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Meet the finalists of the Pushback to the Future Challenge

DrivenData Labs

The Challenge ¶ Motivation ¶ Coordinating our nation's airways is the role of the National Airspace System (NAS). The NAS is arguably the most complex transportation system in the world. Their results will help demonstrate how we might make the most of all of the private data streams to keep flights on track.

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Meet the Final Winners of the U.S. PETs Prize Challenge

DrivenData Labs

Techniques used include homomorphic encryption and/or secure multiparty computation (SMPC) protocols such as secure aggregation and private set intersection. For Track B's pandemic forecasting task, teams had to model a complex dynamical system representing a disease outbreak in a simulated population of Virginia. He received his Ph.D.

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Distributed differential privacy for federated learning

Google Research AI blog

This allows the training of models on locally available signals without exposing raw data to servers, increasing user privacy. The Smart Text Selection models trained with this system have reduced memorization by more than two-fold, as measured by standard empirical testing methods.

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Modular functions design for Advanced Driver Assistance Systems (ADAS) on AWS

AWS Machine Learning Blog

Over the last 10 years, a number of players have developed autonomous vehicle (AV) systems using deep neural networks (DNNs). These systems have evolved from simple rule-based systems to Advanced Driver Assistance Systems (ADAS) and fully autonomous vehicles.

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Google at ICLR 2023

Google Research AI blog

Morcos , Dhruv Batra Offline Q-Learning on Diverse Multi-task Data Both Scales and Generalizes (see blog post ) Aviral Kumar , Rishabh Agarwal , Xingyang Geng , George Tucker , Sergey Levine ReAct: Synergizing Reasoning and Acting in Language Models (see blog post ) Shunyu Yao *, Jeffrey Zhao , Dian Yu , Nan Du , Izhak Shafran , Karthik R.

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Healthcare Datasets: Powering the Future of AI in Healthcare

Defined.ai blog

dollars by 2030, signaling a compound annual growth rate of 37 percent from 2022 onwards. Healthcare datasets serve as the foundational blocks on which various AI solutions, such as diagnostic tools, treatment prediction algorithms, patient monitoring systems, and personalized medicine models, are built.

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Incorporate offline and online human – machine workflows into your generative AI applications on AWS

AWS Machine Learning Blog

In this post, we introduce a solution for integrating a “near-real-time human workflow” where humans are prompted by the generative AI system to take action when a situation or issue arises. This blog post uses RLHF as an offline human-in-the-loop approach and the near-real-time human intervention as an online approach.

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