One screen beats four any day
The idea of swapping 4–5 monitors for one huge TV sounded pretty stupid at first. But I can't see myself going back now, though. My computer runs cooler and quieter, my desk isn't buried under stands and cables, and I actually get more done without hunting for windows across different screens. Bigger ended up being better than more. If you're buried in monitors and wires right now, one large display might be the move. It worked for me.

New “computational Turing test” reportedly catches AI pretending to be human with 80% accuracy.

It might have the first-ever version of UNIX written in C

A tape-based piece of unique Unix history may have been lying quietly in storage at the University of Utah for 50+ years. The question is whether researchers will be able to take this piece of middle-aged media and rewind it back to the 1970s to get the data off.

4 days
jakeSilver badge
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Locking MollyGuards.

Available at a sparky supply shop near you; usually under $CURRENCY20 each. //

Sorry for Molly? Nah.
She has a story to tell that nobody else does.

Many moons ago I took my daughter to SLAC on take your kid to work day. At the ripe old age of 9, she had been there many times before and knew the ropes, but I figured she deserved a day out of school.

She told me as we were walking in that it'd cost me ten bucks for her to not push any buttons. I gave her the money.

On the way back out, I told her that it'd cost her ten bucks for me not to tell her mother she was running a protection racket. She made a face and paid up ... and promptly told her mother as soon as we got home. They both still laugh about it :-)

Here's exactly what made this possible: 4 documents that act as guardrails for your AI.

Document 1: Coding Guidelines - Every technology, pattern, and standard your project uses

Document 2: Database Structure - Complete schema design before you write any code

Document 3: Master Todo List - End-to-end breakdown of every feature and API

Document 4: Development Progress Log - Setup steps, decisions, and learnings

Plus a two-stage prompt strategy (plan-then-execute) that prevents code chaos. //

Here's the brutal truth: LLMs don't go off the rails because they're broken. They go off the rails because you don't build them any rails.

You treat your AI agent like an off-road, all-terrain vehicle, then wonder why it's going off the rails. You give it a blank canvas and expect a masterpiece.

Think about it this way - if you hired a talented but inexperienced developer, would you just say "build me an app" and walk away? Hell no. You'd give them:

• Coding standards
• Architecture guidelines
• Project requirements
• Regular check-ins

But somehow with AI, we think we can skip all that and just... prompt our way to success.

The solution isn't better prompts. It's better infrastructure.

You need to build the roads before you start driving.

Backblaze is a backup and cloud storage company that has been tracking the annualized failure rates (AFRs) of the hard drives in its datacenter since 2013. As you can imagine, that’s netted the firm a lot of data. And that data has led the company to conclude that HDDs “are lasting longer” and showing fewer errors. //

Biffstar Wise, Aged Ars Veteran
2y
152
My 320mb (megabyte) IDE IBM hard drive from 1994 still boots Win3.1 and loads Doom II just fine.

Who says older drives are unreliable?

New design sets a high standard for post-quantum readiness.

23 hrs
jakeSilver badge
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Re: If You Don't Patch Your Devices/Software, You're Begging For It
"When I first got into computing there was no such thing as patching"

You must be very old indeed ... Here's a photo of a patched Harvard Mk I program tape that has been patched:

https://upload.wikimedia.org/wikipedia/commons/f/fa/Harvard_Mark_I_program_tape.agr.jpg

One of the first jobs I had in computing partially involved physically cutting paper tape at the correct point(s), and then taping in either more code, or corrected code, or both, or occasionally undamaged paper with the original code after the tape got "eaten" by the machinery. The bits that got taped in were usually hand-punched. Yes, it was called "patching", for what I hope are obvious. //

21 hrs
that one in the cornerSilver badge
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Re: If You Don't Patch Your Devices/Software, You're Begging For It
Jacquard loom cards: sew them up in a different order to patch the pattern on the patch of material.

