Projects

A digital garden combined with an AI platform would be a highly interactive and personalized learning environment. Here's a brief description:

Digital Garden: This is a metaphor for thinking about writing and creating that focuses less on the resulting " showpiece" and more on the process, care, and craft it takes to get there. It's a place where ideas, thoughts, notes, and learning resources grow over time. It's a de-emphasized publishing, where the importance is on the process of thought and learning, rather than the outcome.

AI Platform: This is a suite of services that provide machine learning and data analysis capabilities. It includes services for data storage, data processing, machine learning model training, and prediction generation.

When combined, a digital garden with an AI platform could look like this:

Personalized Learning Paths: The AI could analyze a user's interactions, interests, and learning progress within the digital garden to suggest personalized learning paths. It could recommend resources, topics, or areas of study that align with the user's goals and interests.

Interactive Content: The AI could generate interactive content based on the user's learning path. This could include quizzes, simulations, or problem-solving exercises that help reinforce learning.

Content Generation and Enhancement: The AI could assist in generating new content for the digital garden. For example, it could suggest new topics to explore, generate summaries of complex materials, or enhance existing content with additional insights or resources.

Community Interaction: The AI could facilitate interaction within the community of learners. It could suggest collaborations based on shared interests, facilitate discussions, or help users find mentors or study groups.

Continuous Learning: The AI could monitor the user's progress and adapt the learning path as needed. It could suggest new resources when the user is ready to advance or provide additional support if the user is struggling.

In essence, a digital garden combined with an AI platform would be a dynamic, adaptive, and interactive learning environment that grows and evolves with the learner.

This website!

The idea: stay in tune with trending software, topics, and people by tracking the following sources:

1. GitHub's trending pages.
2. Hacker News "show" posts and associated comments to identify alternatives.
3. "Awesome" lists on GitHub. https://github.com/topics/awesome
4. Mastodon
5. YouTube channels
6. RSS feeds
7. Job Posts
8. Books about topics you're interested in or by authors you follow.
9. TV shows and movies.
10. Latest papers from arXiv, etc.
11. Local news

Features

• Ability to "follow" specific companies, projects, topics and people/username.
• Recommend books and YouTube channels based on followed companies, projects and people.
• Choose how and when to stay informed. (immediately, daily, weekly, etc.)
• Weighting system based on who/what you follow.
• Latest product releases from companies you follow.
• Stock tickers and news related to companies in your portfolio.
• Keep up to date with the latest framework and library releases you routinely use.

Similar Ideas and Projects

• Reclaiming the Web with a Personal Reader, Hacker News discussion here.

A distributed asynchronous image processing service written using Spring Boot with Kotlin and Coroutines. The service is designed to be horizontally scalable and can be deployed to Kubernetes or run locally. It also uses Postgres and NATS.

A service targeted to job seekers which uses custom algorithms to find jobs that are highly suited to candidates. Based on the candidates values and preferences, the service will search for companies that are a good fit. The service will also provide a list of questions to ask during the interview process to help candidates determine if the company is a good fit for them. An iterative process combined with AI capabilities will be used to refine the algorithm and improve the results.

Simple web scraping API that allows users to scrape a single web page and provide method and selector parameters to extract data from the page. The API will return the data in JSON format.

An example might look like this:

http://futz.io/[url]?method=[method]&selector=[selector]&output=[output]

Where:

• url is the URL of the page to scrape
• method is the method to use to extract data from the page (e.g. querySelectorAll)
• selector is the selector to use to extract data from the page (e.g. div > p)
• output is the format of the output (e.g. json or text)********

For more elaborate needs a POST endpoint could be used to enable providing required credentials or request headers.

A service targeted to DIY automobile mechanics who work on classic Toyota Land Cruisers.

The idea: a composition framework for generating distributed system projects from structured data and predefined, opinionated templates.