🛒 Meta Buys Limitless AI Wearables: Meta acquired pendant-maker Limitless, ending device sales and winding down software as the team joins Reality Labs to accelerate Meta’s AI-enabled wearables.

🚀 ChatGPT Growth Slows as Gemini Surges: Sensor Tower says ChatGPT’s monthly users rose just 6% since August to ~810M, while Gemini jumped 30%, narrowing the gap as Google leverages Android integration and Nano Banana’s popularity.

💼 Hinton Warns of AI Job Losses: Hinton says mass unemployment is very likely due to AI; cites studies predicting up to 100 million jobs lost as tech layoffs highlight accelerating automation risks.

🧐 Huang Downplays AI Doom in Rogan Interview: NVIDIA’s Jensen Huang says AI’s long-term risks remain unknown but rejects apocalypse claims, while praising U.S. tech policy and predicting nuclear-powered data centers within seven years.

👩‍⚖️ NYT Sues Perplexity Over Copyright Use (Paywall): The New York Times filed a federal suit alleging Perplexity reproduced Times articles without permission, joining 40+ similar A.I. disputes as publishers challenge training and output practices.

📝 Meta Signs Broad AI News Deals: Meta inked data agreements with outlets including USA Today, CNN and Le Monde to feed real-time news into its chatbot, aiming to boost AI engagement amid rising competition.

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The Recap: The New York Times writer, Sam Kriss, dissects the increasingly recognizable, and increasingly everywhere, voice of AI-generated prose. Kriss argues that today’s large language models have developed a bizarre, overfitted rhetorical style marked by em-dashes, triplets, spectral metaphors, and an obsession with words like “delve,” shaping not just machine writing but human communication. He warns that as people unconsciously absorb these patterns, the boundary between human and machine style is blurring in ways both cultural and unsettling.

Highlights:

Forward Future Takeaways:
AI’s stylistic fingerprints are no longer just a technical artifact, they’re becoming a cultural feedback loop, shaping how institutions talk to the public and how people talk to one another. As machine-generated language saturates communication channels, distinguishing authorship may become less important than understanding how algorithmically amplified patterns reshape tone, metaphor, and emotional expression. → Read the full article here. (Paywall)

The Recap: The Economist argues that AI-enabled toys, tutors, and entertainment are transforming childhood by offering personalization once reserved for the wealthy. The piece highlights both the promise—tailored learning, adaptive games, bespoke stories—and the hazards, from hallucinating tutors to sexualized toys, echo chambers, and emotionally lopsided relationships with chatbots. The magazine concludes that schools and parents must actively preserve human socialization and limit over-personalization to prevent AI from narrowing children’s experiences and undermining long-term resilience.

Highlights:

Forward Future Takeaways:
AI is accelerating a shift toward hyper-personalized childhoods—efficient, responsive, and emotionally frictionless—but those same qualities risk stripping away the unpredictability and interpersonal challenge that underpin social development. With children forming habits and identities amid AI-mediated play, tutoring, and companionship, the societal responsibility is less about banning technology and more about curating human counterweights: disagreement, diversity of experience, and genuine relationships. → Read the full article here. (Paywall)

Google DeepMind introduced Gemini 3 Pro on December 5, 2025, calling it its most capable multimodal model to date, with state-of-the-art results in document, spatial, screen, and video understanding. The model posts new highs on benchmarks including MMMU Pro, Video MMMU, and CharXiv Reasoning (80.5%), driven by stronger OCR, “derendering,” and multi-step analytical reasoning.

Gemini 3 Pro also expands spatial and screen understanding for robotics and computer-use agents, and lifts video performance through higher framerate parsing and improved temporal reasoning. Google highlights early use cases in education, medical imaging, law and finance, where complex visual and workflow tasks benefit from higher accuracy. Developers can now tune performance via a media_resolution parameter to balance visual fidelity and cost. → Read the full article here.

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Matthew Berman & The Forward Future Team

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