Ian JohnstonSilver badge
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Many (35?) years ago I had to use a PDP-11 running a copy of Unix so old that one man page I looked up simply said: "If you need help with this see Dennis Ritchie in Room 1305". //

Nugry Horace
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Re: Triggering a Specific Error Message
Even if an error message can't happen, they sometimes do. The MULTICS error message in Latin ('Hodie natus est radici frater' - 'today unto the root [volume] is born a brother') was for a scenario which should have been impossible, but got triggered a couple of times by a hardware error. //

5 days
StewartWhiteSilver badge
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Re: Triggering a Specific Error Message
VAX/VMS BASIC had an error message of "Program lost, sorry" in its list. Never could generate it but I liked that the "sorry" at the end made it seem so polite. //

Michael H.F. WilkinsonSilver badge
Nothing offensive, just impossible
Working on a parallel program for simulations of bacterial interaction in the gut micro-flora, I got an "Impossible Error: W(1) cannot be negative here" (or something similar) from the NAG library 9th order Runge-Kutta ODE solver on our Cray J932. The thing was, I was using multiple copies of the same routine in a multi-threaded program. FORTRAN being FORTRAN, and the library not having been compiled with the right flags for multi-threading, all copies used the same named common block to store whatever scratch variables they needed. So different copies were merrily overwriting values written by other copies, resulting in the impossible error. I ended up writing my own ODE solver

Having achieved the impossible, I felt like having breakfast at Milliways //

Admiral Grace Hopper
"You can't be here. Reality has broken if you see this"
Reaching the end of an error reporting trap that printed a message for each foreseeable error I put in a message for anything unforeseen, which was of course, to my mind, an empty set. The code went live and I thought nothing more of it for a decade or so, until a colleague that I hadn't worked with for may years sidled up to my desk with a handful of piano-lined listing paper containing this message. "Did you write this? We thought you'd like to know that it happened last night".

Failed disc sector. Never forget the hardware.

"If you bring a charged particle like an electron near the surface, because the helium is dielectric, it'll create a small image charge underneath in the liquid," said Pollanen. "A little positive charge, much weaker than the electron charge, but there'll be a little positive image there. And then the electron will naturally be bound to its own image. It'll just see that positive charge and kind of want to move toward it, but it can't get to it, because the helium is completely chemically inert, there are no free spaces for electrons to go."

Obviously, to get the helium liquid in the first place requires extremely low temperatures. But it can actually remain liquid up to temperatures of 4 Kelvin, which doesn't require the extreme refrigeration technologies needed for things like transmons. Those temperatures also provide a natural vacuum, since pretty much anything else will also condense out onto the walls of the container. //

Erbium68 Wise, Aged Ars Veteran
8m
1,829
Subscriptor
The trap and what they have achieved so far is very interesting. I have to say the mere 40dB of the amplifier (assuming that is voltage gain not power gain) is remarkable for what is surely a very tiny signal (and that is microwatts out, not megawatts).
But, as a practical quantum computer?
It still has to run at below 4K and there still has to be a transition to electronics at close to STP. The refrigeration is going to be bulky and power consuming. Of course the answer to that is to run a lot of qubits in one envelope, but getting there is going to take a long time.

We seem to have had the easy technological hits. The steam engine, turbines, IC engines, dynamos and alternators all came with relatively simple fabrication techniques and run at room temperature except for the hot bits. Early electronics began with a technical barrier - vacuum enclosures - but never needed to scale these beyond single or dual devices, and by the time that became a barrier to progress, transistors were already happening and it was then a matter of scaling size down and gates up. The electronics revolution happened at room temperature, maybe with some air cooling or liquid cooling for high powers.

Now we have the issue that getting a few gates to work needs a vacuum chamber at below 4K. Scaling is going to be expensive. And progress in conventional semiconductors will continue.
This approach may be wildly successful like epitaxial silicon technology. But it may also flop like the Wankel engine - the existing technology advancing faster than the initially complex and new technology can. //

dmsilev Ars Tribunus Angusticlavius
16y
6,561
Subscriptor

Erbium68 said:
The trap and what they have achieved so far is very interesting. I have to say the mere 40dB of the amplifier (assuming that is voltage gain not power gain) is remarkable for what is surely a very tiny signal (and that is microwatts out, not megawatts).
But, as a practical quantum computer?
It still has to run at below 4K and there still has to be a transition to electronics at close to STP. The refrigeration is going to be bulky and power consuming. Of course the answer to that is to run a lot of qubits in one envelope, but getting there is going to take a long time.

