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) …
Customization has long been a key element of the Bentley experience and now the luxury automaker is taking that to a new level with'adaptive music'. Developed in partnership with LifeScore, Bentley is the first company to apply this technology to a car, creating algorithms that use specific driving inputs to influence the type of music that is created. Music is sourced from a library of audio elements that have been recorded at Abbey Road Studios through 50 microphones in full sphere surround sound and more than 100 billion unique music tracks can be turned into a sixty-minute driving soundtrack. So how does it work exactly? Say you're driving through town, the system monitors this and creates a suitably calm soundtrack and once you've tapped into a sportier driving mode, the music becomes much more energetic, reading things like gear changes and acceleration to create the perfect audio complement to your driving style.
Artificial intelligence has been impacting greatly for the past few years and this is a very good topic to discuss. In the present era of digital marketing, one of the biggest trends is Artificial Intelligence (AI). In simple and understandable language, Artificial Intelligence is a kind of program training smart devices, computers, and robots to think and act like us humans. AI does not require any human interference to make any decision. It has been programmed in such a manner to make decisions on its own.
BRUSSELS, June 23 (Thomson Reuters Foundation) – From Swedish retailer H&M being fined 35 million euros ($42 million) for recording employees' private data to Britain's Barclays bank accused of spying on its staff, workplace surveillance has come into the spotlight in recent months. On Wednesday, the European Trade Union Institute (ETUI), the European Trade Union Confederation's research arm, said planned regulation by the European Union (EU) to improve privacy does not do enough to stop companies from snooping on their workers in the name of security and efficiency. As artificial intelligence (AI) technology becomes ever more accessible and sophisticated, here's why unions are worried: What kind of surveillance are we talking about? Employee monitoring today can involve software programmes for live monitoring, streaming and recording more than a dozen employees' computer screens at a time. Keystrokes, chat programmes, instant messaging and Skype dialogues may also be monitored and recorded in real time.
The exponential growth of data traffic in our digital age poses some real challenges on processing power. And with the advent of machine learning and AI in, for example, self-driving vehicles and speech recognition, the upward trend is set to continue. All this places a heavy burden on the ability of current computer processors to keep up with demand. Now, an international team of scientists has turned to light to tackle the problem. The researchers developed a new approach and architecture that combines processing and data storage onto a single chip by using light-based, or "photonic" processors, which are shown to surpass conventional electronic chips by processing information much more rapidly and in parallel.
As we noted at the beginning of this series on the AI bank of the future, disruptive AI technologies can dramatically improve banks' performance in four key areas: higher profits, at-scale personalization, smart omnichannel experiences, and rapid innovation cycles. The stakes could not be higher, and success requires a holistic transformation spanning all layers of the organization's capability stack. Our previous articles have focused on the capability stack's technology layers: reimagined engagement, 1 1. Leveraging these capabilities to create value requires an operating model combining structure, talent, culture, and ways of working to synchronize all layers of the stack. Synchronizing these layers is not easy. Any organization undertaking an AI-bank transformation must determine how to structure the organization so that its people interact and leverage tools and capabilities to deliver value for each customer at scale. In this article, we take a closer look at the need for a platform operating model, the categories and scope of operating models, and the building blocks of effective models.
The new normal has led organisations to rethink their approach towards digital transformation to ensure business resiliency, by achieving scale and creating democratised systems. When businesses embark on their digital transformation phase, they need to focus on reimagining their customer journeys by breaking the silos across various business functions. Technology facilitates real-time flow of data across the enterprise and enables faster decision-making. Organisations are leveraging AI in confluence with technologies like cloud, analytics, machine learning to transform themselves into a data-driven enterprise for efficient operations, scalability, improved customer experience, and innovative solutions. Skilling and reskilling the workforce to adapt to new models help in accelerating adoption and implementation.
Wind farms are now a reality in the U.S., heralding a new chapter in the country's sustainable energy production ambitions. But new technologies come with new challenges, and for offshore wind generation, inspection is one of the biggest. In much the same way as energy companies operate and maintain oil and gas subsea assets, wind farm cables, structural foundations, and all other components of the turbines need continuous monitoring and maintenance. That's dangerous work for humans, but it's a job tailor made for underwater robots and smart AI-powered analytics. Given the bright future and growing (albeit still small) footprint of offshore wind in the nation's energy power generation infrastructure, I reached out to Harry Turner, a machine learning specialist for Vaarst, a business driving the future of marine robotics, to discuss how robots and machine learning are changing the game for energy creation.