Data platform trinity: Competitive or complementary?

Data platform architecture has an interesting history. Towards the turn of millennium, enterprises started to realize that the reporting and business intelligence workload required a new solution rather than the transactional applications. A read-optimized platform that can integrate data from multiple applications emerged. It was Datawarehouse. In another decade, the internet and mobile started the …

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Google Research, 2022 & Beyond: Language, Vision and Generative Models

Posted by Jeff Dean, Senior Fellow and SVP of Google Research, on behalf of the Google Research community Today we kick off a series of blog posts about exciting new developments from Google Research. Please keep your eye on this space and look for the title “Google Research, 2022 & Beyond” for more articles in …

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New Hires, Lost Keys & Lessons Learned (Passwordless Authentication Series, #3)

Editor’s Note: This is the third and final post in the Passwordless Authentication Series, which shares insights from our journey on enforcing FIDO2 authentication via hardware authenticators (YubiKeys) across all of Palantir. The first post focuses on hardware selection and logistics; the second post covers technical controls, rollout, and edge cases. While Palantir has enforced …

What is an open data lakehouse and why you should care?

A data lakehouse is an emerging data management architecture that improves efficiency and converges data warehouse and data lake capabilities driven by a need to improve efficiency and obtain critical insights faster. Let’s start with why data lakehouses are becoming increasingly important. Why is a data lakehouse architecture becoming increasingly important? To start, many organizations …

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Set up Amazon SageMaker Studio with Jupyter Lab 3 using the AWS CDK

Amazon SageMaker Studio is a fully integrated development environment (IDE) for machine learning (ML) partly based on JupyterLab 3. Studio provides a web-based interface to interactively perform ML development tasks required to prepare data and build, train, and deploy ML models. In Studio, you can load data, adjust ML models, move in between steps to adjust experiments, …

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Built with BigQuery: How to accelerate data-centric AI development with Google Cloud and Snorkel AI

In Deloitte’s annual “State of AI in the Enterprise” survey, 94% of business leaders identified AI as critical to their organizations’ success over the next five years. That survey also uncovered a 29% increase in the number of organizations struggling to achieve meaningful AI-driven business outcomes. Part of this challenge lies in the ability to …

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Giving Life to the Metaverse with 3D Avatars

They say a house is not a home if there is no one there. Well what good is an advanced virtual space without access to digital assets like 3D chatbots to interact with? 3D chatbots are the bridge between the physical and digital as it grants that human-like connection in addition to providing a more seamless, …

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This AI went camping

AI image generators have come a long way in recent years. When they first started out, they were quite bad at drawing tents. This was because they could only generate images based on the few examples that they had been given. However, they have since learned how to generalize from these examples and are now …