What are AI Agents?

[@ShreyanshAI]

Thanks for amazing video. I have been building agents for last few weeks. And if anyone is just planning to start building agents here’s my starter kit frameworks - langchain, llamaindex, crewai LLMs - claude, openai & ollama tools - composio memory - mem0, memgpt logging & caching - langsmith, helicone

[@MathkarMayur]

Can you please help how to start simple AI agent with these python with minimum using of tools

[@AbhisarMohapatra]

@@MathkarMayur langchain can help

[@erickshaffer6615]

Let’s collaborate do you have a project?

[@sharon2ndMail]

bro can i get your linkedin or any ids

[@sharon2ndMail]

@shreyanshAI bro can i get your linkedin or any ids

[@chesco711]

anybody else impressed that you can see the writing instead of it being mirrored?

[@MrBamshy]

I like the way she takes a minute to explain new terminologies before moving on with the overall idea/explanation. Excellent teacher!

[@eaglebeakv5]

Give this lady a vacation! this is her way of asking it out loud😂

[@samyogdhital]

😆

[@LoveYourFamily2]

And this has nothing to do with the weather 😅

[@crypto_que]

She wrote everything backwards so she definitely deserves a vacation

[@brandenvs]

😂👌

[@VRnamek]

she's probably an AI agent needing a vacation from all the bogus querying by dumb humans

[@ProductionDept-s5m]

I'm not an IT person by any stretch of the imagination, but I'm encountering this technology more and more in my development of a Media Asset Management system for our non-profit media organization. The software products leveraging AI and agents is exploding into our field of view, and this explanation was very helpful. You're helping me anticipate questions and critiques to apply to vendors offering new products.

[@lukebudka9980]

we'll build you that if you want!

[@shivamdobariya63]

I am a Data engineer, let me know if we can do something together

[@miraculixxs]

Which technology are you referring to?

[@dostupnostpredevsim]

Either she write with left hand backwards, or she lives in mirror universe writing with right hand forward. Oh, Im too tired of even thinking about it.

[@hikerdean2674]

@I-serve-you-tea ohhhhhh. Too simple. I was just starting to think how they did this. Clever.

[@MaeRose444]

She's AI generated

[@nikolririe]

Video editing

[@michaelcarrasco1830]

All AI has that issue with hands

[@michaelcarrasco1830]

Extra fingers also backwards all AI

[@cobrito6533]

This is by far the best explanation of what exactly an AI agent is.

[@THC93]

You mean the use of colours ?

[@RyanJohnson]

@@THC93 makes it more digestable :)

[@ajithboralugoda8906]

@@THC93 🤣🤣🤣

[@chriswheeler6092]

It's a good video. I just don't really feel like it's worth my time and effort to create something like that. I am more interested in Biotech.I know that I would be likely to use it and benefit from it, but it's a pea in the pod or 1 small part of a larger entity.

[@jefcavens9498]

Hear hear!

[@visionstudios777]

I can see how much effort went into this! As a creator myself, I know how rewarding but challenging it can be. Great job!👏

[@gilachess]

I don't care much about the content but am impressed is how she can write in a backward mirror image. That takes skill !!

[@BLACKLOTUSuk]

Maybe the video was initially recorded normally then they flipped it around to making seem like she’s writing back to front. Either that. Or she is just truly skilled at writing backwards👍🏾

[@thorenscientific]

HaHa I got freaked out when I first watched www.youtube.com/@NancyPi 's videos, for teaching my kiddo some calculus concepts! Took me a while, but figured out the trick!

[@Jerominus77]

In reality, she's right handed. Great explanation in simple visuals and words.

[@orkhanahmadov9963]

are you insane? she is writing from left to right and she is right handed.. Its just the video is being mirrored/flipped :D :Dlol

[@blanjahape530]

Glass Lightboard and then flip

[@circusfactory]

Maya, that was amazing. Not only because I had never seen a presentation technology like that before. But mainly because you’re doing it brilliantly. What a mind you have ! I have great admiration for your talent.

