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) …
The fight against fraud has always been a messy business, but it's especially grisly in the digital age. To keep ahead of the cybercriminals, investment in technology – particularly artificial intelligence – is paramount, says Ajay Bhalla, president of cyber and intelligence solutions at Mastercard. Since the opening salvo of the coronavirus crisis, cybercriminals have launched increasingly sophisticated attacks across a multitude of channels, taking advantage of heightened emotions and poor online security. Some £1.26 billion was lost to financial fraud in the UK in 2020, according to UK Finance, a trade association, while there was a 43% year-on-year explosion in internet banking fraud losses. The banking industry managed to stop some £1.6 billion of fraud over the course of the year, equivalent to £6.73 in every £10 of attempted fraud.
Supply chain management has become a vital strategic opportunity to keep organizations competitive and this statement has taken even more precedence due to the current pandemic situation that the world is facing. The Covid-19 pandemic has resulted in some sort of supply chain disruption related to transportation restrictions created by the lockdown and the economic impact caused by it will be felt for months to come. But at the same time, there has been a sudden increase in the adoption of digital technologies like algorithm development, data analytics, artificial intelligence, machine learning, the internet of things, and cloud computing to make supply chain management ever-evolving. Artificial Intelligence with the help of automated technology processes a large amount of data within few minutes to provide business-based insightful information. AI is already beginning to change the face of the supply chain industry.
Life can come at you in unpredictable ways, and having yourself safely insured is always a smart investment plan. The core of any insurance plan is to provide you with protection. Making small investments in insurance can provide you with financial security in advance. Now, with technological advancements and messaging platforms growing popular, the insurance sector has seen a significant surge in the way it has been running all along. Insurance is a data-driven sector and in the last many years, data corruption has been a persistent problem in this sector.
Bias and ethics in artificial intelligence have captured the attention of the public and some organizations following some high-profile examples of it at work. For instance, there has been work that has demonstrated bias against darker skinned and female individuals in face recognition technology and a secret AI recruiting tool at Amazon that showed bias against women, among many other examples. But when it comes to looking inside at our own houses -- or businesses -- we may not be very far along in prioritizing AI ethics or taking measures to mitigate bias in algorithms. According to a new report from FICO, a global analytics software firm, 65% of C-level analytics and data executives surveyed said that their company cannot explain how specific AI model decisions or predictions are made, and 73% have struggled to get broader executive support for prioritizing AI ethics and responsible AI practices. Only 20% actively monitor their models in production for fairness and ethics.
These days, the task of marketing your business must include a huge digital component as the world increasingly transitions to online from real interactions. For most modern businesses, budgets demonstrate the transition to digital. For instance, digital ad spending increased by 12% in 2020, despite the pandemic. No business can afford to ignore the digital landscape and e-commerce these days. So if you're looking for ways to upgrade your digital marketing for 2021 to take advantage of recent changes, you're in the right place.
In this article, I describe the various steps involved in managing a machine learning process from beginning to end. Depending on which company you work for, you may or may not be involved in all the steps. In larger companies, you typically focus on one or two specialized aspects of a project. In small companies, you may be involved in all the steps. Here the focus is on large projects, such as developing a taxonomy, as opposed to ad-hoc or one-time analyses.
Several recent surveys show that more than 80% of consumers prefer spending with a credit card over cash. Thanks to advances in AI and machine learning (ML), credit card fraud can be detected quickly, which makes credit cards one of the safest and easiest payment methods to use. The challenge with cards, however, is that in some countries when fraud is suspected the credit card is blocked immediately, which leaves the cardholder without a reason as to why, how, or when. Depending on the situation, it can take anywhere from a few hours to days until the customer is notified and even longer to resolve. With Amazon Connect, a cardholder can be notified immediately of a suspected card fraud and interactively verify if the suspected transactions were indeed fraudulent over the phone.
Many Fortune 500 companies - perhaps as many as 20 percent of them - may not survive this year, Forrester Research has predicted. As companies transition to a post-pandemic recovery, savvy CIOs understand that their organizations must continue to accelerate intelligent automation initiatives to thrive in the new digital-first era. Most are looking to remain digital-first even as the crisis dissipates. According to a recent Statista report, spending on the technologies and services that enable digital transformation worldwide is expected to amount to $2.3 trillion. How do CIOs maintain momentum and ensure they have a sustainable digital-first strategy in place to meet new customer expectations post-pandemic? The digital transformation journey starts with prioritizing where to focus and invest in order to build your digital-first landscape.
The Covid-19 pandemic was devastating for many industries, but it only accelerated the use of artificial intelligence across the U.S. economy. Amid the crisis, companies scrambled to create new services for remote workers and students, beef up online shopping and dining options, make customer call centers more efficient and speed development of important new drugs. Even as applications of machine learning and perception platforms become commonplace, a thick layer of hype and fuzzy jargon clings to AI-enabled software.That makes it tough to identify the most compelling companies in the space--especially those finding new ways to use AI that create value by making humans more efficient, not redundant. With this in mind, Forbes has partnered with venture firms Sequoia Capital and Meritech Capital to create our third annual AI 50, a list of private, promising North American companies that are using artificial intelligence in ways that are fundamental to their operations. To be considered, businesses must be privately-held and utilizing machine learning (where systems learn from data to improve on tasks), natural language processing (which enables programs to "understand" written or spoken language) or computer vision (which relates to how machines "see"). AI companies incubated at, largely funded through or acquired by large tech, manufacturing or industrial firms aren't eligible for consideration. Our list was compiled through a submission process open to any AI company in the U.S. and Canada. The application asked companies to provide details on their technology, business model, customers and financials like funding, valuation and revenue history (companies had the option to submit information confidentially, to encourage greater transparency). Forbes received several hundred entries, of which nearly 400 qualified for consideration. From there, our data partners applied an algorithm to identify 100 companies with the highest quantitative scores--and that also made diversity a priority. Next, a panel of expert AI judges evaluated the finalists to find the 50 most compelling companies (they were precluded from judging companies in which they have a vested interest). Among trends this year are what Sequoia Capital's Konstantine Buhler calls AI workbench companies--building of platforms tailored to different enterprises, including Dataiku, DataRobot Domino Data and Databricks.
If there is to be a "6G Wireless," its proponents will need to learn some significant lessons from the era of 5G. Already, 5G Wireless as a market strategy is four years old. The R&D divisions of telecommunications firms whose 5G rollouts are well under way, are now looking ahead to whatever the next version of wireless may be. . . So far, what they're seeing may be a bit far out. It's a capital improvement project the size of the entire planet, replacing one wireless architecture created this century with another one that aims to lower energy consumption and maintenance costs. "6G must deliver an outcome that is aligned with real needs," remarked David Lister, Head of 6G Research and Development Technology at Europe's Vodafone Group, "and deliver outcomes that are sustainable and commercially driven." Lister was speaking at an annual conference called the 6G Symposium. Yes, there is already an annual 6G Symposium. Back in 1998, the leading stakeholders in global telecommunications formed the 3GPP consortium, to officially designate which technologies belong to a "G" and which don't.