Generative AI, short for Generative Artificial Intelligence, is a branch of artificial intelligence that focuses on creating models capable of generating new content that resembles human-generated data. Unlike traditional AI models that are designed for specific tasks, such as classification or prediction, generative AI models are intended to produce original and creative outputs. Generative AI models work by learning patterns and structures from large datasets and then generating new data that shares similar characteristics. These models can be applied to various types of data, such as text, images, audio, and even video. There are several types of generative AI models, including: Generative Adversarial Networks (GANs): GANs consist of two neural networks: a generator and a discriminator. The generator's role is to create synthetic data, while the discriminator's task is to differentiate between real and generated data. Through a competitive process, the generator gets better at producing realistic data as it learns from the feedback given by the discriminator. Variational Autoencoders (VAEs): VAEs are a type of neural network that aims to learn the underlying distribution of the input data. They work by encoding the input data into a lower-dimensional latent space and then decoding it back to generate new samples. Transformer Models: Transformers are a type of neural network architecture that has been highly successful in natural language processing tasks. They can generate human-like text by predicting the probability of the next word in a sequence given the preceding context. Applications of generative AI are diverse and include: Image Generation: Creating realistic images of objects, scenes, or people that do not exist in reality. Text Generation: Generating human-like text for creative writing, chatbots, or language translation. Music Composition: Generating original music compositions in various styles. Video Synthesis: Creating synthetic videos based on given inputs or scenarios. Generative AI has shown impressive results and potential, but it also comes with challenges, such as ensuring the generated content is accurate, safe, and free from biases. Ethical considerations are crucial when deploying generative AI models, as they could potentially be misused or create harmful content if not properly controlled. Nonetheless, generative AI holds promise in pushing the boundaries of creativity and innovation in various fields.
Llm models video please . Can u share few finance domain use cases. Great video and new subscriber. Can u elaborate on how we guage which ML model to use. Feature engineering and hyperparanwter tuning as well
Hello Krish, Needles to say that I am a big fan your teaching style. Why dont you create a series for Generative Modeling? Including GAN, VAE, Diffusion Model, Energy based Model, Normalizing flows, Autoregressive models etc
Krish how it will assign ranks for each response because we are getting the response from the chatgpt but we won't give any feedback hey it is good answer from u like this right .Then how it will assign?
hey krish very informative video but this type of content is available all over the internet today as an ML engineer please explain me my role after this revolution in AI plus also help people like me by teaching us how to create our own LLM's and apply reinforcement learning on it to make a smaller version of chatgpt
The use of Generative AI in Internet Marketing, E-Commerce and Financial Institutions is going to change the way such companies were using their traditional data and face difficulties to get meaningful outcomes. Now Generative AI would do wonders for such companies, by providing more business opportunities that were untapped previously because of a lack of meaningful legacy data outcomes. Hopefully regulatory compliance and risk management would also be enhanced using Gen AI
Hi Krish, Thanks for these videos. They are to the point. Can you tell us about "unimodal AI" vs. "multimodal AI" differences and uses wrt to Generative AI? I will be viewing more of your videos. Thanks for your time!
Sir correct me if I wrong In video you mentioned Chat GPT and Bard are LLM models but as per my understanding GPT4 and PaLM are the LLM models where as there tools work underlying that models. Thanks
Extremely eager for the playlist. I want to build my own LLM model on the data i have, I tried using Llamaindex for this. But didn't give much results. Please tell us how to crack this and create our own chatgpt with our own data
@@pqrstwxyz1175 only few people will be welcomed, if you compare the amount of devastation it will cause compared to new opportunities it will open you will see it's has high devastation
I don’t think so. People thought the same at the time of industrialisation but human made or handmade products now are considered piece of art and even luxury. Same will happen with this case
Got an awesome Idea on Generative AI based education software. Need an amazing developer to team up with me in this entrepreneurial product. High Tech elements involved. ANYONE??!!