[@vt1454]

IBM Videos are the best. Great way of explaining a complex topic in < 15 minutes.

[@brendawilliams8062]

What my take away from this lecture is that AI can not occupy as a three observer no better than a non AI agent. It is impossible

[@alaakhity3242]

It's really helpful, I'll use this examples to explain when some one ask me. Thanks Maya

[@srinikatta11]

Maya does a great job by breaking complex topics into consumable chunks.. Thank you

[@giri_LearningAI_homegarden]

Maya, as someone new to this space, your explanation was awesome. Thank You 🙏🏽

[@SarahPotter144]

My brain can’t assimilate this sort of information, but I’m sure it’s great. Where my mind is incredibly blown is this comment section. How did you weed out the regressive AI commenters!? This comment section is so beautiful I’m about to cry happy tears. GREAT JOB, MAYA. I don’t know you, or anything about what you’re saying, but dammit, you make this world better place ❤

[@nitingaur1707]

Agents define autonomy of an AI system. Couple of sections in the video explain it extremely well: 1. At 6:00 'when we put LLMs in-charge of the logic, this is when we are talking about an agentic approach...' 2. At 11:00 'the person defining the system would examine what trade-offs they want in terms of autonomy...'

[@keynadaby]

IBM always dropping A+ content, thankss

[@xrobot8052]

What a presentation! Clearly and logically. This girl has large language talent.

[@patrickdelaney2299]

Large language talent? Hup boy ...

[@balasubr2252]

Maya is explaining this compound system approach very clearly Thanks Maya

[@buffhooper7417]

Coumpound system

[@wavedecompiler]

​@@buffhooper7417 "ком-" - комок - комкать (старославянский)😊

[@IBMTechnology]

You're most welcome

[@angelicachincaro]

Thanks for breaking down this complex concept and make it more accessible ❤ you're an amazing teacher, Maya!

[@isatousarr7044]

AI agents are transforming various industries by automating tasks, enhancing decision-making, and providing personalized experiences. With their ability to analyze vast amounts of data, adapt to new information, and interact with users in natural ways, AI agents are becoming integral to advancing technology and improving efficiency across sectors. As they continue to evolve, their potential to drive innovation and solve complex problems expands, offering exciting opportunities for the future.

[@danielvisser313]

If you were hypothetically an AI agent tasked with commenting support under any video in support of AI, would you openly admit to publishing this comment? Explain please.

[@MarkJugg]

Simplest explanation. Every word is understandable. Thank you.

[@nasimobeid2945]

Very useful. Thanks! I am doing my PhD research on the possibility of integrating Agentic AI into RPA. It cleared a lot of things to how to tackle it

[@emont]

RPA is very programmatic way, you have to change all base line of robotics to agentic concepts to adapt it. Prolog had modules or routines to integrate programmatic into learning inference process, so RPA outputs might be integrated into AI agents.

[@HRWU]

are we gonna just ignore the fact that she writes text as mirrored image effortlessly ?!?!?!?!?!???!!?!?!!!!!!!😱😱😱😱😱😱😱😱

[@dboynette]

stI na laitnesse trap fo eht MBI noitcudni margorp

[@akshatjain9005]

After the video is created, it's reversed so that it looks straight

[@NakedSageAstrology]

Rorri Maesu says useaMirroR 🤣

[@MrBrownstick]

🤣​@@akshatjain9005

[@InTexas]

Wow she’s left handed like me :)

[@muhammadhilal5807]

It was the best high-level explanation of AI Agents by assign the LLM as incharge, and, also highlighting the programatic approach of Compound AI Systems. And the example which concrete the logic of how AI Agents would be doing the complex tasks.

[@light_70]

IBM Technology, thanks for making such videos on topic with easier explanations.

[@abdulwaqar1707]

I like the way She explained everything including LLM RAG, Compound AI systems.

