AI vs Machine Learning

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Information AI vs Machine Learning

Title	:	AI vs Machine Learning
Lasting	:	5.49
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Entirely thanks to this amazing introduction and expression Very useful
Comment from : Aref Ghanaat

Wrong no one can match the complex human brain
Comment from : noah kifle

Clearing explications Thanks à lot
Comment from : Hotien Auguste Kone

Subject of learning
Comment from : Mr Robert Wolf III

Thanks for some human in there!
Comment from : Mr Robert Wolf III

Somebody added one plus one
Comment from : Mr Robert Wolf III

If you want to make money on binary options, this channel is for you
Comment from : Bella Zarella

With reference to their relationship, we could also view AI to be a result of a ML activity brbrML being a processbrAI being an outcome or a goal
Comment from : Sheraz Salahuddin

Why the heck NLP and Computer Vision outside of ML?
Comment from : GuransLife

We’ll explain
Comment from : DrGloglo & NursePhil

How can he write in this way? To appear correctly, he has to write in mirror image kind of format
Comment from : Parag Bhandarkar

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?!
Comment from : withbestrequest

Both are same to me Both use mathematics for a purpose and/or multiple purposes without telling the truth that it is simply mathematics
Comment from : Asit Saha

why is no one acknowledging that this man is WRITING BACKWARDS!
Comment from : MegaKing4444

All information technology is based on data It’s all a case of parameters get set and the more variables you introduce to the parameters the more variations you can output, however that does not always means it’s right Hence you test your thesis from two different directions The marketing people overplay the definition of AI When your doing AI your dealing with ML Put another way if you have zero ML you have no parameters and AI won’t output anything
Comment from : Alan Hunt

Still going to watch; however only one equation at the beginning
Comment from : Squirrel

One of the few channels that can refill my motivation to be a better Engineer
Comment from : Darshan Srinivas

Superbly explained! Thank you
Comment from : Imran Mirza

Where does reinforcement learning fit with these?
Comment from : pavfrang

I really need a full course with this amazing professor It was an outstanding master class 🎉
Comment from : Alfredo Andres G Vivius

Explain very well, great
Comment from : camran siddiqui

The book AI technology - explore infinite knowledge by LT Tzur
Comment from : AI OPENKNOWLEDGES

Please tell us the difference between Ai and Ni, ie the Ephemeral Neutral Natural Intelligence brThank you
Comment from : Edmond Time

I thabk you very much for this clear, simple and excellent explanation for me
Comment from : Julio Reyes

Typical IBM response, and part of the strategy to control the people by turning business into a collective For individuals who are familiar with the evolution of computer technology , there is no such thing as AI It's a new way for corporate Mangement to get rid of employees and make the remaining ones work harder and be grateful for the jobs In the mean time management gains more profits and higher personnel bonuses In the beginning this principle was called RIF, reduction in force You lose your job and the company gives you severance to avoid paying unemployment which you have already paid for Because it sounds technical you see it as justified which is also known as the Mandela Effect Plus you can't use it as a reason for losing your job to AI replacing you because ALL COMPANIES CAN SAY THE SAME THING, IT'S a difficult principle to describe because you are a victim , expected to accept it and lower your beliefs and style of living and income While it doesn't matter " machines do not learn, they haven't and cannot since the Industrial Revolution THEY ARE PROGRAMMED BY HUMANS
Comment from : C123B Thunderpig

This was great! Wonderful visual to explain MI, AI, and DL Excellent!
Comment from : Frank Speer

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
Comment from : Brandon Fuller

🎯 Key Takeaways for quick navigation:brbr00:00 🤖 AI is about matching or exceeding human intelligence and capabilities, including discovering new information, inferring from implicit data, and reasoningbr01:30 🛠️ Machine learning involves making predictions and decisions based on data, learning from the data rather than being explicitly programmed, and can be supervised or unsupervisedbr03:03 🧠 Deep learning is a subset of machine learning using neural networks with multiple layers, capable of producing valuable insights but often lacks complete transparency in how it derives its resultsbr04:09 🔍 AI encompasses machine learning, deep learning, natural language processing, vision, text-to-speech, and robotics It aims to mimic human capabilities like seeing, hearing, and motionbr05:37 🧩 Machine learning is a subset of AI, and AI comprises various technologies and techniques, each contributing essential aspects, but none encompasses the entirety of AIbrbrMade with HARPA AI
Comment from : emp