Generative AI, short for Generative Artificial Intelligence, is a branch of artificial intelligence that focuses on creating models capable of generating new content that resembles human-generated data. Unlike traditional AI models that are designed for specific tasks, such as classification or prediction, generative AI models are intended to produce original and creative outputs.
Generative AI models work by learning patterns and structures from large datasets and then generating new data that shares similar characteristics. These models can be applied to various types of data, such as text, images, audio, and even video.
There are several types of generative AI models, including:
Generative Adversarial Networks (GANs): GANs consist of two neural networks: a generator and a discriminator. The generator's role is to create synthetic data, while the discriminator's task is to differentiate between real and generated data. Through a competitive process, the generator gets better at producing realistic data as it learns from the feedback given by the discriminator.
Variational Autoencoders (VAEs): VAEs are a type of neural network that aims to learn the underlying distribution of the input data. They work by encoding the input data into a lower-dimensional latent space and then decoding it back to generate new samples.
Transformer Models: Transformers are a type of neural network architecture that has been highly successful in natural language processing tasks. They can generate human-like text by predicting the probability of the next word in a sequence given the preceding context.
Applications of generative AI are diverse and include:
Image Generation: Creating realistic images of objects, scenes, or people that do not exist in reality.
Text Generation: Generating human-like text for creative writing, chatbots, or language translation.
Music Composition: Generating original music compositions in various styles.
Video Synthesis: Creating synthetic videos based on given inputs or scenarios.
Generative AI has shown impressive results and potential, but it also comes with challenges, such as ensuring the generated content is accurate, safe, and free from biases. Ethical considerations are crucial when deploying generative AI models, as they could potentially be misused or create harmful content if not properly controlled. Nonetheless, generative AI holds promise in pushing the boundaries of creativity and innovation in various fields.
Thank you sir, waiting for LLM
Outstanding explanation never seen such great teacher
Thank you very much dear Krish.
Your innocent student from Pakistan
Finally! Was waiting for it from long time!
Thanks for sharing, eagerly waiting this video, easy to understand from your channel.
Thank you sir . Now I know the differences between generative and discriminative Ai in Deep learning. Next level explanation. Love you 😍😍😍
Awesome Video. Thanks Krish Sir
Hello Krish, Wonderfull Content. I want to learn so much from you. Your teaching is excellent and Amazing. Thanks a lot for your time and patience.
this is the master's course, 100x more clear and effective than the same generative AI introduction course by google.
Excited for GenerativeAI playlist.
Wow super Krish, wonderful explanation. Amazing.Completely stick in ur presentation. Magical
Very informative video.....❤ thank you so much for this kind of video....very helpful 🎉
These are the most awaited😍 videos from you
Awesome presentation
Great work sir ...keep uploading such vedioes thank you🙏
We all are waiting for the playlist covering Gen AI, LLM 🙏🏼
Brilliant ...a transformer. ! Transforms complex concepts in simple easy to Digest pieces. God Bless
Woah ! Really excited to learn more
Great explanation
Like the energy and the way he has explained the various details in very nice way
When Krish said: 'Consider you are a Human being' .. that really touched me :D
Great video..
Llm models video please . Can u share few finance domain use cases. Great video and new subscriber. Can u elaborate on how we guage which ML model to use. Feature engineering and hyperparanwter tuning as well
Great Summarization of AI.
Thank you
Egarly waiting for this. Thank you so much sir
Love your english spoken skill ❤❤❤which is very clear and easy to understand ❤
Amazing 😍😍
Well explained 👏👏Tysm Krish 😇
I grateful that you explained gen AI so good...there is not much videos with this much information
nice explanation
Awesome video !
Thanks, Krish.
Very explanatory sir krish
what writing software is this ?
13:45 --> how the data can be trained??
Very nice explanation
Waiting for this playlist thank you krish
Hello Krish, Needles to say that I am a big fan your teaching style. Why dont you create a series for Generative Modeling? Including GAN, VAE, Diffusion Model, Energy based Model, Normalizing flows, Autoregressive models etc
@ Krish - I would like to know, if individuals without a background in Mathematics can pursue a course in Generative AI.
