IBM's $10 billion bet on what comes after AI (with CEO Arvind Krishna) | Masters of Scale

The gist

1. Most enterprises over-deploy massive AI models for simple tasks; smaller, cheaper models can do the same work at a fraction of the cost.
2. Krishna says start with 3 to 5 concrete AI use cases, master them, then expand rather than spreading effort across 100 projects at once.
3. IBM saw $4.5 billion in efficiency gains from AI, but the first 6 to 12 months cost more than they saved before returns compounded.
4. Krishna says quantum computing is nearing practical use in drug discovery and aerodynamics, and leaders should start learning relevant algorithms now.