<a href="#" class="seekto" data-time="34">00:34</a> AI is defined as exceeding or matching the capabilities of a human, including the ability to discover, infer, and reason. <a href="#" class="seekto" data-time="90">01:30</a> Machine learning involves predictions or decisions based on data and learns from the data rather than being programmed. <a href="#" class="seekto" data-time="149">02:29</a> There are two types of machine learning: supervised and unsupervised, with supervised having more human oversight. <a href="#" class="seekto" data-time="183">03:03</a> Deep learning is a subfield of machine learning that involves neural networks with multiple layers, but the system may not always show its work fully. <a href="#" class="seekto" data-time="249">04:09</a> AI is a superset of machine learning, deep learning, and other capabilities such as natural language processing, vision, text-to-speech, and robotics. <a href="#" class="seekto" data-time="337">05:37</a> Machine learning and other capabilities are subsets of AI, and all of them are important parts of AI.

These IBM shorts have become my go-to to get up to speed on technical concepts quickly. I hope you continue to produce these. Thanks a lot!

Big shout out to the creator for explaining everything so clearly and interestingly, BUT MOST IMPRESSIVE TO ME, WRITING EVERYTHING BACKWARDS. WELL DONE!!!!

Simple, concise and well explained. Best explanation I've come across so far on ML vs AI

Excelent video! Had much difficulties to learn the difference between concepts, with this is sums very clearly and comprehends the difference between those two. The Venn diagram helped a lot to understand and comprehend better thank you very much! Nice content!

I really need a full course with this amazing professor. It was an outstanding master class. 🎉

The first clear and concise explanation of this I've found. Awesome thank you

BY FAR the best explanation I have seen of the concepts and great use of visuals. I have watched over 100 videos on the topics and this is the most concise and clear explanation. Great definitions and visuals. Subscribed.

I love when someone can help clearly define something like here, with precise and not dumbed down descriptions.

The simplest , shortest and clearest explanation I have heard so far. Thank you.

Brilliant simple introductory explanation on AI vs ML. Cheers.

This was great! Wonderful visual to explain MI, AI, and DL. Excellent!

An amazing video and explanation. So easy to understand for those with no background to AI.

Another great video from Jeff and the IBM team.

This actially is very timely since we are seeing a lot of tools just immediately being tagged as an AI. A good example of machine learning are image generators such as Bluewillow which uses datasets.

That is an excellent and straightforward explanation. Loved it!! Thank you!

Very well explained. This is a common confusion and it has been tackled brilliantly. Thanks!

Love how that was explained thoroughly, but I'm also expecting in the future, for touch to be a part of the AI, but that might be for future interactions. I believe that AI integration will be a crucial part, and sending this message to the right audience would greatly impact this through platforms like Cleo that pushes the "Marketing for Good" concept.

Love it how simply and concisely he explained.

This was great! As an instructor, I value plain spoken, logical and imformative presentations. This was all of these!. I was surprised that he didn't expound on neural networks, perhaps that a bit too deep into the weeds, but the context of AI, machine learning, and deep learning was very well presented.

Entirely thanks to this amazing introduction and expression. Very useful

Simple and concise. One of the best and easy to understand explanations on ML and AI. Got me to pause several times as the explanations sounded profound at a time where confusing ideas are being shared across.

Superbly explained! Thank you

I love how simply it's clarified, and I believe people should know the difference. I went for the interview for “AI Intern” at a startup, and later found they were doing ML, but referring to it as AI.

Excellent description. Cleared things up for me. Thank you!

Such a good explanation! Keep it up, editor/producer/director/etc.......!!!

The video and the production quality is insane. I have been on UKposts for so long, but this is the one! History!

Thanks for simplicity and yet short compressive explaination of inter related concepts

perfect explanation of diff between AI and ML, I have seen so far. 👏🏻

The best and clearest video of explaining the differences

Thank you so much Sir for this clarification 👌👍! I'm really impressed with the simplicity in your explanation.

This was so simple! At least now I have an idea of the differences. I think some generative AIs are more of machine learning. Like some of the image generators like Bluewillow or Midjourney.

thank you very much for the simplistic explanation

Clearly explained.

Very good explanation video! Though I personally would not say that all of ML is contained in AI. I'd say that ML is one way of building/creating AI, but not everything done with/for ML would be considered AI.

Explain very well, great

Cette vidéo est géniale, synthétique et structurante , bravo à l'interlocuteur pour cette explication simple et condensée.

Thank you, crystal clear now for the three concepts of AL/ML/DL.

Brilliant explanation! Well explained, yet very precise!

Well explained. It tackles the confusion mathematically. Thanks for sharing.

Awesome short videos -excellent for quick learning !

thanks for bringing that out into the open. i was suggesting to my former boss that we could some form of ml or deep learning to get a machine make parts and self adjust, either threw feedback or vision of the part it was suppose to produce. instead of them taking 4 days to get a machine working. he no clue what i was taking about. i would still like to create a business that implements ml or deep learning on machines that have no pid. Using a raspberry pi and some sensors to measure timing and measure point that can be adjusted.

Absolutely fantastic video! Your clear explanations made complex concepts feel so approachable.

Excellent video! Especially works great to make sales people to understand the concept of AI and its subsets!

Clearing explications. Thanks à lot.

Sir explanation was very clear. The content was really easy to understand. Please talk about reinforcement learning.

Are those videos all one continuous take or the editing is so good I can't notice the cut? Great content, really well explained.

Clear Articulation of the AI and ML and how it related. Hats Off.

Very clearly and precisely articulated!

To sum up, ML is integral part of AI!

