Kate, this was awesome. It is so refreshing to find presenters who can take complicated material and explain it, in just a few minutes, in a fashion that makes it so reachable.

So far, by far the best video on Generative AI I’ve seen.

Over the last week, I have been trying to find out the differences between Generative AI and Foundation Models, but could not find the relevant and exact content and this one video has cleared all of that, too good!

I love that this is on KZfaq for free, thank you very much for a great basic understanding! :)

Great explanation at a very basic level, very easy to follow the whole video. Thank you very much.

Very very... very good video. How to use 9 minutes to understand the concepts of Generative AI, Foundation Models, Large Langage Models, etc. Awesome !

The explanation i`m assuming is great for a technical person which knows already a lot about generative ai models but for the larger public you need to explain it way simpler and not using technical terms. Analogies help a lot.

Great presentation. Make such a complex topic seems affordable, means that there a lot work behind! Thanks

Great insights into the concepts of Generative AI. Thanks

Outstanding presentation, thank you IBM

Outstanding explanation. Thank you!!! Please continue such great work.

These videos are simply amazing, thank you IBM.

She just example the whole AI bubble , so awesomely, Kate great job, the best video I have watched so far on the internet. 👏👏👏

Kate, this is really highly informative and one of the best videos I came across for gen ai.

These videos are really amazing and deserve waaaay more attention and credit. IBM Technology, you are doing a great Job!

Very clear and systematic introduction! Thanks

Fantastic presentation and a great way to promote IBM offerings.

The most concise summary / explanation of what is Generative AI 👍💯

Thank you so much for the introduction to a very important topic.

As an IBM Employee this video makes me proud ❤

When I was a kid in the 60s our local TV weatherman (Ralph Ramos) actually wrote like that for real. He stood behind a clear panel with a map outline and used a grease pencil to write temperatures on it backwards.

Excellent presentation Kate ! Thank you !

Thanks. Easy to follow for non-tech. Great!

Thanks Kate for this awesome video. Interesting to see the vast use cases of generating AI other than chatbots.

I loved it! Thanks for this amazing video :)

Very very clear presentation! thanks!

Very precise and accurate video explains things clearly whats gonna up in future ! - thanks Mam.

Thanks IBM Research Team, this videos are amazing as a learning resource

Excellent explanation, top of top

Thanks Kate to simplifying the AI model explanation to general layman, interesting time to be in to see how AI is evolving like what science fiction movies have predicted all these year to become a reality.

Excellent explanation and breakdown by Kate, brilliant woman !

Very informative. Thank you, Kate.

Interesting. Generative A.I: "predict the last word of the sentence based off the words it saw before". My very first A.I. program in college (ages ago) was a game "guess what I'm thinking". For each wrong guess the program was given a clue, thus building its knowledge-base. Prompt: What are you thinking of? (input: animal) (program: shark) (no. hint: mammal) (program: dog)(no. hint: has a trunk)...(no. hint: large ears)....(no. hint: grey) (program needs the answer: elephant). The program now has the definition of an elephant. Without knowing much about Generative A.I. it seems similar except "on steroids", lol "on the internet of data". Will have to follow the links above to learn more. Kate Soule, great explanation. Thanks.

Amazing explaination!!

Excellent presentation. My only gripe is the masses will still think generative AI is simply predicting the next word, one of Jeffery Hinton's concerns. There's a lot more to it than that. When you ask a question, it needs to identify related material in the dataset and then construct specific parameters of the neural net in a way that addresses the structure and meaning of your input that makes sense. Kind of like what we do when we piece together sentences based on our experience. That requires great intelligence. This is why GenAI can already outperform humans in many academic and operational benchmarks, and it's beating us humans in more and more of these by the month. Once you go fully multimodal in these endeavours, we'll very quickly reach AGI.

Very nice insights into the topic. Well done Kate

Great explanation. Thank you.

Awesome Introduction! Looks like I'm hooked on this topic.

Was just amazing, thanks.

Kate, great video!

Very Well Explained !

Great explanation about the Generative AI Models I think your last proposition will make a great impact to the human kind with the help of Generative AI

Excellent explanation.

Like your podcasts(?) guys! Awesome!

