AI vs Machine Learning

Video quality	The size	Download

Information AI vs Machine Learning

Title	:	AI vs Machine Learning
Lasting	:	5.49
Date of publication	:
Views	:	1,3 jt

Thank you for putting this up
Comment from : @Nethanel773

has he practiced writing in reverse so that we could read it correctly? or am I missing some basic logic
Comment from : @dattatraykanaki2469

AI ML haven't found an HIV vaccine, a cure for cancer, a solution to build fusion reactors so nothing has changed Time to move on
Comment from : @charabotte1

Goodbye Machine Learning developer, your services are no longer needed 😂
Comment from : @mariainge2954

How did you write backwards with ease? Did you practice it?
Comment from : @itsjpdelossantos

Comment from : @AlbuquerqueKoller

informative!
Comment from : @tanujthakkar2015

good explanation, but I'm wondering why it would require so much effort to write out the terms he uses, eg, disc or sup
Comment from : @BobWaist

🐢
Comment from : @Esemae

ML is a subset of AI
Comment from : @wulx3i

I am not sure if “infer” is properly explained He said To read data from other sources that hasn’t been stated explicitly Is that it meant ?
Comment from : @revanshraman

After reading for many hours and still not understanding clearly, this short video provided a simple summary Thank you!
Comment from : @hassanlearning4086

Scruffies and Neats
Comment from : @michaeldavis8103

i have also Ai cybersecurity soon not know
Comment from : @Companyellivera

very thanks
Comment from : @qazrj9415

Yes, he is brilliant!!
Comment from : @a320nick

I'm more impressed at his ability to write backwards than the explanation
Comment from : @xpkareem

Naive question, how AI absorbs, analogies and provides information? How is it stimulated? By what or whom? Is the AI simulated by a human who created a model, or it’s naturally this like the way, our DNA are structured by nature?
Comment from : @RickOffical-i9o

All that stuff is easy! Move on with your lives😂😂😂
Comment from : @AlexanderGrant-v9k

That mirror is so clean 😂😂😂 all the nerds in the comments tryin to claim it’s some software 🤣🤣
Comment from : @elliottjameslott

bossss
Comment from : @linlinkaw9662

We make AI simple, impactful, and accessible ❤
Comment from : @GrowStackAi

AI - altruistic imitation
Comment from : @gedbogjid2218

AI subsumes ML
Comment from : @gedbogjid2218

AI…another complete bullshit…how can you make a machine that does what the human mind does when we have basically zero idea of how the mind actually works…?brPlease give this pop-sci promotion a rest…there is massive disinformation going on in the media to make the sheeple believe in fairy tales…and the agenda is to fund ‘busy work’ for a lot of dumb people pretending to be scientists…
Comment from : @patewing5808

I feel like companies are calling anything that looks at data ai now
Comment from : @ryanhakalmazian

No disrespect no diverance they are all from the human imagination
Comment from : @frankthompson6503

AI machines will use CubicWonder and Quad Step Rings because its the most essential system for this Wonderful 3D Geometric Order and not the Chaos Theory Mathematics that is shoved down our throats by the Academics
Comment from : @ThePaulTM

I would say that DL instersect with ML but is not completely contained in ML, although it is completelly contained in AI Take for example DL usage in Reinforcement learning, NLP and computer vision
Comment from : @MrBorest

nice explanation
Comment from : @mantapbetul6686

How did he write backwards? AI (Artificial Intelligence) or BI (Brain Intelligence) 🤔😁
Comment from : @kidsproblemsolving493

Aren't NLP / Vision etc just subset of ML?
Comment from : @Godonstilts

wow its really help i did not know before its really helps
Comment from : @ahsannazir8530

Well said!!! 👏🏾
Comment from : @SarahPoohBear

Aliagents is creating a powerful AI ecosystem, I’m excited to see how this develops
Comment from : @Johnbrownpe

How to record videos like this can anyone explain and give some knowledge about this?
Comment from : @imuniqueshiv

L😮 mmobr😮😮
Comment from : @leonardofarah4697

I think what people call ai today is just a huge excel sheet(/lookup table) and has nothing to do with intelligence
Comment from : @MsFearco

