When’s the last time you watched a race for the braking? It’s the heart-pounding acceleration and death-defying maneuvers that keep most motorsport fans on the edge of their seats. Especially when it comes to Formula E — and really all EVs — the explosive, near-instantaneous acceleration of an electric motor is part of the appeal. …
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The Amazon Bedrock multi-agent collaboration feature gives developers the flexibility to create and coordinate multiple AI agents, each specialized for specific tasks, to work together efficiently on complex business processes. This enables seamless handling of sophisticated workflows through agent cooperation. This post aims to demonstrate the application of multiple specialized agents within the Amazon Bedrock …
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Your customers might not all speak the same language. If you operate internationally or serve a diverse customer base, you need your chatbot to meet them where they are – whether they’re searching for something in Spanish or Japanese. If you want to give your customers multilingual support with chatbots, you’ll need to orchestrate multiple …
Pan-privacy was proposed by Dwork et al. (2010) as an approach to designing a private analytics system that retains its privacy properties in the face of intrusions that expose the system’s internal state. Motivated by federated telemetry applications, we study local pan-privacy, where privacy should be retained under repeated unannounced intrusions on the local state. …
Multimodal fine-tuning represents a powerful approach for customizing foundation models (FMs) to excel at specific tasks that involve both visual and textual information. Although base multimodal models offer impressive general capabilities, they often fall short when faced with specialized visual tasks, domain-specific content, or particular output formatting requirements. Fine-tuning addresses these limitations by adapting models …
Read more “Best practices for Meta Llama 3.2 multimodal fine-tuning on Amazon Bedrock”
Data Streaming: Real-time data for real-time decisions (Palantir RFx Blog Series, #8) Often the most business critical decisions are also the most time-sensitive. Data streaming technologies let organizations act on information (almost) as quickly as it comes in. Editor’s note: This is the eighth post in the Palantir RFx Blog Series, which explores how organizations can better …
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Amazon Bedrock Model Distillation is generally available, and it addresses the fundamental challenge many organizations face when deploying generative AI: how to maintain high performance while reducing costs and latency. This technique transfers knowledge from larger, more capable foundation models (FMs) that act as teachers to smaller, more efficient models (students), creating specialized models that …
Generative AI is rapidly reshaping industries worldwide, empowering businesses to deliver exceptional customer experiences, streamline processes, and push innovation at an unprecedented scale. However, amidst the excitement, critical questions around the responsible use and implementation of such powerful technology have started to emerge. Although responsible AI has been a key focus for the industry over …
At Next ’25, we introduced several new innovations within BigQuery, the autonomous data to AI platform. BigQuery ML provides a full range of AI and ML capabilities, enabling you to easily build generative AI and predictive ML applications with BigQuery. The new AI and ML capabilities from BigQuery ML include: a new state-of-the-art pre-trained forecasting …
As statistical analyses become more central to science, industry and society, there is a growing need to ensure correctness of their results. Approximate correctness can be verified by replicating the entire analysis, but can we verify without replication? Building on a recent line of work, we study proof-systems that allow a probabilistic verifier to ascertain …