In this episode, we discuss Google DeepMind and Singapore's GovTech building an on-device scam detector with Gemma, NVIDIA's $250 million compute pledge for AI agent safety research in the UK, and Liquid AI's new LFM2.5 24B A2B open-weight reasoning model for local AI agents. We explore how the Gemma scam detection model uses a two-stage, on-device design to catch fake bank alerts and government impersonation scams without sending messages to the cloud, and how GovTech's Mark Chen frames scam protection and privacy as goals that must work together. Next, we break down how NVIDIA's compute access will support AI agent safety sandboxes and benchmarks at Oxford's BOLD, UCL's SOFAIR, and Imperial College London, featuring comments from Jakob Foerster. Finally, we look at how Liquid AI's efficient reasoning model brings local AI agents to laptops and Apple silicon, along with its licensing and benchmark caveats.
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This podcast is an independent production and is not affiliated with, endorsed by, or sponsored by Google, Google DeepMind, GovTech Singapore, NVIDIA, Liquid AI, Hugging Face, the University of Oxford, University College London, Imperial College London, or any other entities mentioned unless explicitly stated. The content provided is for informational, educational, and entertainment purposes only and does not constitute professional, technical, financial, or legal advice. This episode contains affiliate links, and we may earn a commission if you make a purchase through them at no additional cost to you. All trademarks, logos, and copyrights mentioned are the property of their respective owners.
