Press

What Netflix, Uber and the Next 100 Unicorns Will Have in Common

Posted December 2, 2015 on Inc.com

In this column, Daphne Koller asks Carlos Guestrin, Amazon professor of machine learning at the University of Washington, to share his thoughts on the growing value of data science.


Coursera's Machine Learning Specialization

Posted November 30, 2015 on I Programmer

Students intent on earning the certificate awarded on successful completion of this Specialization are advised to take its five courses in order. However there is some flexibility and, as the courses appear again regularly in the schedule, if you don't finish in one session you can re-enroll and carry on from where you got to...


Dato Updates GraphLab Create to Build Intelligent Applications Faster

Posted November 28, 2015 on Predictive Analytics Today

Dato has now built in new capabilities for automated feature engineering as well as for automatically tagging and de-duplicating data, greatly reducing the effort needed to accomplish these tasks. Data scientists, developers and engineers working on prototyping models of intelligent applications can now reach deployment-ready versions quickly and efficiently.


Three Unique Ways Machine Learning Is Being Used In the Real World

Posted November 18, 2015 on Datanami

Here are three examples of how actual companies are using machine learning technology upon big data to solve real-world problems in unique and non-intuitive ways.


These are the most mind-blowing robots, according to 18 artificial intelligence researchers

Posted November 12, 2015 on Tech Insider

"The recent results that we're seeing with things such as self-driving cars, like an ability to significantly decrease traffic accidents — I think that's really exciting to think about." - Commentary from Carlos Guestrin, the CEO and cofounder of Dato, a company that builds artificially intelligent systems to analyze data.


Coursera Review: Machine Learning Foundations—A Case Study Approach

Posted November 9, 2015 on Tech Powered Math

After a completing the Data Science Specialization from Johns Hopkins in 2014, my MOOC studies in 2015 have been fairly sporadic, partly as a result of starting a new job, and partly as a result of not seeing something that seemed like the right fit. That’s no longer the case, as I’ve recently jumped into a new specialization, the Machine Learning Specialization from the University of Washington.


A Practical, Hands-On Approach to Machine Learning Education

Posted November 5, 2015 on Datanami.com

If you enroll in a university-level data science program, you’ll likely spend months learning machine learning theory and how to code them. But you won’t necessarily see how they relate to real-world problems. That’s what spurred the folks at Dato to work with Coursera and the University of Washington to create a class that advocates a more practical approach to machine learning.


Industrial analytics delivering greater business value

Posted October 25, 2015 on Tech Target

The company uses software from Seattle-based Dato Inc. to ingest and analyze the sensor data, which allows Compology's customers to efficiently route collection vehicles based on which Dumpsters are most in need of emptying. This approach reduces the number of trucks needed for waste collection by as much as 40% compared to more routine routing, said Jason Gates, one of Compology's founders.


Compology goes Dumpster Diving for Data

Posted October 23, 2015 on CIO Insight

An upstart California company introduces sensors and software to make waste collection far more efficient.

Compology relies on a machine learning platform from software vendor Dato to drive the initiative and provide the data modeling capabilities. Overall, the system automatically classifies between 40 percent and 50 percent of the images and achieves greater than 96 percent accuracy.


This phenomenon explains what everyone gets wrong about AI

Posted October 22, 2015 on Tech Insider

Carlos Guestrin, the CEO of a Seattle-based company called Dato that builds AI algorithms to analyze data, said it might be because ANI looks nothing like human intelligence.

"Once something is done, it's not AI anymore," Guestrin told Tech Insider. "It's a perceptual thing — once something becomes commonplace, it's demystified, and it doesn't feel like the magical intelligence that we see in humans."


Firms Pit Artificial Intelligence Against Hacking Threats

Posted October 14, 2015 on The New York Times

Carlos Guestrin, a well-regarded expert in machine learning, is chief executive and co-founder of a company called Dato. In addition to traditional A.I. businesses like figuring out shopping preferences, he started looking at fraudulent behaviors.

"We caught spam with machine learning by looking at sequences of words, now we look for the code in a virus, like DNA, that makes it do unusual things," Guestrin said. "With human fraud, you look for relationships about who sends money to who, or who is hiding fraudulent transactions. If a finite number of people keep sending each other money, they're probably trying to look like legitimate businesses."


