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The Practical Quant wrote a new blog post titled The evolution and expanding utility of Ray
[A version of this post appears on the O'Reilly Radar.]There are growing numbers of users and contributors to the framework, as well as libraries for reinforcement learning, AutoML, and data science.In a recent post, I listed some of the early use cases described in the first meetup dedicated to Ray—a distributed programming framework from UC Berkeley’s RISE Lab. A second meetup took place a few months later, and both events featured some of the first applications built with Ray. On the development front, the core API has stabilized and a lot of work has gone into improving Ray’s performance...
56 days ago
The Practical Quant wrote a new blog post titled 7 data trends on our radar
[A version of this post appears on the O'Reilly Radar.]From infrastructure to tools to training, here's what’s ahead for data.Whether you’re a business leader or a practitioner, here are key data trends to watch and explore in the months ahead.Increasing focus on building data culture, organization, and trainingIn a recent O’Reilly survey, we found that the skills gap remains one of the key challenges holding back the adoption of machine learning. The demand for data skills (“the sexiest job of the 21st century”) hasn’t dissipated. LinkedIn recently found that demand for data scientists in...
56 days ago
The Practical Quant wrote a new blog post titled 9 AI trends on our radar
[A version of this post appears on the O'Reilly Radar.]How new developments in automation, machine deception, hardware, and more will shape AI.Here are key AI trends business leaders and practitioners should watch in the months ahead.We will start to see technologies enable partial automation of a variety of tasks.Automation occurs in stages. While full automation might still be a ways off, there are many workflows and tasks that lend themselves to partial automation. In fact, McKinsey estimates that “fewer than 5% of occupations can be entirely automated using current technology. However,...
56 days ago
The Practical Quant wrote a new blog post titled How machine learning impacts information security
[A version of this post appears on the O'Reilly Radar.]The O'Reilly Data Show Podcast: Andrew Burt on the need to modernize data protection tools and strategies.In this episode of the Data Show, I spoke with Andrew Burt, chief privacy officer and legal engineer at Immuta, a company building data management tools tuned for data science. Burt and cybersecurity pioneer Daniel Geer recently released a must-read white paper (“Flat Light”) that provides a great framework for how to think about information security in the age of big data and AI. They list important changes to the information...
56 days ago
The Practical Quant wrote a new blog post titled Using machine learning and analytics to attract and retain employees
[A version of this post appears on the O'Reilly Radar blog.]The O'Reilly Data Show Podcast: Maryam Jahanshahi on building tools to help improve efficiency and fairness in how companies recruit.In this episode of the Data Show, I spoke with Maryam Jahanshahi, research scientist at TapRecruit, a startup that uses machine learning and analytics to help companies recruit more effectively. In an upcoming survey, we found that a “skills gap” or “lack of skilled people” was one of the main bottlenecks holding back adoption of AI technologies. Many companies are exploring a variety of internal and...
56 days ago
The Practical Quant wrote a new blog post titled The technical, societal, and cultural challenges that come with the rise of fake media
[A version of this post appears on the O'Reilly Radar.]The O'Reilly Data Show Podcast: Siwei Lyu on machine learning for digital media forensics and image synthesis.In this episode of the Data Show, I spoke with Siwei Lyu, associate professor of computer science at the University at Albany, State University of New York. Lyu is a leading expert in digital media forensics, a field of research into tools and techniques for analyzing the authenticity of media files. Over the past year, there have been many stories written about the rise of tools for creating fake media (mainly images, video,...
56 days ago
The Practical Quant wrote a new blog post titled Books I enjoyed in 2018
Here are nonfiction books I enjoyed reading in 2018 (more precisely, these are books I read during the second part of 2017 through 2018). Not all of these books were released this year, although most them are 2018 releases. I read many of these using Apple Books on my iPad but I've also gotten back to scouring thrift stores and used bookstores (where I've gotten some amazing bargains this year). For more, head over to the Gradient Flow.
