Neurons Are Slow! – Machine Learning Is Not Like Your Brain #1
Biological neurons are just too slow to be useful for Machine Learning algorithms.
While today’s AI has incredible abilities, it does not display any form of general intelligence the way that humans do. Understanding the limits of Machine Learning and how it compares to the human brain is the key for AI to evolve into its next phase, AGI.
Videos in this series will focus on individual facets of Machine Learning which are impossible or highly unlikely in neurons. Subsequent videos will show that neurons and synapses are not able to represent the signal values with the resolution needed by ML, and how the entire backpropagation process cannot be projected into a biological context.
Rather than accepting Machine Learning as the de facto standard, FutureAI is pursuing alternative approaches and algorithms which will lead to breakthroughs in future technology.
Watch the Full Playlist: https://youtube.com/playlist?list=PLyVWtpGV9fFKuIumWa7Q2tFfED6a0TNg7
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For more information, visit:
https://futureai.guru/
Facebook:
https://www.facebook.com/FutureAI.inc
Twitter:
https://twitter.com/FutureAI_inc
Instagram:
https://www.instagram.com/futureai_inc
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FutureAI is an award-winning, early-stage technology company revolutionizing AI by adding actual real-world understanding. This differs from today’s AI, which analyzes massive data sets, looking for patterns and correlations without understanding any of the data it processes.
FutureAI’s radical software creates connections on its own between different types of real-world sensory input (such as sight, sound, and touch) in the same way that a human brain interprets everything it knows in the context of everything else it knows.
Charles J. Simon, BSEE, MSCS, nationally-recognized entrepreneur, software developer and manager. With a broad management and technical expertise and degrees in both Electrical Engineering and Computer Sciences Mr. Simon has many years of computer experience in industry including pioneering work in AI and CAD (two generations of CAD).
Silicon Valley Entrepreneur, Mr. Simon has co-founded three other pioneering technology companies as president and VP of Engineering.
His technical experience includes the creation of two unique Artificial Intelligence systems along with software for successful neurological test equipment. Combining AI development with biomedical nerve signal testing gives him the singular insight.
#machinelearning #artificialintelligence #technologiesthatthink
Biological neurons are just too slow to be useful for Machine Learning algorithms.
While today’s AI has incredible abilities, it does not display any form of general intelligence the way that humans do. Understanding the limits of Machine Learning and how it compares to the human brain is the key for AI to evolve into its next phase, AGI.
Videos in this series will focus on individual facets of Machine Learning which are impossible or highly unlikely in neurons. Subsequent videos will show that neurons and synapses are not able to represent the signal values with the resolution needed by ML, and how the entire backpropagation process cannot be projected into a biological context.
Rather than accepting Machine Learning as the de facto standard, FutureAI is pursuing alternative approaches and algorithms which will lead to breakthroughs in future technology.
Watch the Full Playlist: https://youtube.com/playlist?list=PLyVWtpGV9fFKuIumWa7Q2tFfED6a0TNg7
________________________________________
For more information, visit:
https://futureai.guru/
Facebook:
https://www.facebook.com/FutureAI.inc
Twitter:
https://twitter.com/FutureAI_inc
Instagram:
https://www.instagram.com/futureai_inc
________________________________________
FutureAI is an award-winning, early-stage technology company revolutionizing AI by adding actual real-world understanding. This differs from today’s AI, which analyzes massive data sets, looking for patterns and correlations without understanding any of the data it processes.
FutureAI’s radical software creates connections on its own between different types of real-world sensory input (such as sight, sound, and touch) in the same way that a human brain interprets everything it knows in the context of everything else it knows.
Charles J. Simon, BSEE, MSCS, nationally-recognized entrepreneur, software developer and manager. With a broad management and technical expertise and degrees in both Electrical Engineering and Computer Sciences Mr. Simon has many years of computer experience in industry including pioneering work in AI and CAD (two generations of CAD).
Silicon Valley Entrepreneur, Mr. Simon has co-founded three other pioneering technology companies as president and VP of Engineering.
His technical experience includes the creation of two unique Artificial Intelligence systems along with software for successful neurological test equipment. Combining AI development with biomedical nerve signal testing gives him the singular insight.
#machinelearning #artificialintelligence #technologiesthatthink