Smart Robots Will Take Our Jobs — But It Won't Be As Bad As You Might Think

Posted October 14, 2015 on Tech Insider

Robots are getting so sophisticated that some people fear they'll eventually replace human laborers. After all, robots have already transformed factories and other industrial work.

"Over the years we've seen tech develop further and further, and we've seen the nature of different jobs change," Carlos Guestrin, the CEO and co-founder of Dato, told Tech Insider.


Google must consider ‘unintended consequences’ of AI says machine learning expert

Posted October 8, 2015 on Tech World

Technology companies including Google must consider the “unintended consequences” when investing in AI, an eminent machine learning professor and founder of multimillion startup, Dato, warns.

The ethics surrounding machine learning is a hot topic. Google, which this morning announced it had invested an undisclosed sum in a top German AI research centre will instate an ethics board to monitor its AI efforts. It made the promise after buying Cambridge-based machine learning startup, Deepmind, last year.


Google must consider ‘unintended consequences’ of AI says machine learning expert

Posted October 8, 2015 on Tech World

Technology companies including Google must consider the “unintended consequences” when investing in AI, an eminent machine learning professor and founder of multimillion startup, Dato, warns.

The ethics surrounding machine learning is a hot topic. Google, which this morning announced it had invested an undisclosed sum in a top German AI research centre will instate an ethics board to monitor its AI efforts. It made the promise after buying Cambridge-based machine learning startup, Deepmind, last year.


Seattle Roundup: Dolly, ISB, Machine Learning, & More

Posted October 5, 2015 on Xconomy

Speaking of machine learning, Dato, the company making tools to help its customers incorporate machine learning capabilities into their products and services, is developing a six-course curriculum in partnership with the University of Washington and Coursera. The cost for the courses starts at $79. The company also released toolkits to help developers more-easily implement machine learning for specific tasks such as making recommendations, searching images, and predicting churn.


Machine learning helps build better applications

Posted September 29, 2015 on Beta News

"We see a huge number of developers adding machine learning to their applications using the Dato platform, which is really exciting for us. Recommendation engines, sentiment analysis, churn prediction and deep learning are some of the most sought after machine learning technologies that help companies like Pandora, Zillow and StumbleUpon create new personalized customer experiences in real time".


Watson-Type Machine Learning Affordable for Small Business

Posted September 29, 2015 on EE Times

A name well-known in Fortune 500 circles, with customers like Cisco, Bosch and Adobe, machine-learning software company Dato Inc. (Seattle, Wash.) is branching out to the mid-sized and even small-enterprises with graphical user interface (GUI) toolkits and online training to implement machine learning. Founded in 2012, the company has in just three-years skyrocketed into the major corporations by offering them IBM Watson calibre learning capabilities at a fraction of the price and in a bundled package that can be embedded inside existing applications.


Dato Announces New Machine Learning Toolkits and Coursera Training

Posted September 29, 2015 on SYS-CON Media

Dato, creator of the popular machine learning platform GraphLab Create, announced today toolkits and training for developers building Intelligent Applications. Developers can use Dato toolkits to build software that leverages machine learning technology, combining historical data and real time user interaction to make predictions and decisions. The toolkits allow developers to add recommendations, sentiment analysis, churn prediction and deep learning to create Intelligent Applications, delivering rich and adaptive experiences to users.

Dato also announced a partnership with Coursera and the University of Washington to deliver a six-course machine learning curriculum. The partnership addresses widespread demand for the machine learning developer capabilities needed to build Intelligent Applications.


Will machine learning become part of our everyday lives?

Posted September 28, 2015 on CIO

Carlos Guestrin, who’s been practising machine learning long before it was cool, expects every application to have some form of embedded intelligence in five years. "In the next five years, every successful breakthrough app is going to use machine learning at its core. Machine learning is what’s going to make an app truly useful and different to other things out there,” he said in the lead up to the Strata conference in New York City.


API for Prediction and Machine Learning: poll results and analysis

Posted September 1, 2015 on KDnuggets

Here, we analyzed major players in the big data domain are providing machine learning APIs.


B2B Marketers: Meet the Amazon Professor of Machine Learning

Posted August 27, 2015 on Business 2 Community

“The main thing that has caused companies to fail, in my view, is that they missed the future,” – Larry Page, co-founder Google. Earlier this month, Brandon Butler of Network World interviewed Carlos Guestrin, Amazon Professor of Machine Learning at the University of Washington. The conversation made it clear that machine learning and predictive technologies are more applied sciences than theoretical studies.