Compared to a datacenter computing system, it's actually not all that hugely power consuming. In rough numbers, 10-12 kW of electricity will get you a pulse tube cryocooler which can cool 50 or 100 kilograms of stuff down to about 4 K and keep it at that temperature with 1-2 W of heat load at the cold end. That's enough for a lot of 4 K qubits and first-stage electronics. Add in an extra kW for another pump and you can cool maybe 10 kg to ~1.5 K, with about 0.5 W of headroom. A couple more pumps at a kW or so each, some helium3 and a lot of expensive plumbing, and you have a dilution refrigerator, 20 mK with about 20-40 uW of headroom.

Compare that 10-15 kW with the draw from a single rack of AI inference engines.

Notion just released version 3.0, complete with AI agents. Because the system contains Simon Willson’s lethal trifecta, it’s vulnerable to data theft though prompt injection.

First, the trifecta:

The lethal trifecta of capabilities is:

1. Access to your private data—one of the most common purposes of tools in the first place!
2. Exposure to untrusted content—any mechanism by which text (or images) controlled by a malicious attacker could become available to your LLM
3. The ability to externally communicate in a way that could be used to steal your data (I often call this “exfiltration” but I’m not confident that term is widely understood.)
   This is, of course, basically the point of AI agents. //

The fundamental problem is that the LLM can’t differentiate between authorized commands and untrusted data. So when it encounters that malicious pdf, it just executes the embedded commands. And since it has (1) access to private data, and (2) the ability to communicate externally, it can fulfill the attacker’s requests. I’ll repeat myself:

This kind of thing should make everybody stop and really think before deploying any AI agents. We simply don’t know to defend against these attacks. We have zero agentic AI systems that are secure against these attacks. Any AI that is working in an adversarial environment­—and by this I mean that it may encounter untrusted training data or input­—is vulnerable to prompt injection. It’s an existential problem that, near as I can tell, most people developing these technologies are just pretending isn’t there.

Even a wrong answer is right some of the time

AI models often produce false outputs, or "hallucinations." Now OpenAI has admitted they may result from fundamental mistakes it makes when training its models.

The admission came in a paper [PDF] published in early September, titled "Why Language Models Hallucinate," and penned by three OpenAI researchers and Santosh Vempala, a distinguished professor of computer science at Georgia Institute of Technology. It concludes that "the majority of mainstream evaluations reward hallucinatory behavior."

Language models are primarily evaluated using exams that penalize uncertainty

The fundamental problem is that AI models are trained to reward guesswork, rather than the correct answer. Guessing might produce a superficially suitable answer. Telling users your AI can't find an answer is less satisfying. //

"Over thousands of test questions, the guessing model ends up looking better on scoreboards than a careful model that admits uncertainty," OpenAI admitted in a blog post accompanying the release.

ben_s
Any half decent IT department would get an alert if they couldn't ping an AP, and they would have a look at the switch to see that an interface was disconnected, then go and take a look.

They'd then notice a pattern, take a look at the records to see who was connected to any nearby APs at the time, and because you'd have to do it when the office was quiet, fairly soon work out who it was disconnecting them.

Anonymous Coward
You think we don't have a vm on that network that will easily accept additional network interfaces, created with the access point's mac address and ip addresses to fool the monitoring system? Some of us weren't born yesterday.

rIf you really want to confuse people, you can use a $250 spool of fiber and make their computer, which is 50m from the network closet, appear to be 25km farther away. If you can't get your hands on a spool of fiber, but have a box of patch cables and a spare 48 port switch, you can connect the user to port 1 and the upstream switch to port 48, and then put ports 1-2 in vlan 1, 3-4 in vlan 2. 5-6 in vlan 3, etc, and cable ports 2-3, 4-5, 6-7, etc, making his computer 25 hops away from the actual network.

anon for legal reasons.

GeekyOldFart
Three languages
And I'm not talking about programming languages, where most of us are fluent in half a dozen or so.

