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What is really the difference between Artificial intelligence (AI) and machine learning (ML)? Are they actually the same thing? In this video, Jeff Crume explains the differences and relationship between AI & ML, as well as how related topics like Deep Learning (DL) and other types and properties of each.
#ai #ml #dl #artificialintelligence #machinelearning #deeplearning #watsonx
Video Rating: / 5
brilliant demystifying
The definition given of AI was the definition of AGI.
Makine öğrenmesi direkt çevirince böyle çevriliyor.
Thanks for the video. Would you please compare mathematical optimization vs AI and ML?
humanities are fundamental in these processes! what about NN that manage decision makings? human rights? who's feeding the bias to the algorithms??? great explanation for ppl that are not tech guys like me:) cheers
Machine learning, natural language processing, reactive machines, computer vision are all subsets of AI. Thank you for this very helpful video.
Great job sir
Can AI sit on top of a Graph Theory algorithm to somehow enhance it? The application I am looking at is to apply Graph theory to plan out offshore logistics for the oil and gas industry. It's a very complicated thing to achieve with hundreds of offshore locations and boats/helicopters running 24/7. I can't visualize in my head how AI might fit into the process, but maybe I am missing something?
that pen is mesmerizing
How the F did they make this video? He is writing in reverse
This guy is casually writing backwards.
Writing on my screen, how dare you.
So the present v2.0 “AI trend” is just a fad, what the simple people call “AI” is not really proper AI and still archaic, even with the latest and greatest parallel computing processors. But Machine Learning is becoming a reality and having useful results in business and statistics right now.
very good thank u
This really helped
This was very helpful. Thank you for making this
Simple, subset
Hey how's it going ibm. Jumping on the ai band wagon I, see? I hope this video teaches me something cool.
Edit: This was a good video. If the information is 100% accurate and I'm sure ibm has their t's dotted and i's crossed, then I was on the right path of thinking for AI.
A simple and clunky explanation of some of the most basic concepts, but with some mathematical-looking symbols thrown in to make it look clever, informed, technical or more advanced? I hope this is the IBM marketing department and not the IBM engineering department.
Side note – NPL and sight are pretty rudimentary tasks for a brain. If you're throwing around phrases like "A.I. ≥ ????", then perhaps you should mention such tasks as a system that can propose new and more insightful philosophical or ethical questions than we've come up with yet. For starters. (So many excitable reports of what questions AI can answer – ya know coming up with the questions is the harder part, right?)
In recent times, contemporary AI applications have progressively leaned on machine learning, especially deep learning, to attain noteworthy outcomes across diverse tasks. Consequently, the conventional perspective that considers machine learning as a subset of AI requires a reconsideration.