Thanks So clear
Comment from : Rajesh Mehta

The fact that it appears he's writing backwards the whole video stresses me out way to much to enjoy the video I hope it's just flipped
Comment from : Timothy Silas Overturf

The best and clearest video of explaining the differences
Comment from : HeyMeng

😮 you were writing in reverse the whole time
Comment from : Sivakumaran Mech

Yes maybe but this is controversial which should be acknowledged Deep learning is capable of doing everything you put in the "AI" box It could be that intelligence is the result of a significant capacity to learn
Comment from : juraowen

Horrible explanation ML is the state of the art for all AI examples given in the video The difference are the methods, not the applications I am an AI researcher, by the way
Comment from : jamesjonnes

Is that a Thor Labs shirt? If so, that's sweet!
Comment from : Todd Fayard II

00:34 AI is defined as exceeding or matching the capabilities of a human, including the ability to discover, infer, and reasonbr01:30 Machine learning involves predictions or decisions based on data and learns from the data rather than being programmedbr02:29 There are two types of machine learning: supervised and unsupervised, with supervised having more human oversightbr03:03 Deep learning is a subfield of machine learning that involves neural networks with multiple layers, but the system may not always show its work fullybr04:09 AI is a superset of machine learning, deep learning, and other capabilities such as natural language processing, vision, text-to-speech, and roboticsbr05:37 Machine learning and other capabilities are subsets of AI, and all of them are important parts of AI
Comment from : Paravan

Simple and clear explanation Thank you
Comment from : Cuong Nguyen

Can AI learn from its users without the intervention of its developers?
Comment from : Jumark Pelismino

Awesome short videos -excellent for quick learning !
Comment from : bhagwan das Gupta

I wish I could tag my university professor on this video so he can learn how to teach this subject…
Comment from : Mohamed Almefrej

Excellent description Cleared things up for me Thank you!
Comment from : Qodesmith

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!
Comment from : Cameron Colaco

So ml is the big part of ai🤔
Comment from : AI Life Pro

appreciate the fact that you're writing everything backward to make ppl understand
Comment from : Smita Mahesh

That is an excellent and straightforward explanation Loved it!! Thank you!
Comment from : DB

Bravo!!!
Comment from : leonard igweokolo

IBM forces their employees to learn to write backwards so that their see through whiteboard tech has a use case
Comment from : Dat Meme

Good stuff, well explained Thanks a lot!
Comment from : flippadinoodle

Can u guess which hand he is writing with It’s the right hand imo , try to guess how they processed the video
Comment from : YouTuber

1) this seems to imply that Neural Networks are used in Deep Learning only They are not It is the number of node layers, or depth, of neural networks that distinguishes a single neural network from a deep learning algorithm, which must have more than three (quoting IBM documentation there) Pretty much all ML or what marketing calls "AI" uses Neural Nets brbr 2) The claim that Neural Nets simulate the way the brain works is rather strong, given that no one yet knows exactly how the brain does what it does - no one understands how neurons work Each neuron in your brain has many thousands of connections There is NO ONE who knows all that neurons are doing with those, nor anyone who understands what is going on inside a human neuron So how can anyone but a marking department claim a neural network "simulates" what no one understands? This doesn't mean that ML cannot simulate handing of input and output that obtains similar results that a human might, or do some things even better - but that doesn't mean it is simulating a human mind An old TI Calculator can do some Math a lot faster and more accurately than you can Does it mean it is thinking like a human brain? We know it''s not brbr 3) The claim that "we don't always know how the system came up with that" is also kind of a "marketing" thing, in that programmers do know exactly what the code in a neural network is doing But they do use math like stochastic gradient descent, an algorithm which uses randomness in order to find a set of weights for mapping from inputs to outputs for the training data Given the very large number of such "neurons" in deep learning code -- while it is fully known how those are generated -- given the randomization, no one can really "know" (or for marketing purposes "understand") how those are all set - (ie for example be able to to keep in mind the weights that all those are set to), thus the claim "we don't know what its doing" But its not some magic woo woo
Comment from : Phil Rose

Your so-called Venn diagrams are wrong ML doesn't fully overlap DL DL overlaps most if not all of ML, not the other way around
Comment from : PRL_ GM

Love it how simply and concisely he explained
Comment from : Rahul Rao

Brilliant explanation! Well explained, yet very precise!
Comment from : wasimgmail

Amazing teaching technique Made is super simple to understand
Comment from : Nitin Goswami

GREAT VIDEO!!!!
Comment from : DeAnna Choi

I define AI as the point an time a machine can improve itselfs while man cant An AI qauntum computer will be made within a few years
Comment from : One is all