1: Regulatorian: This is the language of politicians and lawyers. It sets the mandates on banks, hospitals, schools etc. It contains nuances and terms of art that sometimes make a word mean something totally different to what you would infer if you heard it in general conversation.

2: Beancounterese: Spoken by accountantrs, salesmen and middle manglement. It sounds very similar to regulatorian but is sufficiently different in some of its meanings that it's as big a gulf as between old scots and english.

3: Geekian: The language of hard science, mathematics, real-world realities and the only one to use when specifying what a programmer needs to code. Because they will code what you tell them to, and it will work the way this language describes it.

The same word can mean different things in these three languages.

We have to be fluent in all three to accurately interpret requirements and predict what the emerging software will look like, to take error logs and demonstrate to (sometimes hostile) manglement what corrective action is needed and where it needs to be applied.

Michael H.F. WilkinsonSilver badge
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Re: Three languages
It gets worse, as there are quite a few Geekian dialects. I have learnt to speak a couple over the years, and know the word "morphology" can have radically different meanings, depending on whether you are talking to a medical doctor, an astronomer, or an image processing specialist. Great fun when you are in a project with different geeks each speaking their own dialect.

Shirley Knot
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Re: Three languages
Well said!

When writing specs for dev projects and talking to those speaking Regulatorian or Beancounterese it involves finding out what they actually mean, without saying "What the fuck do you actually mean?!" The skill is in performing iterative attempts without making them blow their stacks! The most frustrated person I had to deal with was a lovely chap that'd been doing his thing for decades, in manufacturing/engineering. He knew exactly what he was doing, but couldn't articulate it - quite understandable, not part of his world. Once he understood that I was just a white collar noob and he was the expert he calmed right down and enjoyed going into as much detail as needed. Explosive decompression averted and job done!

Historic interpreter taught millions to program on Commodore and Apple computers.

On Wednesday, Microsoft released the complete source code for Microsoft BASIC for 6502 Version 1.1, the 1978 interpreter that powered the Commodore PET, VIC-20, Commodore 64, and Apple II through custom adaptations. The company posted 6,955 lines of assembly language code to GitHub under an MIT license, allowing anyone to freely use, modify, and distribute the code that helped launch the personal computer revolution.

"Rick Weiland and I (Bill Gates) wrote the 6502 BASIC," Gates commented on the Page Table blog in 2010. "I put the WAIT command in.". //

At just 6,955 lines of assembly language—Microsoft's low-level 6502 code talked almost directly to the processor. Microsoft's BASIC squeezed remarkable functionality into minimal memory, a key achievement when RAM cost hundreds of dollars per kilobyte.

In the early personal computer space, cost was king. The MOS 6502 processor that ran this BASIC cost about $25, while competitors charged $200 for similar chips. Designer Chuck Peddle created the 6502 specifically to bring computing to the masses, and manufacturers built variations of the chip into the Atari 2600, Nintendo Entertainment System, and millions of Commodore computers. //

Why old code still matters
While modern computers can't run this 1978 assembly code directly, emulators and FPGA implementations keep the software alive for study and experimentation. The code reveals how programmers squeezed maximum functionality from minimal resources—lessons that remain relevant as developers optimize software for everything from smartwatches to spacecraft.

This kind of officially sanctioned release is important because without proper documentation and legal permission to study historical software, future generations risk losing the ability to understand how early computers worked in detail. //

the Github repository Microsoft created for 6502 BASIC includes a clever historical touch as a nod to the ancient code—the Git timestamps show commits from July 27, 1978.

Ersatz-11 emulates an entire DEC PDP-11 system in software while running on low-cost PC hardware. It outperforms all of the hardware PDP-11 replacements on the market, outstripping them by a particularly wide margin in disk-intensive applications.

The PDP-11 was, and is, an extremely successful and influential family of machines which has spanned over two decades from the early 1970s through the mid 1990s. This note is an attempt to gather some of the knowledge on this family and present it for the benefit of those who are enthusiasts, curious, or downright confused as to what the -11 was and is, and how it related and still relates to its world.

What operating systems were written for the PDP-11?

Government: 'Trust us, it'll be different this time'

"AI solutions that are almost right, but not quite" lead to more debugging work.