Medb Corcoran, Ireland lead for Accenture Labs, talks about her career journey and why data skills will be critical for businesses going forward. As the Ireland lead for Accenture Labs, Medb Corcoran oversees a team of AI researchers that seeks to address critical business problems with tools such as machine learning, natural language processing and knowledge representation. This team is based at The Dock, Accenture's R&D and innovation centre in Dublin. Corcoran is also the company's global responsible AI lead for technology innovation, helping organisations integrate a data-driven assessment of algorithmic fairness into their processes. Here, she reflects on her career and why she believes workplaces of the future will rely on data skills like never before.

Car makers are recognizing the need for AI methods that consume less energy, which is one reason why neuromorphic computing can be beneficial, said Tim Shea, technology researcher at Accenture Labs. "They're already running up against limitations of [current chips] not being scalable enough," he said. German auto maker Mercedes-Benz AG announced last week it had joined the Intel Neuromorphic Research Community to explore how neuromorphic chips could help increase energy efficiency, speed and accuracy for vehicle-related AI uses. "With the knowledge we'll gain, we want to achieve a significant boost for our AI applications in and around our vehicles," said Jasmin Eichler, director of future technologies at Mercedes-Benz, in a statement. Intel's neuromorphic chips could begin selling commercially within five years, according to Mike Davies, director of Intel's Neuromorphic Computing Lab.

Fashion is a fast-changing industry where designs are refreshed at large scale every season. Moreover, it faces huge challenge of unsold inventory as not all designs appeal to customers. This puts designers under significant pressure. Firstly, they need to create innumerous fresh designs. Secondly, they need to create designs that appeal to customers. Although we see advancements in approaches to help designers analyzing consumers, often such insights are too many. Creating all possible designs with those insights is time consuming. In this paper, we propose a system of AI assistants that assists designers in their design journey. The proposed system assists designers in analyzing different selling/trending attributes of apparels. We propose two design generation assistants namely Apparel-Style-Merge and Apparel-Style-Transfer. Apparel-Style-Merge generates new designs by combining high level components of apparels whereas Apparel-Style-Transfer generates multiple customization of apparels by applying different styles, colors and patterns. We compose a new dataset, named DeepAttributeStyle, with fine-grained annotation of landmarks of different apparel components such as neck, sleeve etc. The proposed system is evaluated on a user group consisting of people with and without design background. Our evaluation result demonstrates that our approach generates high quality designs that can be easily used in fabrication. Moreover, the suggested designs aid to the designers creativity.

Neuromorphic chips are expected to be the predominant computing architecture for new, advanced forms of artificial-intelligence deployments by 2025, according to technology research firm Gartner Inc. By that year, Gartner predicts, the technology is expected to displace graphics processing units, one of the main computer chips used for AI systems, especially neural networks. Neural networks are used in speech recognition and understanding, as well as computer vision. With neuromorphic computing, it is possible to train machine-learning models using a fraction of the data it takes to train them on traditional computing hardware. That means the models learn similarly to the way human babies learn, by seeing an image or toy once and being able to recognize it forever, said Mike Davies, director of Intel's Neuromorphic Computing Lab.

No. 1 – Detecting abnormal travel expenses Most existing systems for reporting travel expenses apply pre-defined views, such as time period, service or employee group. While these systems aim to detect abnormal expenses systematically, they usually fail to explain why the claims singled out are judged to be abnormal. To address this lack of visibility into the context of abnormal travel expense claims, Accenture Labs designed and built a travel expenses system incorporating Explainable AI. By combining knowledge graph and machine learning technologies, the system delivers insight to explain any abnormal claims in real-time. No. 2 – Project risk management Most large companies manage hundreds, if not thousands, of projects every year across multiple vendors, clients and partners.

