The common approach to communicate a large language model’s (LLM) uncertainty is to add a percentage number or a hedging word to its response. But is this all we can do? Instead of generating a single answer and then hedging it, an LLM that is fully transparent to the user needs to be able to …
Read more “SelfReflect: Can LLMs Communicate Their Internal Answer Distribution?”
Editor’s Note: This blog post responds to allegations published by the Electronic Frontier Foundation (EFF) in relation to Palantir’s work with Immigration and Customs Enforcement (ICE). We believe it’s important to address misconceptions (as we have previously) about our technology and business practices with transparency and factual accuracy. Introduction The Electronic Frontier Foundation (EFF) has …
Read more “Correcting the Record: Response to the EFF January 15, 2026 Report on Palantir”
This post was co-written with Saurabh Gupta and Todd Colby from Pushpay. Pushpay is a market-leading digital giving and engagement platform designed to help churches and faith-based organizations drive community engagement, manage donations, and strengthen generosity fundraising processes efficiently. Pushpay’s church management system provides church administrators and ministry leaders with insight-driven reporting, donor development dashboards, and automation …
The world of artificial intelligence is moving at lightning speed. At Google Cloud, we’re committed to providing best-in-class infrastructure to power your AI and ML workloads. Dataflow is a critical component of Google Cloud’s AI stack that lets you create batch and streaming pipelines that support a variety of analytics and AI use cases. We’re …
The AI Evolution of Graph Search at Netflix: From Structured Queries to Natural Language By Alex Hutter and Bartosz Balukiewicz Our previous blog posts (part 1, part 2, part 3) detailed how Netflix’s Graph Search platform addresses the challenges of searching across federated data sets within Netflix’s enterprise ecosystem. Although highly scalable and easy to configure, …
AWS AppSync Events can help you create more secure, scalable Websocket APIs. In addition to broadcasting real-time events to millions of Websocket subscribers, it supports a crucial user experience requirement of your AI Gateway: low-latency propagation of events from your chosen generative AI models to individual users. In this post, we discuss how to use …
Read more “Build a serverless AI Gateway architecture with AWS AppSync Events”
The digital landscape is flooded with unstructured data — images, videos, audio, and documents — that often remain untapped. To help you unlock this data’s potential with minimal friction, we have integrated Gemini and other Vertex AI models directly into BigQuery, simplifying how you work with generative AI and embedding models using BigQuery SQL.New launches …
Editor’s Note: In this blog post, Palantir’s Information Security (InfoSec) team shares their approach to implementing a comprehensive VS Code extension management program, demonstrating practical solutions to a frequently overlooked attack vector. Introduction Integrated development environments (IDEs) serve as the primary interface for authoring code and managing infrastructure, sitting at the heart of every software company. …
Read more “Managing and Securing VS Code Extensions at Scale”
Agentic-AI has become essential for deploying production-ready AI applications, yet many developers struggle with the complexity of manually configuring agent infrastructure across multiple environments. Infrastructure as code (IaC) facilitates consistent, secure, and scalable infrastructure that autonomous AI systems require. It minimizes manual configuration errors through automated resource management and declarative templates, reducing deployment time from …
Read more “Build AI agents with Amazon Bedrock AgentCore using AWS CloudFormation”
Google’s Agent Development Kit (ADK) gives you the building blocks to create powerful agentic systems. These multi-step agents can plan, loop, collaborate, and call tools dynamically to solve problems on their own. However, this flexibility also makes them unpredictable, leading to potential issues like incomplete outputs, unexpected costs, and security risks. To help you manage …
Read more “Monitoring Google ADK agentic applications with Datadog LLM Observability”