Category: FAANG

(Scroll down for English translation below) Wie können wir Polizeibehörden ermöglichen, den Herausforderungen der digitalen Zeit besser gerecht zu werden? Wie können wir gleichzeitig Grundrechte wahren? Dies sind Fragen, mit denen sich die Innenministerien des Bundes und der Länder bereits seit 2016 im Rahmen der sogenannten Saarbrücker Agenda beschäftigen. Konkret geht es darum, eine “moderne, …

Read more “Wie Palantir die Digitalisierung deutscher Polizeien unterstützt”

Posted by Krzysztof Choromanski, Staff Research Scientist, Robotics at Google, and Xuesu Xiao, Visiting Researcher, George Mason University Despite decades of research, we don’t see many mobile robots roaming our homes, offices, and streets. Real-world robot navigation in human-centric environments remains an unsolved problem. These challenging situations require safe and efficient navigation through tight spaces, …

Read more “Performer-MPC: Navigation via real-time, on-robot transformers”

Amazon Kendra is a highly accurate and simple-to-use intelligent search service powered by machine learning (ML). Amazon Kendra offers a suite of data source connectors to simplify the process of ingesting and indexing your content, wherever it resides. Valuable data in organizations is stored in both structured and unstructured repositories. An enterprise search solution should …

Read more “Index your Microsoft Exchange content using the Exchange connector for Amazon Kendra”

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 “