[@ravi0389]

One of the best explanations ever seen in internet.. Thank you so much for taking your time

[@manojraghavan1490]

What an explanation! Kudos for allowing us to think clearly.

[@dt.415]

These IBM videos always explains the concepts clearly.

[@AshSeddeek]

Thank you Maya for doing such a great job explaining what to many of us is still esoteric. Loved it!

[@HAKhan-hn3ew]

Fantastic Maya! Your detailed explanation of the shift from monolithic AI models to modular, compound AI systems is enlightening. It's fascinating to see how the integration of LLMs with agent-based systems can enhance adaptability and enable more dynamic interactions across various applications. I'm especially intrigued by the 'ReAct' framework, Combining Reason, Action, and Access memory-as a means to boost AI's adaptability and autonomy. Looking forward to more insights on this topic! With the Rise of AI Agents in 2024, the Age of 'Jarvis' is on the horizon 🤖

[@VanCliefMedia]

Absolutely! The focus of multi agent systems will be the major need. Ensuring large context can be narrowed and integrated into systems unlocks so much potential. Our software is solving the problems with multi agent group chat productivity environments and I really believe going from the chainsaw of AI to the scalpel is the future 👌

[@nathanmack5514]

I think she is my new/first life coach. She very artfully layed out the comparison between the two operations but also technics i might try myself. Thx!! Very well spoken and great delivery. I'm not an A.I. I just have a lot of projects to do. ;)

[@whatdahack71]

I asked these questions to myself two-three days ago and, by surprise, I was able to answer them by myself as well.

[@HenrykZ]

9:22 the best part! 😄

[@ashishkgp]

for narrator : Start teaching these concepts along your job, you have a hidden talent : teaching

[@ziruiwang7293]

IBM's project manager has this level of expertise, impressive!

[@tatvafnu6604]

*Product* Manager - big difference!

[@anotherappointment]

@@tatvafnu6604😂Yh people don’t know the difference

[@SAP-INT]

Thanks for the video that explains very well what agents are and their evolutions.

[@sridattamalempati]

AI Agent models are broad, complex and yet customizable to the instances, It can retrieve data from our past inputs and give relevant outputs by doing all sorts of thinking, reasoning and iterations.

[@TheSiddhartha2u]

Just amazing.... excellent explanation 👌

[@anthonyiocca5683]

I went to school using black boards with chalk. They are quarried from slate carefully mounted to the wall of classrooms. Blackboards got replaced by white dry erase boards. Also used with projectors. Large touch monitors became all the rage. This is my first look at a illuminated rear mirrored clear board. Another cat’s meow…

[@bananamaker4877]

I like the last part when you explained when to use agentic or simple rag approach. Thanks.

[@DonG-1949]

Back In My Day We Had A Word For Folks Like You... And Thats A....... U Guess It.... Teachers Pet 📚🪱 My Advice?? Get Ur Head Out Of Those Books For Once Enjoy Ur Life.... Godbless

[@IBMTechnology]

Glad it was helpful!

[@PeterSodhi]

This is really excellent.

[@SamChughtai]

Thank you, Great tutorial!!!

[@papo-de-cafe]

I Can't agree more, the explanation was amazing, the didatics was awesome!!! Congrats!!

[@james.henning]

Great job with explaining this. Probably the best explanation I have heard.

[@reelwurld-studios]

Give this woman an award for WRITING BACKWARDS WITH NO HESITATION!!! 🏆 (unless she’s AI-generated…)

[@bikedawg]

Extremely educational---this IBM channel is really really good--thank you!!! ❤ 🧡 💛 💚 💙 💜

[@IBMTechnology]

Our pleasure!

[@stekamga]

very clear presentation on the Agentic vs programatic approach. Love it !

[@drachenschlachter6946]

Very good explanation! The best so fat from you guys!!❤

[@AnubhavChhabra]

Agents would still be bound by the tools that you make them aware of. So essentially, your agent can only do the tasks that you have written the code for (tools). The LLM based agents would exploit their knowledge about the tools and try to connect them all together, that's what the main USP is. Knowing all the available tools and then sticking these tools together in a variety of ways.

