Do We Get the $100 Trillion AI Windfall? Sam Altman’s Plans, Jobs & the Falling Cost of Intelligence

Sam Altman predicted this week that OpenAI could capture up to $100 trillion of the world’s wealth. But what are his plans for OpenAI to distribute that wealth? I analyse all three plans, cover his financial stake, his case for UBI, a science org and the American Equity Fund.

From papers and interviews released in recent days, I go over his predictions for massive inequality, which jobs will be impacted most, what tasks OpenAI thinks will be automated, recent surveys of business leaders and their plans to use ChatGPT for job replacement, the Goldman Sachs job analysis and which jobs Altman thinks will be hit first (customer service).

I also cover two recent productivity experiments to test the impact of GPT models and the YouGov survey on stopping it all. President Biden weighs in, Levi’s gets backlash, Wired thinks human work has a chance and Sam reveals his back-up plan to use AGI to solve AGI’s problems.

GPT 4 Can Improve Itself – (ft. Reflexion, HuggingGPT, Bard Upgrade and much more)

GPT 4 can self-correct and improve itself. With exclusive discussions with the lead author of the Reflexions paper, I show how significant this will be across a variety of tasks, and how you can benefit.

I go on to lay out an accelerating trend of self-improvement and tool use, laid out by Karpathy, and cover papers such as Dera, Language Models Can Solve Computer Tasks and TaskMatrix, all released in the last few days.

I also showcase HuggingGPT, a model that harnesses Hugging Face and which I argue could be as significant a breakthrough as Reflexions. I show examples of multi-model use, and even how it might soon be applied to text-to-video and CGI editing (guest-starring Wonder Studio). I discuss how language models are now generating their own data and feedback, needing far fewer human expert demonstrations. Ilya Sutskever weighs in, and I end by discussing how AI is even improving its own hardware and facilitating commercial pressure that has driven Google to upgrade Bard using PaLM.

Artificial Intelligence – Are We There Yet?

Ask AI experts about the progress of artificial intelligence and they may say “We’re only five or ten years away.” Five or ten years later, are experts still saying the same thing? In this video with Martin Keen and Jeff Crume, they review the progress in AI and try to answer the question: Are we there yet?

GPT 4: 9 Revelations (not covered elsewhere)

This video will give nine more insights from the bombshell GPT 4 Technical Report. It is the companion video to the ’14 Crazy Details’ released the day before. In this video, I will cover:

Tests on how to ‘shut down’ the model in the wild, and how that might go wrong. Sam Altman requesting more regulation (!), milestone moments for humanity as more benchmarks fall, a hidden constitution, why GPT 5 might already be trained and much more.

What are Generative AI models?

Generative AI has stunned the world with its ability to create realistic images, code, and dialogue. Here, IBM expert Kate Soule explains how a popular form of generative AI, large language models, works and what it can do for enterprise.