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Comment Re:But what do they do? (Score 1) 3

Ok, to clarify a few things:

Current designs I've put up:

1. A modernised version of the DeHavilland DH98 and Merlin engine, where I basically fed ChatGPT and Claude with all of the known historic faults and some potential solutions to various problems, then let them run wild, feeding off each other to fix, refine, and clarify the various design. The premise here is that we're using known designs with known properties, changing only materials but doing so carefully so as to ensure that the balance is unchanged from the historic design. The aircraft is probably the least interesting part, as it would be very hard to make that safe, but a fully modernised Merlin that starts where Rolls Royce left off is something that could be built with minimal risk and could be quite interesting in its own right.

2. A High Dynamic Range microphone. This basically riffs off assorted physics technologies for measurement and the basic idea in many HDR schemes that you can split an input into the fine detail (essentially an equivalent of a mantissa) and a magnitude (essentially an exponent), producing a design that aught to permit (if it works) the same microphone with no adjustments handling everything from a nearby whisper to the roar of a jet engine -- but with all of the fine detail still captured from that engine.

3. An electric guitar that operates not by magnetic pickups but by accurate mapping of string behaviour in two dimensions via lasers, where this is then turned into an accurate representation of the sound in an external device. So it's not a synth guitar in the classic sense, it's actually modelling the waveform for each string in two dimensions precisely. The reason for doing 2D modelling is that this has the potential for novel behaviours but without an obligation for it to do so.

4. A synthesiser/wave processor that looks at everything that they knew how to do, and allows you to link it together arbitrarily. It is designed in two forms. The first is engineered to match the components, materials, and knowledge available in 1964, so it is something they could have built if sufficiently insane. The second is a modernised extrapolation of that, using modern digital electronics, where I can show that the modern version is a strict superset of any existing DAW, simply because I started with none of the assumptions and metaphors around which DAWs were subsequently designed.

5. Multiband camera. An attempt to build a digital camera that is far smaller and more compact than a 3CCD camera, but (like the 3CCD design) produces a far better picture than a conventional digital camera, where I don't stop at three frequencies but support many, albeit with the limitation that the time required for a photograph is abysmal.

Each design I've put up has a detailed hardware specification (including wiring where appropriate), validation/verification documents, and testing procedures. Software is defined by means of formal software contracts and occasionally Z-like forms. The designs are extremely detailed, although not quite at the level you could build them right there and then. However, the synthesiser is described right down to the level of individual transistors, diodes, and connectors, and the Merlin engine specifies precise materials, expected temperature ranges, material interactions (and how they're mitigated), and other such information.

Again, it's precise but not quite at the point where an engineer would feed comfortable feeding the specifications into an AI, having it order the bits online, and be sure of building something that works, but it's intended to be close enough that (provided the AIs actually did what they were supposed to) that an engineer would feel very comfortable taking the design and polishing it to working level.

If, however, an engineer looking at these designs comes to the conclusion that the AIs were utterly deluded, then obviously they can't handle something as simple as selecting candidate items from ranged data.

Submission + - Mozilla Firefox uses AI to hunt bugs and suddenly zero days do not feel so untou (nerds.xyz)

BrianFagioli writes: Mozilla says it used an AI model from Anthropic to comb through Firefoxâ(TM)s code, and the results were hard to ignore. In Firefox 150, the team fixed 271 vulnerabilities identified during this effort, a number that would have been unthinkable not long ago. Instead of relying only on fuzzing or human review, the AI was able to reason through code and surface issues that typically require highly specialized expertise.

The bigger implication is less about one release and more about where this is heading. Security has long favored attackers, since they only need to find a single flaw while defenders have to protect everything. If AI can scale vulnerability discovery for defenders, that dynamic could start to shift. It does not mean zero days disappear overnight, but it suggests a future where bugs are found and fixed faster than attackers can weaponize them.

User Journal

Journal Journal: Inventions to stress-test AI 3

I have been using AI to see if I could invent non-trivial stuff through recycling existing ideas (because AI is bad at actually creating new things). I've been reluctant to post this in my journal, as I dislike self-promotion, but there's so much discussion on AI and whether it is useful, that this isn't really a matter of self-promotion, but rather evidence in the debate on AI as to whether you can actually do anything useful with it.

https://gitlab.com/wanderingnerd50

Comment Re:The purpose of art (Score 1) 88

Art is a dialogue. It is a conversation between humans--those who feel joy and pain, sorrow and hope;

I can accept art as communication, but how do you consider it dialogue? A dialogue requires the listener to respond in some way, it's a two way communication. How is the listener answering back to the artist?

Comment Re:A serious question (Score 1) 41

It's a good question and one I'm working on trying to get an answer to. By giving AI hard, complex engineering problems, and then getting engineers to look at the output to determine if that output is meaningful or just expensive gibberish.

By doing this, I'm trying to feel around the edges of what AI could reasonably be used for. The trivial engineering problems usually given to it are problems that can usually be solved by people in a similar length of time. I believe the typical savings from AI use are in the order of 15% or less, which is great if you're a gecko involved in car insurance, but not so good if you're a business.

If the really hard problems aren't solvable by AI at all (it's all just gibberish) then you can never improve on that figure. It's as good as it is going to get.

I've open sourced what AIs have come up with so far, if you want to take a look. Because that is what is going to tell you if good can come out of AI or not.

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