The carbon fiber is a protective overwrap, much like anti-spalling wrap on ballistic armor.
Anthropic is likely training its models with your data. If your data is cruel then the models can become cruel as well.
Considering they likely used credit,
not to review techical documentation to identify design issues
But this is exactly where AI can actually be useful — so long as you don't depend on it to identify all of the design issues. It can review mountains of information and find things in it you might not have caught. You just can't assume that it will catch everything it "should" — that is, what it should be capable of catching is not necessarily what you are capable of catching.
Yes, and it requires a multi-layerd approach to how they system raises issues. One simple prompt pass is not enough, however a multi-tiered approach can increase teh success rate. It'll never catch everything, and neither will a human, the tool is merely a way to remove much of the grunt work searching though documents so teh analyst can focus on what is important and make it easier ot find where things are referenced.
Meanwhile, that periodic report has requirements, so you're going to have to ask it to write the report, then to review it to see if it met the requirements, then to review its own statements about whether it successfully met each requirement, because it won't do any of that sanity checking without being told to do so.
There are two different types of reports to develop - one that validates meeting requirements and one that is merely reporting results or periodic required reporting. The former is challenging, the later a lot less so, and reducing the time spent on the later frees up time for the former. Of course, many such reports do not need AI since they merely compile data, and that is easy to program in any of a number of tools. AI just adds hype and market cap...
Monitor, certainly. But why would they have remote control that can set a FREEZER to 50C?
The manager would.
Been a long time since I've seen a Russian troll doll do the Boris NATO dance.
I guess Yandex's DR sites don't have the latest updates installed.
Given that Russia can't refine crude or deliver fuel and now it's data centers are dropping like flies, they're the ones heading for the bronze age.
Sooner or later, the oligarchs will be showing Putin the window. He's making it hard to make a dishonest buck.
Exactly this. I have experimented with using AI, but absolutely forbid it to actually check in code. I just let it show me it's proposal. It can be useful at that, but often needs to be prodded about criteria it left out and frequently the final result needs a re-write for maintainability at least. It has a tendency to use really convoluted logic which can be greatly simplified without changing the result.
It does much better as a search tool. It's pretty good at finding exactly where some feature is implemented in a large codebase.
While I agree that AI is not truly deterministic, that doesn't mean you will get widely divergent results from teh same data.
Widely? No. Divergent? Yes. Run the same query multiple times and you'll get different answers. The more input you give, the more subtle the differences are likely to be, but there's always a chance it will go completely off its nut and follow some line of "reasoning" that goes someplace utterly unrelated to what you asked for. This is less likely in special-purpose models, but never impossible.
Of course, which is why for special purpose models this can work; especially since you can train it to be more accurate once you have enough real life data. This tool is not likely using the commercial ChatGpt but a bespoke setup.
Tailoring the LLM to taht can save a lot of time for an analyst/engineer/operator by identifying and collecting teh information needed for analysis and reporting
It can't, though, and for two reasons. One, a person is required to check off on the data. Two, LLMs don't faithfully represent data. They ingest it as tokens and then what they crap out is influenced by random numbers produced internally as part of the token selection process. That means a person cannot certify that the data was faithfully reproduced without checking literally every value, because that's simply not how LLMs work.
You can potentially address this with a hybrid approach, where the LLM uses a tool to collect and manipulate the data, but this is shifting the problem to whether the LLM used the tool correctly. It might be more obvious when it doesn't, though, so it might still be a win.
What LLMs seem best at when it comes to text processing, and they are still not infallible, is summarization. But you can't trust its negatives, so it's only useful for identifying other possible positives. That's not worthless, it can help you catch things, but you can't trust it to do the parts you'd most want it to do.
While I agree that AI is not truly deterministic, that doesn't mean you will get widely divergent results from teh same data. There is some run to run variant, but in my experience, working with very specific criteria, it tends to be in the ranking order and not a failure to identify relationships. That can be addressed in a number of ways. While positive hits are easier, negative ones can be checked in a number of ways to increase the confidence level that they truly are negative, in the sense they are not relevant to the tested data set. To me, one of teh keys is to work with a well defined set of criteria, something I think is possible with tehy type of information they are dealing with, especially since much of the input data will be well structured and in a consistent format.
A human must always be the final arbitrator, and needs to realize the AI is not fool proof and you can't accept everything at face value.
I wouldn't want them to be relying on AI to do reviews though. Maybe two AI, looking only for issues and reporting them back, like you can have AI look for security issues with computer code. And a proper review done by a human.
I was think more along the lines of "Here is the periodic report on X" or "Here all the similar events and corrective actions..." to basically act like a research librarian; not to review techical documentation to identify design issues.
You wrap them in plastic carefully first. The cameras are perfectly safe in the protective concrete packaging.
I remember listening in on a great phone call to a network provider about sending someone to pick up their expensive Cisco router. It ended with "in 30 days, it's going in the dumpster.
I personally 'uninstalled' another router by disconnecting the fiber cables...with side cutters. 2 months later, they actually tried to bill us for bandwidth we supposedly used from the completely disconnected router. We sent them a picture.
"Pay no attention to the man behind the curtain." -- Karl, as he stepped behind the computer to reboot it, during a FAT
