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With more AI/ML models coming out, how will they be measured for performance, accuracy and efficiency. Also will there be established a format for what AI/ML models will have access to and will there be a way for sites to determine if AI/ML is using them and to what degree. Will there be walled off sites with access charges for information that has real and effective value? Any thoughts on how the AI/ML ecosystem will or might evolve will be appreciated. Nothing is free, someone has to work for it or buy it. What will the future ecosystems look like and how will the evolve. The world is in the very early stages fo the AI/Ml revolution that will change societies entire structure in social, work and government in ways we have yet even imagned. Could the use of AI/ML models replace most educational and professional models we have today? and Any thoughts or comments in this new area would be appreciated.
With more AI/ML models coming out, how will they be measured for performance, accuracy and efficiency. Also will there be established a format for what AI/ML models will have access to and will there be a way for sites to determine if AI/ML is using them and to what degree. Will there be walled off sites with access charges for information that has real and effective value? Any thoughts on how the AI/ML ecosystem will or might evolve will be appreciated. Nothing is free, someone has to work for it or buy it. What will the future ecosystems look like and how will the evolve. The world is in the very early stages fo the AI/Ml revolution that will change societies entire structure in social, work and government in ways we have yet even imagned. Could the use of AI/ML models replace most educational and professional models we have today? and Any thoughts or comments in this new area would be appreciated.
If the output from AI is to your benefit or you are in agreement with it , then it will be considered as performing accuratly end efficently and will be the future.
If the output from AI is to your benefit or you are in agreement with it , then it will be considered as performing accuratly end efficently and will be the future.
Who wants to waste a lot of time picking an AI/ML platform, just like people and businesses look at reputation and ratings before making any major purchases, even minor ones sometimes. Like they have said "Mistakes are human, to really screw up takes a computer" from the early days when the computer ecosystem was well settled. Who wants to waste a large amount of time experimenting with their money when they could look at ratings and others experience?
I'm loosely enabling a "business development" group that is currently evaluating 6 different AI tools to assist with researching and writing business proposals.. 5 are external, 1 is in-house.
The in-house (as you might expect) is a "must do" because of the chance that it gives the company a unique advantage to capture other business. The other 5 are in the category of "seem practical, let's see if they work because we don't want to lose business to others using this tech". I imagine it's pretty similar to other tech curves.
In the case of Business Development AI, it's going to honestly take a few years before they really know which to trust.. if only because (IMO) round 1 is going to be "did we win the contract".. round 2 will then move on to "how much human rework was required".. then round 3 "but did the ones with high rework give us unique insights", etc..
There's going to be a whole lot of trial and error - with clear winners and losers.
As far as "why experiment with their money" - it's a combo of prudent first mover advantage trialing, and more "feely" FOMO.