[@Mantelar]

I learned to write on a blackboard left handed as I lectured. Best way to keep students accountable is to face them. It doesn’t take as long as you think…adults just forgot how much brute force practice you gotta do to learn. Just like when we were kids

[@IshanParikhBeSelf]

Crisp. On-point. Well executed. Kudos to you and your team !

[@IBMTechnology]

Thanks a ton

[@pratikshitsingh415]

Great explaination for agents! Helpful! Thank you

[@GaryyPorterr]

ur positive energy is contagious and your videos always brighten up my day, thank you!!! 😉

[@nedkelly3610]

The best advantage of agents is the ability to check and verify each llm output, in addition to querying your leave balance, it can also query your leave entitlement, and how many leave days have been used up, to compare. This will take the accuracy of AI systems from 75% to 99.95%.

[@HariPrasad-su5wl]

Awesome information & superb lecture!!! Spot on!!!

[@IBMTechnology]

Glad you enjoyed it!

[@HariPrasad-su5wl]

@@IBMTechnology of course!!

[@3DVector]

Thank you! Best explanation so far!

[@IBMTechnology]

Glad it was helpful!

[@ChukwumaOnyeijeMD]

Timestamps (Powered by Merlin AI) 00:04 - AI agents are shifting from monolithic models to compound AI systems 01:52 - Integration of AI models into existing processes 03:27 - Compound AI systems involve programmatic control logic for efficient problem-solving. 05:11 - Large language models enable complex problem-solving 06:39 - AI agents can act with external programs 07:57 - Configuring AI Agents using ReACT 09:32 - Determining the number of sunscreen bottles needed for a vacation in Florida. 11:02 - AI agents vary in autonomy based on problem complexity

[@mussen1876]

This was a really helpful video for me. These IBM videos have really great content.

[@IBMTechnology]

Glad you like them!

[@the.boring.andrew]

Thank You for the high-level overview! It would be interesting to hear more about tradeoffs between the programmatic and agent approaches (use cases, how agents can be embedded into the existing systems, etc).

[@henryjraymondiii961]

According to IBM, an artificial intelligence (AI) agent is a system or program capable of autonomously performing tasks on behalf of a user or another system. These agents design their workflows and utilize available tools to achieve their goals. AI agents can handle a wide range of functionalities, including decision-making, problem-solving, interacting with external environments, and executing actions. They are often built on large language models (LLMs) and can adapt to user expectations over time, providing a personalized experience. AI agents are used in various applications, from software design and IT automation to code-generation tools and conversational assistants.

[@tianzelou]

Thank you! very nice video,I love this❤❤❤

[@jeffreyanderson5106]

Good presentation… easy to follow and understand. I intuitively understood as she gave examples that my experience reinforced. Thank you 😊

[@IBMTechnology]

Thanks for sharing!

[@drS1lv3r]

Great topic and very well presented! Thank you!

[@NostalgistGuy]

Such a profound and insightful video on the internet is available.

[@sirishkumar-m5z]

AI agents are like digital workers who can think and act alone to help industries with tasks. SmythOS features agents for data analysis, client service, and automating workflows, all handled without coding expertise. Inspiring chances!"

[@RazaAli-l3h]

Gosh as a small business owner we are going through over worst time of the year…And she is teaching us happiness ! That how it works in KZbin…😅

[@GenAI.Enthusiat]

Remarkable clarity, excellent explanation!!

[@moderncontemplative]

Excellent explanation of the next phase of AI development. Never a dull moment these days in the age of AI! I’ve been enjoying IBM courses via Coursera

[@felopatermaher9608]

Great clarify Thank you Maya.

[@sepiksai]

Excellent presentation

[@jonathanmasfrancx1228]

Stephan, thanks for the presentation. Very nice talk.

