Data can be used in a variety of ways to satisfy the needs of different business units, such as marketing, sales, or product. In this post, we focus on using data to create personalized recommendations to improve end-user engagement. Most ecommerce applications consume a huge amount of customer data that can be used to provide personalized recommendations; however, that data may not be cleaned or in the right format to provide those valuable insights. The goal of this post is to demonstrate how to use AWS Glue to extract, transform, and load your JSON data into a cleaned CSV format. We then show you how to run a recommendation engine powered by Amazon Personalize on your user interaction data to provide a tailored experience for your customers.

U.K.-based Featurespace, which offers anti-fraud systems for financial institutions (FIs), on Thursday (Feb. In a press release, the company said the new product, intended for the card and payments industry, provides a "deeper layer of defense to protect consumers from scams, account takeover, card and payments fraud, which cost an estimated $42 billion in 2020." The new product is "truly the next generation of machine learning," said Dave Excell, founder of Featurespace. The company said that it involves "a breakthrough in deep learning technology" that is capable of pinpointing potential fraud before the victim's money is removed from their account. That serves as "the best line of defense against scams, account takeover, card and payment fraud attacks," the release stated.

Click here to learn more about Gilad David Maayan. What Is Artificial Intelligence Marketing? In marketing, artificial intelligence (AI) is the process of using data models, mathematics, and algorithms to generate insights that marketers can use. Marketers use insights gained from AI to guide future decisions on event spending, strategy, and content topics. AI also makes it possible to measure and optimize marketing activities without human intervention.

Toyota Motor Corporation started construction this week on a 175-acre smart city at the base of Japan's Mount Fuji, about 62 miles from Tokyo, the company announced Tuesday. The city, which Toyota has dubbed the "Woven City," is expected to function as a testing ground for technologies like robotics, smart homes, and artificial intelligence. A starting population of about 360 inventors, senior citizens, and families with young children will test and develop these technologies. These residents, who are expected to move into the Woven City within five years, will live in smart homes with in-home robotics systems to assist with daily living and sensor-based artificial intelligence to monitor health and take care of other basic needs, according to the company. The eventual plan is for the city to house a population of more than 2,000 Toyota employees and their families, retired couples, retailers, and scientists.

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Quantiphi, an applied AI and data science software and services company, today announced that it has been named an IDC Innovator in the IDC Innovators: Artificial Intelligence Services, 2020 ( Doc # US45733220, December 2020) report. Quantiphi is one of just four companies featured in the report, which covers a selection of vendors that offer an innovative new technology or a groundbreaking business model, or both in artificial intelligence (AI) services. "AI has quickly evolved from a'nice-to-have technology' to a business imperative, driving enterprise demand for expertise from solution design through production at scale," said Jennifer Hamel, Research Manager for IDC's Worldwide Services team. "Quantiphi approaches the AI services market in distinct ways, partnering with its clients to apply complex AI techniques to solve real business problems." The report acknowledges Quantiphi's broad portfolio of repeatable IP and accelerators, and strong partnerships with major AI technology providers (e.g., Google, AWS, and NVIDIA) to assemble and scale AI solutions for clients in a variety of industries, leveraging a talent pool of industry analysts, cloud/data engineers, and ML engineers.

A mere two months after acquiring Uber's self-driving car unit (and a $400 million investment from the company), autonomous vehicle startup Aurora is partnering with the world's largest automaker. On Tuesday, the company announced a partnership with Toyota and Japanese auto parts supplier Denso (via The Verge) that will see the three firms work together to develop and test vehicles with Aurora's Driver technology. They'll first integrate the hardware and software into a fleet of Toyota Sienna minivans before deploying it within a full-scale robotaxai service. "By the end of 2021, we expect to have designed, built and begun testing an initial fleet of these Siennas near our areas of development," the company said. "It brings our companies together to lay the groundwork for the mass-production, launch and support of these vehicles with Toyota on ride-hailing networks, including Uber's, over the next few years."

Artificial intelligence already is making strides in the development of new drugs, and now the pesticide industry wants in on the action. Switzerland's Syngenta has teamed up with Insilico Medicine to use its deep-learning tools to produce sustainable weedkillers. As well as taking on some of the early-stage work traditionally conducted in a lab, AI could design molecules used in crop-protection tools that are more sustainable and environmentally friendly, the companies said last week. AI is among new methods emerging as environmental and health concerns spur a quest for sustainable alternatives to traditional pesticides used by farmers. Demand also is being supported by regulatory pressures and lawsuits, most notably Bayer's $11 billion settlement deal over claims its long-used glyphosate herbicide causes cancer.

Toyota Motor Corp. is tapping a star Silicon Valley robotics expert to help put the final touches on an operating system it says will go up against that of Tesla Inc. Called Arene, the system allows new features to be installed in a car's existing hardware over the air and provides a platform for developers to create software. It's being developed by Toyota's new technology research arm Woven Planet Holdings Inc., led by Chief Executive Officer James Kuffner, a former Google engineer. Tesla is already a leader when it comes to over-the-air updates of a car's operating systems, which control everything from braking to Wi-Fi, locking and lights. It has been upgrading its electric vehicles' battery range and autonomous functions remotely via updates since 2012. On an earnings call last week, Chief Executive Officer Elon Musk said Tesla is willing to license its software capabilities to third parties and is already in talks with original equipment manufacturers.

Analytics leader SAS continues to innovate by making it easier to access its powerful, cloud-native SAS Viya platform. Recent product developments help customers more efficiently democratize analytics throughout their organizations while seamlessly managing analytic workloads and building SAS into a variety of applications. "Among analytics providers, SAS is a recognized leader for reimagining the way analytics and machine learning are consumed so users realize optimal results that solve business challenges faster with more accuracy," said Ritu Jyoti, Program Vice President of Artificial Intelligence Research at IDC. "This iteration of the SAS Viya platform gives users at all levels of an organization an agile, powerful advanced machine learning engine to help master the complex data that's in cloud environments." Recognizing that so many organizations have struggled with the global pandemic and its effects, SAS CEO and founder Jim Goodnight says SAS Viya can help in the toughest times. "SAS Viya helps organizations see their data, customers and operations in new ways that encourage confident decision making," said Goodnight.