What makes Ilya Sutskever believe that superhuman AI is a natural extension of Large Language Models?

I came across a 2 minute video where Ilya Sutskever — OpenAI's chief scientist — explains why he thinks current 'token-prediction' large language models will be able to become superhuman intelligences. How? Just ask them to act like one.

State of the Art Gemini, GPT and friends take a shot at learning

Google’s Gemini has arrived. Google has produced videos, a blog, a technical background paper, and more. According to Google: "Gemini surpasses state-of-the-art performance on a range of benchmarks including text and coding." But hidden in the grand words lies another generally overlooked aspect of Large Language Models which is important to understand. And when we use that aspect to try to trip up GPT, we see something peculiar. Shenanigans, shenanigans.

The hidden meaning of the errors of ChatGPT (and friends)

We should stop labelling the wrong results of ChatGPT and friends (the 'hallucinations') as 'errors'. Even Sam Altman — CEO of OpenAI — agrees, they are more 'features' than 'bugs' he has said. But why is that? And why should we not call them errors?

The Truth about ChatGPT and Friends — understand what it really does and what that means

On 10 October I gave an (enthusiastically received) explainer talk at the EABPM Conference Europe 2023, making clear what ChatGPT and friends actually do — addressing the technology in a non-technical but correct way — and what that means. That presentation fills the gap between the tech and the results. At the end you will understand what these models really do in a practical sense (so not the technical how) when they handle language, see not only how impressive they are, but also how the errors come to be (with a practical example), and what that means what we may expect from this technology in the future.