Is Gen AI replacing Classical Machine learning Models and Project Life Cycle?

I am not yet convinced that Gen AI has the ability to replace the machine learning models used to solve regression, classification, vision and its project life cycle.

It was enriching experience to learn about Gen AI , performance tuning, RLHF around it as well project life cycle. This can be used to create intelligent Chatbots and Robots and has greater cost and training efforts associated to it.

I feel for specific uses cases still classical machine learning has its significance and will continue to play a significant role.

I would like to hear your views on this.

I agree with you.

The landscape of artificial intelligence is indeed evolving, and the emergence of Generative AI (Gen AI) has sparked discussions about its potential impact on classical machine learning models and project life cycles. While Gen AI brings exciting possibilities, it’s important to recognize that it may not necessarily replace classical machine learning models but rather complement them in certain scenarios.

Classical machine learning models have proven effective in various applications and industries, and they continue to be a reliable choice for many use cases. These models, based on established algorithms and statistical methods, excel in tasks where large labeled datasets are available.

Therefore, rather than viewing Gen AI as a replacement, it seems more fitting to regard it as a powerful addition to the AI toolkit. The synergy between classical machine learning models and Gen AI has the potential to drive innovation and efficiency across various domains.