Technical Annex: Announcing Palantir Government Web Services Editor’s note: The Technical Annex is the second blog of a two part series. Read the first, From Last Supper to First Breakfast, here. Palantir Government Web Services (PGWS) aims to make the building blocks we developed over 20 years to break into and scale our government business available …
Brands that deliver an excellent customer experience (CX) will always be more resilient than those that don’t. Giving our customers personalized support at every stage of their journey is proven to earn their longtime loyalty—and keep them from switching to a competitor. The challenge, however, is that many teams operate in siloes that inhibit them …
Read more “Generative AI: Meet your partner in customer service”
For modern companies that deal with enormous volumes of documents such as contracts, invoices, resumes, and reports, efficiently processing and retrieving pertinent data is critical to maintaining a competitive edge. However, traditional methods of storing and searching for documents can be time-consuming and often result in a large effort to find a specific document, especially …
Read more “Implement smart document search index with Amazon Textract and Amazon OpenSearch”
Cloud Bigtable is a highly scalable, fully managed NoSQL database service that offers single-digit millisecond latency and an availability SLA up to 99.999%. It is a good choice for applications that require high throughput and low latency, such as real-time analytics, gaming, and telecommunications. Cloud Bigtable change streams is a feature that allows you to …
Read more “Actuate your data in real time with new Bigtable change streams”
Posted by Shantanu Shahane, Software Engineer, and Matthias Ihme, Research Scientist, Athena Team Turbulence is ubiquitous in environmental and engineering fluid flows, and is encountered routinely in everyday life. A better understanding of these turbulent processes could provide valuable insights across a variety of research areas — improving the prediction of cloud formation by atmospheric …
Read more “A novel computational fluid dynamics framework for turbulent flow research”
The effects of climate change grow more tangible by the day. As a result, the electric power industry is hastening efforts to reduce environmental impact. To do so, they need help to get a clearer picture of where they fall on the emissions reduction roadmap, and to better understand their opportunities for improvement. This is …
Read more “Harnessing AI and data analytics can make clean energy more viable”
Posted by Shantanu Shahane, Software Engineer, and Matthias Ihme, Research Scientist, Athena Team Turbulence is ubiquitous in environmental and engineering fluid flows, and is encountered routinely in everyday life. A better understanding of these turbulent processes could provide valuable insights across a variety of research areas — improving the prediction of cloud formation by atmospheric …
Read more “A novel computational fluid dynamics framework for turbulent flow research”
Efficient control policies enable industrial companies to increase their profitability by maximizing productivity while reducing unscheduled downtime and energy consumption. Finding optimal control policies is a complex task because physical systems, such as chemical reactors and wind turbines, are often hard to model and because drift in process dynamics can cause performance to deteriorate over …
Read more “Optimize equipment performance with historical data, Ray, and Amazon SageMaker”
To empower developers to identify sensitive content in a rapidly changing media environment, we are excited to announce Text Moderationpowered by PaLM 2, available through the Cloud Natural Language API. Built in collaboration with Jigsaw and Google Research, Text Moderation helps organizations scan for sensitive or harmful content. Here are some examples of how the …
Read more “Improving Trust in AI and Online Communities with PaLM-based Moderation”
Posted by Si-An Chen, Student Researcher, Cloud AI Team, and Chun-Liang Li, Research Scientist, Cloud AI Team Time series forecasting is critical to various real-world applications, from demand forecasting to pandemic spread prediction. In multivariate time series forecasting (forecasting multiple variants at the same time), one can split existing methods into two categories: univariate models …
Read more “TSMixer: An all-MLP architecture for time series forecasting”