Inside the Zestimate: Data Science at Zillow

Posted August 12, 2015 on Datanami

Zillow is also using machine learning to improve the accuracy of error and fraud detection. Like any popular online resource, Zillow attracts its share of thieves and con-artists. The data science team uses a combination of Scikit Learn, a collection of Python-based data mining and machine learning tools, as well as Dato’s GraphLab Create to flush out bad guys.


5 questions for a top machine learning expert

Posted August 05, 2015 on Network World

Carlos Guestrin has always been a big dreamer. As a kid he was a sci-fi fan and longed to build robots. Today, as a professor at the University of Washington he’s one of the country’s leading thinkers in machine learning technology. We sat down with Guestrin, who is also CEO of machine learning company Dato, to learn how this technology works, what the current and emerging use cases are and why regular businesses should pay attention to it.


Eight Tools That Show What’s on the Horizon for the Python Data Ecosystem

Posted July 31, 2015 on Galvanize

Galvanize recently attended the Dato Data Science Summit in San Francisco, a gathering of more than 1,000 data scientists and researchers from industry and academia to discuss and learn about the most recent advances in data science, applied machine learning, and predictive applications. Here are eight Python tools that our instructors think data scientists will be using in the coming months and years.


How to Turn Your Company Into a Data-Driven Enterprise

Posted July 15, 2015 on Datanami

Data scientists want to get their hands dirty in the world of algorithms, so if you answered yes to 3, there are a number of different possibilities depending on the make-up of your IT staff. R, MATLAB, and SAS are generally tools relevant for statisticians and others in the applied sciences. NumPy or SciPy are a good fit for Python developers. And Dato (formerly GraphLab), Apache Spark, and Apache Mahout are a good fit when it comes to distributed development.


'Avengers: Age of Ultron,' 'Ex Machina' Reflect Hollywood's Growing Obsession With Artificial Intelligence

Posted May 06, 2015 on The Wrap

"If you think about it, we've been experiencing artificial intelligence in our lives for quite some time," said University of Washington professor Carlos Guestrin, an AI expert and Carnegie Mellon transplant whose work is funded by Jeff Bezos' Amazon. "Think about ten years ago when you couldn't use your device for an Uber or shop in your mobile browser. But pulling out your phone and asking Siri for a restaurant recommendation doesn't make the most exciting movie," Guestrin said.


Artificial-Intelligence Experts Are in High Demand
Tech firms, universities stock research centers amid push in hot area of computer science

Posted May 01, 2015 on The Wall Street Journal

When the University of Washington’s computer-science department wanted to poach artificial-intelligence expert Carlos Guestrin from Carnegie Mellon, it turned to Amazon.com Inc.

The Seattle-based tech giant ponied up $2 million to fund two professorships: one for Mr. Guestrin, and another for his wife, who also works in the field. To seal the deal, Amazon Chief Executive Jeff Bezos met the academic during a campus visit.

“[Mr. Bezos] is a very smart guy. He has a crazy laugh,” said Mr. Guestrin, now UW’s Amazon Professor of Machine Learning. “We got quickly into technical things: What was I working on in large-scale machine learning? How could I impact Amazon? What could this mean for the business of data?”UW also has become a Silicon Valley hunting ground. Before it recruited Mr. Guestrin—who earned his reputation creating artificial-intelligence-related tools for developers—the university lost seven AI-related professors to Google.


Dato Updates Machine Learning Platform

Posted February 25, 2015 on insideBIGDATA

Dato (formerly known as GraphLab) announced new updates to its machine learning platform, GraphLab Create, that allow data science teams to wrangle terabytes of data on their laptops at interactive speeds so that they can build intelligent applications faster. With Dato, users leverage machine learning to build prototypes, tune them, deploy in production and even offer them as a predictive service, all in minutes. These are the intelligent applications that provide predictions for a myriad of use cases including recommenders, sentiment analysis, fraud detection, churn prediction and ad targeting.


Dato Updates Machine Learning Platform, Puts Spotlight on Data Engineering Automation, Spark and Hadoop Integrations

SEATTLE – February 17, 2015 – Today at Strata + HadoopWorld San Jose, Dato (formerly known as GraphLab) announced new updates to its machine learning platform, GraphLab Create, that allow data science teams to wrangle terabytes of data on their laptops at interactive speeds so that they can build intelligent applications faster. With Dato, users leverage machine learning to build prototypes, tune them, deploy in production and even offer them as a predictive service, all in minutes. These are the intelligent applications that provide predictions for a myriad of use cases including recommenders, sentiment analysis, fraud detection, churn prediction and ad targeting.


