Laurent Giraid has spent years building AI systems that move beyond raw data into meaningful representations—first with hand-tuned encodings, then with neural features, and now with multimodal encoders that read text, see images, and interpret context at once. In this conversation with Dustin
Bottlenecks that once hid behind peak FLOP charts had begun showing up in the places that matter most—latency-bound inference paths, goodput on sprawling training jobs, and the hard ceilings of data center power—which set the stage for a deliberate split in silicon designed to tame the opposing
Marketers chasing attention in crowded video feeds have long gambled budgets on gut feel and post-campaign learning curves that arrive too late to rescue underperforming ads, and that lag has become a strategic liability as video spend concentrates on platforms where seconds define outcomes. A new
Power decisions that once required night-long simulations now had to be made between scheduler heartbeats as AI clusters pushed against power limits and procurement cycles, turning energy from a back-office metric into a gating factor for throughput. As data centers edged toward consuming a
Quarterly plans now hinge on streaming dashboards, real-time alerts, and automated triggers that claim to capture a market’s pulse in seconds yet often mask the hard work of framing the right questions and interpreting messy signals under pressure. The promise sounds simple: more sensors, more
Budgets compress while deadlines accelerate, so insight teams are turning to a surprising accelerator: synthetic audiences that emulate real consumers in software, at scale and speed once unimaginable. In plain terms, these are AI-generated, attribute-rich stand-ins—demographics, locality, even
Consumers now expect mobile calls with crisp background effects, lag-free transcription, and expressive avatars that mirror every micro‑expression without stutter, yet the physics of thin devices and small batteries punish AI that surges beyond thermal headroom and drifts from steady frame budgets
When the raw processing power of the world's most advanced silicon meets the distributed intelligence of a global hyperscale network, the very definition of computational possibility begins to shift toward a new era of enterprise scale. This partnership between NVIDIA and Google Cloud represents
Laurent Giraid is a veteran of the artificial intelligence landscape, having watched the industry shift from niche laboratory research to the current explosion of Large Language Models. As a technologist specializing in machine learning and the ethical frameworks of automation, he brings a nuanced
Logistics facilities across the globe are currently grappling with an increasingly fragmented operational landscape where standardized solutions often fail to meet the unique physical demands of specialized cargo. The rise of diverse shipping formats, ranging from specialized pharmaceutical
