AI Meets DNA: Small Models, Big Data, Huge Impacts

AI Meets DNA: Small Models, Big Data, Huge Impacts

In this episode of the Shared Everything podcast, Derrick Harris speaks with Oxford Nanopore VP of Machine Learning Mike Vella about the company’s relatively unique approach to doing AI in the fast-moving field of genomics. From hand-programming CUDA kernels to dealing with the gigabyte per second of data coming off its DNA sequencers, Vella explains how his team balances the promise of fast, inexpensive sequencing with the realities of edge computing.

Where Data Stops Being "Data" in Quantum Systems

On this episode of the Shared Everything podcast from VAST, Nicole talks with Chris Powell, Quantum Information Science Lead at SAIC, about what “data” actually means in a quantum system. We move past storage and into representation, where problems have to be mapped into mathematical forms like Hamiltonian matrices and expressed directly into quantum hardware with no traditional memory or registers. We also delve into how hybrid architectures tie CPUs, GPUs, and QPUs together, why classical data infrastructure becomes more important rather than less so, and how quantum computing shifts the model from retrieving answers to shaping systems where answers emerge from probabilities.

From Detection to Reasoning: Scaling the Infrastructure of Autonomous AI

In this episode of the Shared Everything podcast, Nicole Hemsoth Prickett speaks with Norm Marks, VP of Automotive at NVIDIA, about how autonomous systems are evolving from detection to prediction and now reasoning-driven AI. Marks explains how that shift is driving massive increases in GPU scale, synthetic data generation, and simulation, forcing companies to rethink infrastructure as training pipelines expand across hybrid datacenter and cloud environments. The result is a new class of AI factories built to train and operate autonomy at industrial scale.

Beating the Flash Crunch With Efficiency, Not Supply

In this episode of Shared Everything, we sit down with Jeff Denworth, co-founder of VAST Data, and Scott Shadley of Solidigm to unpack what’s actually driving the current flash supply crunch. The conversation moves from NAND physics and fab constraints to hyperscaler buying behavior and the sudden surge in AI-driven demand, explaining why this cycle is fundamentally different from past downturns. At the center is a clear reality check for anyone building AI infrastructure right now: flash has become a limiting resource, and software efficiency and architecture now determine how much usable capacity the industry really has.

How TACC Pushed Supercomputing Toward an IO-First Architecture

On today's episode of the Shared Everything podcast, Nicole is live at SC25 with Dan Stanzione, Executive Director of the Texas Advanced Computing Center (TACC), for a look at why Horizon required a fundamental architectural reset. Stanzione explains how rising GPU power densities, liquid cooled 20 megawatt racks, and an increasingly irregular IO profile forced TACC to abandon long held assumptions about parallel filesystems. Years of watching billions of tiny files, unpredictable 4k and 64k reads, and metadata stalls slow entire machines led them to an all solid state tier and a VAST global namespace built for resilience, consistency, and shared access at scale. He describes how this model simplifies AI and hybrid scientific workflows, why the file system has always been the real point of failure, and how Horizon’s architecture reflects a world where IO, not FLOPS, determines what large scale science can do next.