Next in Tech

The popular image of quantum computers is the sparkling "chandelier" of the superconducting approach, but this next episode in our Quantum CEO series looks neutral atom quantum computers. Quantum analyst Ellie Brown returns to the podcast to join Andy Ory, the CEO of QuEra, to discuss their approach, the benefits of practical fault tolerant qubits and the advantages of quantum hubs that may have a dearth of beer with host Eric Hanselman. Neutral atom systems don't require the ultra-low operating temperatures used for superconduction. They stabilize the atoms they're using with lasers that still their motion. That free space setting allows simpler interaction between larger numbers of qubits that improves scaling of quantum computations. Stability reduces error rates and can improve the effectiveness of quantum error correction.
Quantum computing has become a very buzzy topic, with IPO's and major funding announcements. There is growth of the supporting ecosystems around quantum application development, with software tools and cloud-based services offerings that are expanding access. The greatest challenge is the supply of a quantum workforce that can put quantum capabilities to work. Systems doing optimization approaches, like quantum annealing, are here today. The date for the availability of general purpose, practical quantum computers keeps getting closer. Some have said 2030 might be a target date and QuEra is talking about delivering their next-generation system in 2028. It's time to be getting quantum-literate today!
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Host/Author: Eric Hanselman
Guests: Andy Ory and Ellie Brown
Producer/Editor: Dylan Scheible
Published With Assistance From: Feranmi Adeoshun and Sophie Carr

This episode of our AI CEO series looks at the potential for AI capabilities to address one of AI's largest challenges – energy availability. Dr. Varun Sivaram, founder and CEO of Emerald AI, joins host Eric Hanselman to explore how greater flexibility is AI workloads can unlock unused capacity. Traditionally, data center construction has focused on delivering peak capacity, even at those times when it may not be needed. That doesn't mesh well with a power grid that is already under stress. AI intelligence can shift workloads dynamically to reduce data center demands when the power grid needs it and to leverage excess grid capacity when it's available.
Flexing AI workloads to respond to grid conditions isn't simple, but it can be more attractive than alternatives. Adding generation capacity is a long-term and expensive process and community concerns about rate increases are creating headwinds for new data center builds. Adding Battery Energy Storage Systems (BESS) are costly and have their own capacity and durability limitations. Flexing workload demand could address grid integration problems on a much shorter timeline.
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Host/Author: Eric Hanselman
Guest: Varun Sivaram
Producer/Editor: Dylan Scheible
Published With Assistance From: Feranmi Adeoshun and Sophie Carr

Market dynamics in data center buildouts and dealmaking are complex, but there are some common threads that are spanning the globe. Analysts Soon Chen Kang and Stefanie Williams join host Eric Hanselman to explore their research in the Asia Pacific market. AI demand is a driving force and concerns about power availability can be a headwind, but there are regional nuances that make the markets that comprise the APAC region unique. One treats the market as a cohesive whole at one's peril!  Geopolitical concerns have a significant impact on both demand forces and capacity uptake. Access to GPU's to feed AI applications takes on new dimensions in a market where technology embargoes are moving workloads. Neoclouds are a new market provider and driving new builds, as well.
The boom days of speculative building have tapered off, in many cases, due to the availability of power, but that doesn't mean activity is slowing. Activity is shifting to find available capacity, but a common challenge in some of these early markets is the lack of transparency on both power deals and the build and financing processes. Check out the research to get more details.
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Host/Author: Eric Hanselman
 
Guests: Soon Chen Kang, Stefanie Williams
Producer/Editor: Dylan Scheible 
Published With Assistance From: Feranmi Adeoshun, Sophie Carr, Kyra Smith,

We're in the early days of cost impacts for AI applications. While there are some cautionary tales, current spending seems to be a small fraction what's to come. Analysts Jean Atelsek and Melanie Posey return to the podcast to talk about what they heard at the FinOps X conference with host Eric Hanselman. The need for cost management in AI is seen as so great that the FinOps Foundation, a project of the Linux Foundation, is talking about morphing its conference into Tokenomicon and pivot into token economics. The portmanteau of tokenomics is sweeping across cloud and AI services providers, as well as IT vendors, as enterprises wrestle with dueling forces of AI acceleration and management constraints for access and cost.
Unlike FinOps for cloud operations, the costs and metrics for AI are fairly opaque. Some enterprises are trying to manage costs by limiting access, but that risks stifling the innovation and democratization that is supposed to come with AI transformation. Request routing is promising, but it requires understanding the nature of the request and the suitability of available infrastructure to fulfill it, something that is not well understood by many. Most are just getting comfortable with managing model lifecycles and the step up to cost management can be a large one.
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Host/Author: Eric Hanselman 
Guests: Jean Atelsek, Melanie Posey
Producer/Editor: Dylan Scheible
Published With Assistance From: Feranmi Adeoshun, Sophie Carr, Kyra Smith,

There's great momentum in moving to greater levels of agentic automation, but there are critical areas where deeper consideration is required in how it's applied. In capital markets, trust is a foundational element on which transactions are built and Krisha Vinjamuri, Head of Technology, Enterprise Solutions at S&P Global Market Intelligence, joins host Eric Hanselman to talk about how this can be achieved and the important aspects of successful implementations.
One of the useful things in capital markets, is that there are open standards on which to base data ontologies. It's not exciting, but it's the basis of a semantic foundation that can not only ensure that there is depth in data definitions, but can also reduce errors generated by agents. The larger question that looms beyond the construction of foundational architecture, is how the operational envelope that bounds agentic action will be established. This has to be built from policy definitions that take those actions into account. There is great promise and much work that needs to be done.
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Credits:
Host/Author: Eric Hanselman
Guest: Krishna Vinjamuri
Producer/Editor: Feranmi Adeoshun
Published With Assistance From: Sophie Carr, Kyra Smith, Dylan Scheible