Tag: AI

Worried AI is going to steal your job and kick you to the curb? If you watched the video, you can probably see why I’m not worried about my job security. While AI is going to change the way we do a lot of things, it still needs some time before it’s cracking the kind of nuanced jokes I’m famous for.

Note: This video was recorded prior to the GPT-4 update

In his book “A Brief History of AI,” Michael Wooldridge, a professor of computer science at the University of Oxford and an AI researcher, explains that AI is not about creating life, but rather about creating machines that can perform tasks requiring intelligence.

Wooldridge discusses the two approaches to AI: symbolic AI and machine learning. Symbolic AI involves coding human knowledge into machines, while machine learning allows machines to learn from examples to perform specific tasks. Progress in AI stalled in the 1970s due to a lack of data and computational power, but recent advancements in technology have led to significant progress. AI can perform narrow tasks better than humans, but the grand dream of AI is achieving artificial general intelligence (AGI), which means creating machines with the same intellectual capabilities as humans. One challenge for AI is giving machines social skills, such as cooperation, coordination, and negotiation.

The path to conscious machines is slow and complex, and the mystery of human consciousness and self-awareness remains unsolved. The limits of computing are only bounded by imagination.

Can GPT 4 Prompt itself? Give it a mission and it will come up with the prompts. This video showcases the rise of autonomous AI, including 5 major developments in the last 48 hours.

Starting with the OG Auto-GPT, we see how it quickly gain text-to-speech, coding and more. Karpathy weighs in and then we see how you can now create an app with just your voice, with a Jarvis demo and another route via Imagica.AI.

I then showcase MemoryGPT, a brand new model that can permanently store previous conversations and remembers topics the next time you ask.
I also cover the concerningly rise of models such as ChaosGPT that show how people will create malicious goal-seeking models just for fun.

The video shows how you can now create a shareable bot on poe.com, with any personality you like (images were from Midjourney v5) and what Anthropic are working on with Claude Next [plus Nvidia million x quote].

You’ll see how Microsoft Jarvis, using HuggingGPT, is hit and miss, and how Sebastien Bubeck shows we are not even seeing the raw potential of GPT 4. I end with a disagreement between Yudkowsky and Altman, via Baby AGI, on whether we can use AGI to align AGI.

ing vs Google. Bard vs ChatGPT. A winner will be crowned… For now.

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.

Over the past few months, artificial intelligence has managed to create award-winning art, pass the bar exam and even diagnose illnesses better than some doctors. But as AI grows more sophisticated and popular, the voices warning against the potential dangers are growing louder. Geoff Bennett discussed the concerns with Seth Dorbin of the Responsible AI Institute.

There is so much being said about artificial intelligence these days. In order to understand this latest wave of AI, it is important to know how it works and why this moment is different from developments in the past.

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.

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?