Updates to AI Tools for Research, Art, Video & Code
This week we look at NotebookLM's new research features, Midjourney's personalized art generation, Kling AI's video creation tools, and GitHub Copilot's free tier making AI tools more accessible.
🎨 NotebookLM Unveils New Look and Interactive Features: Enhanced UI and Audio Overviews Make Research More Engaging
What it is: NotebookLM is Google's AI-powered research assistant that helps users understand and work with their documents and sources. Think of it as a smart study buddy that can chat about your content, create summaries, and turn your research materials into engaging audio conversations.
The platform's new design brings a thoughtfully organized workspace with three seamless panels: Sources for your materials, Chat for discussions, and Studio for content creation. The most exciting addition is the ability to have natural conversations with AI hosts during Audio Overviews – imagine having a knowledgeable tutor who can explain complex topics exactly when you need clarification.
Why it matters: For researchers, students, and curious minds, these updates transform solitary study sessions into interactive learning experiences. Whether you're reviewing documents at your desk or listening to summaries during your commute, NotebookLM now adapts to your learning style. The fluid interface lets you naturally flow between reading a source document, discussing its implications, and creating new content – all while maintaining context and momentum in your research process. blog.google
🎨 Midjourney Introduces "Moodboards" for Personalized AI Art: Transform Your Visual Ideas into Custom Models
What it is: Midjourney is a leading AI art generation platform that turns text descriptions into stunning images. Their latest update introduces two powerful personalization features: Moodboards and Personalization Profiles.
Moodboards let you inspire the AI by uploading collections of images that represent your desired style or aesthetic. Think of it like creating a Pinterest board that the AI can learn from. Meanwhile, Personalization Profiles work through a rating system – you rate image pairs to help the AI understand your preferences. These profiles need just 40 ratings to get started, though they continue to improve with more feedback (up to 2,000 ratings for subtle refinements).
Why it matters: For creators, designers, and artists, these features eliminate the frustration of trying to perfectly describe your vision in words. Whether you prefer collecting inspiration images or rating examples, you can now train Midjourney to understand your aesthetic. The addition of multiple personalization profiles means you can maintain different styles for different projects – perhaps one for your client work, another for personal projects, and a third for experimental pieces. Combined with the 5x faster image ranking process, you can now move from inspiration to creation more efficiently than ever. x.com/midjourney
🎉 Kling AI's Text-to-Video Model Gets Major Upgrade: Creating Dynamic Videos Just Got Easier
More AI everywhere doesn’t mean better results. Small teams of AI experts beat mass licenses. Attackers now use AI to run cybercrime at machine speed. Leaders can’t keep up. Tools still forget us. The winners? Focused expertise and hybrid AI, not AI everywhere.
You've built something and you need to know if it works. So you do what's sensible—you ask an LLM to grade it. Factual accuracy, code quality, agent outputs. The machine judges the machine, and you get a number you can act on. Except that number
Imagine you have a bunch of teams, some with AI, some without, and some where everyone gets their own AI. Researchers ran a big experiment with over 400 people to see what actually happens when you mix and match humans and AI in different ways.
Here’s what they found:
