According to Yann LeCun on X (formerly Twitter), who responded to a post by @polynoamial, there is strong support among AI leaders for a nuanced perspective on the role and limitations of foundation models in artificial intelligence. LeCun's endorsement highlights an ongoing industry discussion about the practical scalability and adaptability of large language models in real-world business applications (source: https://twitter.com/ylecun/status/1994533846885523852). This conversation signals the need for enterprises to critically assess the adoption of AI foundation models, balancing innovation with realistic expectations for operational integration, cost, and performance. AI technology providers and startups should take note, as this trend opens opportunities for specialized, domain-adapted AI solutions tailored to specific industry needs.

According to God of Prompt on Twitter, Gemini 3 Pro successfully created a superior version of a Perplexity AI clone in a single attempt, then further improved upon it when prompted. This demonstrates Gemini 3 Pro’s advanced AI chatbot capabilities, setting a new benchmark for real-time question-answering tools. The rapid iteration and enhancement highlight the model’s potential in driving business applications such as customer support automation, knowledge management, and AI-driven research assistants. These developments indicate a growing trend toward more capable, easily customizable foundation models for enterprises, increasing efficiency and reducing deployment time (source: @godofprompt, Nov 18, 2025).

According to Soumith Chintala (@soumithchintala), he is stepping down as leader of PyTorch and leaving Meta after 11 years, marking a significant leadership transition for one of the most widely adopted AI frameworks in the world. Chintala emphasized that PyTorch now powers exascale AI training, supports advanced foundation models, and is deployed at nearly every major AI company, highlighting its critical role in AI development and business applications (Source: Soumith Chintala, Twitter, Nov 6, 2025). He expressed strong confidence in PyTorch's stability and the resilience of its core team, citing their technical and organizational readiness. This leadership change signals both the maturity of the PyTorch ecosystem and ongoing opportunities for innovation in AI infrastructure, as open-source tools remain foundational to the global AI industry.

According to Anthropic (@AnthropicAI), the company has announced plans to expand its use of Google TPUs, securing approximately one million TPUs and more than a gigawatt of capacity for 2026. This large-scale investment aims to significantly boost Anthropic's AI model training and deployment capabilities, positioning the company to scale up its advanced AI systems and support enterprise demand. This move highlights the accelerating trend of hyperscale AI infrastructure investment and demonstrates the growing importance of robust, energy-efficient hardware for training next-generation foundation models and powering AI-driven business applications (Source: AnthropicAI on Twitter, Oct 23, 2025).

According to Yann LeCun (@ylecun), his keynote and fireside chat with Melissa Heikkilä from the Financial Times at Vivatech 2025 focused on emerging AI research trends and their business applications. LeCun discussed the evolution of foundation models, the commercial impact of generative AI, and strategies for leveraging advanced machine learning in enterprise solutions. The session emphasized practical pathways for AI integration in sectors like finance and manufacturing, offering actionable insights for companies looking to capitalize on the latest AI innovations (Source: Yann LeCun on Twitter, linkedin.com/posts/yann-lecun, June 18, 2025).