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Quantum Computing · Krishna targets 2029 for useful quantum computers with materials, finance, optimization use cases
now playing · Quantum Computing
AI Bubble / Capex Debateheadwindscore 9/10arvind krishna
Krishna warns AI infrastructure build-out exceeds near-term revenue potential
Over 100 GW of committed AI data center capacity implies $6-8T capex requiring $1-2T/year incremental revenue for payback, which Krishna believes is not achievable, suggesting many infrastr…
Quantum Computingtailwindscore 9/10arvind krishna
Krishna targets 2029 for useful quantum computers with materials, finance, optimization use cases
Quantum computers will reach production utility in 2028-2030 range, first unlocking materials science (corrosion, pharmaceuticals, fertilizers, magnets), financial risk pricing, and logisti…
Frontier AI Modelsmixedscore 8/10arvind krishna
Krishna predicts largest AI models become commodities with only 2-3 survivors
Frontier models will have low switching costs and commoditized margins without massive moats; only 2-3 companies can sustain the capital expense to build the largest models, while others wi…
AI Impact on Softwareheadwindscore 8/10arvind krishna
Krishna says AI agents will replace software front-ends, pressuring seat-based models
AI agents will replace the front-end of many software applications, reducing total value for seat-based software where the front-end was the primary value driver; systems of record and busi…
Enterprise AI Adoptiontailwindscore 7/10arvind krishna
Krishna contrasts IBM's enterprise AI focus with consumer AI of hyperscalers
IBM targets enterprise workflows (procurement, accounts payable, data leverage) for specific clients like Nestle and Bank of America, avoiding consumer distribution battles; enterprise AI a…
AI Regulation & Policyriskscore 7/10arvind krishna
Krishna skeptical global AI technology regulation is feasible, favors use-case regulation
Digital goods cross borders instantly making global technology regulation impractical; only specific use cases can be effectively regulated, as demonstrated by inconsistent internet control…
Mainframe Resiliencetailwindscore 7/10arvind krishna
Krishna explains mainframe growth driven by critical workloads, economics, and AI integration
Mainframes thrive on mission-critical workloads (banking, airlines) requiring 6-9 nines availability and batch processing; cloud migration costs 3x more; IBM integrated AI (fraud detection,…