Is CODING still worth it in 2024 ? | The Truth about Artificial Intelligence , GEN AI and ChatGPT 4


Summary

The video provides a comprehensive overview of various AI tools like Chat GPT and Bard, emphasizing Python's prevalence over R for programming in AI. The speaker shares insights on career transitions within the AI field, discussing challenges and the impact of cloud providers on productivity. They delve into their career journey from TCS to Horiba, detailing experiences in different roles and the transition from management to technical positions. Exploring the significance of AI in software development, the discussion includes the hierarchy of human intelligence, AI, machine learning, and deep learning, as well as the role of generative AI in mimicking human intelligence. The video underscores the importance of upskilling and understanding AI components for effective collaboration with AI teams in various industries.


Introduction to AI Tools

Introducing different AI tools like Chat GPT and Bard, preferences for programming languages like Python over R, and collaboration tools like Google Collab.

Discussion on AI and Career Changes

Insights on career changes in the AI field, challenges in profile changes with experience, and the impact of cloud providers on productivity.

Career Journey from TCS to Horiba

Detailed discussion on the speaker's career journey from TCS to Horiba, including experiences in different roles and the transition from management to technical roles.

Transition to Data Science

Explanation of transitioning from C, C++ to data science, experiences in different companies, and the role of upskilling and internal discussions in career transitions.

Exploring AI and Gen AI

Discussion on the speaker's exploration of AI, the importance of understanding Gen AI, and the role of generative AI in mimicking human intelligence.

Importance of AI Engineering

The significance of AI in software development, examples of generative AI and its tech stack, and the use of Python and C, C++ in AI development.

Overview of Machine Learning and Deep Learning

Explanation of the hierarchy of human intelligence, AI, machine learning, and deep learning, including the use of statistical methods in machine learning.

Introduction to Deep Learning

Exploration of the transition from Machine Learning to Deep Learning inspired by the human brain's neurons and the development of Natural Networks.

Applications of NLP and Computer Vision

Explanation of Natural Language Processing (NLP) and Computer Vision as fields that mimic human intelligence in language and vision, respectively.

Generative AI

Discussion on Generative AI, its focus on mimicking generative capabilities, the preference for deep learning due to its accuracy in large data, and its integration with Deep Learning.

Role of AI in Future Products

Overview of AI integration in future products, the persistence of existing roles like front-end and back-end, and the need for upskilling to interact with AI teams.

Enhanced Collaboration with AI Teams

Importance of understanding AI components for effective collaboration with AI teams, highlighting the increasing presence of AI in various products and the necessity to learn for future interactions.

TA Special Rapid Fire

Quickfire questions on AI tools, programming language, collaboration tools, cloud providers, and IDEs, showcasing preferences in the AI field.

Advice for Students and Professionals in AI

Guidance for individuals in different roles to adapt to the AI trend, with insights for management, IT professionals, and aspiring AI engineers on learning generative AI tools to enhance productivity and explore new career pathways.

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