Category: FAANG

Editors Note: Written by Courtney Bowman, Palantir’s Global Director of Privacy and Civil Liberties Engineering, this blog highlights our belief in the need for an integrated and operationally-orientated approach to artificial intelligence, which acknowledges its limitations, while placing ethics and efficacy at the heart of its use. You can read more about our principled approach …

Read more “The Efficacy and Ethics of AI Must Move Beyond the Performative to the Operational”

Posted by Florian Hartmann, Software Engineer, and Peter Kairouz, Research Scientist, Google Research Federated learning is a distributed way of training machine learning (ML) models where data is locally processed and only focused model updates and metrics that are intended for immediate aggregation are shared with a server that orchestrates training. This allows the training …

Read more “Distributed differential privacy for federated learning”

Financial market participants are faced with an overload of information that influences their decisions, and sentiment analysis stands out as a useful tool to help separate out the relevant and meaningful facts and figures. However, the same piece of news can have a positive or negative impact on stock prices, which presents a challenge for …

Read more “Accelerate hyperparameter grid search for sentiment analysis with BERT models using Weights & Biases, Amazon EKS, and TorchElastic”

Are you looking for a way to inject a bit of humor into any occasion? Have you ever wanted to have an AI joke generator that could think up hilarious lines in an instant? Well, then look no further – because this blog post is all about finding the best AI joke generator out there! …

Read more “What is the best AI joke generator?”

Posted by Minji Yoon, Research Intern, and Bryan Perozzi, Research Scientist, Google Research, Graph Mining Team Industrial applications of machine learning are commonly composed of various items that have differing data modalities or feature distributions. Heterogeneous graphs (HGs) offer a unified view of these multimodal data systems by defining multiple types of nodes (for each …

Read more “Teaching old labels new tricks in heterogeneous graphs”

The fashion industry is a highly lucrative business, with an estimated value of $2.1 trillion by 2025, as reported by the World Bank. This field encompasses a diverse range of segments, such as the creation, manufacture, distribution, and sales of clothing, shoes, and accessories. The industry is in a constant state of change, with new …

Read more “Virtual fashion styling with generative AI using Amazon SageMaker “

Editor’s Note: In this blog post, Palantir’s Apollo & USG Tech teams pair up to describe how we deploy Palantir Apollo as the foundation of our Impact Level 6 (IL6) product offering. Building secure software requires robust delivery and management processes, with the ability to quickly detect and fix issues, discover new vulnerabilities, and deploy …

Read more “How Palantir Meets IL6 Security Requirements with Apollo”

Posted by Natasha Noy, Research Scientist, and Omar Benjelloun, Software Engineer, Google Research Access to datasets is critical to many of today’s endeavors across verticals and industries, whether scientific research, business analysis, or public policy. In the scientific community and throughout various levels of the public sector, reproducibility and transparency are essential for progress, so …

Read more “Datasets at your fingertips in Google Search”