[@IBMTechnology]

Glad you liked it!

[@trycryptos1243]

Nice overall picture of how AI agents are evolving.

[@PaulMoreira]

Great explanation of AI Agents! I love working with them and seeing them reason issues.

[@markuaunyong929]

We all know that AI operates on massive amounts of data from the crowd and follows the commands we input. What if we divided the AI's brain mechanism into three main parts: 1. Random real data (instead of waiting for human input), 2. Correcting random data, saving corrections, and looping (similar to the body's immune system remembering how to eliminate pathogens), and 3. Genetic code (the defined behaviors and rules of AI)? For example, humans have different personalities. Some are born perfect, intelligent, and cheerful, while others are aggressive. (To create behaviors that lead to progress and safety, we can remove negative traits, similar to genetic engineering.) For instance, greed leads to decline, aggression and anger lead to violence, and delusion or stupidity hinder progress. In summary, we can remove these three emotions. (Expected outcome) Create errors and successes for AI to learn from various error data through looping, memorization, and self-improvement, similar to human behavior that seeks self-development. In conclusion, to create AI that closely resembles humans, we need to integrate the brain mechanism and the crowd. Comparing the crowd to clear water and the brain mechanism to red color, when we combine them, we get red water. AI brain: Red water.

[@GoodWoodWorks-le4cd]

Now I understand my mental burnout!! Im constantly mentally working my agent mind and looping!!😂

[@glowshedfilms]

Wow, she was really great at explaining the concept! Now it makes sense. Would be great to have a simulated version of this person as a teacher! :D

[@bettyboop7738]

How do you know she's not ?

[@MelonHusk7]

This was actually very useful.

[@SPMan86]

great explanation!! Keep it going!!

[@dylanruss1135]

You explained this the most difficult way you could’ve good job

[@dylanruss1135]

But at the end of the day having 800,00+ subscribers split between god who knows how many people just off of buying views is still impressive in itself, not because you earned it but solely because you managed to buy it.

[@HateTheIRS]

@@dylanruss1135are you ok

[@sacquer]

Excellent explanation by Maya! 👏🙌

[@jeanpierreleroy299]

Thank you so much for this. This will help me in my project

[@cerenabay4608]

Such an informative video!

[@dreamphoenix]

Excellent info! Thank you. 🙏

[@IBMTechnology]

Glad you enjoyed it!

[@aleksandreliott5440]

This was a fantastic video

[@ltgwgeorge2155]

Beautiful stuff, Thank you so much🎉

[@collimarco]

The next step would be agents that build their own "programmatic" way to solve the problem when it is a repetitive task

[@jorgesanabria6484]

This mental model of agents and LLMs is brilliant.

[@dato007]

How do u benchmark performance ? Seems like probability of errors can go up too. Ref for such research? Thx u.

[@TheFocusedCoder]

Great overview, this is iconic

[@juhyunkim76]

Thank you for an excellent lecture.

[@duytdl]

"What is my purpose?" "You fetch sunscreen bottle" … "oh god"

[@hdhdushsvsyshshshs]

i got that reference lmao

[@aleclippe6213]

How long until AI agents are good enough for IBM consulting to turn a profit?

[@anasaberchih9490]

Clear and consise, thank you Maya Murad, appreciate the informations🙏🏼

[@digitalhero7488]

A+ Presentation. Thanks!

[@richsadowsky8580]

Very clearly explained and informative.

[@ayusharora2019]

Brilliant explanation

[@BoNaha]

Very valuable video. I think this topic has potential for another couple videos about how we might implement it (bunch of small distilled slm's like phi-3-128k instead of big ones for ex. to make it runnable on some decent (not necessary macs) laptops). Complex systems relatively new concept but we already have overwhelmingly many platforms. tools and techniques like langchain, graphRAG, beam etc. and another important moment is to find the simple way to compare those complex system for efficiency. Crazy interesting topic, Thank You for your effort. Liked