India, the second-most populous country in the world with over 1.2 billion people, boasts one of the fastest-growing economies bolstered by the youngest workforce in the world. While millions of dollars are spent every year on tackling malnutrition, 3,000 children die every day due to hunger. In a bid to combat this problem, Accenture Labs has teamed up with Akshaya Patra, the world's largest NGO-run mid-day meal program, to use disruptive technologies such as the blockchain, the Internet of Things (IoT) and artificial intelligence (AI) to boost the number of meals served to children in schools in India that are run and aided by the government. Since 2000, Akshaya Patra has been working toward reaching more children to provide them with wholesome food every single school day. When it first started it was serving 1,500 schoolchildren in five schools.

At first glance, the letter from the Delhi police commissioner's desk could have easily been dismissed as another routine laundry list of his department's "achievements" in the previous year. A closer look at the letter, written a little over two years ago, would have sprung a pleasant surprise in the context of the city police's technology prowess. The Delhi Police, according to the letter, had partnered with the Indian Space Research Organisation to implement CMAPS--Crime Mapping, Analytics and Predictive System--under the "Effective use of Space Technology-based Tools for Internal Security Scheme" initiated by Prime Minister Narendra Modi in 2014. CMAPS generates crime-reporting queries and has the capacity to identify crime hotspots by auto sweep on the Dial 100 database every 1-3 minutes, replacing a Delhi Police crime-mapping tool that involved manual gathering of data every 15 days. It performs trend analysis, compiles crime and criminal profiles and analyses the behaviour of suspected offenders--all with accompanying graphics.

Accenture Labs and Akshaya Patra Use Disruptive Technologies to Enhance Efficiency in Mid-Day Meal Program for School Children "Million Meals" project applied artificial intelligence, the Internet of Things and blockchain to drive efficiency and timeliness of lunch program in government schools across India BENGALURU, India; Apr. 20, 2017 – Accenture (NYSE: ACN) and Akshaya Patra, the world's largest NGO-run Mid-Day Meal Program, collaborated on an innovative project that used disruptive technologies to exponentially increase the number of meals served to children in schools in India that are run and aided by the government. The "Million Meals" project revolutionized Akshaya Patra's supply chain and operations, resulting in improved food quality and expanded service reach. Rooted in a vision to eliminate child hunger, the "Million Meals" project demonstrated how disruptive technologies such as artificial intelligence (AI), the Internet of Things (IoT) and blockchain can help address significant challenges in mass meal production and delivery. Accenture Labs, the research and development arm of Accenture, executed the project over a period of six months in Akshaya Patra's Bengaluru kitchen. An analysis of the project indicated a potential to improve efficiency by 20 percent, which could boost the number of meals served by millions.

"Million Meals" project applied artificial intelligence, the Internet of Things and blockchain to drive efficiency and timeliness of lunch program in government schools across India Accenture and Akshaya Patra, the world's largest NGO-run Mid-Day Meal Program, collaborated on an innovative project that used disruptive technologies to exponentially increase the number of meals served to children in schools in India that are run and aided by the government. The "Million Meals" project revolutionized Akshaya Patra's supply chain and operations, resulting in improved food quality and expanded service reach. Rooted in a vision to eliminate child hunger, the "Million Meals" project demonstrated how disruptive technologies such as artificial intelligence (AI), the Internet of Things (IoT) and blockchain can help address significant challenges in mass meal production and delivery. Accenture Labs, the research and development arm of Accenture, executed the project over a period of six months in Akshaya Patra's Bengaluru kitchen. An analysis of the project indicated a potential to improve efficiency by 20 percent, which could boost the number of meals served by millions.

MUMBAI: Accenture has entered into a joint research collaboration with IIT Bombay and IIT Patna focused on the different application aspects of Artificial Intelligence. The research, focused on IT services and social good, will look at augmenting software engineers with powerful Artificial Intelligence insights and recommendation for improved productivity. The focus areas of the program includes research in natural language processing, machine learning, neural network, virtual agents, deep learning and other areas of artificial intelligence. It will include software analytics - building, testing, managing and modernization of applications, solving real life social issues such as malnutrition, human trafficking, climate, etc. through prediction and recommendation models, using Artificial Intelligence. "One of the major areas that the research will focus on is natural language processing," said Pushpak Bhattacharyya, director, IIT Patna.