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Chatbots are a buzz-worthy topic for all organizations, including credit unions. Members can interact with chatbots in the digital channels they use regularly, like messaging apps and smart speakers, to receive personalized service and support. Chatbots can help fulfill common tasks like verifying account balances, paying bills, and transferring funds between accounts without having to speak with a member service representative. Implementing a chatbot can provide a custom-tailored experience for members while streamlining internal operations for credit unions.Although chatbots are designed to be user-friendly and intuitive, understanding how they work can be a challenge. There’s complex technology running behind the scenes that make chatbot interactions so effortless. You may have heard terms like artificial intelligence, natural language processing, and machine learning in relationship to chatbots. What do these terms mean and how do they come together to create a chatbot? Here’s a shortlist of chatbot-related terminology to help get you started. CHATBOT – A chatbot is a computer program that’s designed to simulate a two-way conversation with another human. Chatbots rely on text input (for example, a user typing a question and submitting it to a chatbot via Facebook Messenger) or speech input (for example, a user initiating a chatbot conversation with voice commands via a smart speaker like Amazon Alexa). For credit unions, chatbots can be an automated means of interacting with members to answer questions and deliver service around the clock. VIRTUAL ASSISTANT – A chatbot might seem similar to a virtual assistant, but they are two different technologies. Virtual assistants (Apple’s Siri, for example) perform simple task completion like checking the weather or locating the nearest restaurant. Although virtual assistants make use of some aspects of artificial intelligence, they aren’t a chatbot because they’re focused on task completion rather than two-way conversation. Another key distinction is that chatbots can chain together several different instructions to achieve goals while virtual assistants typically do not. ARTIFICIAL INTELLIGENCE (AI) – AI allows a computer program to complete tasks that would otherwise require human intervention. For example, facial recognition once required both cameras and human beings to make positive identifications. Computer programs now perform this task quickly and at scale by digitizing facial characteristics to find matches. Another example is language translation. Translation programs powered by AI can now translate speech in real time to break down barriers in interpersonal communication. MACHINE LEARNING (ML) – ML is a subset of AI that allows computer systems to learn and improve from experience without direct programming. The technology allows programs to learn from what they do successfully as well as from the mistakes they make, giving them the ability to grow without explicit intervention from a programmer. NATURAL LANGUAGE PROCESSING (NLP) – NLP is a subset of computer science that’s focused on the interaction between computer programs and human languages. NLP combines with ML and AI to understand commands submitted by a human in their own language. Using bill payments as an example, a member might ask a similar question in many ways. For instance, “What do I owe this month?” “What is my current bill?” “How much is my balance?” “What do I need to pay?” These questions are all worded differently, but the intention behind them is the same. NLP helps computer systems understand that, although each question is unique, all should yield the same answer. 1SHARESShareShareSharePrintMailGooglePinterestDiggRedditStumbleuponDeliciousBufferTumblr,Alison Arthur Alison creates timely product marketing and thought leadership content that keeps Alacriti’s community informed on the latest developments in billing and payments technology. With a background in payments and financial … Web: https://www.alacriti.com Details AI, ML, and NLP all combine to form the heart of a chatbot. What are some of the specific benefits that a chatbot can deliver to your credit union? Watch our webinar recording to learn more. read more
By Joshua SchneyerNEW YORK,(Reuters)-Karolina Pliskova suffered a narrow U.S. Open defeat at the hands of Angelique Kerber on Saturday, but the Czech 10th seed also proved her mettle as one of the most dangerous attacking players in women’s tennis.The 6-foot 1-inch (185 cm) Pliskova fought back from a set down at Arthur Ashe Stadium to give Kerber, one of the best defensive players in history, a major scare in the grand slam final. Kerber finally prevailed 6-3 4-6 6-4.Kerber will move to the number one world ranking on Monday.That in part is due to 24-year-old Pliskova’s previous win. She felled top seeded American Serena Williams in straight sets in the semi-finals, and took down sister Venus Williams earlier in the tournament.For Pliskova, making the final was the best showing of her five year professional career. Ranked No. 11 in the world, she had not previously advanced beyond the third round of a grand slam.Kerber’s win ended an 11-match winning streak for the big-serving Pliskova, who had beaten the German just three weeks earlier in the Cincinnati final.Pliskova said she hopes it will be the first of many slams finals.“I found out I can play my best tennis on these big courts,” she told reporters. “I believe I can win matches like this next time.”Though Pliskova prefers blistering ground strokes to the serve-and-volley game that defined past Czech champions such as Martina Navratilova and Helena Sukova, her serve remains her biggest weapon.She has crushed more aces than any other player on the WTA tour this year, but on Saturday that weapon was not quite enough.In the muggy air at Flushing Meadows, the average speed of her first serve, 102 miles-per-hour (164 kph), was her slowest of the tournament.Although Pliskova won 80 percent of her serve and volley points, she deployed the tactic only ten times.Against the fierce counter-punching German, Pliskova said she had to try everything in her toolbox to take control of points.She made 47 unforced errors, against just 17 for Kerber, but on the other side of the equation hit nearly twice as many winners, 40 to the German’s 21.“You know, it’s never easy for the player who is attacking and is doing more mistakes,” Pliskova said.The Czech player could become a constant threat to other top women, said Mary Jo Fernandez, a former world number four and a well known tennis commentator.“She’s really grown as a player,“ Fernandez said. “I don’t think Serena’s going anywhere but it gets more difficult as the younger players come up.” read more
A 20-year-old Stabroek Market vendor of D’Urban Street, