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david_chisnall's posts Back to profile
4 posts total
david_chisnall

I have #Rust, I don't need #CHERI! I have CHERI, I don't need Rust!

No, you need both, they solve different problems and Rust + CHERI solves problems that neither Rust nor CHERI solve alone.

cheriot.org/cheri/myths/2024/0

28 August at 15:39 | Open on infosec.exchange
Saar Amar
Edwin Török

@david_chisnall how quickly can you emulate CHERI on x86-64? (Does qemu support it for example?) If you compile your C code, or language bindings/runtime to a CHERI architecture could that act as a better valgrind/ASAN?
Probably not what you had in mind when designing the hardware, but might be a useful intermediate step until CHERI hardware is widely available.

28 August at 17:45 | Open on discuss.systems
david_chisnall

If cancel culture is so powerful, can we just cancel everything for the next 6-12 months and give everyone a bit of time to recover?

25 August at 10:36 | Open on infosec.exchange
plat

@david_chisnall you can't cancel anything if nothing ever happens

25 August at 10:51 | Open on uwu.social
Sonikku

@david_chisnall I would not mind if taxes were canceled- that would sit very well with me. And the governments around the world too.

25 August at 12:08 | Open on oldbytes.space
MrClon
david_chisnall

Someone recently suggested to me that AI systems bring the users' ability closer to the average. I was intrigued by this idea because it reflects my experience. I am, for example, terrible at any kind of visual art, but with something like Stable Diffusion I can produce things that are merely quite bad, whereas without it I can produce things that are absolutely terrible. Conversely, with GitHub Copilot I can write code with more bugs that's harder to read. Watching non-programmers use it and ChatGPT with Python, they can produce fairly mediocre code that mostly works.

I suppose it shouldn't surprise anyone that a machine that's trained to produce output from a statistical model built from a load of examples would tend towards the mean.

An unflattering interpretation of this would suggest that the people who are most excited by AI in any given field are the people with the least talent in that field.

Someone recently suggested to me that AI systems bring the users' ability closer to the average. I was intrigued by this idea because it reflects my experience. I am, for example, terrible at any kind of visual art, but with something like Stable Diffusion I can produce things that are merely quite bad, whereas without it I can produce things that are absolutely terrible. Conversely, with GitHub Copilot I can write code with more bugs that's harder to read. Watching non-programmers use it and ChatGPT...

21 July at 9:38 | Open on infosec.exchange
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Impertinenzija

@david_chisnall I'm a supposedly decent German writer (or that's what ppl keep telling me) and I think ChatGPT output sucks.

21 July at 15:32 | Open on mastodon.social
Rich Felker

@david_chisnall Thus the management/C-suite being the most excited of all.

21 July at 15:38 | Open on hachyderm.io
MylesRyden

@david_chisnall

I agree with this take on the AI Hype in that, pretty obviously what we have in general AI applications is a regression to the mean.

The real shame is that there are quite a few fields in science where machine learning is really extremely useful in finding patterns in data that might be too subtle for ordinary perception. The hype covers up (for people in the general public) this actual advance.

21 July at 16:00 | Open on social.vivaldi.net
david_chisnall

It’s really not fair to blame CrowdStrike for the outages today. The blame lies with the people in a position to make procurement decisions, who saw a product that added a load of additional code that runs in Ring 0 and though ‘yes, this will make us more secure, I will mandate this must be deployed across the entire company’. A large part of the blame lies with the people who created auditing frameworks that would lead people to believe that this was necessary for compliance.

19 July at 17:21 | Open on infosec.exchange
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