In this episode, we explore Google's Ironwood TPU chip engineered for high-volume, low-latency AI inference with 4x performance improvements, Meta's SAM 3 model that enables text-driven video object tracking for creators through Instagram Edits, and Alibaba's Qwen3 VL featuring 256,000 token multimodal context windows with advanced reasoning capabilities. We discuss how Google Ironwood transforms real-time AI deployment economics, how Meta SAM 3 democratizes sophisticated video editing through natural language prompts, and how Alibaba Qwen3 VL enables long-form video comprehension and autonomous multimodal agents. These developments signal a major shift from AI training infrastructure toward production inference systems, intuitive creator tools, and expanded context handling that removes constraints from complex multimodal workflows.https://www.aiconvocast.comHelp support the podcast by using our affiliate links:Eleven Labs: https://try.elevenlabs.io/ibl30sgkibkvDisclaimer:This podcast is an independent production and is not affiliated with, endorsed by, or sponsored by Google, Meta, Alibaba, Instagram, or any other entities mentioned unless explicitly mentioned. The content provided is for educational and entertainment purposes only and does not constitute professional, financial, or technical advice. Affiliate links may generate compensation for the podcast.

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