SPOTLIGHT. Unified Flash Memory and Reduced HBM are Reshaping AI Training and Inference with Phison
An episode of the Tech Field Day Podcast podcast, hosted by Tech Field Day, titled "SPOTLIGHT. Unified Flash Memory and Reduced HBM are Reshaping AI Training and Inference with Phison" was published on September 16, 2025 and runs 23 minutes.
September 16, 2025 ·23m · Tech Field Day Podcast
Summary
AI will need less HBM (high bandwidth memory) because flash memory unification is changing training and inference. This episode of the Tech Field Day podcast features Sebastien Jean from Phison, Max Mortillaro, Brian Martin, and Alastair Cooke. Training, fine-tuning, and inference with Large Language Models traditionally use GPUs with high bandwidth memory to hold entire data models and data sets. Phison’s aiDaptiv+ framework offers the ability to trade lower cost of infrastructure against training speed or allow larger data sets (context) for inference. This approach enables users to balance cost, compute, and memory needs, making larger models accessible without requiring top-of-the-line GPUs, and giving smaller companies more access to generative AI.Learn more about Phison's solutions here.Phsion Representative: Sebastien Jean, CTO of Phison ElectronicsHostAlastair Cooke, Tech Field Day Event LeadPanelistsBrian Martin, VP of AI and Datacenter Performance at Signal65Max Mortillaro, Chief Research Officer at Osmium GroupFollow the Tech Field Day Podcast on X/Twitter or on Bluesky and use the Hashtag #TFDPodcast to join the discussion. Listen to more episodes on the podcast page of the website.Follow Tech Field Day for more information on upcoming and current event coverage on X/Twitter, on Bluesky, and on LinkedIn, or visit our website.
Episode Description
AI will need less HBM (high bandwidth memory) because flash memory unification is changing training and inference. This episode of the Tech Field Day podcast features Sebastien Jean from Phison, Max Mortillaro, Brian Martin, and Alastair Cooke. Training, fine-tuning, and inference with Large Language Models traditionally use GPUs with high bandwidth memory to hold entire data models and data sets. Phison’s aiDaptiv+ framework offers the ability to trade lower cost of infrastructure against training speed or allow larger data sets (context) for inference. This approach enables users to balance cost, compute, and memory needs, making larger models accessible without requiring top-of-the-line GPUs, and giving smaller companies more access to generative AI.
Learn more about Phison's solutions here.
Phsion Representative: Sebastien Jean, CTO of Phison Electronics
Host
Alastair Cooke, Tech Field Day Event Lead
Panelists
Brian Martin, VP of AI and Datacenter Performance at Signal65
Max Mortillaro, Chief Research Officer at Osmium Group
Follow the Tech Field Day Podcast on X/Twitter or on Bluesky and use the Hashtag #TFDPodcast to join the discussion. Listen to more episodes on the podcast page of the website.
Follow Tech Field Day for more information on upcoming and current event coverage on X/Twitter, on Bluesky, and on LinkedIn, or visit our website.
Similar Episodes
Apr 8, 2026 ·4m
Apr 2, 2026 ·22m
Apr 1, 2026 ·58m