Going from the State of the Art (SOTA) to the Future of LLMs and Generative AI

What is the future of AI? There has been a buzz lately about ChatGPT and Large Language Models (LLMs). It helps to understand the past, current state of the art, before discussing the future trends, concerns and excitement. This presentation intended to broadly cover many topics, to get a broad sense of what is going on.

AI Progress in the PAST
* Types of AI Algorithms
* Growth in Complexity over Time
* Time Series, From Regression to Large Language Models (LLMs)
* How LLM is a Time Series
* Caution: a model is no better than it's training data
* Emergent Properties

AI State of the Art NOW
* Emergent Properties
* One Place to find State of the Art (SOTA)* AI's rapid growth
* Generative AI: Text to Image DALL*E2
* Microsoft's New AI Can Simulate Anyone's Voice From a 3-Second Sample
* I Challenged my AI Clone to Replace me for 24 Hours - WSJ
* Intel Introduces Real-TIme Deep Fake Detector
* ChatGPT 4.2 Test Taking, Languages
* Chain of Thought - Size Matters for Reasoning
* ChatGPT + Tree of Thoughts Reasoning
* Constitutional AI (for ethics and rules)
* There is a lot of Generative AI Evolution in a Short Time
* Portugal Startup Makes ChatGPT its CEO
* ChatGPT 5 coming in 2024
* Meta's ImageBind

Looking to the FUTURE of AI
* LLM Short term impact to the economy, McKinsey report
* Supporting Tech to drive AI
* AI in 2-5 years
* AI in 10+ years
* 3 Levels of Future Impossibilities, Michio Kaku
* AI, Class I-II Impossibilities

Speaker: Greg Makowski, Johnson Controls

Register at weblink to attend online or in person