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.

For the First Time in History the Nobel Prize in Physics is awarded for work related to AI.

This now gives AI and its related fields of study a new place in Academic History

The 2024 Nobel Prize in Physics was awarded to John Hopfield and Geoffrey Hinton for their groundbreaking work in artificial neural networks. Hopfield, known for his Hopfield network, focused on bridging the gap between physics, biology, and computer science, using insights from the brain to improve AI. Hinton, considered the "godfather of AI," developed methods allowing computers to recognize patterns in data, revolutionizing fields like speech and image processing.

Both researchers, while optimistic about AI's potential, have raised concerns about the technology's rapid advancement, Inevitably as it may be in its benefits to humanity, the further this technology goes the more its potential to transform society as a whole. Present concerns range from its potential for job displacement, misuse, and the possibility of AI exceeding human intelligence. At the same time its benefits are far outreaching and will continue to demonstrate its incredible capacity for scientific and technological breakthroughs.