
Hosted by Bloomberg · EN

The chip design industry continues to push the frontier of semiconductor power, performance and area. On this episode of the Tech Disruptors podcast, Synopsys Vice President of AI and Machine Learning Thomas Andersen discusses the evolution of the company’s AI portfolio. He joins Bloomberg Intelligence analyst Niraj Patel to explain how Synopsys progressed from leveraging AI through reinforcement learning across design, verification and test workflows to introducing AgentEngineer, a multi-agent AI-orchestrated workflow. Andersen also discusses the intersection of simulation and electronic design automation (EDA), the role of humans in the loop for chip design, AI’s current shortcomings, the pace of AI-tool adoption, the industry’s path beyond Moore’s law and much more.

In this episode IOWN Global Forum board members Chris Wright (Chief Technology Officer and Senior Vice President of Global Engineering, Red Hat) and Jefferson Wang (Chief Strategy & Innovation Officer, Cloud, Accenture) talk through the accelerating shift towards photonics-based networks and how this next-generation technology can help unlock the full potential of the AI economy. Replacing electrical-based connectivity with optics promises to drastically increase processing speeds, reduce latency, and lower power consumption for high-demand AI, cloud computing, and financial networks.

Uniphore CEO Umesh Sachdev joins Bloomberg Intelligence analyst Mandeep Singh on this episode of the Tech Disruptors podcast to discuss his company’s platform for developing ontologies compared with the use of forward-deployed engineers (FDEs) by hyperscalers and frontier large-language-model companies. He explores Uniphore’s approach to leveraging small language models for use cases such as claims and billing, as well as the trade-offs with frontier models used for cybersecurity and coding agents.

“So, there are plenty of failure points, and when you have hundreds of thousands or millions of something, something will eventually fail,” Peter Salanki, co-founder and CTO of CoreWeave, tells Bloomberg Intelligence Senior Technology Analyst Anurag Rana. “Instead of throwing out half the potential capacity, we say that we expect some of these to fail. Then we build systems, automation and processes around handling those failures gracefully.” In this episode of Tech Disruptors, the pair discuss why AI infrastructure requires a fundamentally different architecture to traditional CPU-based cloud. Salanki also explains how CoreWeave is addressing training, inference and agentic workloads while navigating token costs, Nvidia chip demand and power constraints.

The governance landscape for AI agents is evolving amid new developments around agentic workflows, says SailPoint President Matt Mills. He joins Bloomberg Intelligence analyst Mandeep Singh on this episode of the Tech Disruptors podcast. The conversation also explores how agentic AI could reshape identity governance, from internal functions and product capabilities to potential shifts in pricing models and customer adoption.

“Source code became almost free, like cheap and not important. And binaries became king because this is the outcome,” says Shlomi Ben Haim, co-founder and CEO of JFrog. Ben Haim joins Bloomberg Intelligence analyst Mandeep Singh in this episode of the Tech Disruptors podcast to discuss the impact of large-language-model coding agents, the challenges of keeping up with model guardrails, and why software supply-chain security and governance are top of mind for modern enterprises. Ben Haim explains how JFrog acts as the infrastructure and control plane for developer workflows, using JFrog Boost, a Model Context Protocol registry and JFrog Curation to help customers optimize token consumption, block malicious packages and automate software governance without compromising speed.

“The minute it worked, we actually started to use smaller models for the things we knew that it worked and see what they could accomplish at a fraction of the price,” says Matt Hicks, CEO of Red Hat, in a discussion with Bloomberg Intelligence Senior Technology Analyst Anurag Rana. In this episode of the Tech Disruptors podcast, the pair discuss Red Hat’s role inside IBM, the durability of hybrid cloud and why OpenShift, virtualization and AI are becoming key growth drivers. Hicks explains how Red Hat is applying AI across engineering and business operations, using smaller models, containers and OpenShift to help customers build more flexible, cost-efficient AI infrastructure.

“Data centers are here to stay, and the world is going to need them as AI adoption accelerates,” says Steven Siesser, partner at Lowenstein Sandler, chair of the firm’s private equity practice and co-lead of its data center practice, in conversation with Bloomberg Intelligence’s Associate Director of Research Alexandra Davidov and Senior Technology Analyst Anurag Rana. In this episode of Tech Disruptors, they discuss how AI data centers are reshaping infrastructure finance, from hyperscaler-backed leases and neo-cloud credit risk to private equity, private credit and sovereign capital. Siesser explains why power, community acceptance and supply-chain constraints remain key bottlenecks, while long-term leases and hyperscaler demand are reshaping how lenders underwrite the build-out.

The cybersecurity industry is facing unprecedented challenges as AI models become more capable. On this episode of Tech Disruptors, SentinelOne co-founder and CEO Tomer Weingarten talks about deploying security for AI agents and the evolution of the security operations center (SOC) with LLMs. He joins Bloomberg Intelligence analyst Mandeep Singh to discuss the impact of Anthropic Mythos, M&A in cybersecurity and the changing nature of attacks as tools become more sophisticated.

Matt Fitzpatrick, CEO of Invisible Technologies, joins Bloomberg Intelligence’s Mandeep Singh on this episode of the Tech Disruptors podcast to discuss the use of reinforcement learning by frontier model providers for training, as well as the company’s enterprise business. They explore reinforcement learning from human feedback (RLHF), agentic AI and self-improvement, the evolution of large language models, coding agents and contact centers.