LAKE OSWEGO, Ore.--(BUSINESS WIRE)--Vesta, a pioneer in guaranteed payment and fraud technologies, announced today that it has hired Tan Truong as chief information officer. He will be responsible for all aspects of the company's technology, operations and product development as well as spearheading innovation globally. Truong joins Vesta after building the global issuing platform for SVM LP, a leading provider of gift and prepaid cards for the incentive industry, and has more than 15 years of experience in financial technology. His track record includes two successful exits for companies whose technology platforms and teams he helped build, with FSV Payment Systems being acquired by U.S. Bank and UniRush being acquired by Green Dot. He has worked at startups and large corporations, in both strategic and hands-on technologist roles.

Managing the Machine Learning Lifecycle We review new and existing MLflow capabilities that help you keep track of experiments runs and results, execute projects remotely and quickly productionize models. Automated Hyperparameter Tuning, Scaling and Tracking We review the most popular techniques for hyperparameter tuning and discuss open-source tools. Productionizing Machine Learning: Deployment to Drift Detection You'll learn how to detect model drift using MLflow and Apache Spark Streaming on Databricks. How to Automate Machine Learning and Scale Delivery Understand how to use automation to dynamically select optimal machine learning models for your use case and automatically deploy models to production. Have a question about our products, pricing, training or anything else?

The biggest impact DataRobot has had on Lenovo is that decisions are now made in a more proactive and precise way. As we get better and forecast accuracy keeps improving, people are becoming more confident and trusting of the process, the data, the models, and DataRobot.

GUILFORD, Conn., Sept. 17, 2019 -- InveniAI Corporation, a global leader pioneering the application of artificial intelligence (AI) and machine learning (ML) to transform innovation across healthcare and other industries, today announced the expansion of its flagship AI- and ML-driven innovation monitoring platform, AlphaMeld . This expansion will provide a suite of products to facilitate the democratization of data analysis across the life sciences value chain and tap into InveniAI's extensive domain expertise and curated data sets that have been aligned with industry specific algorithms. CIMeld, an AlphaMeld powered product, will be launched at the upcoming PharmaCI USA 2019 Conference and Exhibition set for September 18-19, where competitive intelligence executives in pharma, biotech and medical devices meet at one of the largest CI assemblies in the world. CIMeld is a unique product that takes advantage of the digital data deluge and leverages AI-powered technology to triangulate signals from multiple sources to generate insights and identify opportunities and threats across diseases, companies, drug portfolios, and early innovation. The AlphaMeld suite of products is accessible via a secure, customized, cloud-based interface with the option to personalize the definition of success and failure that lends a unique competitive advantage to its users.

Tony has worked in the same automotive plant in north-west Ohio, US, for nearly two decades. During that time, he moved from a part-time line associate on the third shift to a line supervisor, where he now oversees 35 general assembly workers. Occasionally, one of his workers will come to him with an article about a nearby Indiana plant that plans full automation, and ask Tony if robots will take their jobs as well. Fortunately, Tony knows the numbers. The International Federation of Robotics projects 250,000 industrial robots will be deployed globally every year.

Artificial intelligence is infiltrating every industry, allowing vehicles to navigate without drivers, assisting doctors with medical diagnoses, and mimicking the way humans speak. But for all the authentic and exciting ways it's transforming the tasks computers can perform, there's a lot of hype, too. As Jeremy Achin, CEO of newly minted unicorn DataRobot, puts it: "Everyone knows you have to have machine learning in your story or you're not sexy." The inherently broad term gets bandied about so often that it can start to feel meaningless and can be trotted out by companies to gussy up even simple data analysis. To help cut through the noise, Forbes and data partner Meritech Capital put together a list of private, U.S.-based companies that are wielding some subset of artificial intelligence in a meaningful way and demonstrating real business potential from doing so. One makes robots that can whir around shoppers to help workers restock shelves. Another scans recruiting pitches for unconscious bias. A third analyzes massive data sets to make street-by-street weather predictions. To be included on the list, companies needed to show that techniques like machine learning (where systems learn from data to improve on tasks), natural language processing (which enables programs to "understand" written or spoken language), or computer vision (which relates to how machines "see") are a core part of their business model and future success. Find all the details on our methodology here. The honorees span categories like human resources, security, insurance, and finance, with healthcare, transportation, and infrastructure startups best represented on the list.

With the rise of artificial intelligence and voice recognition technology, there has been a plenty discussion about how industries, the labour force, and business models will change, but how will these technologies change the way consumers and brands interact? The explosion of smartphones and social media opened a new world of opportunities to communicate. Mobile messaging apps like Facebook Messenger, WhatsApp, and WeChat became the norm. Chatbots followed, which allowed brands to communicate on a one-to-one, personal level. Voice recognition erupted in the same way as social media and is completely changing the way we interact.

"We lived and breathed data science," DataRobot CEO Jeremy Achin says of himself and his cofounder Tom de Godoy. "And we asked ourselves, 'How would we automate our jobs?'" DataRobot wants to make machine learning so simple that a business analyst with basic training can run predictive models without breaking a sweat. The Boston-based startup just raised a $206 million Series E funding round led by Sapphire Ventures to expand the business, which sells software that helps companies across industries develop and deploy in-house AI models. The billion-dollar valuation makes it the highest-ranking of the "picks-and-shovels" startups featured on Forbes' inaugural AI 50 list (meaning the companies that provide tools to help their customers develop their own AI).

This is the web version of Data Sheet, Fortune's daily newsletter on the top tech news. To get it delivered daily to your in-box, sign up here. There's enthusiasm about the healthcare industry--I badly want to call it infectious or contagious but fear that would be in poor taste--and it is abundantly evident at Fortune's Brainstorm Health conference in San Diego this week. The exceedingly well-funded startup is more than a curio, and its technology vastly bests annoying quad-copters. Zipline's drones are airplanes that land by an innovative tail hook mechanism. Technology is transforming healthcare, mostly for the good.

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