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Success of implementation is irrelevant. They’ve already proven viability of the technology. Even with failure under Amazon, funding will continue elsewhere.
Actually no ... If there is anything you can count on is the corporation greed
If an initiative is not successful and winds up costing more money, they'll abandon it
The issue is they may keep on pushing while losing money while they think it has potential ... However, AI is about half as effective as they have "sold it" to the public and it's increasingly doubtful they would actually be able to address the hallucination problem
Amazon will abandon it if their implementation does not meet their needs. However, the technology has already proven itself viable in the industry, and the tech will only improve with more time and funding. Someone else will begin where Amazon left off.
How has it "proven itself"?... All the demos shown had been at least partially faked, most AI usage in the wild has produced at least some embarrassing example
At best AI has shown to be a decent programming aid
Not saying it won't have any uses but it's been overhyped to death...
Where I work it was given to "management" and so far all it does is record Teams meetings and produces crappy meeting notes
Warehouse automation has come a long way in the last year. The most notable benefits of AI are in cost of implementation and improvements. Previously, programmers would need to analyze every aspect of every task, and create custom software to meet the needs of the business. Every time the business has a new task, they needed to contact the developers to implement the changes.
Now, AI powered hardware works along side of the employees, learning the task on its own. Over time, it identifies and implements its own efficiency improvements.
This also applies to your own disappointing AI experience. Any successfully programmed AI will be more effective tomorrow than it was yesterday. The more exposure it has to relevant feedback data, the faster it will improve.
I'm not sure LLM model can really "learn" much... they can be tinkered for sure and more/better data fed to them... but at the end of the day, LLM models are just very smart parrots, there is no real "I" in these "AI" models
I assume government employees are talking about AI in general, not exclusively LLMs, ML, or generative AI. They don’t really know the difference in the subcategories anyway.