GraphLab Changes Name to Dato, Raises $18.5 Million to Enable Creation of Intelligent Applications

SEATTLE – January 8, 2015 – GraphLab today announced it closed an $18.5 million Series B funding round led by Vulcan Capital with participation from Opus Capital Ventures and existing investors New Enterprise Associates (NEA) and Madrona Venture Group. The company has also changed its name and brand from GraphLab to Dato, reflecting the evolution of its popular machine learning platform which now enables the creation of intelligent applications based on any type of data, including graphs, tables, text and images. Dato will use the investment to expand its business development, engineering and customer support teams to serve a rapidly growing customer base. The Series B round brings the total amount raised by Dato to $25.25 million. Steve Hall from Vulcan Capital will join Dato’s board of directors.


GraphLab Empowers Data Scientists with First Major Version of Its Flagship Product

SEATTLE and NEW YORK – October 15, 2014 – Today at Strata + HadoopWorld 2014, GraphLab announced the general availability of its flagship product, GraphLab Create 1.0, a software platform that brings large-scale machine learning capabilities to data scientists at any organization. GraphLab Create 1.0 debuts enhanced capabilities, including predictive analytics and is available today in three pricing editions which are meant to map to the typical predictive application development journey: Discover, Develop, Deploy. GraphLab will also support Enterprise-wide programs.


GraphLab Off to Fast Start with System for Building Predictive Apps

Posted 7/29/14 on xconomy.com

In the course of a mere 14-months, Seattle startup GraphLab, Inc. has gone from a computer science professor and a few colleagues creating open source software to analyze graph datasets to a 25-person company with a new, full-fledged system for building predictive applications that draw on a range of data types.


New Products of The Week

Posted 7/21/14 on networkworld.com

GraphLab Create™ 1.0 brings large-scale machine learning capabilities to data scientists at every enterprise.


GraphLab Create™ 1.0 – Automating Big Data Analytics

Posted 7/17/14 on dataconomy.com

This article provides an overview of the technical product details, including quotes from Johnnie’s recent interview with IT Specialist. In addition, Eileen mentions the integration with Hadoop distributions Cloudera and Pivotal, and notes the upcoming GraphLab Conference with a link to the event page. Eileen also includes GraphLab’s image of the entire data product development pipeline to help readers visualize the process from prototype to production.


GraphLab Wises Up Machine Learning Platform

Posted 7/16/14 on datanami.com

This article gives a comprehensive overview of the benefits afforded by GraphLab Create™ 1.0, emphasizing both the simplicity and speed that the software brings to data scientists for better insights. He includes commentary from Johnnie’s recent IT Specialist interview, as well as quotes from Carlos via the press release. The piece links to the Conference website and notes conference sponsors include Adobe, Google, Oracle and Rackspace.


GraphLab Thinks its New Software Can Democratize Machine Learning

Posted 7/15/14 on gigaom.com

A Seattle-based machine learning startup called GraphLab is releasing the first official version of its software, which the company hopes can democratize an historically difficult space. Called Create, the software is focused on simplicity, speed and being able to handle a wide variety of applications.


GraphLab Unleashes the Power of Machine Learning

Posted 7/15/14 on betanews.com

The increased demand for solutions based on big data has led to something of a shortage of data scientists, which means in many cases companies are struggling to unlock the information they already have.

A new tool from data specialist GraphLab provides enterprise-grade machine learning to simplify and automate the handling of big data. By bringing together ease of use and computing scale the software makes it possible for one data scientist to do the job of many.


GraphLab Makes Big Data Machine Learning More Accessible

Posted 7/15/14 on adtmag.com

Seattle-based start-up GraphLab Inc. today emerged from stealth mode with a new platform designed to make large-scale machine learning more accessible to data scientists and developers everywhere.

GraphLab Create™ 1.0, to be officially unveiled at the company's conference in San Francisco next week, promises to be 100 to 10,000 times faster at analytics operations and model training than industry alternatives, company exec Johnnie Konstantas said in an e-mail to this site.


