Tag: ai/ml

Editor’s Note: In light of the recent New York Times article, this blog post seeks to identify and respond to specific allegations, assumptions, and statements made in the article about Palantir, offering corrections to inaccuracies and clarifying misrepresentations about the work Palantir does and doesn’t do. Overview At Palantir, we welcome, to the greatest extent possible, …

Read more “Correcting the Record: Responses to the May 30, 2025 New York Times Article on Palantir”

Voice AI is transforming how we interact with technology, making conversational interactions more natural and intuitive than ever before. At the same time, AI agents are becoming increasingly sophisticated, capable of understanding complex queries and taking autonomous actions on our behalf. As these trends converge, you see the emergence of intelligent AI voice agents that …

Read more “Building intelligent AI voice agents with Pipecat and Amazon Bedrock – Part 1”

A refresher on the most common misconceptions about Palantir, what we do, and how we work Editor’s Note: This is the seventh post in Palantir Explained, a series that explores a range of topics, including our approach to privacy, security, AI/ML safety, and more. In this post, we revisit some of the themes discussed in our …

Read more “Palantir Is Still Not a Data Company (Palantir Explained, #7)”

Recordings of business meetings, interviews, and customer interactions have become essential for preserving important information. However, transcribing and summarizing these recordings manually is often time-consuming and labor-intensive. With the progress in generative AI and automatic speech recognition (ASR), automated solutions have emerged to make this process faster and more efficient. Protecting personally identifiable information (PII) …

Read more “Build a serverless audio summarization solution with Amazon Bedrock and Whisper”

This post is co-written with Qing Chen and Mark Sinclair from Radial. Radial is the largest 3PL fulfillment provider, also offering integrated payment, fraud detection, and omnichannel solutions to mid-market and enterprise brands. With over 30 years of industry expertise, Radial tailors its services and solutions to align strategically with each brand’s unique needs. Radial …

Read more “Modernize and migrate on-premises fraud detection machine learning workflows to Amazon SageMaker”

Today, we are excited to announce that Gartner® has named Google as a Leader in the 2025 Magic Quadrant™ for Data Science and Machine Learning Platforms report (DSML). We believe that this recognition is a reflection of continued innovations to address the needs of data science and machine learning teams, as well as new types …

Read more “Google is a Leader in the 2025 Gartner® Magic Quadrant™ for Data Science and Machine Learning Platforms report”

This post is co-written with Tatia Tsmindashvili, Ana Kolkhidashvili, Guram Dentoshvili, Dachi Choladze from Impel. Impel transforms automotive retail through an AI-powered customer lifecycle management solution that drives dealership operations and customer interactions. Their core product, Sales AI, provides all-day personalized customer engagement, handling vehicle-specific questions and automotive trade-in and financing inquiries. By replacing their …

Read more “Impel enhances automotive dealership customer experience with fine-tuned LLMs on Amazon SageMaker”

Last month at Google Cloud Next ‘25, we announced MCP Toolbox for Databases to make it easier to connect generative AI agents to databases, and automate core enterprise workflows. MCP Toolbox for Databases (Toolbox) is an open-source Model Context Protocol (MCP) server that allows developers to easily connect gen AI agents to enterprise data. It …

Read more “Announcing new MCP integrations to Google Cloud Databases to enable AI-assisted development”