56 days ago
The Practical Quant wrote a new blog post titled In the age of AI, fundamental value resides in data
[A version of this post appears on the O'Reilly Radar.]The O'Reilly Data Show Podcast: Haoyuan Li on accelerating analytic workloads, and innovation in data and AI in China.In this episode of the Data Show, I spoke with Haoyuan Li, CEO and founder of Alluxio, a startup commercializing the open source project with the same name (full disclosure: I’m an advisor to Alluxio). Our discussion focuses on the state of Alluxio (the open source project that has roots in UC Berkeley’s AMPLab), specifically emerging use cases here and in China. Given the large-scale use in China, I also wanted to get...
56 days ago
The Practical Quant wrote a new blog post titled Deep automation in machine learning
[A version of this post appears on the O'Reilly Radar.]We need to do more than automate model building with autoML; we need to automate tasks at every stage of the data pipeline.By Ben Lorica and Mike LoukidesIn a previous post, we talked about applications of machine learning (ML) to software development, which included a tour through sample tools in data science and for managing data infrastructure. Since that time, Andrej Karpathy has made some more predictions about the fate of software development: he envisions a Software 2.0, in which the nature of software development has fundamentally...
56 days ago
The Practical Quant wrote a new blog post titled Assessing progress in automation technologies
[A version of this post appears on the O'Reilly Radar.]When it comes to automation of existing tasks and workflows, you need not adopt an “all or nothing” attitude.In this post, I share slides and notes from a keynote Roger Chen and I gave at the Artificial Intelligence conference in London in October 2018. We presented an overview of the state of automation technologies: we tried to highlight the state of the key building block technologies and we described how these tools might evolve in the near future.To assess the state of adoption of machine learning (ML) and AI, we recently conducted a...
133 days ago
The Practical Quant wrote a new blog post titled Tools for generating deep neural networks with efficient network architectures
[A version of this post appears on the O'Reilly Radar.]The O'Reilly Data Show Podcast: Alex Wong on building human-in-the-loop automation solutions for enterprise machine learning.In this episode of the Data Show, I spoke with Alex Wong, associate professor at the University of Waterloo, and co-founder of DarwinAI, a startup that uses AI to address foundational challenges with deep learning in the enterprise. As the use of machine learning and analytics become more widespread, we’re beginning to see tools that enable data scientists and data engineers to scale and tackle many more problems...
133 days ago
The Practical Quant wrote a new blog post titled Building tools for enterprise data science
[A version of this post appears on the O'Reilly Radar.]The O'Reilly Data Show Podcast: Vitaly Gordon on the rise of automation tools in data science.In this episode of the Data Show, I spoke with Vitaly Gordon, VP of data science and engineering at Salesforce. As the use of machine learning becomes more widespread, we need tools that will allow data scientists to scale so they can tackle many more problems and help many more people. We need automation tools for the many stages involved in data science, including data preparation, feature engineering, model selection and hyperparameter tuning,...
148 days ago
The Practical Quant wrote a new blog post titled Managing risk in machine learning
[A version of this post appears on the O'Reilly Radar.]Considerations for a world where ML models are becoming mission critical.In this post, I share slides and notes from a keynote I gave at the Strata Data Conference in New York last September. As the data community begins to deploy more machine learning (ML) models, I wanted to review some important considerations.Let’s begin by looking at the state of adoption. We recently conducted a surveywhich garnered more than 11,000 respondents—our main goal was to ascertain how enterprises were using machine learning. One of the things we learned...
156 days ago
The Practical Quant wrote a new blog post titled Lessons learned while helping enterprises adopt machine learning
[A version of this post appears on the O'Reilly Radar blog.]The O'Reilly Data Show Podcast: Francesca Lazzeri and Jaya Mathew on digital transformation, culture and organization, and the team data science process.In this episode of the Data Show, I spoke with Francesca Lazzeri, an AI and machine learning scientist at Microsoft, and her colleague Jaya Mathew, a senior data scientist at Microsoft. We conducted a couple of surveys this year—“How Companies Are Putting AI to Work Through Deep Learning” and “The State of Machine Learning Adoption in the Enterprise” — and we found that while many...
