Tech Disruptors

“It’s clear to us that the world is short compute right now, and the industry is racing to catch up,” Rob Bittencourt, partner and head of thematic investing at Apollo, tells Bloomberg Intelligence’s Alexandra Davidov and Paul Gulberg on this episode of the Tech Disruptors podcast. Bittencourt discusses why AI is becoming a private-credit story, with trillions of dollars of data-center, power, chip and infrastructure investment needed to support the next phase of adoption. He also explains how Apollo underwrites AI infrastructure risk, why hyperscaler demand and investment-grade financing matter, and how investors should separate temporary software valuation resets from true business-model disruption.

“Every data center will need some part of AI capabilities to run workloads like inference, because it’s just becoming such a fundamental part of all of this cloud technology,” says Alistair Speirs, general manager of Microsoft’s Azure Infrastructure. Speirs joins Bloomberg Intelligence Senior Technology Analyst Anurag Rana on this episode of the Tech Disruptors podcast to discuss how AI infrastructure is reshaping the modern data center, from liquid cooling and dense networking to custom silicon and distributed supercomputing. Speirs explains how Azure is preparing for a world where training, inference and traditional workloads increasingly converge, making software-defined infrastructure, power availability and global scale central to Microsoft’s cloud strategy.

“This year is a much more radical technology shift and the most consequential, I believe, ever. But still, you need all foundations of the house to be in order,” Sebastian Steinhaeuser, Chief Operating Officer at SAP, tells Bloomberg Intelligence Senior Technology Analyst Anurag Rana. In this episode of Tech Disruptors, the pair discuss SAP’s autonomous enterprise vision, the rise of Joule assistants and agents, and why AI may strengthen the case for cloud migration, data modernization, and application consolidation. Steinhaeuser explains how SAP is embedding business process context, governance, and industry-specific knowledge into its agentic layer while navigating shifts in software pricing, model strategy, and customer demand for measurable AI adoption.

Bloomberg Intelligence Head of Technology Research Mandeep Singh is joined by Nicole Hu, a Silicon Valley technology veteran and GLG expert, to explore the implications of Google’s TurboQuant paper and the evolving economics of AI infrastructure. As hyperscalers look to improve the efficiency of AI workloads, advances in quantization are redefining the tradeoffs between memory and compute, with far-reaching implications for cost, latency, and datacenter architecture. They examine how new approaches to model optimization and inference could reshape hardware requirements, deployment strategies, and the next wave of AI investment.

“OpenAI has only two AI accelerator compute vendors in production today, Cerebras and Nvidia,” Cerebras CEO Andrew Feldman says. Four days after Cerebras went public, Feldman joined Bloomberg Intelligence’s Kunjan Sobhani to discuss the company’s next chapter and the rapidly shifting AI infrastructure landscape. Feldman breaks down the OpenAI deal, the strategic AWS partnership around disaggregated inference and why Cerebras believes fast inference is becoming the industry’s defining battleground. He explains how Cerebras evolved from building the world’s largest chip to operating one of the fastest inference platforms, why disaggregated inference could reshape hyperscale AI deployments and how the company is navigating power, memory and data-center constraints. The episode also explores the competitive landscape beyond GPUs and Feldman’s broader perspective on the next phase of AI compute.