Your writing in reverse is surprisingly skillful; great coverage of models. Thank you

good work and fluid presentation, many thanks

Good Job Kate. Also, good use of the whiteboard and colour annotations. It helped that you also used simple language, didn't over-crowd the whiteboard and effectively used spacing between the concepts, as well as with the groupings for the workflow components ie: (FM /Prompting on the right of the board) , from the (LLMs)concepts on the left hand-side of the board. Thanks for sharing your gift of teaching. your contribution is appreciated. If you have a course or workshop that you teach on GenAI, I would be interested in learning more. (hint, hint) Cheers

Thank you that was very helpful

Great content explained with simplicity!

Great video!!! IBM used to be the undisputed leader of computer technology. Would be great to see Big Blue back in the game and become a leader again!!!! (Apple's market cap 2 trillion dollars, Nvidia's market cap 1 trillion dollars, IBM (the former world leader of computer technology) 120 billion dollars). Hope to see a publicly-available LLM from IBM soon!!!!

Really well explained

Thank you so much for such an amazing video! It is informative, helpful and engaging. 😀

Are the 2 latest foundation models you mentioned, molformer and Earth Science for climat change, available as demos?

Informative video. Thanks

Intern Jr. GenAI Engineer here. You make me understand the larger scope of what Im doing.

Good Explanation Kate.

Very well explained

very well explanation for beginner like me

I just love this videos

Yes, really informative. Thank you.

Very informative; thank you!

69th comment! As a researcher, it feels nice to see IBM will be researching with me this great new innovations! Best of luck IBM, you are going to need it!

Great Video. Very Clear. Thanks.

Quality vid IBM.

nice video!!

using this to study for university, thank you!

Excellent. Thanks

thanks kate this is useful to me.

This video offers concise and informative insights into the AI journey, perfect for those who are new to the topic and seeking a clear understanding

Awesome. Thank you

Thank you, for the nice presentation

I'm a '70s AI guy. I have done many parsers and translators. I have done old-style theorem proving and structure learning. I keep asking myself, in this multi-layer perceptron formulation, how is the parse tree represented? How are logic statements represented? How is knowledge manipulated? All I seem to get is generalities about training and "the next word". Where should I be looking?

Truly nice way of explaining. .

This "blackboard" is so good :)

amazing and great presentation

Is there an assembly LLM kit sold in Amazon that I could assemble and understand?

Good explanation

Thank you.

Nice .. are you writing over mirrors or this is some digital tool

Great explanation.

very nice presentation thank you

Great info Kate. What kind of White Board are you writing on? It's so cool!

Thank You

Very good!

Thank you

Its highly impresive

Very very high level.

@1:55 Isn't the training supervised rather than unsupervised? It is predicting the next word that follows the given text: the next word is known.

Outstanding explanation, I'm even more impressed for your hability to invert your writing effortlessly... mindblowing! congratulations!

Great work

as for the Trust issue, is there some kind of "bill of meterials" for what has been processed which could be reviewed? i think this would be crucial for transparency

Great explanation of course! I'm also equally impressive with her (mirror ?) writing skill.

Good informative video.

I know someone else who wrote inverted..he also painted well. impressive

I think I can make a slight correction here. Let me know if I'm wrong. The idea of "generative" in Generative AI isn't the ability to "generate" the next word, but in that the model is able to generate new observations (or data points) based on the distributions in the data. As she describes, LLMs are part of the idea of foundation models, and LLMs are the NLP derivative of FMs that are able to sample from those distribution of words (or tokens).

thanks to ch*tgpt i've finally been able to build my own RNN in c/c++ and dozens of other things. simple series prediction (audio spectral extension) took a few hours to train a FFNN to satisfactory results, but training a RNN on 96 input "hot one" text chars has taken over a month to train on my little asus L210 and i'm maybe a third of the way based on loss. there's one thing i've observed in decades of procedural media programming, procedure tends to express outside of human discretion and can expand or distend our experience and concept of expression. plus, per burroughs' cut-up method, you do tend to get a bit of EVP and transduction in procedure. aheheh.

Great!

Apart from the details on the subject ! Got curious to see how did the visual writing in front transparent screen been done

Also, how do you do this graphics presentation? :) It is like you are able to write in reverse. It looks like the camera is simply filming your reflection, but that doesn't seem like it would work.

As impressive as AI is, Kate writing inverted is just as impressive.