Understanding the Ray ecosystem and community

Ray is both a general purpose distributed computing platform and a collection of libraries targeted at machine learning and other workloads. By Ben Lorica and Ion Stoica. [This post originally appeared on the Anyscale blog.] Ray is usually described as a distributed computing platform that can be used to scale Python applications with minimal effort.Continue reading “Understanding the Ray ecosystem and community”

What Is a Lakehouse?

by Ben Lorica, Michael Armbrust, Ali Ghodsi, Reynold Xin and Matei Zaharia. [This post originally appeared on the Databricks blog.] Over the past few years at Databricks, we’ve seen a new data management paradigm that emerged independently across many customers and use cases: the lakehouse. In this post we describe this new paradigm and itsContinue reading “What Is a Lakehouse?”

The Road to Software 2.0

It’s clear that AI can and will have a big influence on how we develop software. By Mike Loukides and Ben Lorica. [A version of this post appears on the O’Reilly Radar.] Roughly a year ago, we wrote “What machine learning means for software development.” In that article, we talked about Andrej Karpathy’s concept of SoftwareContinue reading “The Road to Software 2.0”

How New Tools In Data And AI Are Being Used In Healthcare And Medicine

An overview of applications of new tools for overcoming silos, and for creating and sharing high-quality data. By Ben Lorica and Mike Loukides. [A version of this post appears on the O’Reilly Radar.] AI will have a huge impact on healthcare. It is currently moving out of the laboratory and into real-world applications for healthcareContinue reading “How New Tools In Data And AI Are Being Used In Healthcare And Medicine”

Managing machine learning in the enterprise: Lessons from banking and health care

A look at how guidelines from regulated industries can help shape your ML strategy. By Ben Lorica, Harish Doddi, David Talby. As companies use machine learning (ML) and AI technologies across a broader suite of products and services, it’s clear that new tools, best practices, and new organizational structures will be needed. In recent posts,Continue reading “Managing machine learning in the enterprise: Lessons from banking and health care”

RISELab’s AutoPandas hints at automation tech that will change the nature of software development

Neural-backed generators are a promising step toward practical program synthesis. There’s a lot of hype surrounding AI, but are companies actually beginning to use AI technologies? In a survey we released earlier this year, we found that more than 60% of respondents worked in organizations that planned to invest some of their IT budgets intoContinue reading “RISELab’s AutoPandas hints at automation tech that will change the nature of software development”

What are model governance and model operations?

A look at the landscape of tools for building and deploying robust, production-ready machine learning models. By Ben Lorica, Harish Doddi, David Talby. Our surveys over the past couple of years have shown growing interest in machine learning (ML) among organizations from diverse industries. A few factors are contributing to this strong interest in implementingContinue reading “What are model governance and model operations?”

How AI and machine learning are improving customer experience

From data quality to personalization, to customer acquisition and retention, and beyond, AI and ML will shape the customer experience of the future. By Ben Lorica and Mike Loukides. What can artificial intelligence (AI) and machine learning (ML) do to improve customer experience? AI and ML already have been intimately involved in online shopping since, well,Continue reading “How AI and machine learning are improving customer experience”