Mark Zuckerberg is Making Big Cuts to the Metaverse After $77 Billion Loss

A coalition of state attorneys general has issued a warning to major tech companies, including Meta, Microsoft, Google, and Apple, regarding the potential legal implications of their chatbots producing what they describe as 'delusional outputs.' This letter emphasizes concerns that such outputs may violate state laws, highlighting the need for accountability in AI technologies.

Meta is reportedly developing a new AI model named 'Avocado,' which may not be open source. This initiative reflects the company's ongoing commitment to advancing its artificial intelligence capabilities amidst a competitive landscape.

Meta is reportedly transitioning from its open Llama models to a new AI model codenamed 'Avocado,' which is expected to be a closed model aimed at direct sales, with a potential release in spring 2026. This shift indicates a strategic pivot in Meta's approach to AI development.

Meta's leading artificial intelligence team is experiencing internal friction, creating an us-versus-them mentality with long-standing associates of CEO Mark Zuckerberg. This discord arises amid significant changes in the company's AI initiatives and strategic direction.

Meta Platforms Inc. is reportedly developing a new artificial intelligence model, codenamed Avocado, which is expected to launch in spring 2026 as a closed model. This shift towards closed models is advocated by Alexandr Wang, indicating a strategic pivot for Meta as it seeks to monetize its AI technologies.

Google’s Tensor Processing Units (TPUs), specifically the TPUv7, are emerging as a formidable alternative to Nvidia’s GPUs, which have dominated AI advancements for over a decade. This shift is exemplified by the training of cutting-edge models like Google’s Gemini 3 and Anthropic’s Claude 4.5 Opus on TPUs rather than Nvidia hardware.

The paper presents a novel approach to Federated Learning (FL) within the Industrial Internet of Things (IIoT), focusing on a satisfaction-aware incentive scheme that utilizes a deep reinforcement learning-based Stackelberg game. This method aims to optimize the balance between model quality and training latency, addressing a significant challenge in distributed model training while ensuring data privacy.

Meta is implementing changes to simplify Facebook, aiming to enhance user experience by streamlining features and reducing complexity. This initiative reflects the company's ongoing efforts to address user feedback and improve engagement on the platform.