In this Newsletter Today:

• Google adds a way to create automated workflows to Opal

• Nvidia challenger AI chip startup MatX raised $500M

• Uber engineers built an AI version of their boss

• AI Tutorial

• 5 Best AI Tools

TODAY'S AI" NEWS

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Google adds a way to create automated workflows to Opal

Google is updating Opal, its no-code AI tool. Now, it will add automated workflow creation using an AI agent. This new feature lets users build interactive mini-apps and workflows with easy text prompts. They don't need any technical skills.

Key Points

• AI-powered workflows: A new feature in Opal lets users describe a task in simple English. It builds a workflow that plans and executes tasks, automatically choosing the right tools.

• Gemini AI inside: This uses Google’s Gemini 3 Flash model. It understands user goals, picks tools like Google Sheets, and plans the next steps by itself.

• Interactive and smart: If the workflow needs more detail, the agent can ask follow-up questions or offer choices before proceeding.

• No coding needed: Now, anyone can create complex multi-step processes. You can manage shopping lists or plan tasks simply by writing what you want.

• Enhanced mini-apps: The upgrade changes static app templates into dynamic workflows. These workflows can remember details from past sessions. They adjust based on user input and work intelligently.

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Nvidia challenger AI chip startup MatX raised $500M

MatX is a new AI chip company founded by former Google hardware engineers. They have raised $500 million in Series B funding to develop next-gen processors to compete with Nvidia’s GPUs in AI tasks. This investment shows strong confidence from backers in alternatives to Nvidia’s dominance in AI hardware.

Key Points

• MatX raised $500 million in Series B funding. Jane Street and Situational Awareness, a fund created by a former OpenAI researcher, led the round. Other supporters are Marvell Technology, NFDG, Spark Capital, and Stripe co-founders Patrick and John Collison.

• Founded by Google experts, the startup was started by Reiner Pope and Mike Gunter. They both worked on Google’s Tensor Processing Unit (TPU) chips. This gives MatX strong expertise in AI hardware design.

• MatX has bold goals. It wants to make AI chips that are better for training and inference than Nvidia’s GPUs. This is a bold move in a market where Nvidia is the clear leader.

• Chip timeline: MatX plans to work with TSMC for manufacturing. Shipments are expected to start in 2027, once designs are complete.

• Market landscape: The AI chip sector is getting competitive. Startups and tech giants want to find alternatives to Nvidia’s GPU monopoly. Demand for AI training and inference hardware is rising quickly.

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Uber engineers built an AI version of their boss

Uber engineers made a chatbot that mimics CEO Dara Khosrowshahi. They used internal company data for this project. This tool aims to help employees find answers and context about the company. However, it raises concerns about responsibility, accuracy, and how AI represents actual leaders.

Key Points

• What they built: Uber engineers developed a chat-style AI that mimics CEO Dara Khosrowshahi’s communication style. It uses internal data, like HR policies and product plans, to answer employee questions.

• Purpose: The aim is to help employees grasp company strategy, internal rules, and business details easily. This way, they won’t need to sift through many documents or ask managers directly. It’s for internal use only, not available to customers.

• High expectations come with high risk. The tool is meant to help, but using a simulated voice of a real CEO raises concerns. These include accuracy, misrepresentation, and accountability. This is especially true if the AI sounds like it’s giving official instructions.

• Internal governance: Uber executives are figuring out how to use AI responsibly. They are picking safeguards to use and deciding who will fix any mistakes or miscommunication.

• Wider discussion: This project asks a larger question in the industry — should AI imitate real leaders? Companies are trying new things, but mistakes can lead to confusion. Employees may believe that AI responses show true leadership opinions. This could damage the company's reputation.

Read more

AI TUTORIAL

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