A look under the hood: How (and why) we built Question Assistant
Evaluating question quality and determining the appropriate feedback required some classic ML techniques in addition to our GenAI solution.
ML
Improving error monitoring with AI
Tillman Elser, AI/ML lead at Sentry, joins Ryan for a conversation about improving error monitoring with AI and ML. They talk through the challenges of analyzing stack traces, the innovative use of embeddings to improve error grouping, the trial-and-error process of developing algorithms, and where Sentry’s AI capabilities are headed next.
MosaicML: Deep learning models for sale, all shapes and sizes (Ep. 577)
Ben and Ryan talk with Jonathan Frankle and Abhinav Venigalla of MosaicML, a startup trying to make deep learning and generative AI efficient and accessible for everyone.
ML and AI consulting-as-a-service (Ep. 542)
The home team talks with Jaclyn Rice Nelson, cofounder and CEO of Tribe AI, about the explosion of hype surrounding generative AI, what it’s like to work at a startup after working at Google, and how Tribe is leveraging the power of a specialist network.
Plug-and-play AI for your own projects (Ep. 482)
Ben talks with Dylan Fox, founder and CEO of rapid-growth startup AssemblyAI, about how he became interested in AI and machine learning, why he left a steady job at a tech giant to create something new, and what AI can offer creators like writers and visual artists.
Why AI is having an on-prem moment (Ep. 476)
The home team discusses how Instagram’s evolving platform has alienated some creators, why AI and machine learning are moving on-premises, and why Amazon’s acquisition of the company behind the Roomba is striking from a privacy perspective.