#1APR: Deepfake Chance The Rapper rapping about RAG + Events, Lectures, and More!

To kick off our April Digest, here are some interesting events and platforms our team has recently curated:

Hacking The Web Day 2024

Join the hacking community for a knowledge-sharing meetup at the IESB University Center on April 13th. The day will be packed with talks and workshops on hot topics like bug hunting, cloud security, and more.

For more info and registration, head over to: https://gdg.community.dev/events/details/google-gdg-cloud-brasilia-presents-hacking-na-web-day-2024/

Walt.id

Walt.id empowers anyone to build secure digital identities, wallets, and manage NFTs with their open-source toolkit. This all-in-one platform offers various developer kits, like SSI for self-control of digital information, NFT creation and management, and secure wallet building. Walt.id prioritizes transparency with open-source tools, uses secure standards, adheres to regulations, and provides flexible deployment options for both on-premise control and a user-friendly managed service.

Would you use their toolkits? Let us know in the comments!

Blackbox: AI

Blackbox: AI, a company specializing in AI systems, offers powerful tools for developers and content creators. However, these tools come with a caveat: they are "black box" models, meaning the inner workings of the AI are hidden from the user. This lack of transparency can be concerning, as it's difficult to understand how the AI arrives at its decisions. Despite this, Blackbox: AI's models leverage deep learning networks, where the AI is trained on massive datasets and refines its internal algorithms to excel at tasks like image and speech recognition, making them effective for specific applications that require fast and accurate data classification.

Jam

Our last tip before diving into the next section is Jam! This user-friendly tool is a lifesaver for streamlining bug reporting.

Now we'll delve into some fascinating videos and documentaries on technology that have captivated our team. Stay tuned for some mind-blowing insights!

How RAG works by Chance The Rapper

Ever dreamed of having Dua Lipa make your unbearable physics class bearable? AI's rapid development in the past year is no surprise, and now incredibly realistic videos can be generated from text.

A collaborator sent us a video from @howtofly, a YouTube channel creating engaging explainer videos on various generative AI topics. They also empower viewers with "How To" tutorials to help build and test their own generative AI ideas quickly and affordably. Their latest video features a deepfake of Chance The Rapper explaining how Retrieval-Augmented Generation (RAG) improves the up-to-dateness of LLMs like ChatGPT. It's not just curious and impressive; it sparks the imagination! Those who watched definitely thought so too:

This approach could be a valuable resource for educators struggling to compete with the allure of screens in the classroom. What do you think? Would you prefer Ryan Gosling explaining how an LLM model works?

For JavaScript lovers, a documentary about the origin of Node.js

The documentary, titled "Node.js: The Documentary", was released in 2014 and tells the story of how Node.js came to be. Featuring interviews with key figures like Ryan Dahl (the creator), the documentary unveils the journey of Node.js from its early days to its current status as a web development powerhouse. It delves into the impact Node.js has had on the community and leaves you with a newfound appreciation for this popular platform.

What's next for AI agentic workflows?

Dr. Andrew Ng, a globally recognized leader in Artificial Intelligence (AI), holds a distinguished career. He founded DeepLearning.AI and Landing AI (as Founder & CEO), serves as General Partner at AI Fund, and currently acts as Adjunct Professor at Stanford University's Computer Science Department. Dr. Ng recently spoke at Sequoia Capital's AI Ascent about the future of AI agentic workflows and their potential to significantly propel AI advancements—perhaps even surpassing the impact of the forthcoming generation of foundational models.

Building and Understanding LLMs with Andrej Karpathy

This lecture by Andrej Karpathy dives deep into building a tokenizer from scratch, just like the ones used in OpenAI's GPT series. Interestingly, Karpathy explores how many of the quirks and issues we see in LLMs can be traced back to the tokenizer itself. He'll delve into these problems and explore why an ideal solution might involve removing this stage altogether.

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