Meta is reportedly ditching open Llama models for Avocado, a closed model built for direct sales

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'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.

Nvidia has stated that it has not observed any substantiation or received tips regarding chip smuggling through data centers outside of China, following a report by The Information about the Chinese AI startup DeepSeek's use of banned Nvidia chips for its AI models.

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.

A recent study introduces a hybrid model for stock market forecasting that integrates news sentiment and time series data using Graph Neural Networks (GNNs). This approach contrasts with traditional models that primarily rely on historical price data, aiming to enhance prediction accuracy by incorporating external signals from financial news articles. The GNN model was evaluated against a baseline Long Short-Term Memory (LSTM) model, demonstrating superior performance in predicting stock price movements.

Accenture and Anthropic have announced a significant expansion of their partnership, forming the Accenture Anthropic Business Group, which will involve training approximately 30,000 professionals to facilitate the transition from AI pilots to full-scale deployment. This initiative was discussed by the CEOs of both companies on Bloomberg's 'The Close.'