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MIT and Mass General Brigham have launched a joint seed program, funded by Analog Devices Inc., to accelerate interdisciplinary innovations in health through collaborative research integrating AI, machine learning, and clinical expertise.

Explore how GPT-4o enables customizable, no-code automation of voice agents for streamlined interactions.

Developed a specialized benchmark dataset with expert CPCUs to evaluate and reveal error modes of AI agents in nuanced insurance underwriting tasks within complex enterprise ecosystems.

Iambic leverages Lambda's NVIDIA HGX B200 GPU cluster to accelerate training of Enchant, a cutting-edge AI model that predicts molecular properties for advanced drug discovery and development.

LOBSTgER combines generative AI and underwater photography to create scientifically accurate and artistically immersive visualizations of marine biodiversity in the rapidly changing Gulf of Maine.

Leveraging AI-driven testing, telemetry analysis, and region-specific simulations to optimize Salesforce Code Builder's performance, scalability, and developer productivity while reducing setup time and infrastructure costs.

AlphaGenome is a cutting-edge AI model that predicts the regulatory effects of genetic variants across long DNA sequences with high resolution, enabling enhanced understanding of genome function and aiding diverse genomic research applications.

Exploring the impact of OpenAI o3, GPT-4.1, and CUA technologies in enabling scalable growth strategies.

Demonstrates how Pinterest leveraged Ray to revolutionize their ML infrastructure by integrating feature development, sampling, and labeling into a scalable, efficient end-to-end ML pipeline, cutting iteration times and infrastructure costs significantly.

Explores Airbnb's approach to enhancing SwiftUI performance through understanding view diffing, leveraging an @Equatable macro for efficient re-rendering, breaking complex views into smaller components, and implementing tooling to manage view complexity at scale.

Gemini Robotics On-Device delivers an advanced, low-latency AI model for local execution on robotic devices, enabling versatile dexterous manipulation and rapid task adaptation without dependency on network connectivity.

Explore essential practices, tools, and challenges in monitoring, evaluating, and optimizing large language models (LLMs) for enterprise applications with a focus on ensuring reliability, safety, and business alignment.