Zoom's Inexpensive AI Rivals Microsoft & Google ⚔️🥊💣
Plus: Google DeepMind Scaling Up Robotics Learning, OpenAI Unlocking New Careers in AI/ML.
Hello Engineering Leaders and AI Enthusiasts!
Welcome to the 118th edition of The AI Edge newsletter. This edition brings you Zoom’s new AI, a Cost-Effective Alternative to Microsoft and Google.
And a huge shoutout to our incredible readers. You all rock! 😊
In today’s edition:
⚔️ Zoom's Inexpensive AI Rivals Microsoft & Google
👏🤖Google DeepMind Scaling Up Robotics Learning
🎓 OpenAI Unlocking New Careers in AI/ML
🧠 Knowledge Nugget: How to make history with LLMs & other generative models by
Let’s go!
Zoom's Inexpensive AI Rivals Microsoft & Google
Zoom has announced the launch of Zoom Docs, a collaboration-focused "modular workspace" with built-in AI collaboration features. The platform integrates Zoom's AI Companion, which can generate new content or populate documents from other sources.
Users can ask the AI Companion to summarize meetings, chats, and information, and the platform supports inter-document linking and embedding. Zoom AI Companion is included in the price of paid subscription plans.
Why does this matter?
Zoom is now a stronger contender against Google and Microsoft by offering a comprehensive office suite with AI features at a lower cost, potentially attracting more users away from these giants.
Also, Businesses can save on software costs while improving collaboration and productivity, especially in remote or hybrid work environments.
Google DeepMind Scaling Up Robotics Learning
Researchers of Google Deepmind have created a dataset called Open X-Embodiment, which combines data from 22 different types of robots. They also developed a robotics transformer model called RT-1-X, trained on this dataset, to transfer skills across various robot types.
Testing showed that the RT-1-X model performed significantly better than models trained on data from individual robot types. Additionally, training a visual language action model on data from multiple embodiments tripled its performance. The Open X-Embodiment dataset and RT-1-X model are now available to the research community, with the aim of advancing cross-embodiment research and transforming the way robots are trained.
Why does this matter?
This research holds the promise of delivering more capable and versatile robots, which could translate to improved services and solutions for end users across various industries. It means that we may soon see more adaptable and efficient robots applied in real-world scenarios, from manufacturing to healthcare and autonomous vehicles, ultimately enhancing productivity and safety.
OpenAI Unlocking New Careers in AI/ML
OpenAI has launched “OpenAI Residency”, a six-month program that helps exceptional researchers and engineers from different fields gain the necessary skills and knowledge to transition into the AI and ML space.
It is ideal for researchers specializing in fields like mathematics, physics, or neuroscience, as well as talented software engineers looking to work in AI research. Residents work on real AI problems with OpenAI's Research teams and receive a full salary during the program.
Why does this matter?
The OpenAI Residency program bridges the gap for researchers and engineers, enabling them to enter the AI and ML domain. It also emphasizes value and excellence from diverse educational backgrounds and encourages applicants from all walks of life to apply.
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Knowledge Nugget: How to make history with LLMs & other generative models
This goldmine article by
discusses the evolving landscape of LLMs and generative models, emphasizing the potential for groundbreaking innovations and $10 billion-plus companies in this field. The author reflects on the diverse opinions within the tech community regarding whether startups or established incumbents will lead in harnessing the power of generative technology.They acknowledge the importance of identifying promising areas within the LLM ecosystem and share their personal perspective as an investor, highlighting some ideas and companies they find particularly compelling while remaining open to changing viewpoints.
Why does this matter?
The article explores the dynamic possibilities and challenges associated with LLMs and generative models in the tech industry. It's important for tech stakeholders to grasp the potential to make informed decisions and allocate resources effectively.
What Else Is Happening❗
✅ LinkedIn rolls out new AI tools powered by OpenAI
To enhance learning, recruitment, marketing, & sales, its unveiling features include AI assistance in its Recruiter talent sourcing platform, an AI-powered LinkedIn Learning coach, and an AI tool for marketing campaigns. Also, AI-powered writing suggestions and AI-created job descriptions. (Link)
✅ Arc browser reveals AI features that combine OpenAI's GPT-3.5 & Anthropic's models
Users can converse with ChatGPT, rename pinned tabs and downloaded files, and get a summary preview of links. These features can be accessed through the command bar, and users can choose which ones to enable. (Link)
✅ Spotify is reportedly developing AI-generated playlists that users can create using prompts
Tech veteran Chris Messina discovered references to "AI playlists" and "playlists based on your prompts" in the app's code. This feature may be integrated into the Blend genre, where different users' tastes are mixed to create a playlist. (Link)
✅ New AI startup Ideogram solved the problem of generating images with readable text
Existing AI models like Dall-E 2 and Stable Diffusion often struggle to render text clearly. Ideogram's technology allows users to create images with text that is legible and easy to read. (Link)
✅ An AI algorithm has proven to be more effective than humans at detecting problematic images in research papers
The algorithm, which takes just seconds to scan a paper for duplicated images, identified almost all of the suspect papers that a human biologist had identified, as well as additional ones that the biologist had missed. (Link)
That's all for now!
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