by Gabriela Alessio, Cameron Taylor, and Cameron R. Wolfe Introduction When members log into Netflix, one of the hardest choices is what to watch. The challenge isn’t a lack of options — there are thousands of titles — but finding the most intriguing one is complex and deeply personal. To help, we surface personalized promotional assets, especially the show synopsis — a …
Read more “Evaluating Netflix Show Synopses with LLM-as-a-Judge”
For decades, expense automation relied on a simple premise: If the machine can read the text, it can do the work. But anyone who has ever tried to scan a crumpled, smudged, or sun-bleached receipt from their pocket knows that reading isn’t enough. When key data is missing, such as a city name or a …
Read more “How SAP Concur automates expense reporting with agentic AI”
After traveling a greater distance from Earth than any humans before them, the astronauts of Artemis II have safely returned home.
A new chip design from UC San Diego could make data centers far more energy-efficient by rethinking how power is converted for GPUs. By combining vibrating piezoelectric components with a clever circuit layout, the system overcomes limitations of traditional designs. The prototype achieved impressive efficiency and delivered much more power than previous attempts. Though not …
Read more “This new chip could slash data center energy waste”
The heads of America’s biggest banks met this week with Federal Reserve Chairman Jerome Powell and Treasury Secretary Scott Bessent to weigh the security implications of a new artificial intelligence system developed by Anthropic, according to reports Friday.
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This paper provides a theoretical framework for interpreting acoustic neighbor embeddings, which are representations of the phonetic content of variable-width audio or text in a fixed-dimensional embedding space. A probabilistic interpretation of the distances between embeddings is proposed, based on a general quantitative definition of phonetic similarity between words. This provides us a framework for …
Read more “A Theoretical Framework for Acoustic Neighbor Embeddings”
Amazon Bedrock regularly releases new foundation model (FM) versions with better capabilities, accuracy, and safety. Understanding the model lifecycle is essential for effective planning and management of AI applications built on Amazon Bedrock. Before migrating your applications, you can test these models through the Amazon Bedrock console or API to evaluate their performance and compatibility. …
Enterprises are rapidly moving AI workloads from experimentation to production on Google Kubernetes Engine (GKE), using its scalability to serve powerful inference endpoints. However, as these models handle increasingly sensitive data, they introduce unique AI-driven attack vectors — from prompt injection to sensitive data leakage — that traditional firewalls aren’t designed to catch. Prompt injection …
Read more “Guardrails at the gateway: Securing AI inference on GKE with Model Armor”