Google Fires 28 Employees After Sit-in Protest Over Controversial Project With Israel. Google dismissed 28 employees after they protested Project Nimbus, a $1.2 billion contract with Israel, alleging it supports military actions. The protests highlight ethical concerns about AI use in conflicts. Google defends the project, countering claims about its military applications. (Link)

AI Frenzy Fuels TSMC's Explosive Growth Forecast. Taiwan Semiconductor Manufacturing Company projects a 30% sales surge due to booming AI chipset demand. With substantial investments in advanced semiconductor technology, TSMC is becoming a dominant force in the AI revolution, positioning it for sustained growth in the tech sector. (Link)

Microsoft Just Revealed VASA-1's Real-Time Talking Faces. Microsoft's VASA-1 introduces real-time talking faces, enhancing digital communication with unprecedented realism. This breakthrough could reshape virtual interactions in sectors from gaming to teleconferencing, setting a new standard for lifelike digital personas. The technology promises a profound shift in the landscape of online interaction. (Link)

How People Are Using Their ‘Digital AI Clones’ To Attend Zoom Meetings. Companies like Delphi and Alt.ai are pioneering digital cloning, enabling people like Deepak Chopra to automate their participation in meetings and other work. These platforms use data to create AI clones that can think, speak, and even appear impatient like their human originals. (Link)

Strut is a comprehensive writing workspace that integrates notes, documents, and projects into one AI-enhanced platform.

It transforms disorganized ideas into structured projects, boosting productivity for both individuals and teams. With features like project workspaces, deep focus modes, and an AI collaborator, Strut supports seamless transitions between writing, collaboration, and project management. It's ideal for writers looking to streamline their creative process.

Explainable AI (XAI) refers to systems and methodologies within artificial intelligence that strive to provide clarity about how AI models reach their decisions.

The goal of XAI is to make the outcomes of AI models comprehensible to human users, particularly in scenarios where transparency is crucial, such as in healthcare, finance, and legal environments. This transparency is essential for trust and helping users make informed decisions based on AI outputs.

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