Meta trains home-cleaning AI agents
Plus: NVIDIA's AI teaches robots complex skills, OpenAI's secret sauce to Dall-E 3's accuracy.
Hello Engineering Leaders and AI Enthusiasts!
Welcome to the 131st edition of The AI Edge newsletter. This edition brings you Meta’s advancements to develop socially intelligent AI agents.
And a huge shoutout to our incredible readers. We appreciate you😊
In today’s edition:
🤖 Meta’s Habitat 3.0 can train AI agents to assist humans in daily tasks
🔥NVIDIA's AI teaches robots complex skills on par with humans
🧪 OpenAI’s secret sauce behind Dall-E 3’s accuracy
📚 Knowledge Nugget: 10x Charting the AI Frontier by
Let’s go!
Meta’s Habitat 3.0 can train AI agents to assist humans in daily tasks
Meta has announced three major advancements toward the development of socially intelligent AI agents that can cooperate with and assist humans in their daily lives:
Habitat 3.0: The highest-quality simulator that supports both robots and humanoid avatars and allows for human-robot collaboration in home-like environments. AI agents trained with Habitat 3.0 learn to find and collaborate with human partners at everyday tasks like cleaning up a house. These AI agents are evaluated with real human partners using a simulated human-in-the-loop evaluation framework (also provided with Habitat 3.0).
Habitat Synthetic Scenes Dataset (HSSD-200): An artist-authored 3D scene dataset that more closely mirrors physical scenes. It comprises 211 high-qualtiy 3D scenes and a diverse set of 18,656 models of physical-world objects from 466 semantic categories.
HomeRobot: An affordable home robot assistant hardware and software platform in which the robot can perform open vocabulary tasks in both simulated and physical-world environments.
Why does this matter?
This marks a significant shift in the development of AI agents. In addition, it is a leap in the field of robotics. These innovations enable AI agents to intelligently assist humans, paving way for making AI a more valuable part of our daily lives and even the business world.
NVIDIA's AI teaches robots complex skills on par with humans
A new AI agent developed by NVIDIA Research that can teach robots complex skills has trained a robotic hand to perform rapid pen-spinning tricks– for the first time as well as a human can.
The above are some of nearly 30 tasks that robots have learned to expertly accomplish thanks to Eureka, which uses LLMs to automatically generate reward algorithms to train robots. Eureka is powered by the GPT-4. Eureka-generated reward programs outperform expert human-written ones on more than 80% of tasks.
Why does this matter?
Another game changer in robotic training with AI. It seems AI/LLMs will continue to ease training of robots, making them as proficient as humans in various tasks.
OpenAI’s secret sauce of Dall-E 3’s accuracy
OpenAI published a paper on DALL-E 3, explaining why the new AI image generator follows prompts much more accurately than comparable systems.
Prior to the actual training of DALL-E 3, OpenAI trained its own AI image labeler, which was then used to relabel the image dataset for training the actual DALL-E 3 image system. During the relabeling process, OpenAI paid particular attention to detailed descriptions.
Why does this matter?
The controllability of image generation systems is still a challenge as they often overlook the words, word ordering, or meaning in a given caption. Caption improvement is a new approach to addressing the challenge. However, the image labeling innovation is only part of what's new in DALL-E 3, which has many improvements over DALL-E 2 not disclosed by OpenAI.
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Knowledge Nugget: 10x Charting the AI Frontier
There’s no better teacher than experience. In a podcast hosted by
at ManagersClub, gives pragmatic strategies and insights on successfully adopting AI technologies in engineering teams. He delves into:Changes in his team’s approach to software development with the advent of GenAI
Where GenAI can fall short, and how to communicate these limitations to your team and stakeholders
Tools, platforms, or frameworks that have been invaluable in accelerating AI integration
How GenAI changed collaboration between data scientists, software engineers, and product managers
Challenges faced and solutions adopted in implementing an AI strategy
And so much more. This blog transcribes and augments some of the discussion from the podcast.
Why does this matter?
AI is rapidly evolving, and implementing it in tech companies can be a complex endeavor. This discussion offers some practical advice based on real-life experience, making it a valuable resource for those navigating the AI landscape.
What Else Is Happening❗
🧠IBM is developing a brain-inspired chip for faster, more energy-efficient AI.
New research out of IBM Research’s lab, nearly two decades in the making, has the potential to drastically shift how we can efficiently scale up powerful AI hardware systems. The new type of digital AI chip for neural inference is called NorthPole. (Link)
🔁Oracle loops in Nvidia AI for end-to-end model development.
Oracle is bringing Nvidia AI stack to its marketplace to simplify AI development and deployment for its customers. It gives Oracle customers access to the most sought-after, top-of-the-line GPUs for training foundation models and building generative applications. (Link)
🎤YouTube is developing an AI tool to help creators sound like famous musicians.
In beta, the tool will let a select pool of artists give permission to a select group of creators to use their voices in videos on the platform. Negotiations with major labels are ongoing and slowing down the project's beta release. (Link)
🎗️There’s now an AI cancer survivor calculator.
Researchers have created an AI-based tool to predict a cancer patient's odds of long-term survival after a fresh diagnosis. It was found to accurately predict cancer survival length for three types of cancers. (Link)
📸Instagram’s latest AI feature test is a way to make stickers from photos.
Meta’s newest sticker feature is much like the one built into the iPhone Messages app in iOS 17– Instagram detects and cuts out an object from a photo so you can place it over another. (Link)
That's all for now!
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