Personal AI for your podcasts and community
A podcast AI for your community.
Personal AI is a GPT implementation designed to mimic an individual’s behavior and to speak like them. It’s similar to ChatGPT in its functions but built on the personal data of the individual, providing personal attribution scores for each AI response. For a full review of Personal AI vs Open AI, give this article a read.
We find that people have multiple personas and profiles of their lives and that they need a way to organize them. Examples include differentiating between family, friends, Twitter, podcasts, school, projects, communities, etc. So we have created a way for people to replicate their multiple personas in the form of AI profiles.
Various AI Profiles including Podcasts
In this article, I’ll be explaining and demonstrating my method of using AI profiles to create a podcast persona from all the podcast episodes I’ve been a part of. Of course, all the profiles I do create are accumulated in my primary personal AI, which is composed of all my profiles.
Personal AI currently supports using Youtube URLs for media upload. Your personal AI automatically processes the transcriptions to your memory stack. It makes it easy to use one standard medium since Youtube supports different types of media.
I collected all my podcasts and uploaded them to a personal Youtube channel. Some of my podcast episodes are already on youtube, so I don’t have to re-upload them as much as I would like to add to my collection. I then got all the links handy.
Create a new personal AI profile. I named it “My Podcasts”. Simply paste the youtube URL in the message bar and send. Repeat the process to push all your podcasts. Once the stack is updated and trained (which happens automatically after you press stack next to the URL) it’s time to interact.
Personal AI calls their chat implementation of GPT architecture; ChatGGT, more simply put- it’s a personal ChatGPT.
Me> what are you passionate about?MyAI> I am passionate about solving problems for humans by converging multiple emerging technologies.Me> when did you get involved with AI?MyAI> I got involved with AI in 2016–2017 when I started working on Aira.Me> list your principles on how AI is applicable to Web3MyAI> 1. Data is needed to create the model 2. Data ownership is a key principle of web3 3. NFTs are a good example of how data can be sold as an asset on the internetMe> write a tweet about your principles of AI in Web3MyAI> Web 3 is all about data ownership and privacy. AI can help extract utility and value from this data to create own, individual models.Me> write a blog about your principles of AI in Web3MyAI> My principles of AI in web3 are data ownership, privacy, and trust. Data ownership means that everyone who creates data on the internet owns it. Privacy means that individuals can walk away with their own data. Trust means that blockchain can be used to establish trust between humans and AI.Me> write a blog about AI impact in Web3MyAI> The impact of artificial intelligence (AI) on web 3.0 is far-reaching and potentially game-changing. For starters, AI can help to improve the quality of data that is available on the web. This, in turn, can make search engines more effective and efficient, as well as help to reduce spam and other unwanted content.In addition, AI can also be used to create more personalized experiences for users of web 3.0 applications. By understanding a user’s preferences and behaviour, AI can provide recommendations or tailor content in a way that is most relevant to the individual. This could result in a more engaging and enjoyable experience for users, which could lead to increased adoption of web 3.0 applications.Finally, AI can also help to improve the security of web 3.0 applications by identifying potential threats and vulnerabilities before they are exploited. In this way, AI can play a key role in protecting users’ data and privacy while also helping to ensure the smooth functioning of the overall system.
Screenshot me talking with my podcasts AI profile