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) …
Netradyne's advanced artificial intelligence and machine learning technologies are creating deep driver, vehicle and environmental analysis; yielding unique opportunities to create efficiencies in risk identification, data trend analysis and timely payment of insurance claims. Their robust commercial fleet platform currently captures and analyzes several million driving miles each month and Willis' expertise will allow the company to turn this insightful data into comprehensive offerings insurance companies can use to underwrite and analyze professional drivers across the country. In parallel, Willis will support customers who are actively reducing fleet risk by managing relationships with insurance carriers to provide evidence of improvement. He will also foster relationships with captive program managers to help drive fleet sales growth. "Netradyne is experiencing explosive growth, with new avenues and uses for our technology approach coming to life every day.
Artificial intelligence is not about robots taking over the world, but about leveraging the powerful technology to capture and analyse vast quantities of data, and making the best use of that information. That--s the belief of Noel Pearman, Bermuda professional lines underwriter and cyber product lead at XL Catlin, who has been speaking on the subject in the US. For the insurance sector, one likely manifestation of AI will see customers purchase increasingly tailored policies based on data directly relevant to the way they live their lives. Mr Pearman explained: --One of the things we are doing now is capturing data at a rate that we were never able to do before.-- The prevalence of --The Internet of Things-- devices that collect real-time data will allow insurance companies to mine information and offer better rates to customers whose behaviours represent a lower risk, such as those with better driving habits.
BOULDER, Colo.--(BUSINESS WIRE)--Artificial intelligence (AI) has worked its way into a variety of industries, from the obvious (autonomous vehicles) to the hidden (anti-money laundering due diligence). But according to a new report from Tractica, while organizations are clearly recognizing the value associated with incorporating AI into their business processes, they are also encountering a number of challenges with integrating this new intelligence into operational processes. Taking AI beyond the proof-of-concept phase to the enterprise scale will require a significant level of professional services to support large implementations, with key service categories including application integration, support and maintenance, training, customization, and installation. Tractica forecasts that the worldwide market for AI services will grow from $10.1 billion in 2017 to $188.3 billion by 2025. The market intelligence firm anticipates that the industry sectors using the highest levels of professional services to support AI deployments will include business services, consumer, healthcare, advertising, and automotive.
The value that can be extracted from a growing wealth of data across boundless sectors is only just beginning to be grasped. If you look at search engines or digital commerce platforms, an almost direct relationship exists between the amount of data users willingly give up and the value this has. There is also the fact that those with the most data at their disposal will probably have the best artificial intelligence in the future, making them nigh on invincible. In finance, data of one sort or another has always held intrinsic value. People who trade in the zero-sum game of capital markets all need a Bloomberg terminal or Thomson Reuters data to have a look at all the traditional price information, earnings estimates and so on.
When Trevor McFedries set out last year to raise money for Brud, his robotics and artificial intelligence start-up, he found himself in many meetings with "a ton of white guy" venture capitalists. So Mr. McFedries, who is black, and his co-founder, Sara DeCou, a Latino woman, added a condition for investors: The pair would accept money only from venture firms that had a woman or a person of color in a position to write them a check. "It was counterintuitive for us to raise money from a bunch of white guys who want to extract all the value from the world," said Mr. McFedries, who eventually collected several million dollars from firms that met the condition. "We're interested in reshaping the way that tech looks." Mr. McFedries is one of more than 400 tech entrepreneurs and chief executives who have now banded together, in a loose coalition known as Founders for Change, to pressure the venture capital industry to diversify its ranks.
KT will apply its artificial intelligence technologies to insurance and health care services in partnership with Lina Life Insurance, the mobile carrier said Tuesday. The two companies signed a memorandum of understanding Monday to improve Lina's digital health care services by adding KT's AI platform technologies at the insurer's headquarters in central Seoul. Under the agreement, KT's AI GiGA Genie speaker will offer users informative health care content insurance services provided by Lina, including dental care tips for kids, descriptions of medial terms and insurance bills. There are more than 600,000 GiGA Genie users as of this month, according to KT. Benjamin Hong, CEO of Lina Life Insurance (left), poses with Koo Hyun-mo, president of KT's corporate planning group after signing a MOU on artificial intelligence cooperation at Lina's head office in central Seoul on Monday. KT will also provide speech-to-text conversion and text analysis technologies to the insurer to help improve the company's call center system for customers.
ARTIFICIAL intelligence (AI) has already changed some activities, including parts of finance like fraud prevention, but not yet fund management and stock-picking. That seems odd: machine learning, a subset of AI that excels at finding patterns and making predictions using reams of data, looks like an ideal tool for the business. In San Francisco, however, where machine learning is so much part of the furniture the term features unexplained on roadside billboards, a cluster of upstart hedge funds has sprung up in order to exploit these techniques. These new hedgies are modest enough to concede some of their competitors' points. Left to their own devices, machine-learning techniques are prone to "overfit", ie, to finding peculiar patterns in the data.
The warning stirs distant memories of the recessionary year 2008 and the Dotcom bust a few years earlier. So many companies, from startups to one-time Blue Chips, laid off thousands of workers or simply disappeared through bankruptcy or acquisition. Their IT teams, entrenched in dated technologies, went from unemployed to unemployable. Could something similar happen in the near future? David Foote says that is a real possibility, but that there is an opportunity for companies and IT professionals to change their paths.
Tokyo Stock Exchange operator Japan Exchange Group Inc. said Monday it has introduced artificial intelligence systems aimed at detecting market price manipulations and other misconduct. According to Japan Exchange Regulation, the group's self-regulatory body, the AI systems are designed to conduct preliminary surveillance to identify suspicious transactions. Surveillance personnel will analyze the results closely to determine whether the transactions should be reported to financial authorities. The AI systems are designed to help improve the quality of overall surveillance and speed up preliminary probes, giving staff more time to closely examine suspicious transactions, an executive of the self-regulatory body said. The group began research in August 2015 to see whether AI could be used for any of its operations, and later confirmed that systems developed by NEC Corp. and Hitachi Ltd. can detect unfair transactions with high accuracy.
S&P Global plans to buy machine-learning, analytics and artificial intelligence provider Kensho Technologies for about $550 million to boost its emerging fintech capabilities. The news comes just two weeks after the data, ratings and benchmarks provider said it was acquiring Panjiva, a fintech firm that uses technology to mine large, unstructured datasets tied to the global supply chain. "In just a short amount of time, Kensho's intuitive platforms, sophisticated algorithms, and machine-learning capabilities have established a wide following throughout Wall Street and the technology world," said S&P Global President & CEO Douglas Peterson, in a statement. "Via this acquisition, S&P Global is demonstrating a strong commitment to not just participating in the fintech evolution, but leading it," Peterson explained. S&P Global, which issues ratings, benchmarks and other data to capital and commodity markets, launched a Fintech Venture Investment program and also invested in several fintech companies last year: Kensho, Algomi of London and Ursa Space Systems, an alternative data technology company.