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) …
Several major classes of technology stand a good chance of changing healthcare as we know it. Home healthcare, in particular, could see tremendous benefits from digital breakthroughs like the Internet of Things, more advanced medical-minded wearables, blockchain and artificial intelligence. All of this tech is already finding a home in a variety of types of medicine -- let's take a look at how. If you follow the money, you'll find a lot of excitement in the healthcare wearables market -- 14.41 billion dollars' worth of excitement, in fact. That's how much this entire healthcare category is expected to be worth by the year 2022.
In scripted environments like video games, you can train an AI based on a limited number of pre-defined actions, reading the code of the game and in this kind of environment, machine learning algorithms can make decisions based on that. In open and non-scripted environment, things are a little bit more complicated. For example, in social media AI's have to deal with fake news, self-reported data, bots and so on. You can create algorithms that are smarter enough to recognize some of them, but, remember in this case you need a lot, I mean "A LOT" of computational power to run every calculation, so at the end of the day it's incredibly expensive and at the same time with a vast percentage of errors. Usually, the most useful AIs in open environments are made by the same Company that owns the platform, because they can read their scripts that they own servers are running every time users make specific actions, understanding the quality of data and how to use it as well.
SK Telecom and Deutsche Telekom will collaborate to create a new blockchain ID that will borderless, they said. SK Telecom and Deutsche Telekom will collaborate to create a blockchain ID with the aim to ease authentication processes, the companies have announced. The South Korean telco will sign an memorandum of understanding to that effect with its German counterpart's research arm, T-Labs, at the upcoming Mobile World Congress (MWC). The two will use blockchain technology to create a mobile digital ID that can be used for authentication, entry control, transactions, and contracts. The ultimately aim will be to make a "borderless" ID, much like a passport, that can used across different countries.
The story of data and analytics is one that keeps evolving; from appointing chief data officers to procuring the latest analytics software, business leaders are desperately trying to utilise it, but it's not easy. "The size, complexity, distributed nature of data, speed of action and the continuous intelligence required by digital business means that rigid and centralised architectures and tools break down," says Donald Feinberg, vice president and distinguished research analyst at Gartner. "The continued survival of any business will depend upon an agile, data-centric architecture that responds to the constant rate of change. But while business leaders have to tackle digital disruption by looking for the right services and technology to help streamline their data processes, unprecedented opportunities have also arisen. The sheer amount of data, combined with the increase of strong processing capabilities enabled by cloud technologies, means it's now possible to train and execute algorithms at the large scale necessary to finally realise the full potential of AI. According to Gartner, it's critical to gain a deeper understanding of the following top 10 technology trends fuelling that evolving story and prioritise them based on business value to stay ahead. Gartner says by 2020, augmented analytics will be the main selling point for analytics and BI solutions. Using machine learning and AI, augmented analytics is considered, by Gartner, as a disrupter in the data and analytics market because it will transform how analytics content in developed, consumed and shared. Augmented data management utilises machine learning capabilities and AI technology to make data management categories including data quality, master data management, metadata management, data integration as well as database management systems (DBMSs) self-configuring and self-tuning. According to Gartner, this is a big deal because it automates many of the manual tasks opening up opportunities for less technically skilled users to use data. It also helps highly skilled technical resources to focus on more value-adding tasks. Through to the end of 2022, manual tasks in data management will be cut by 45% thanks to ML and automated service-level management. Continues data is more than a new way to say real-time data. Instead, it's about a design pattern where real-time analytics are combined with business operations, processing current and historical data to prescribe actions in response to events. "Continuous intelligence represents a significant change in the job of the data and analytics team," says Rita Sallam, research vice president at Gartner. "It's a grand challenge -- and a grand opportunity -- for analytics and BI (business intelligence) teams to help businesses make smarter real-time decisions in 2019.
Change can be defined as taking the properties of a subject or object and transforming it to become different from what already exists. Whether change is big or small, it ultimately has lasting consequences that impacts society positively and negatively. Among the many domains change occurs in, technology is a prominent one that goes through trials of success and failure before becoming accepted by society. In the ever-changing technologically-driven world that we preside in today, nothing remains constant. As society takes strides to continually re-invent itself, industries must keep up in order to survive.
In discussions I've had with CIOs via my weekly #CIOChat sessions this year, the top 5 priorities are: And while there are differing opinions regarding the ownership of the analytics function, one thing is clear: CIOs need a better understanding regarding the potential for analytics and what is required to get data into a shape for their organization's data scientists. CIOs also need very clear mutual direction established with business leaders – in other words, what questions should be answered with data? Against this backdrop, "AI, Analytics, and New Machine Age" – published by Harvard Business Review earlier this month – is a timely, relevant compendium of HBR articles. The authors' insights should have value for CIOs and business people trying to use analytics in the running their businesses. Davenport contrasts the results obtained from large AI projects versus Robotic Process Automation (RPA).
Technology is presently evolving at such a rapid pace that yearly predictions of trends can seem to be obsolete before they even go live as a published article blog post. As technology evolves, it empowers much quicker change and progress, causing the increasing speed of the rate of change, until eventually, it will become exponential. The newest member community set up by CompTIA, the leading trade association for the global technology industry, is empowering the selection of new and emerging technologies to enhance business outcomes, however, in a rational, thoughtful way that makes sense for tech organizations and their customers alike. "It's an energizing time for innovation on numerous fronts," said Estelle Johannes, CompTIA's staff liaison to the Emerging Technology Community. Artificial Intelligence, or AI, has effectively received a ton of buzz in recent years, however, it keeps on to be a trend to watch since its consequences on how we live, work and play are just in the early stages.
"At its flagship technology conference Think 2019, Armonk-headquartered tech giant IBM is addressing the issue of hunger and will introduce scientists working on solutions to the global food crisis at the event, a report by the tech giant stated. The company will showcase how blockchain can prevent food from going to waste, how technology can map the microbiome of bad bacteria and how artificial intelligence-based micro sensors can detect food pathogens at home…"
Machine learning and AI are all about data. We give AI-powered systems massive amounts of data to ingest and analyze, and then we trust the results. But I want to know how we can ensure the integrity of those systems, from the algorithms to the data sources. I believe the issue of data integrity is a huge challenge for the AI community, both for users and developers. And I don't think we're looking at it closely enough.
The 2019 IBM Think Conference in San Francisco offered several glimpses at how the venerable technology company and its partners envision the future of advertising. With blockchain, artificial intelligence and more, IBM expects a more efficient market as it becomes easier to track the flow of ad dollars from brands to consumers and as consumers become easier to track across multiple devices and online identities. All of which is sprinkled with what CEO Ginni Rometty called "random acts of digital and AI." In January, IBM and Mediaocean rolled out an initiative for brands, agencies and publishers to better track their campaigns, expanding on a pilot program last summer. Although results won't be announced until the Cannes Lions festival in June, there was a lot of optimism at the conference.