The Economics of AI Explained | Neil Thompson on AI, Chips, & What's Next | Techcetra | Salesforce

PARTNERED Artificial Intelligence is advancing faster than ever—but can this pace continue? In this episode of Techcetra partnered with Salesforce , Leslie D'Monte speaks with Neil Thompson, Director of the FutureTech Research Project at MIT, to explore the economics driving today's AI revolution. While recent breakthroughs have transformed what AI can do, Neil explains that much of this progress has come from scaling compute—using more GPUs, more power and larger investments. But is that model sustainable? What happens when compute demand outpaces supply? The conversation dives into the economics of AI, chip shortages, NVIDIA's dominance, large language models, small language models, Agentic AI, AI in scientific research, digital labour, and the future of AI infrastructure. Neil also shares his perspective on India's AI ambitions, semiconductor manufacturing, local language models and why continuously improving smaller models may be a smarter long-term strategy. In this episode: Why we're living through AI's golden age The economics behind AI scaling Why chip shortages could continue for years Compute vs algorithmic innovation LLMs vs SLMs The rise of Agentic AI AI's role in scientific research Can AI compete with human labour? NVIDIA, GPUs and the future of AI infrastructure India's AI roadmap and semiconductor ambitions Whether you're an AI enthusiast, business leader, developer, researcher or policymaker, this conversation offers a practical look at the technological and economic forces shaping the future of artificial intelligence. Subscribe to Mint Techcetra for more conversations with global technology leaders, researchers and innovators.