This episode explores not only the overall AI Landscape advancements of 2025 but it builds upon the AI evolution in 2024 and its incredible advancements.

Some key likely trends that we will see AI evolving into during 2025 are:

1. Clearly its pervasiveness and growing ubiquity in everyday life.
2. The growth of Generative AI and its increased capabilities
3. AI influenced if not determined healthcare
4. Continued AI Relevance and adoption in Education
5. And also AI Driven Environment Relevant systems - key word "sustainability"

... Maye even Quantum AI?...

To learn more listen to this unique view of the likely trends we will experience with the Advancement of AI in 2025.

And with that, thank you for your audience in 2024 and wish you a healthy and successful NEW YEAR 2025! May the worth of AI and all its benefits be with you!!

This Episode summarizes the main milestones that AI achieved during the year 2024. From becoming a promising advancement to receiving 2 Nobel Prizes, one for Physics and one for Chemistry. Of course too many other advancements in this field have taken place in 2024, nevertheless in this case we review some of the major events including the new LLM by Google Gemini 2.0 Trillium Chip making an incredible accelerator in AI Model Performance, The Nobel Price in AI Ethics, a must that AI should never be without in its Governance Framework, The Centerstage take over by Gen AI as well as medical applications. The investment focus and competition that AI has driven as it establishes itself as a mainstream technology with true scientific and practical applications across the board. And of course also making reference to real challenges, be it in bias or displacements in the job market, concerns about regulatory, ethics and privacy concerns.

The podcast explores the different types of artificial intelligence (AI) and their capabilities.

It distinguishes between narrow AI (weak AI), which performs specific tasks, general AI (strong AI) with broad human-like cognitive abilities, and superintelligent AI (ASI), which surpasses human intelligence in all aspects.

It also explores the AI categories based on functionality (e.g., reactive machines, limited memory, theory of mind), learning models (supervised, unsupervised, reinforcement, and deep learning),

It exemplifies specific branches of AI like machine learning, robotics, and natural language processing.

Finally, it concludes with an examination of Artificial General Intelligence (AGI), exploring its potential benefits, risks, and societal implications.