Aliagents is definitely ahead of the curve with their tokenized AI approach, the potential here is huge
Comment from : @JustinBerlowski

So a calculator is AI? methinks not
Comment from : @aiwithaustin

When encoding 4 colours into 10 grids representing the pairs as 2 1's for each row column and subgrid and you infer if a possible 1 is invalid your comparing against pair clues and full clues your not just comparing against full clues this helps find hidden clues
Comment from : @JikeWimblik

al
Comment from : @mohammed-shahrukh-shah

Absolutely wonderful explanation, thank you!
Comment from : @nordoonAI

The issue with that defintion is that human intelligence varies greatly So you're trying to compare it to something that inherently is vastly different in each person
Comment from : @AIHumanEquality

As per my understanding AI is gimmick, machine deep leaning can be more dangerous for human kind Example if u collect data from all source of network connected and commend deep learn to invest my 5k dollars and make it 10k in 30 days , it will with your single concern will invest inside and start manipulating inside by deep multilayer investing in so-many platforms Beware it’s happening,
Comment from : @sweatpassion

Is the instructor writing backwards? How come what he writes is readable by us in front of him?
Comment from : @Chanchanchan169

Lee Elizabeth Martin Robert Martinez Shirley
Comment from : @waynewenashasa8674

147 Taylor Hill
Comment from : @LambAntony

ML is subset of AI
Comment from : @yasiraqueel4175

Non of them are AI, they are all machine learning
Comment from : @BRunner12

Please, Someone have a good class for learn IA and machine learn?
Comment from : @cauemendes9703

Vicky Flat
Comment from : @RoyLisi-u4q

"Unsupervised and finding things that were not explicitly stated" is the space that is going to blow everything up like we can't even imagine Words like Trust, Bias, Ethics and Transparency will drive most AI related human activity in the future Will we have the resolve and government to manage that safely and accept outcomes that highlight our limits, fears, flaws, wokeness and unjust history without full scale sabotage and revolution
Comment from : @12vLife

I know this ain't the point, but he's not writing backwards, have you never seen a mirror people?, jesus christ
Comment from : @HentMas

great explanation!
Comment from : @thecowardlycode

Machine learning is a core component of AI Algorithms enable machines to learn from data, identify patterns, and make predictions
Comment from : @molugusatyapriya2

AI is a superset of machine learning, deep learning, and other capabilities! That's a great thought! At JetSoftPro, a software development service, we believe that everyone needs to understand this technology a little more or turn to technical vendors to use their full power to grow their business
Comment from : @JetSoftProHQ

thank you
Comment from : @ilyasmidou9978

Davis Charles Rodriguez Paul Thompson Shirley
Comment from : @JoeCharlotte

Notes on Artificial Intelligence and Machine Learning br1 Introduction brThe lecture discusses the relationship between Artificial Intelligence (AI) and Machine Learning (ML) brIt addresses common questions about whether AI and ML are the same, different, or if one includes the other 1 br2 Defining AI brDefinition: AI is about matching or exceeding human capabilities and intelligence brKey Aspects: brAbility to discover brNatural language processing brVision (seeing and distinguishing objects) brHearing and audio processing brText-to-speech conversion brMotion and robotics 2 3 4 br3 Understanding Machine Learning (ML) brDefinition: ML involves making predictions or decisions based on data brCharacteristics: brSophisticated form of statistical analysis brImproves with more data input brFocuses on finding patterns and making predictions 5 br4 Deep Learning (DL) brDefinition: A subfield of Machine Learning brKey Features: brInvolves neural networks brModels the way human minds work brUses multiple layers of neural networks (hence "deep") brCan provide interesting insights brMay not always provide clear explanations for its decisions 6 br5 Relationship between AI, ML, and DL brAI is presented as the superset brML is a subset of AI brDL is a subset of ML brOther AI capabilities exist beyond ML and DL 3 br6 Additional AI Capabilities brNatural Language Processing: Understanding and generating human language brComputer Vision: Ability to see and interpret visual information brSpeech Recognition: Understanding spoken language brText-to-Speech: Converting written text to spoken words brRobotics: Enabling motion and physical interaction with the environment 3 4 brKey Takeaways brAI is the broadest category, encompassing various technologies that aim to replicate or exceed human intelligence brML is a subset of AI, focused on making predictions and decisions based on data analysis brDL is a specialized form of ML, using complex neural networks to process information brAI includes additional capabilities beyond ML and DL, such as natural language processing, computer vision, and robotics
Comment from : @mohammadridwanul5916

