MACHINE INTELLIGENCE IS RED HOT SPACE BUT STARTUPS FACE UPHILL BATTLE
In 'The current state of machine intelligence 2.0', Shivon Zilis stated one of biggest changes seen over past year is startups shifting away from building broad technology platforms with “machine intelligence as magic box” to focusing on solving specific business problems to deliver real value.
So as more enterprises are becoming “machine intelligence literate”, with machine intelligence players having figured how to speak the language of solving a business problem, we have a perfect storm for tremendous upsides. Shivon does a nice job delineating the many ways to go to market (Machine Intelligence In The Real World) but it’s no slam dunk because there’s three significant hurdles to overcome:
Full post here https://re-work.co/blog/guest-steve-ardire-machine-intelligence-startups
Steve, thanks for sharing!
Thx Paul and Mark. Take a look at What Is Machine Intelligence Vs. Machine Learning Vs. Deep Learning Vs. Artificial Intelligence (Ai)? http://numenta.com/blog/machine-intelligence-machine-learning-deep-learning-artificial-intelligence.html by Numenta Jeff Hawkins & Donna Dubinsky Nice characterization and summary table of characteristics of the three different approaches 1) Classic AI Approach <<< nice velvet glove smackdown of @ibmwatson 2) Simple Neural Network Approach <<< getting very crowded 3) Biological Neural Network Approach <<< this approach has most upsides with Nice summary table of characteristics of the three different approaches