What Skillsets Takes You To Become a Pro Generative AI Engineer #genai

Summary

In this video, Kish Naak discusses essential skills for becoming a generative AI engineer, focusing on understanding large language models, image models, and multimodal models. He emphasizes the importance of learning both open-source and paid models, exploring frameworks like Lang Chain and Llama Index, and practicing with various projects to gain expertise in the field.

Takeaways

• 😀 The video is aimed at individuals interested in generative AI engineering and provides insights into the skills required for the field.
• 🔍 The speaker is Kish naak, a data science educator, who discusses the importance of understanding generative AI for those transitioning into the field.
• 📚 The video offers a comprehensive list of resources and playlists for learning about generative AI, including end-to-end projects and tools.
• 💡 Generative AI involves creating new content based on context, with a focus on large language models (LLMs), large image models, and multimodal models.
• 🏭 The video highlights the competition among tech giants like Google, Microsoft, and Meta to develop the best LLMs and image models.
• 🛠️ It emphasizes the importance of learning both open-source and paid models for generative AI, as well as understanding their advantages and disadvantages.
• 🔑 The speaker mentions frameworks like Lang chain and Llama Index as essential tools for developing applications using generative AI models.
• 📈 The video stresses the significance of practicing with various use cases and understanding the deployment and scalability aspects of generative AI models.
• 📝 There is a strong focus on the importance of fine-tuning models with custom data, which is considered a crucial skill in the field.
• 📚 The prerequisites for entering the field of generative AI include knowledge of Python, machine learning, deep learning, NLP, and advanced concepts like RNNs and Transformers.
• 🛑 The video concludes with a roadmap for becoming a generative AI engineer, urging viewers to learn the basics and practice with projects to improve their skills.

Q & A

What is the main focus of the video by Kish naak?

The main focus of the video is to discuss the important skill sets required to become a generative AI engineer and to provide necessary materials and resources for learning about generative AI.

Why is Kish naak making this video?

Kish naak is making this video because many of his students who have transitioned into the data science field are getting work in generative AI and are using large language models and large image models to solve various use cases.

What are the two main types of models discussed in the video?

The two main types of models discussed are large language models (LLMs) and large image models, with a third type being multimodal models that combine text and images.

What is the main aim of generative AI models?

The main aim of generative AI models is to generate new content based on any given context.

What are some of the companies mentioned in the video that are in competition to create the best LLM models?

Some of the companies mentioned are OpenAI, Google, Microsoft, and Meta, all of which are competing to create the best large language models or large image models.

What are the two important categories of generative AI models discussed in the video?

The two important categories are open source models and paid models, which the video suggests one should have a complete understanding of both.

What is AWS Bedrock and how does it relate to generative AI?

AWS Bedrock is a service that provides APIs for various generative AI models, both open source and paid, allowing users to solve business use cases and perform fine-tuning without worrying about the cloud part.

What are some frameworks that one should be good at for developing applications in generative AI?

Some frameworks mentioned are Lang chain, Llama Index, and Chainlink, which provide tools for various functionalities from data injection to transformation and the ability to call both paid and open source models.

Why is understanding vector databases important for generative AI?

Understanding vector databases is important because they are essential for converting text into vectors, which is a key process in developing applications related to text in the generative AI field.

What is the importance of fine-tuning custom data with LLMs in the context of generative AI?

Fine-tuning custom data with LLMs is crucial as it allows models to be adapted to specific use cases and business requirements, making it a vital skill for generative AI engineers.

What is the prerequisite knowledge required to start learning about generative AI according to the video?

The prerequisite knowledge includes Python programming language, basics of machine learning and NLP, deep learning concepts, advanced NLP concepts like RNN, LSTM, and Transformers.