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) …
Robot-led automation has the potential to transform today's workplace as dramatically as the machines of the Industrial Revolution changed the factory floor. Both Robotic Process Automation (RPA) and Intelligent Automation (IA) have the potential to make business processes smarter and more efficient, in very different ways. Both have significant advantages over traditional IT implementations. Robotic process automation tools are best suited for processes with repeatable, predictable interactions with IT applications. These processes typically lack the scale or value to warrant automation via IT transformation.
Deloitte announced a collaboration today with Automation Anywhere to drive further adoption of cloud deployments on Automation 360, the first cloud-native, AI-powered robotic process automation (RPA) platform. Deloitte will combine its leading capabilities in cloud infrastructure and automation to provide a first-of-its-kind solution that enables a successful migration of client automations to the cloud, helping organizations accelerate the rate and delivery of business performance while effectively limiting costs. Mutual customers, both first-time RPA and existing Automation Anywhere users, will experience a smooth transition to the cloud platform with Deloitte's migration as a service capabilities. "The need for digital transformation is more prevalent than ever as organizations continue to navigate the effects of the pandemic and pivot to cloud-based solutions that can seamlessly integrate with their existing systems," said Douglas Williams, managing director, Deloitte Consulting LLP. "Our solutions are designed for Automation 360 to help customers through the migration process to get the most value out of their RPA investment with minimal disruption, all while finding efficiencies and reducing investment costs."
Engineers and computer scientists spent decades perfecting computers' abilities to solve classical math and logic problems. But as it would turn out, a huge set of real-world decision-making isn't readily framed as a tidy math problem. Machine learning (ML) earns its paycheck in these kinds of situations: When we're unable to logically or cost-effectively use math to tell a computer what to do, we can use ML to teach a computer what to do by showing it examples of how it's been done. This current AI/ML "Cambrian explosion" is resulting in a radical rethink of what computers can realistically learn. Startups and incumbents alike are teaching machines to emulate an ever-increasing share of capabilities once thought of as "uniquely human." Other frontiers of AI advancement include sensation and discernment (the five "senses"); creativity (reading, writing, and the arts); and congeniality (emotional intelligence).
PwC announced that it was cited as a Leader in The Forrester Wave: AI Consultancies, Q1 2021. In the report, Forrester notes that "AI consultancy customers should look for providers that: Commenting on PwC, the report states that: "The PwC backstory has two facets -- client transformations and its own. PwC helps transform client businesses, but its own transformation is part of its story. PwC doubled down on its own upskilling and IP-building platform and then launched this for clients. One-off simulation projects are now scaled offerings for strategic planning, operations, and continuous scaling of business models. Even strategic innovation partnerships are points of excellence; one client specifically selected PwC because of the consultancy's relationship with Carnegie Mellon."
I joined the Technology Research & Development team from Advanced Technology & Architecture where I was the global lead for Emerging Technology. I have held several global leadership roles within our technology group for Application Portfolio Optimization and SOA/Integration Architecture. I have worked at the leading edge of technology, notably in voice recognition, knowledge-based systems and neural networks.
The AI industry is playing a dangerous game right now in its embrace of a new generation of citizen developers. On the one hand, AI solution providers, consultants, and others are talking a good talk around "responsible AI." But they're also encouraging a new generation of nontraditional developers to build deep learning, machine learning, natural language processing, and other intelligence into practically everything. A cynic might argue that this attention to responsible uses of technology is the AI industry's attempt to defuse calls for greater regulation. Of course, nobody expects vendors to police how their customers use their products.
Apple's been on a shopping spree in a bid to make Siri smarter, according to a new report by GlobalData. The market research firm says the tech giant bought more AI companies than anyone else between 2016 and 2020. The second biggest AI acquirer was Irish consultancy Accenture. But the rest of the top five were all based in the US. Google grabbed the third spot on the list, followed by Microsoft and Facebook.
Artificial Intelligence has come of age. The "Age of WithTM," where humans and machines work together, is upon us. Our ability to connect, collaborate, and innovate is creating remarkable new possibilities for businesses and the society, at large. And though AI has become ubiquitous in many ways--guiding strategies, improving processes, shaping business models, rethinking customer experiences, and even finding cures--we are only scratching the surface of what it can do. The power of automation and AI lies in re-imagining the way we do things.
An unknown number of people around the world are earning income by working through online labour platforms such as Upwork and Amazon Mechanical Turk. We combine data collected from various sources to build a data-driven assessment of the number of such online workers (also known as online freelancers) globally. Our headline estimate is that there are 163 million freelancer profiles registered on online labour platforms globally. Approximately 19 million of them have obtained work through the platform at least once, and 5 million have completed at least 10 projects or earned at least $1000. These numbers suggest a substantial growth from 2015 in registered worker accounts, but much less growth in amount of work completed by workers. Our results indicate that online freelancing represents a non-trivial segment of labour today, but one that is spread thinly across countries and sectors.
Establish a solid data foundation: Achieved through an agile data supply chain with cloud-based and scalable platforms. Such a foundation helped one of our clients realize a 40 percent increase in conversion rates for new lending products--this was over and above the industry benchmarks. Ensure data is secure, relevant and trustworthy: Accomplished through robust data governance, metadata management and data veracity solutions. This is enabled by machine learning (ML) or artificial intelligence (AI) technologies, right people structures and processes. According to our research, only a third of firms trusted their data enough to use it effectively and derive value from it.