D
@wendythedruid @cascheranno okay. I thought about it, and have a potential solution that you can use.
The catch is that there is a small chance you might not like it, so I hesitate to say.
I.e. I said it in my books and even condensing it to fit in 500 characters may take multiple messages.
The short version: to change the tech side of the business, you need to change the human side first.
@cascheranno @wendythedruid like, at some level you are going to need a trusted execution environment as the computational complexity increases. Data storage costs decreasing are one thing, but there is not really a good way to address increasing time and space complexity for algorithms without throwing money at it. And, since the money has to come from somewhere, it is not really feasible to expect a private or small company to have that kind of free cash flow. Hence, Google found their market.
@wendythedruid @cascheranno ...what? okay. Uh. So... you realize that AI is a tool, right? At best, an amalgam of statistics and math. Same type of tool like a sword, an axe, a hammer, or a shovel. Why, exactly, would you expect a sophisticated calculator to have an imagination?
I mean, to be honest, I really do not grasp why the past year or so has been filled with a lot of nonsense about AI having any distinct mind of its own. Like, did everyone magically forget how forecasting works?
@wendythedruid @cascheranno Why? Lack of visibility into what it is actually doing with its integrations? Lack of explanations for its output? I wrote about XAI some years ago, before I started Shaolin Data Services. At the time, there was a big push for explainability in models to address both cases I mentioned here.
...or is it the whole thing about using probabilistic outcomes in a deterministic context?
@wendythedruid interesting. So the actual operational plane in use is "AI as a Service" and not "software"? Very interesting.
@cascheranno @wendythedruid HAHAHA!! Right! Okay. I will admit this was genuinely funny. Same way I should trust GitHub not to leak my private repo data, right?
But no, seriously. That sounds like a great way to prioritize short term ROI over longevity.
@wendythedruid I have a question. The AI that your company uses, is pushing, or whatever. Is it a model that you guys bought, got via open source, or in some way have access to the actual weights / codebase? So to say, is it actually trained specifically on your own internal data / code to accelerate your workflow, or is it somebody else's model that you have a subscription to?
@hannorein hang on. What? How is that a problem? If they were going to cheat, they would have found a method to do so anyway. So to say, students setting themselves up for failure is entirely not a new thing; students have always found methods to circumvent their systems. For example, how many students would ever be trusted by their professors to practice their learned trade? Not many, if any, according to anecdotal evidence or unofficial surveys of STEM professors.
Risk is not a normal distribution. For tech stack risk, the Lognormal distribution is critical for capturing "fat-tail" events. These extreme, low-probability events carry high-impact, existential financial damage that standard models ignore.
Ref: Vizule. (n.d.). How to stop guessing: A Monte Carlo guide.
@sundogplanets @action_jay Heya!
Disclaimer: I am only asking you this question because I feel that you have a better handle on the subject than I do
Does fracking happen in your area? If so, do you know of the legislation around produced water? E.g., Arizona and Colorado (may) only require ~4% of it to be reused whereas the other 96% is left as toxic waste & a new industry to clean and use the water for other purposes (like cooling) would be illegal because of legacy water rights claims