Amazing teaching technique. Made is super simple to understand

🎯 Key Takeaways for quick navigation: <a href="#" class="seekto" data-time="0">00:00</a> Artificial Intelligence (AI) aims to match or exceed human capabilities, involving tasks like discovering new information, inferring from various sources, and reasoning. <a href="#" class="seekto" data-time="90">01:30</a> Machine Learning (ML) is a subset of AI, focusing on predictions and decisions based on data, utilizing sophisticated statistical analysis. It learns from data rather than being explicitly programmed. <a href="#" class="seekto" data-time="183">03:03</a> Deep Learning (DL) is a subset of ML, involving neural networks with multiple layers. It can provide valuable insights, but the process may not always be transparent. <a href="#" class="seekto" data-time="249">04:09</a> AI encompasses ML, DL, and more, including natural language processing, vision, robotics, text-to-speech, and motion. It is a superset that covers a broadrange of human-like capabilities. <a href="#" class="seekto" data-time="337">05:37</a> The correct perspective is that machine learning is a subset of AI, emphasizing that when engaging in machine learning or other AI-related activities, one is inherently involved in AI. Made with HARPA AI

Now I understood AI & ML Great explanation

Wow. Very understandable explanation. You explained it effectively.

Thanks for the explanation. I remember back in University we also have a thing in AI subject called Expert System

Danke für die Klärung der Begriffe.

Everything outside the ML box is domain of AI. ML is what is used to make models in each of the domains. Not sure if this classification makes sense. It's like placing gradient descent in the bucket of ML. It's an algorithm which could be used for training an ML model.

Simple and clear explanation. Thank you.

This is explained perfectly. Thank you!

simple, easy, clear explanation

Super knowledgeable! Thank you very much. 😊

The most essential fact, in my opinion, is that AI and ML are literally subsets of " Computer Science. " If you can acknowledge all the abilities of critiquing & becoming a computer scientist then every other subject follows as they all coincide. Correct me if I'm wrong, but CS is basically the Godfather of learning any type of machine learning or artificial intelligence in the technology field. Anyways thanks for this brilliant video, Mr. Crume! Oh yeah, all of these subjects are subsets of us humans, it's funny because AI and ML learn from us just like we learn from each other on a daily basis.

Very Easy Explanation , Well Done !!!

This was very helpful, thank you!

Thank you for presenting a way to think about AI and ML. I have been thinking that the vast number of people talking about AI today are really meaning ML.

Good stuff, well explained. Thanks a lot!

Trust me ! You are only guy in the whole wide world that got the layman question and answered it properly

So informative ,thanks for sharing

Awesome job. I'd love to see a video that discusses generative AI as well.

In a way, we can say AI as a mission i.e, we are trying to achieve human like intelligence in machine which is AI and ML and DL are ways to go for it?

For people who want to know how he is able to write in reverse, so that we, watching the video, could understand, is that they edited it to be a mirror reflection, meaning he actually writes with his right hand.

One of the few channels that can refill my motivation to be a better Engineer

Machine learning, natural language processing, reactive machines, computer vision are all subsets of AI. Thank you for this very helpful video.

Thanks. So clear.

Thanks.. clearly explained

Clear and concise big W 👍

Aren’t NLP, vision etc simply different applications of ML/DL? He makes it sound like they are „something different“. Then how does NLP work or text to speech if not via ML/DL techniques?

Good stuff! More journalists need to watch this type of PSA to stop inadvertently spread misinformation!

Aha 😮 - now I get it, thanks a ton . Very clearly explained

I love AI topic, thanks for sharing such great content 👏

This method used to draw on the board is very successful. Most of the old fashioned board is not efficient because while u are writing something on the table you lose the interaction with listener. For example, You need to turn your back to listener. If you are talking when you are using the board, then the listener's attention is distracted between what you wrote and what you said. If you don't saying anything when you are using board, then there will be weird silence. So, i really liked this style of using board.

I like this definition. Thank you!

Awesome, the Venn diagram wins in explanation power. I'll never forget this.

Great, thx! How does this writing projection tech work, which you use in your videos? I assume you somehow don't need to write mirror text?!

Awesome video!! Wondering how this video is created? Is it done by Surface Pro with some special app?

Thanks! Very interesting!

very good. tks for the content.

This guy is casually writing backwards.

This is BRILLIANT. Great micro-learning - THANK YOU!

That's right. Equating AI to ML only was a global PR campaign involving really huge money. A few distinct features in addition: A common program executes a ready algorithm. AI can generate new algorithms. This is called problem solving. ML can't be equated to neural nets either. Training modifies synapses and creates some structure, but you can do it manually yourself. There are very useful solutions of this kind.

How is Artifical Intelligence achieved - through machines learning? In that case, does this Venn Diagram hold true? Looks like this is a comparison between a goal and the tools used to reach a goal. Would like to understand more.

Very clear explanation, but... May I say I totally disagree with the definition of AI altogether? Why would any kind of "intelligence" be defined as something than can do "at least everything a human being can do"? How is an intelligence connected with the kind of input it can process, or with the capability to move? What about an hypotethical alien who could process, say, electric and magnetic field variation instead of light and sound? Wouldn't he be intelligent because he feeds on a different input than a human being? I'm a bit at a loss here.

Great clarity

but, NLP, computer vision, and robotics it could be a part of ML and/or DL? i mean, it involves using neural networks like CNN, DNN, and RNN in most cases, so i always struggle when try to explain the application of AI except ML and DL?

great explanation!

Thanks for this very much.

Nice trick to "rotate" image left-right so we can see what you write in a non-viceversa mode, but, do not use a wathc on hand, as now looks like your watch is on your right hand :)

Beautifully explained

I know it's something talked about here and there but it's fun to think about how we were ourselves essentially primitive intelligence at one point and got to this stage through trial and error for a big part and now we are learning to essentially replicate ourselves and even exceed our capacities. Interesting and scary.

Great quick explanation