Where is playlist for GAN?
How do you learn and where do you learned all these
Thank you for your time and I feel these sessions are very easy to understand based on your teaching style
Krish how it will assign ranks for each response because we are getting the response from the chatgpt but we won't give any feedback hey it is good answer from u like this right .Then how it will assign?
Well explained. Waiting for more in this
hey krish very informative video but this type of content is available all over the internet today as an ML engineer please explain me my role after this revolution in AI plus also help people like me by teaching us how to create our own LLM's and apply reinforcement learning on it to make a smaller version of chatgpt
🙌
Amazing content
👌👌
The use of Generative AI in Internet Marketing, E-Commerce and Financial Institutions is going to change the way such companies were using their traditional data and face difficulties to get meaningful outcomes. Now Generative AI would do wonders for such companies, by providing more business opportunities that were untapped previously because of a lack of meaningful legacy data outcomes. Hopefully regulatory compliance and risk management would also be enhanced using Gen AI
How ? Can you give any problems?
Hi Krish, Thanks for these videos. They are to the point. Can you tell us about "unimodal AI" vs. "multimodal AI" differences and uses wrt to Generative AI? I will be viewing more of your videos. Thanks for your time!
We need more videos like this
What have to learn for gen AI...?
Playlist link please?
Thank you , you explained in really simplified way.
Very informative as always
I am going to add this info to my AI copybook
Sir correct me if I wrong
In video you mentioned Chat GPT and Bard are LLM models but as per my understanding GPT4 and PaLM are the LLM models where as there tools work underlying that models.
Thanks
Thanks sir
Prompt Engineering: Explanation about prompt engineering is completely wrong. Can you please check and correct that portion. Rest all looks good.
Extremely eager for the playlist. I want to build my own LLM model on the data i have, I tried using Llamaindex for this. But didn't give much results. Please tell us how to crack this and create our own chatgpt with our own data
Thank you Krish. One request. Can you make tutorial video about langchain? 😊
Hi Krish It would be good to have Langchain based use cases, integrating different tools..
Generative ai will kill creativity and several jobs like playwrights, poets, music composers, artists, architects, etc
I don't completely agree with you generative AI will increase the productivity of composer, architect etc
But will open more field like prompt engineering
@@pqrstwxyz1175 only few people will be welcomed, if you compare the amount of devastation it will cause compared to new opportunities it will open you will see it's has high devastation
I don’t think so. People thought the same at the time of industrialisation but human made or handmade products now are considered piece of art and even luxury. Same will happen with this case
@@Rinks10 ok I hope it's like that but remember the world has got complicated and more advanced than those era
hey sir, is NLP a part of generative AI ?
First comment 🎉
Could you plz provide us Ai course
Sir generative ai ki coding implementation bhi krwa dijiye
Namaskar sir.
Thanx...
Sir. Instead of just thinking about jobs, can we think of it like how generative AI will empower individual human beings
Sir iss playlist ko Hindi mai start kr do please
*Sir make prompt engineer playlist*
Got an awesome Idea on Generative AI based education software. Need an amazing developer to team up with me in this entrepreneurial product. High Tech elements involved. ANYONE??!!
Bhai jaldi karo
open source contri ka video bnao sir please
Sir agr Hindi or English dono Mai pdha do to hum bhi pdh lenge please sir
Are you Indian??? Where is your Anchestor land, Mumbai, New Delhi, Gujarat, Uttar Pradesh???
Nice, but you say “right” a lot. In case no-one had mentioned it before
Sir hindi english mix pdha do please
Please sir hindi mai padhaao
Not very useful .
Open AI founder challenge India don't make chatgpt 😠😡
Toh ro kyu rha hai
true
indian companies don't hv such huge data to train
Thanks sir
waiting for prompt engineering play list