According to Google DeepMind on X, the company upgraded its specialized reasoning mode Gemini 3 Deep Think to address complex science, research, and engineering problems, highlighting a real-world use case where Duke University’s Wang Lab applies the model to design new semiconductor materials. As reported by Google DeepMind, the upgrade targets systematic multi-step reasoning, enabling hypothesis generation, literature-grounded planning, and constraint-aware optimization for materials discovery workflows. According to the same source, the lab workflow integrates Gemini 3 Deep Think to propose candidate materials, assess properties against fabrication constraints, and iterate designs, indicating potential reductions in design cycles and improved researcher productivity in semiconductor R&D. As posted by Google DeepMind, this positions multimodal reasoning models as decision-support tools for labs seeking faster experimentation, with opportunities for industry partners to accelerate materials screening, process tuning, and yield optimization.

According to Sawyer Merritt on Twitter, Elon Musk identified chip production as the primary limiting factor for Tesla’s future growth, particularly for AI-driven applications. Musk stated that even the most optimistic supply forecasts from current suppliers fall short, prompting Tesla to consider constructing a large-scale domestic semiconductor fabrication plant, or 'terafab'. This move targets removing chip constraints within three to four years, a key step to enable Tesla’s AI and machine learning advancements at scale. As reported by Sawyer Merritt, Musk emphasized Tesla’s history of tackling challenging projects, suggesting that vertical integration in chip manufacturing could become central to Tesla’s AI business strategy.