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) …
For the modern enterprise, services done well often drive growth. For example, quality IT infrastructure services and/or outsourced marketing can accelerate a company's competitive advantage in multiple ways. Although it's sometimes hard to measure the specific outcomes that services yield, they can have a major impact on a company's results, such as with more successful marketing campaigns, digital transformations, legal wins or other organizational efforts. That's why, in recent years, many Fortune 100 companies have significantly increased spend on service providers to meet competitive, productivity and business velocity demands. Companies can't hire and cultivate enough internal expertise as the work gets more sophisticated and specialized and the opportunities more global.
It's true, the recent advancements of narrow AI are mind-blowing: algorithms are beating humans in applications ranging from gaming to healthcare. But however'magical' these accomplishments may seem – especially when we retrospectively look back at what we thought AI would be able to do just a couple of years ago – this is far from the reality of the everyday work we do at Ericsson. For us, the'magic' of AI is making it work for us to make our everyday lives better and more efficient as a result. Now is the moment when AI goes from hype to reality. Already in our own industry we can see that AI is being embraced by service providers around the world.
The 3rd AI for Good Global Summit, a leading United Nation platform for multilateral dialogue on Artificial Intelligence (AI), was kicked off in Geneva, Switzerland, May 28-31. Bringing together over 1,200 interdisciplinary participants from 200 countries, the AI for Good Global Summit connects AI innovators with problem owners to identify practical applications of AI to accelerate process towards the United Nations Sustainable Development Goals (SDGs). Speakers from industry giants such as Microsoft, Google, Mastercard, IBM, Airbus, Siemens, Danone and Roland Berger were present at the Summit. "Zero Hunger" is one of the 17 UN SDGs expected to be achieved by 2030. According to the United Nations, up to 80% of food consumed in most developing countries are produced by smallholder farmers who, however, account for approximately 50% of the 815 million people suffering from hunger worldwide.
"Zero Hunger" is one of the 17 UN SDGs expected to be achieved by 2030. According to the United Nations, up to 80% of food consumed in most developing countries are produced by smallholder farmers who, however, account for approximately 50% of the 815 million people suffering from hunger worldwide. At the Summit's session on AI and Agriculture, Justin Gong, Co-founder and Vice President of XAG, together with other panel experts from Microsoft, Tata Group and Connecterra has proposed projects and initiatives to exploit new possibilities of AI technology to improve food security and end hunger. Artificial Intelligence, through continuously analysing massive data related to climate, lands, crop growing, etc., while automatically designing and optimising algorithms for decision-making, can help farmers diagnose plant diseases, predict natural disasters and employ appropriate resources to close the yield gap. At XAG, AI-powered intelligent devices such as drones and sensors have been leveraged to establish digital farming infrastructure in rural areas and enable precision agriculture which, for example, accurately target pesticides, seeds, fertilisers and water to wherever it is needed.
Over the last few decades, the telecom industry has rapidly shifted from basic phone and internet services to a far more evolved space featuring mobile, wearables and automation, making it one of the biggest businesses in the world currently and always upgrading to the cutting edge technology. According to IDC, 63.5% of telecommunications organizations are making new technology investments for AI systems. While having to be on the bleeding edge of technology is a good thing for customers and the competition. The industry itself is a great candidate for adopting AI driven solutions which offer the hope of reduced costs and increased efficiencies through automation. Needless to say, frontrunners have already started playing with AI solutions and deploying them across various business areas including customer-facing and internal processes.
The UK, which spends more than £2bn on video surveillance each year, is to mark National Surveillance Camera Day on 20 June as part of the National Surveillance Camera Strategy. The aim of the national event is to raise awareness about surveillance cameras and to encourage debate about the use of surveillance cameras in modern society by highlighting how they are used in practice, why they are used and who is using them. The initiative by the Surveillance Camera Commissioner (SCC) and the Centre for Research into Information, Surveillance and Privacy (Crisp) is also aimed at starting a nationwide conversation about how camera technology is evolving, especially around automatic face recognition and artificial intelligence (AI). The organisers hope that the resultant public debate will help inform policy-makers and service providers regarding societally acceptable surveillance practices and legitimacy for surveillance camera systems that are delivered in line with society's needs. As part of the initiative, the SCC is encouraging surveillance camera control centres to throw their "doors open" so that the public can see how they operate.
Decision-makers should reflect on several key points when assessing a conversational artificial intelligence (AI) solution. As an example, many millennials favor connecting with brands through live chat. The millennial population could be worth up to $24 trillion by 2020, making them one of the largest expected consumer groups over the next decade. What's more, 59-percent of those consumers will leave a review about their experience – either positive or negative – with a majority of judgment based on quick responses when they reach out to brands for help or information. Although a challenge, C-suite executives and companies need not worry as conversational AI has proven to be a reliable and quick solution for appeasing millennial consumers.
Similar to the growth in the number of vehicles in an urban area, the number of aircraft and the passengers they ferry, are in a phase of constant growth. Globally, the number of aircraft is expected to double from the base year of 2015 up to 2035. Since there are only limited number of airports and limited amount of space in each airport, this implies that each aircraft movement on the ground needs to be efficiently handled for faster turnaround. Faced with the pressure of managing multiple cost heads, airlines are now outsourcing their airport ground handling and cargo management services to specialist companies, and focusing on their core competence. While growth trends in passenger volumes tend to follow macroeconomic fundamentals, the growth in aircraft turnarounds are more immune to such highs and lows.
Automatic service composition in mobile and pervasive computing faces many challenges due to the complex and highly dynamic nature of the environment. Common approaches consider service composition as a decision problem whose solution is usually addressed from optimization perspectives which are not feasible in practice due to the intractability of the problem, limited computational resources of smart devices, service host's mobility, and time constraints to tailor composition plans. Thus, our main contribution is the development of a cognitively-inspired agent-based service composition model focused on bounded rationality rather than optimality, which allows the system to compensate for limited resources by selectively filtering out continuous streams of data. Our approach exhibits features such as distributedness, modularity, emergent global functionality, and robustness, which endow it with capabilities to perform decentralized service composition by orchestrating manifold service providers and conflicting goals from multiple users. The evaluation of our approach shows promising results when compared against state-of-the-art service composition models.
One can argue that even the most innovative banking institutions are bureaucratic enough, and their slow decision-making causing banks to lose their premium over fintech applications, peer to peer lending marketplaces, and payment processors. At the same time, many expanded into the business of micro-lending. Banking services are no longer a monopoly of banks, and traditional financial institutions have to innovate in order to survive. The era of non-traditional financial services providers such as Amazon Payments, PayPal Payments and PayU, has risen. The launch of the Payment Services Directive II in Europe unlocks new dynamics for FinTech and Payment Services.