161 days ago
The Practical Quant wrote a new blog post titled Machine learning on encrypted data
[A version of this post appears on the O'Reilly Radar.]The O'Reilly Data Show Podcast: Alon Kaufman on the interplay between machine learning, encryption, and security.In this episode of the Data Show, I spoke with Alon Kaufman, CEO and co-founder of Duality Technologies, a startup building tools that will allow companies to apply analytics and machine learning to encrypted data. In a recent talk, I described the importance of data, various methods for estimating the value of data, and emerging tools for incentivizing data sharing across organizations. As I noted, the main motivation for...
175 days ago
The Practical Quant wrote a new blog post titled How social science research can inform the design of AI systems
[A version of this post appears on the O'Reilly Radar.]The O'Reilly Data Show Podcast: Jacob Ward on the interplay between psychology, decision-making, and AI systems.In this episode of the Data Show, I spoke with Jacob Ward, a Berggruen Fellow at Stanford University. Ward has an extensive background in journalism, mainly covering topics in science and technology, at National Geographic, Al Jazeera, Discovery Channel, BBC, Popular Science, and many other outlets. Most recently, he’s become interested in the interplay between research in psychology, decision-making, and AI systems. He’s in the...
188 days ago
The Practical Quant wrote a new blog post titled Why it's hard to design fair machine learning models
[A version of this post appears on the O'Reilly Radar.]The O'Reilly Data Show Podcast: Sharad Goel and Sam Corbett-Davies on the limitations of popular mathematical formalizations of fairness.In this episode of the Data Show, I spoke with Sharad Goel, assistant professor at Stanford, and his student Sam Corbett-Davies. They recently wrote a survey paper, “A Critical Review of Fair Machine Learning,” where they carefully examined the standard statistical tools used to check for fairness in machine learning models. It turns out that each of the standard approaches (anti-classification,...
203 days ago
The Practical Quant wrote a new blog post titled Using machine learning to improve dialog flow in conversational applications
[A version of this post appears on the O'Reilly Radar.]The O'Reilly Data Show Podcast: Alan Nichol on building a suite of open source tools for chatbot developers.In this episode of the Data Show, I spoke with Alan Nichol, co-founder and CTO of Rasa, a startup that builds open source tools to help developers and product teams build conversational applications. About 18 months ago, there was tremendous excitement and hype surrounding chatbots, and while things have quieted lately, companies and developers continue to refine and define tools for building conversational applications. We spoke...
216 days ago
The Practical Quant wrote a new blog post titled Building accessible tools for large-scale computation and machine learning
[A version of this post appears on the O'Reilly Radar.]In this episode of the Data Show, I spoke with Eric Jonas, a postdoc in the new Berkeley Center for Computational Imaging. Jonas is also affiliated with UC Berkeley’s RISE Lab. It was at a RISE Lab event that he first announced Pywren, a framework that lets data enthusiasts proficient with Python run existing code at massive scale on Amazon Web Services. Jonas and his collaborators are working on a related project, NumPyWren, a system for linear algebra built on a serverless architecture. Their hope is that by lowering the barrier to...
231 days ago
The Practical Quant wrote a new blog post titled Simplifying machine learning lifecycle management
[A version of this post appears on the O'Reilly Radar.]The O'Reilly Data Show Podcast: Harish Doddi on accelerating the path from prototype to production.In this episode of the Data Show, I spoke with Harish Doddi, co-founder and CEO of Datatron, a startup focused on helping companies deploy and manage machine learning models. As companies move from machine learning prototypes to products and services, tools and best practices for productionizing and managing models are just starting to emerge. Today’s data science and data engineering teams work with a variety of machine learning libraries,...
245 days ago