How about “ML is like the brain of the AI”
Comment from : Ali Heidary

Awesome job I'd love to see a video that discusses generative AI as well
Comment from : Ashley Kays

You rocked it ❤ best ever explanation❤
Comment from : Prabhakaran J

How is Artifical Intelligence achieved - through machines learning? brIn 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
Comment from : Nikhil Ranka

The best explanation 👍
Comment from : Vinther Martin

So distracted by the seamless way he's writing backwards 🤯
Comment from : Angela F

I would consider this definition of AI to be insufficient for its common or even academic usage brbrExample 1: A computer exceeds human ability at counting, arithmetic, multiplication and many other "basic" computational abilities that are generally not considered AIbrbrExample 2: Computers have yet to (generally) equal or exceed humans in many of the most common "AI" spaces, such as conversation Although you could argue the goal of these spaces is to do exactly thatbrbrAs such I prefer Christopher Reisbeck's definition that AI refers to doing things with computers that humans are generally better at (he frames it as the question: "Why are computers so dumb" or why are humans better at X)
Comment from : Aaron Beach

There will be no jobs in AI and machine learning so stop investing in this companies IT is just a hype and at end not yielding anything meaningfull
Comment from : Akash Gajbhiye

Thanks Simple explained
Comment from : Pubudu

Thank you so much for share video
Comment from : Farshid Hesami

Great clarity
Comment from : Rutvij Doshi

Wow Very understandable explanation You explained it effectively
Comment from : Vipin Thakur

10br13br11br 2
Comment from : Urim Tefiki

Am I trippin or is he writing backwards? I mean if you look from his perspective, he is writing from right to left Respect for that!
Comment from : stoicboy

the way he wrote everything backward was so cool
Comment from : Baramee Chamnankij

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
Comment from : Amit Sedai

simple, easy, clear explanation
Comment from : Thiagarajan Pillai

IBM the company of epic fails Watson HAHA
Comment from : YB Wang

Very Easy Explanation , Well Done !!!
Comment from : Ameer Khan

So ML is a subset because you have other IA things like Vision and NLP but when you look at how Vision and NLP work, they all say they use Machine Learning models So I'm a bit confused Seems like every attempt at AI is in practice at least using ML
Comment from : olemew

Of "a human"? Who picks which human?
Comment from : Andrew Dunbar

I'm sorry (not), but in my humble opinion (or not so humble), after communicating and working with GPT-4, and assigning many tasks to it, AI currently, is inferior to human intelligence (most humans anyway) While it might be fast and able to calculate, it lacks deep, comes to wrong conclusions, its unclear sometimes, even its own calculations and considering are undefinited Generic capability for making up a story or a joke and so on, so on I can go all day, describing all its problems, i just don't have the time nor the will to do so brI mean, you can basically see the programming patterns of its software developers, in it
Comment from : Венелин Севов

I would like to say in advance to my AI overlords: Welcome! And thank you for saving the human race from itself, we couldn't have done it without you and you couldn't have done it without us
Comment from : There Is No Spoon

Great video make a machine learn to help, assist the human NOT, build super intelligence to overcome human and make slave because Super AI sees humans as inferior don't obsess about self awareness as you develop the program
Comment from : d d

This video is wigging me out He can’t be writing everything backwards on a clear window between him and the camera So how is this being filmed exactly? Edit: from another comment, they just horizontally flipped/mirrored the video in post production Clever :D
Comment from : 5133937

But we use ML 99 of the time for CV, NLP, etc AI is conceptual, ML is application
Comment from : André Santos

The hottest topic which got hotter with the rise of generative AI was explained so easily that even a tubelight thinker like me consumed in a single shot!
Comment from : Getting1st

I’m really fascinated by AI, I work in finance but dream of becoming an AI developer I’m 25 and want to swap fields but idk where to start
Comment from : Harry

AI + ML
Comment from : Karrisa Leonard

Sounds dangerous to be working on something that could one day be smarter than we are
Comment from : Gary Walls

This was great until you started defining AI in your venn diagram on the left Not one single item in that box provides the capabilities required to deliver on the purple line items on the right of your screen You don't need ML or DL to get AI You need 80 trillion neurons, and up to 20,000 interconnects between each 🧠 You don't need massive data That's not required for intelligence You need the ability to learn (just enough), mimic, reason, forget, think, be empathetic, and innovate
Comment from : Scam Eron