00:00 – 02:00
Intro and Kartik’s background in physics and industry evolution; early days of personalized medicine and genomic research.
02:00 – 04:30
Breakdown of three main advances in life sciences: genomics, gene editing (CRISPR), and long-read sequencing technologies like Oxford Nanopore and PacBio.
04:30 – 06:30
Deep technical dive into nanopore sequencing: how it works, why it matters, and why it requires GPU acceleration.
06:30 – 08:30
The computational bottleneck: memory mapping, random I/O, why short-read sequencers are now limiting, and why SSDs are necessary.
08:30 – 10:00
Parallel file systems break under modern life sciences loads; shift toward storage architectures that can handle random I/O at scale.
10:00 – 12:30
How AlphaFold reshaped structural biology and compute expectations; protein folding as a graph neural network challenge.
12:30 – 15:00
LLMs in pharma, managing clinical trial data, and the rise of mixed, hybrid workloads in research computing.
15:00 – 17:00
Microscopy at scale (cryo-EM, light sheet imaging) and the data tsunami—petabytes per microscope, per year.
17:00 – 19:30
Shifting away from HPC-era assumptions: new workloads, new storage expectations, and lessons from vendors like Oxford Nanopore.
19:30 – 20:36
What’s next: generative AI models trained on molecular sequences and protein structures; a vision of disease-free future.
