81–90 of 116 posts
This resonates with what I'm seeing in the enterprise adoption layer. The pitch for 'Agentic AI' is enticing, but for mid-market operations, predictability is the primary feature, not autonomy. A system that works 90% of the time but hallucinates or leaks data the other 10% isn't an 'agent', it's a liability. We are still in the phase where 'human-in-the-loop' is a feature, not a bug.
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Modern TEE is actually performant for industry needs these days. Over 400,000x gains of zero knowledge proofs and with nominal differences from most raw inference workloads.
I agree that is performant enough for many applications, I work in the field. But it isn't performant enough to run large scale LLM inference with reasonable latency. Especially not when we compare the throughput numbers for a single-tenant inference inside a TEE vs batched non-private inference.
https://pasteboard.co/k1hjwT7pWI6x.png
reach out if interested in collab.
This isn't an AI problem, its an operating systems problem. AI is just so much less trustworthy than software written and read by humans, that it is exposing the problem for all to see. Process isolation hasn't been taken seriously because UNIX didn't do a good job, and Microsoft didn't either. Well designed security models don't sell computers/operating systems, apparently. That's not to say that the solution is unk…
Recall itself is absolutely ridiculous. And any solution like it is as well. Meanwhile, Anthropic is openly pushing the ability to ingest our entire professional lives into their model which ChatGPT would happily consume as well (they're scraping up our healthcare data now). Sandboxing is the big buzzword early 2026. I think we need to press harder for verified privacy at inference. Any data of mine or my company's g…
Earlier quoted context omitted.
Are there other obvious tradeoffs, in addition to speed, to these more secure OS systems vs status quo?
Yes, money. Making good software is very expensive.
Developers will militate against anything that they perceive to make their life difficult, eg anything that stops them blindly running ‘npm get’ and running arbitary code off the internet.
Recall itself is absolutely ridiculous. And any solution like it is as well. Meanwhile, Anthropic is openly pushing the ability to ingest our entire professional lives into their model which ChatGPT would happily consume as well (they're scraping up our healthcare data now). Sandboxing is the big buzzword early 2026. I think we need to press harder for verified privacy at inference. Any data of mine or my company's g…
Who are we going to press for this (if we're in the US)... the AI companies who have spent the last 3-5 years ingesting all the data they can find, legality be damned?
Or the presidential administration... the only branch of our supposed 3 branch system that hasn't abdicated its own power and who very obviously doesn't give a shit what you think about anything if you have nothing to offer them?
> Microsoft is trying to bring agentic AI to its Windows 11 users via Recall. Recall takes a screenshot of your screen every few seconds, OCRs the text, and does semantic analysis of the context and actions. Good old Microsoft doing microsofty things.
"Hey, you know that thing no one understands how it works and has no guarantee of not going off the rails? Let's give it unrestricted access over everything!" Statements dreamed up by the utterly deranged. I can see the value of agentic AI, but only if it has been fenced in, can only delegate actions to deterministic mechanisms, and if ever destructive decision has to be confirmed. A good example I once read about wa…
Another example might be taking a layperson's description "articles about Foo but not about Bar published in the last two months" and using to suggest (formal, deterministic) search-parameters which the can view and hopefully understand before approving.
Granted, that becomes way trickier if the translated suggestion can be "evil" somehow, such as proposing SQL and the dataset has been poisoned so that it "recommends" something that destroys data or changes a password hash... But even that isn't nearly the same degree of malpractice as making it YOLO everything.
This isn't an AI problem, its an operating systems problem. AI is just so much less trustworthy than software written and read by humans, that it is exposing the problem for all to see. Process isolation hasn't been taken seriously because UNIX didn't do a good job, and Microsoft didn't either. Well designed security models don't sell computers/operating systems, apparently. That's not to say that the solution is unk…
There are two problems that get smooshed together. One is that agents are given too much access. They need proper sandboxing. This is what you describe. The technology is there, the agents just need to use it. The other is that LLMs don't distinguish between instructions and data. This fundamentally limits what you can safely allow them to access. Seemingly simple, straightforward systems can be compromised by this.…
Earlier quoted context omitted.
> If you want the AI to do anything useful, you need to be able to trust it with the access to useful things. Sandboxing doesn't solve this. By default, AI cannot be trusted because it is not deterministic. You can't audit what the output of any given prompt is going to be to make sure its not going to rm -rf / We need some form of behavioral verification/auditing with guarantees that any input is proven to not produ…
Determinism is an absolute red herring. A correct output can be expressed in an infinite amount of ways, all of them valid. You can always make an LLM give deterministic outputs (with some overhead), that might bring you limited reproducibility, but that won't bring you correctness. You need correctness, not determinism. >We need some form of behavioral verification/auditing with guarantees that any input is proven t…
You need both. And there AI models where it's input+prompt+seed that are 100% deterministic.
It's really not much to ask that for the exact same input (data in/prompt/seed) we get the exact same output.
I'm willing to bet that it's going to be the exact same as 100% reproducible builds: people have complained for years "but timestamps about build time makes it impossible" and whatnots but in the end we got our reproducible builds. At some point logic is simply going to win and we'll get more and more models that are 100% deterministic.
And this has absolutely no relation whatsoever to correctness.
