Really??!? What could possibly go wrong.
I'm currently trying to do a large ORC project using Google Vision API, and then Gemini 1.5 Pro 002 to parse and reconstruct the results (taking advantage, one hopes, of its big context window). As I'm not familiar with Google Vision API I asked Gemini to guide me in setting it up.
Gemini is the latest Google model; Vision, as the name implies, is also from Google. Yet Gemini makes several egregious mistakes about Vision, gets names of fields or options wrong, etc.
Gemini 1.5 "Pro" also suggests that concatenating two json strings produces a valid json string; when told that's unlikely, it's very sorry and makes lots of apologies, but still it made the mistake in the first place.
LLMs can be useful when used with caution; letting one loose in an enterprise environment doesn't feel safe, or sane.
Sonnet 3.5 for coding is fine but makes "basic" mistakes all the time. Using LLMs is at times like dealing with a senior expert suffering from dementia: it has arcane knowledge of a lot of things but suddenly misses the obvious that would not escape an intern. It's weird, really.
So if you want accurate results on writing code you need to put all the docs into the input and THEN ask for your question. So download all docs on Vision, put them in the Gemini prompt and ask your question or code on how to use Vision, and you'll get much closer to truth
I've been peddling my vision of "AI automation" for the last several months to acquaintances of mine in various professional fields. In some cases, even building up prototypes and real-user testing. Invariably, none have really stuck.
This is not a technical problem that requires a technical solution. The problem is that it requires human behavior change.
In the context of AI automation, the promise is huge gains, but when you try to convince users / buyers, there is nothing wrong with their current solutions. Ie: There is no problem to solve. So essentially "why are you bothering me with this AI nonsense?"
Honestly, human behavior change might be the only real blocker to a world where AI automates most of the boring busy work currently done by people.
This approach essentially sidesteps the need to have effect a behavior change, at least in the short-term while AI can prove and solidify its value in the real-world.
AI is squarely #1. You can't trust it with your credit card to order groceries, or to budget and plan and book your vacation. People aren't picking up on AI because it isn't good enough yet to trust - you still have the burden of responsibility for the task.
Nobody likes to change a system where they already have their own little comfortable spot and figured it out and just want to seep in the lukewarm there until retirement. Fully understandable. But at least in the private sector this will not save them.