If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
AI Daily Roundup starts today! We are covering the top updates from around the world. The updates will feature state-of-the-art capabilities in artificial intelligence, Machine Learning, Robotic Process Automation, Fintech and human-system interactions. We will cover the role of AI Daily Roundup and their application in various industries and daily lives. In Bangalore, India, 10th grader Rahul Jaikrishna developed Cyber Detective – an artificial intelligence-based model that detects cyber bullying with an accuracy of up to 80%.
In keeping with our mission to provide comprehensive advertising analysis, MediaRadar puts together a report of the most important mergers and acquisitions news each week. Stay in the loop, whether you sell advertising space or focus on business development. This week, Gilead takes out FortySeven, Apple acquires start-up Voysis and Infor is purchased by Koch Industries. The American biotechnology company, Gilead has completed an acquisition of Forty Seven, Inc. at a rate of $97.50 per share that equates to a lump sum of $4.9 billion in cash. The deal bolsters Gilead's portfolio of oncology drugs through Forty Seven Inc.'s blood cancer medicine, which is expected to be on the market within 2 years.
Bottom line: Enterprises are attaining double-digit improvements in forecast error rates, demand planning productivity, cost reductions and on-time shipments using machine learning today, revolutionising supply chain management in the process. Machine learning algorithms and the models they're based on excel at finding anomalies, patterns and predictive insights in large data sets. Many supply chain challenges are time, cost and resource constraint-based, making machine learning an ideal technology to solve them. From Amazon's Kiva robotics relying on machine learning to improve accuracy, speed and scale to DHL relying on AI and machine learning to power their Predictive Network Management system that analyses 58 different parameters of internal data to identify the top factors influencing shipment delays, machine learning is defining the next generation of supply chain management. Gartner predicts that by 2020, 95% of Supply Chain Planning (SCP) vendors will be relying on supervised and unsupervised machine learning in their solutions.
Organizations have been striving to increase productivity since the days of the cotton gin, steam power and Model T assembly lines. Today, maximizing productivity is often associated with software technology, from virtual assistants to predictive science. But, as the pace of innovation has accelerated, the practical ability to implement and monetize the exciting new technologies hasn't always kept up. It's time for solution providers to step up their game and take a more active role in supporting software implementation efforts. Today's common tactics for deploying software are flawed.
Infor has signed a new research partnership with the University of Oxford and extended its partnership with Carnegie Mellon University, both to study machine learning. Infor awarded an unrestricted research gift of $100,000 USD to support on-going work on in-database machine learning to the Factorised Databases (FDB) Project of the Computer Science Department at Oxford in the UK. Professor Dan Olteanu leads the FDB Project. "Our goal is to build a scalable system for training machine learning models over relational databases. Our approach comes with both theoretical and practical benefits. It enjoys lower computational complexity than the existing approaches, which means, in practice, training over larger datasets and orders-of-magnitude faster than state-of-the-art analytics systems."
When reviewing 2018's retail landscape, there have certainly been ongoing challenges and opportunities that have pushed the evolution of retail to match the demands of a changing consumer. Mobile technology, speed of service/delivery, and low prices are just the tip of the iceberg. In recent discussions with a variety of retailers and retail analysts in Australia and New Zealand, artificial intelligence (AI) and machine learning (ML) are high on everyone's list of toys for the New Year to generate efficiencies across the retail enterprise. The question retailers are asking is whether to build an AI/ML engine themselves or, more probable, turn to a specialised software company already operating in the AI/ML space. Consumers want their product and they want it now -- in their size, flavour, length, shape, brand, weight.
At Infor's Inforum conference in Washington, DC, Infor launched its Coleman Digital Assistant. It is the first of the Coleman AI family products that the company is planning. Enterprise Times sat down with Massimo Capoccia, SVP Infor OS, Technology, Infor to talk about Coleman and other technologies that Infor is planning to bring to market. Unlike many of its competitors, Infor has developed Coleman completely in-house. This is a brave move.
Renowned theoretical physicist and futurist Steven Hawking was torn on the value of artificial intelligence. At one point, he said, "AI could be the biggest event in the history of our civilization. We don't know if we will be helped by AI … or conceivably destroyed by it." But just before his death earlier this year, Hawking appeared to change his AI calculus: "Perhaps we should all stop for a moment, and focus not only on making our AI better, but also (focus) on the benefit to humanity." There, in a nutshell, from one of the most brilliant minds of the century is the AI conundrum.
Infor, a leading provider of beautiful business applications specialized by industry and built for the cloud, today announced that it will highlight Coleman AI capabilities, utilizing Amazon Lex, at AWS re:Invent 2017, which will take place Nov. 27 to Dec. 1 in Las Vegas, NV. Infor will lead and contribute to conference sessions that discuss how Amazon Lex is powering functionality in Coleman AI, which help it act as a digital assistant in the enterprise to boost business productivity. "Amazon Lex helps us power the ability to execute intelligent skills to perform a quick Q&A with the system expert, conduct self-service analytics, and quickly automate tasks through our Infor OS platform and our Infor Coleman AI platform," said Massimo Capoccia, Infor Senior Vice President of Software Development. The AWS re:Invent sessions at which Infor will be represented include: Session: MCL308 - Using a Digital Assistant in the Enterprise for Business Productivity 2:30 p.m., Tuesday, Nov. 28 Venetian Hotel, Level 5, Palazzo N - 650, T1 Manjunath Ganimasty, Vice President of Software Development at Infor; Rick Rider, Product Director-Technology at Infor; and Harshal Pimpalkhute, Product Manager at Amazon Web Services, Inc., will present "Infor Coleman - Using a Digital Assistant in the Enterprise for Business Productivity," during which they will demonstrate how Infor integrated Amazon Lex into its standard technology stack, with several use cases based on advisory, assistant, and automation roles deeply rooted in its expanding Artificial Intelligence (AI) strategy. They will discuss how Amazon Lex has become a pivotal component of Infor's AI strategy, powering one of the major functionalities of Infor Coleman as a digital assistant. Sandy Carter, Vice President for Amazon Elastic Compute Cloud (Amazon EC2) and Enterprise Workloads at Amazon Web Services, Inc., will note, in her Amazon EC2 "State of the Union" address, how Infor is building more than 250 industry-specific, AI-based skills in Coleman, using the services in the AWS AI stack.