AIGuys Digest
🌟 Welcome to the AIGuys Digest Newsletter, where we cover State-of-the-Art AI breakthroughs and all the major AI news🚀
In this thrilling edition of April 2024, we’re diving headfirst into the ever-evolving universe of Artificial Intelligence. 🧠✨ Here, innovation isn’t just a buzzword — it’s the heartbeat of our community.
And if you want to up your AI game, please check my new book on AI, which covers a lot of AI optimizations and hands-on code:
Ultimate Neural Network Programming with Python
🔍 Inside this Issue:
- 🤖 Latest Breakthroughs: This month it is all about Self Reward, LLMs, and RAG 2.0.
- 🌐 AI Monthly News: Discover how these innovations are revolutionizing industries and everyday life: Meta Stepping into Hardware, Best Open Source Llama 3, Adobe Stealing Data, and Microsoft’s VASA: Facial Video Generation.
- 📚 Editor’s Special: This covers the interesting talks, lectures, and articles I came across recently.
Join us on this exciting journey as we navigate the frontiers of AI, where each discovery is a stepping stone towards a smarter, more interconnected world. 🌌
Let’s embark on this journey of discovery together!* 🚀🤖🌟
Follow me on Twitter and LinkedIn at RealAIGuys and AIGuysEditor.
Latest Breakthroughs
Current Language models are bottlenecked not only by the quantity of labeled data but also by the quality of labeled data. Let’s take a deep dive into the world of Self-Rewarding LLM.
Next, we look into the production issues that you might face during the productionization of RAG applications. This contains things like, how to parse PDFs, how to extract tables and put them in the RAG, and many more.
Solving Production Issues in RAG
Solving Production Issues in RAG-II
Finally, let’s look at the RAG 2.0 blog, one of the most comprehensive piece on Advance RAG solutions. This blog has garnered a lot of attention and is a kind of research summary of the entire RAG technology.
RAG 2.0: Retrieval Augmented Language Models
AI Weekly News
Meta Stepping into Hardware
Meta’s Next-Generation Training and Inference Accelerator (MTIA): Meta unveiled its second-generation AI training and inference chip, which shows substantial improvements in performance over its predecessor. This new chip, produced with TSMC’s 5nm process, features increased processing capabilities, memory bandwidth, and energy efficiency, enhancing the performance of AI-driven applications and services significantly. This development marks a significant step for Meta in boosting its AI infrastructure to support more complex AI workloads efficiently (Meta AI)
Meta’s Blog: click here
Llama 3: A Big Win for Open Source
The state-of-the-art performance of Llama 3, is an openly accessible model that excels at language nuances, contextual understanding, and complex tasks like translation and dialogue generation. Llama 3 can handle multi-step tasks effortlessly, while our refined post-training processes significantly lower false refusal rates, improve response alignment, and boost diversity in model answers. Additionally, it drastically elevates capabilities like reasoning, code generation, and instruction following. Build the future of AI with Llama 3.
Llama 3 Blog: click here
Adobe Firefly stealing data
Adobe introduced Firefly AI, trained on images from Midjourney, basically, they stole the Midjourney’s database. This move by Adobe points to the growing trend of ethical considerations in AI development, focusing on responsibly sourced training materials to avoid biases and improve the generality of AI models.
Bloomberg’s report: Click here
Microsoft’s VASA: Generating Hyperrealistic human face videos
VASA, is a framework for generating lifelike talking faces of virtual characters with appealing visual affective skills (VAS), given a single static image and a speech audio clip. Our premiere model, VASA-1, is capable of not only producing lip movements that are exquisitely synchronized with the audio, but also capturing a large spectrum of facial nuances and natural head motions that contribute to the perception of authenticity and liveliness. The core innovations include a holistic facial dynamics and head movement generation model that works in a face latent space, and the development of such an expressive and disentangled face latent space using videos.
Research report: click here
Editor’s Special
- A talk from Prof. Subbarao on LLM planning and reasoning capabilities (CoT and ReAct) @ Google: Click here
- What’s next for LLM by Dietrich: Click here
- Debunking the hyped Automated AI software Engineer Devin: Click here
As we wrap up this edition of AIGuys Digest, we hope you’ve found inspiration and insight in our curated collection of AI news and breakthroughs. 🌌✨ Remember, each article, each update, and each discussion is a tile in the vast mosaic of AI’s future.
🚀 Stay Curious, Stay Informed: We encourage you to keep exploring, questioning, and learning. AI isn’t just a field of study; it’s a journey of continuous discovery and innovation.
🤝 Join the Conversation: Your thoughts and insights are valuable to us. Share your perspectives, and let’s build a community where knowledge and ideas flow freely. Follow me on Twitter and LinkedIn at RealAIGuys and AIGuysEditor.
🔔 Stay Tuned: We’ll be back with more AI insights and news. Until then, keep an eye on the horizon of AI, where the possibilities are as limitless as our collective imagination.
Thank you for being part of the AIGuys community. Together, we’re not just observing the AI revolution; we’re part of it. 🚀🌟
Until next time, keep pushing the boundaries of what’s possible.
Your AIGuys Digest Team
