Planning & Scheduling

Chatbot technology is at an inflection point. The promises made about the potential for the technology have yet to come true. The market is predicted to grow 25% year-on-year to reach $1.25 Billion by 2025. Yet current attempts to build chatbots are failing. It is not clear how this apparent contradiction will resolve.

Following Madison's trip to Naomi's former camp in the last episode of "Fear the Walking Dead," the Clark matriarch secretly told her daughter Alicia to make a just-in-case Land Rover getaway car. Madison's decision to arrange a backup plan was quite surprising as she seemed to be the one person at the Stadium that had not even considered an emergency scheme since the Vultures showed up in their parking lot. In an interview with Entertainment Weekly, co-showrunner Ian Goldberg said that learning what happened to the FEMA shelter where Naomi (Jenna Elfman) used to live was one of the things that made Madison (Kim Dickens) realize that any community could crumble in an instant. "I think in a sense that plays a big role in it," Goldberg said. "Going through this experience with Naomi, learning what she went through with her daughter [Rose] -- certainly that plays a huge role in that moment we see with Madison at the end where she tells Alicia to pack her car just in case.

MAOS-FSP [1] is a multiagent optimization system (MAOS) for solving the Flowshop Scheduling Problem (FSP). MAOS-FSP shares the MAOS kernel with other MAOS applications (e.g. MAOS-GCP and MAOS-TSP), and contains some modules that are specifically for tacking FSP. Related Information: Please find other related code and software in our Source Code Library. License information: MAOS-FSP is free software; you can redistribute it and/or modify it under the Creative Commons Non-Commercial License 3.0.

As industries journey towards the Fourth Industrial Revolution, where people and robots will work together seamlessly, it's becoming more important than ever for organisations to integrate artificial intelligence (AI), robotics and the internet of things (IoT) into their digital game plan. However, much like policy makers, business leaders are struggling to keep up with these advancements. They're failing to leverage technology in areas such as human resources, payroll and workforce management. According to Deloitte's Human Capital Trends Report 2018, almost 95% of organisations worldwide don't know how to manage their workforce effectively. It's a confronting statistic and it's one Jarrod McGrath, founder and CEO of strategic workforce management consultancy Smart WFM, has set out to change.

While Artificial Intelligence and automation technologies is still nascent, the building blocks exist to suggest that Machine Learning could ease the burden of complex analysis, surface insights and trigger actions on behalf of managers. Workforce management is essentially the art and science of managing people in order to have a productive workforce. While there is a lot of science and methodology around this domain, with many current modern methods evolving from the foundational scientific management techniques propounded by Taylor over a century ago, it still requires the fine art of understanding an individual's capabilities and balancing human expectations to get the most out of people. Traditionally, in high empathy countries like India, this has largely been the responsibility of the manager, who balances an organisation's needs with individual wants and abilities. In short, the manager decides who needs to do what, when and where.

While Artificial Intelligence and automation technologies is still nascent, the building blocks exist to suggest that Machine Learning could ease the burden of complex analysis, surface insights and trigger actions on behalf of managers. Workforce management is essentially the art and science of managing people in order to have a productive workforce. While there is a lot of science and methodology around this domain, with many current modern methods evolving from the foundational scientific management techniques propounded by Taylor over a century ago, it still requires the fine art of understanding an individual's capabilities and balancing human expectations to get the most out of people. Traditionally, in high empathy countries like India, this has largely been the responsibility of the manager, who balances an organisation's needs with individual wants and abilities. In short, the manager decides who needs to do what, when and where.

Pilot Tammie Jo Shults, who was previously a Navy fighter pilot, had to make an emergency landing after an engine explosion; Linda Maloney, a friend and former combat pilot, shares details on'The Story.' Captain Tammie Jo Shults and First Officer Darren Ellisor revealed they "pushed fear" away in landing fatal flight 1380 in their first public interview since the harrowing April 17 incident that left one passenger dead. On May 11, the pair's appearance on ABC's "20/20" aired, in which they revealed new details from the cockpit during the tragic flight from New York's LaGuardia Airport to Dallas' Love Field. Forced to make an emergency landing at Philadelphia International Airport after an engine exploded mid-air, Shults and Ellisor had to act quickly to save the 149 people on board, People reports. "My first thoughts were actually, 'Oh, here we go' -- just because it seemed like a flashback to some of the Navy flying that we had done," 56-year-old Navy veteran Shults recalled. "But really, Darren is just very easy to communicate with and we had to use hand signals because it was loud and it was just hard to communicate for a lot of different reasons."

India is the latest country to announce a national AI initiative. But AI's leading countries are unlikely to let another player muscle in on their turf. The challenge: India is on course to become the third-largest economy in the world (by GDP) within the next few years. But the country may find it hard to kick-start its own AI revolution. India is playing catch-up with China and the West in terms of technology, research prowess, investment, and--crucially--data, the lifeblood of AI.

Hospitals have to solve a thousand logistical challenges every day, but perhaps none are more difficult than operating room schedules. Surgeries can be difficult to predict -- in fact, less than half of surgeries in the U.S. start and end on time. That can create chaos for patients and doctors, and costs hospitals $5.2 billion every year, according to University of Washington spinout Perimatics. The startup, which develops a variety of technologies for hospitals, is taking aim at the operating room problem with a new AI technology that uses data on patients and surgeons to more accurately predict how long each surgery will take. The startup recently deployed the technology at a large academic medical institution in Seattle.

Machine vision, says Utrip, TUI's chosen partner in AI, natural language processing and machine learning From being one of the first to dabble in blockchain technology to driving forward with AI-fuelled partnerships, the TUI Group is on a mission to remain a travel heavy weight. In a recent move, the world's biggest travel company has signed a deal with Seattle-based AI firm Utrip, to up its game in offering a deeply personalised experience throughout the customer journey. The idea, David Schelp, managing director of TUI Destination Services (DS), said in a press release, is to combine its "inventory of unique destination experiences with Utrip's artificial intelligence solution to provide our guests with the most personalised travel planning experience available today". TUI passed on an opportunity to hop on a call to discuss the deal further, the ever enthusiastic Gilad Berenstein, CEO and co-founder of Utrip, was keen to talk about how far his company, which launched in 2012, has come. "The power of AI today is that we can match up people's preferences with the inventory that has already been curated by TUI or by any of the partners we work with," he says.