Good and brief explanation
Comment from : @obadimuadewunmi3127

Think of AI as the broader goal of creating intelligent machines, and ML as a specific approach within that field to achieve this goal by learning from data
Comment from : @mahiaravaarava

Thank You Sir
Comment from : @shgg5996

Ex e
Comment from : @Rampritkumar-vr9ee

Nvqqq x ex
Comment from : @Rampritkumar-vr9ee

ML quantifies AI infers from those quantifications
Comment from : @rmcgraw7943

Beautiful Refined my mental model 10 fold
Comment from : @jorgesanabria6484

which tool the prof is using to record the lecture and write the notes?
Comment from : @khurramaltaf9688

AI vs ML: What's the difference? AI is like a skilled artist, creating and innovating, while ML is a master-apprentice, learning and refining Both collaborate to shape the future
Comment from : @Anusiri-r9s

Finally a a great grasp of it all!
Comment from : @Tooshbaba

Amazing videos on this channel
Comment from : @johnconnor9787

Very well explained
Comment from : @MUHAMMADALI-ij2zg

What's the difference between a sentient ai and a normal AI
Comment from : @BlackReaper-z5n

Thank you for explaining these concepts succinctly ❤
Comment from : @akerenkater8437

Absolutely fantastic You're a great teacher
Comment from : @everettscott4745

Your too smart bro i didnt get shit
Comment from : @faarhaannkhan-kb3vh

❤
Comment from : @drpsrinivasaragavanperum2911

Because
Comment from : @drpsrinivasaragavanperum2911

Understood
Comment from : @drpsrinivasaragavanperum2911

Space
Comment from : @drpsrinivasaragavanperum2911

Thanks
Comment from : @drpsrinivasaragavanperum2911

👏👏
Comment from : @sk3ffingtonai

Almost 6 minutes of effort to derive - ML is part of AI br😅
Comment from : @niltmp7126

Yes, there are indeed a lot of unclear things and people often confuse similar and not quite the same things, and I think it would be appropriate for you to make a video about the ethical side and how generative intelligence is still different from artificial intelligence
Comment from : @insights_universe

Generative AI applications and AGI (Artificial General Intelligence) are distinct concepts within the field of artificial intelligencebrbrGenerative AIbrGenerative AI refers to AI systems that can create content, such as text, images, music, and more These systems use machine learning models, often trained on large datasets, to generate new data that resembles the training data Examples of generative AI applications include:brbrLanguage Models: GPT-4 (developed by OpenAI) can generate human-like text, answer questions, and assist in creative writingbrImage Generation: Tools like DALL-E (also by OpenAI) can create images from textual descriptionsbrMusic and Art: Systems that can compose music or create visual art based on learned patterns from existing worksbrGenerative AI is an example of advanced ANI (Artificial Narrow Intelligence), as it is designed to perform specific tasks within a defined domainbrbrArtificial General Intelligence (AGI)brAGI, on the other hand, is a theoretical concept referring to AI that possesses the ability to understand, learn, and apply intelligence across a wide range of tasks at a human-like level AGI would not be limited to specific tasks or domains; it would have the capacity for general cognitive abilities, reasoning, and problem-solving across diverse situations AGI remains a long-term goal in AI research and has not yet been achievedbrbrKey DifferencesbrScope and Capability: Generative AI is specialized and excels in specific tasks such as generating text or images AGI would have broad, human-like cognitive abilities applicable to a wide range of tasksbrCurrent Status: Generative AI applications are widely available and used in various industries today AGI is still a theoretical concept and has not been realizedbrFocus: Generative AI focuses on creating content based on learned patterns AGI would focus on general understanding and problem-solving across diverse contextsbrIn summary, while generative AI applications represent significant advancements in specific areas of artificial intelligence, they are not the same as AGI The development of AGI involves overcoming substantial scientific and technical challenges and remains a long-term objective in the field of AI
Comment from : @HowlingNinjaWolfGaming