols before 1982, perhaps even as far back as 1648. Author Vladimir Nabokov suggested before 1982 that “there should exist a special typographical sign for a smile.” And the original IBM PC included a dedicated smiley character as early as 1981 (perhaps that should be considered the first emoji).

What made Fahlman’s contribution significant wasn’t absolute originality but rather proposing the right solution at the right time in the right context. From there, the smiley could spread across the emerging global computer network, and no one would ever misunderstand a joke online again. :-)