GraphLab Create™ Aims to be the Complete Package for Data Scientists

Posted 7/15/14 on semanticweb.com

Data scientists can add another tool to their toolset today: GraphLab has launched GraphLab Create™ 1.0, which bundles up everything starting from tools for data cleaning and engineering through to state-of-the-art machine learning and predictive analytics capabilities.

Think of it, company execs say, as the single platform that data scientists or engineers can leverage to unleash their creativity in building new data products, enabling them to write code at scale on their own laptops.


GraphLab Create™: Large-Scale Machine Learning Platform for Graph, Structured, and Text Data

Posted 7/15/14 on kdnuggets.com

GraphLab Create™ 1.0 brings large-scale machine learning capabilities to enterprises, and is the first to handle graph, structured, and text data in one platform.

GraphLab key advantages are performance and scaling. GraphLab Create™ has optimized out-of-core scaling enabling iteration of 1TB of data on a single machine, and can easily scale to distributed compute in the cloud for production environments that have high data volume and velocity.


CSE Startup GraphLab to Release GraphLab Create™

Posted 7/15/14 on news.cs.washington.edu

GraphLab, a Seattle-based startup launched in 2013 by UW CSE professor Carlos Guestrin and backed by our friends at Madrona Venture Group, is releasing next week its first commercial software, called GraphLab Create™.

Guestrin says that the goal of Create is to help savvy engineers or data scientists take their machine learning projects from idea to production. It includes modules for building certain types of popular workloads, including recommendation engines, graph analysis and clustering and regression algorithms.


New Software from GraphLab Puts the Power of Large-Scale Machine Learning in the Hands of Data Scientists in Every Enterprise

“GraphLab Create™ 1.0” Platform Simplifies and Automates Analytics So Companies Can Use Machine Learning to Get More Value from Big Data

Software Will Be Unveiled at GraphLab Conference Sponsored by Google, ExxonMobil, Oracle, Adobe, Pandora, Rackspace, StumbleUpon, NeoTechnology, Objectivity, Trifacta and Zillow

SEATTLE – July 15, 2014 – GraphLab today unveiled GraphLab Create™ 1.0, a new platform to bring large-scale machine learning capabilities to data scientists at every enterprise. GraphLab Create™ provides organizations of all sizes and across industries with advanced big data analytics, enabling them to build scalable data products quickly. Hundreds of businesses using the Beta version of GraphLab Create™ report better and faster insights from their big data.


Startup GraphLab Unleashes Machine Learning for Enterprise Big Data

Posted 6/23/14 on itspecialist.com

IT Specialists interviews Johnnie Konstantas, VP of Marketing at GraphLab, Inc., about GraphLab's machine learning solution for enterprise companies.


Easily Manipulate Terabyte-Sized Datasets With GraphLab

Posted 2/24/14 on Forbes via O'Reilly Media

GraphLab’s SFrame, an interesting and somewhat under-the-radar tool was unveiled1 at Strata Santa Clara. It is a disk-based, flat table representation that extends GraphLab to tabular data...


Ben Lorica, Chief Data Scientist at O'Reilly Media, on GraphLab

Posted 8/25/13 on O'Reilly Media blog

A new set of tools make it easier to do a variety of data analysis tasks. Some require no programming, while other tools make it easier to combine code, visuals, and text in the same workflow...


Amazon's CTO, Werner Vogels on GraphLab

Posted 8/23/13 on All Things Distributed weblog

The intense travels around the world in the spring have kept me from keeping up on the historical reading that I would like to do, as such there have not been that many suggesting for the back-to-basics reading list...


Facebook evaluates graph processing platforms, mentions GraphLab

Posted 8/14/13 on Facebook Engineering page

Graph structures are ubiquitous: they provide a basic model of entities with connections between them that can represent almost anything...


Follow The Data blog writes about GraphLab Create™

Posted 3/19/14 on Follow the Data blog

Just a heads-up that you can now get a free beta version of GraphLab Create™. It’s a Python library that lets you use GraphLab functionality to easily do stuff like calculating page ranks, building recommender systems and so on...


GraphLab Announces $6.75 million in Funding from Madrona Venture Group and NEA to Fuel the Fastest Graph Analysis for Modern Datasets

May 14, 2013, Seattle, WA - GraphLab Inc.(graphlab.com) today announced a $6.75 million Series A funding led by Madrona Venture Group and NEA. GraphLab Inc is innovating on the popular open source distributed graph computation framework (graphlab.org) that is used millions of times per day to deliver recommendations through popular consumer services.