The Democratic National Committee was watching earlier this year as campaigns nationwide were experimenting with artificial intelligence. So the organization approached a handful of influential party campaign committees with a request: Sign onto guidelines that would commit them to use the technology in a “responsible” way.
The draft agreement, a copy of which was obtained by The Associated Press, was hardly full of revolutionary ideas. It asked campaigns to check work by AI tools, protect against biases and avoid using AI to create misleading content.
“Our goal is to use this new technology both effectively and ethically, and in a way that advances – rather than undermines – the values that we espouse in our campaigns,” the draft said.
The plan went nowhere.
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.