During my AI module at uni a while back, my lecturer (a leading AI researcher) basically said that the huge wave in AI/ML success is basically running AI/ML theories from the AI boom in the 60's and 70's. Now we have the easy access to data and processing power to actually get somewhere with it.
New approaches to AI/ML are rare and tools like TensorFlow basically slow actual innovation.
AFAIK the new stuff is 'just' practical stuff about what structures work better for tasks, and way too expensive for most companies.
Most of the industry still neglects data bias, one of the first things I learned about AI, with urban legends about soviet tanks and sunshine going back to the early days of AI...
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During my AI module at uni a while back, my lecturer (a leading AI researcher) basically said that the huge wave in AI/ML success is basically running AI/ML theories from the AI boom in the 60's and 70's. Now we have the easy access to data and processing power to actually get somewhere with it.
New approaches to AI/ML are rare and tools like TensorFlow basically slow actual innovation.
Can confirm.
AFAIK the new stuff is 'just' practical stuff about what structures work better for tasks, and way too expensive for most companies.
Most of the industry still neglects data bias, one of the first things I learned about AI, with urban legends about soviet tanks and sunshine going back to the early days of AI...