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AI News Brief: Google has launched an AI assistant called Gemini Spark, positioned as a round-the-clock automation assistant to help users handle daily repetitive tasks. Based on available information, its features cover use cases like email inbox summarization and local event planning suggestions, aiming to cut down the time and energy users spend on trivial information processing. In hands-on testing, Gemini Sp…

AI News Brief: According to tech media reports, Meta is developing an AI wearable device, reportedly in the form of a smart pendant that hangs around the neck. This move shows Meta continuing to extend its AI capabilities into hardware devices, following up on its Ray-Ban smart glasses with another strategic bet on AI hardware. However, public information remains extremely limited, with product specs, positioning, and launch timing all still undisclosed.

AI news brief: Box founder Aaron Levie recently called out a phenomenon he calls ‘AI psychosis’ - the executives who confidently decide ‘AI can replace this role’ are often the people who understand that job the least. He points out this decision-making blind spot is spreading across tech, as leaders get so swept up in AI’s potential that they push through layoffs without really understanding the workflows, responsibilities, and human judgment the job actually requires.

AI News Brief: As artificial intelligence technology rapidly goes mainstream, the industry has spawned a flood of specialized jargon and slang that leaves many newcomers confused. TechCrunch has put together a glossary of common AI terms, covering definitions for the most important terms right now — from technical concepts like hallucination, model, and training data to AI slang that’s increasingly popping up in everyday conversation. The glossary aims to help readers quickly grasp context and meaning when reading AI news or talking with people in the industry.

AI news brief: Researchers warn that while AI tools let developers ship code faster, overall code quality isn’t necessarily improving — and may even be declining. What’s worrying about this trend is that as developers get used to relying on AI autocomplete and generation, their own coding logic and debugging judgment may gradually atrophy, and once enough low-quality code piles up, it can trigger unpredictable chain reactions down the line in maintenance, scaling, and security.