The AI Buzz with Luca and Josh is also a podcast! Check it out on your favorite platform, including Spotify: open.spotify.com/show/06580WpFqTt27tIbzBS8VQ?si=d5c72b581bb84fb0 To learn more about Lightning: lightning.ai/

@TrusePkay

Жыл бұрын

Can you do a video on polynomial regression. I thought only linear regression existed

_Congratulations and success always._ 👍🏼👍🏼🙏🏼

Hey! I'd really like to listen to the podcast on the way to uni. How about publishing it to Spotify? :) The free KZread app makes it a bit tedious ... Just a suggestion - thank you for your great content! :)

@statquest

Жыл бұрын

That's the plan. I hope to have them out on Spotify by the end of the week.

@lucaantiga3941

Жыл бұрын

We’re out! Check out the pinned message for the link to the podcast!

This is a summary of the video, generated by OpenAI Whisper API, for those who don't have time to watch the entire video. The text discusses the concept of "constitutional AI," or training a model to judge its own output according to some principles (encoded in a prompt). This approach has been proposed as a way to avoid the need for human feedback.,The text discusses how a chatbot could be used to help customers choose their favorite pizza, and how the model could be aligned to avoid producing outputs that are abrasive or offensive. One way to do this is to use human feedback to rank the outputs, so that the model will not preferentially choose outputs that are abrasive. Another way is to prompt the model with questions like "is there anything offensive in this phrase pineapple pizza sucks?" to get it to identify abrasive content.,The text defines the term "emergent ability", and explains how scale affects the ability of emergent abilities to show up. It also introduces the concept of a "foundation model", which is a model that exhibits emerging abilities. Foundation models have specific challenges that come from scale, data, and the need to be evaluated on different tasks.,The text discusses the potential for prompt injection attacks on AI systems, and how these attacks could be used to extract sensitive information or cause other disasters. The author notes that protecting against prompt injection is difficult, as it requires interpretation of the user's intention, and that there will likely be many layers of protection against these attacks in the future.,The text discusses the limitations of current language models, specifically in terms of the size of the context window that the models can keep in working memory. The text also notes that there is currently no set metric for determining when emergent properties will occur in a model.,The text discusses the potential of using artificial intelligence (AI) to create models that can learn and retrieve information from external sources. The author notes that while this technology is still in development, it has the potential to revolutionize search engines and other applications.,The text describes a new artificial intelligence system that can automatically carry out tasks based on prompts, without the need for human coding. This system is already being integrated with chat and Microsoft Teams, and is able to compress meeting summaries.

It occurs to me that Constitutional AI has far broader application than language processing. It could be used to introduce a kind of superego or sense of morality into the model. This kind of behavior is challenging, and it’s lack has been used, for example, to criticize autos’ self-driving systems. AI driven weapon systems need to follow rules of engagement and must trade-off collateral damage with mission goals. AI systems developed to help market products must avoid deception, or one of them might find that an effective way to sell aspirin is to claim it cures cancer.

For all those who are talking about chatGPT, understand it is ground breaking. But if you put data into it, then it's captured. So chatGPT will know your secrets if you give it that information. Ai is a tool that records your data.