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Methodology available in Editorial Guidelines Debunking the myth that AWS Lambda can’t power real GenAI workloads by redefining the boundary between the “Brain” and the “Nerves.” Key Takeaways: The Architecture: Stop trying to run the Brain (model) in Lambda. Use Lambda as the Nervous System to orchestrate and route signals. The Financials: Idle GPUs are…
Policy Response to Global GenAI Bans and Deepfake Risks. Key Takeaways Indonesia’s Grok ban marks the first sovereign enforcement action against a live generative AI platform for deepfake risk. Generative AI regulation is shifting from transparency debates to content liability and human harm prevention. Governments are converging on risk-based frameworks modeled after EU-style compliance regimes….
If you had told me in 2024 that I’d be running production GenAI workloads on AWS Lambda, I would have laughed you out of the room. Back then, Lambda was for glue code, JSON shuffling, and maybe a cron job. The idea of shoving a memory-hungry, GPU-craving LLM into a 15-minute ephemeral function felt like…
The “T-Shirt Sizing” Era of AI is Over For the last year, sizing AI workloads on-premises has felt a bit like the Wild West. We’ve been relying on rough spreadsheets, “t-shirt sizes” (Small, Medium, Large), and a fair amount of guesswork regarding inference overhead. That changed today. Nutanix released Sizer 6.0.94 (Release Date: 16-Dec-2025), and…
