Google's RoboCat Operates Multiple Robots
Plus: vLLM for fast, easy, and cheap LLM serving
Hello Engineering Leaders and AI Enthusiasts!
Welcome to the 46th edition of The AI Edge newsletter. This edition brings you Google DeepMind’s RoboCat operates multiple robots.
And a huge shoutout to our amazing readers. We appreciate you!😊
In today’s edition:
🤖 Google DeepMind’s RoboCat operates multiple robots
🛠️ vLLM: Easy, fast, and cheap LLM serving
📚 Knowledge Nugget: LLM fine-tuning guide for enterprises in 2023
Let’s go!
Google DeepMind’s RoboCat operates multiple robots
Google DeepMind has created RoboCat, an AI model that can control and operate multiple robots. It can learn to do new tasks on various robotic arms with just 100 demonstrations - and improves skills from self-generated training data.
RoboCat learns more quickly than other advanced models because it uses a wide range of datasets. This is a significant development for robotics research as it reduces the reliance on human supervision during training.
Here’s RoboCat’s training cycle, boosted by its ability to generate additional training data autonomously.
Why does this matter?
RoboCat's advancements in learning efficiency, diverse training, and tackling complex skills contribute to the evolution of robotics research, aiming to create more capable and versatile robotic systems.
Moreover, by mastering complex actions such as shape matching and building structures, RoboCat pushes the boundaries of robotic capabilities.
vLLM: Easy, fast, and cheap LLM serving
The performance of LLM serving is bottlenecked by memory. vLLM addresses this with PagedAttention, a novel attention algorithm that brings the classic idea of OS’s virtual memory and paging to LLM serving. It makes vLLM a high-throughput and memory-efficient inference and serving engine for LLMs.
vLLM outperforms HuggingFace Transformers by up to 24x (without requiring any model architecture changes) and Text Generation Inference (TGI) by up to 3.5x, in terms of throughput.
Why does this matter?
Serving refers to making a trained model available for use by applications or systems. However, actually serving LLMs is challenging and can be surprisingly slow, even on expensive hardware. vLLM makes Chatbot/LLM serving faster and more accessible to everyone, enabling developers and organizations to leverage the capabilities of AI easily and cheaply.
Knowledge Nugget: LLM fine-tuning guide for enterprises in 2023
Large language models have greatly enhanced our language processing capabilities. However, their general training may not perform best for specific tasks. To address this, fine-tuning methods are used to customize LLMs for different application areas.
This article provides an in-depth exploration of the reasons, methods, and processes involved in fine-tuning large language models for enterprises. The goal is to optimize these tools to align with different tasks' specific requirements and intricacies.
Also, Foundation models, like large language models, are a core component of AI research and applications. They provide a basis for building more specialized, fine-tuned models for specific tasks or domains.
Why does this matter?
Fine-tuning addresses the limitations of generic LLMs in specialized domains. Enterprises can experience improved task performance, leading to enhanced productivity and decision-making. Moreover, fine-tuning existing LLMs is cost-effective compared to building models from scratch, making it an efficient solution for enterprises.
What Else Is Happening
🖼️ Woo-hoo! See the miraculous results of adding the year to the Midjourney prompt! (Link)
🎉 Cisco has AI networking chips to compete with Broadcom & Marvell. (Link)
📱 OpenAI is creating an App Store for AI Software. (Link)
💰 Teleperformance signs a $185M deal with Microsoft to launch GenAI tool. (Link)
💲 Parrot AI raises $11M Series A! (Link)
🎵 Accurately predicting hit songs w 97% accuracy using neurophysiology & ML. (Link)
Trending Tools
Luma AI: Create lifelike 3D renders of objects for videos. Future of VFX, accessible to all.
Coachvox AI: AI coach/mentor in your style. Add value, engage with clients, generate leads 24/7.
AI Torke: Virtual assistant for content creators & influencers. Faster content creation, attract/monetize followers.
The Drive AI: Organize, read, and write with AI. Group documents, ask questions, AI-powered writing.
AI to Cards: Convert text into flashcards. Export and practice with any repetition system.
SwiftCover AI: Craft tailored cover letters in seconds. Let AI do the work for you.
LowTech AI: AI tools for non-tech-savvy individuals. Simple sharing and using of prompts.
Venturus AI: Refine business ideas with instant insights. Industry trends, marketing strategies, test your idea.
That's all for now!
If you are new to ‘The AI Edge’ newsletter. Subscribe to receive the ‘Ultimate AI tools and ChatGPT Prompt guide’ specifically designed for Engineering Leaders and AI enthusiasts.
Thanks for reading, and see you tomorrow.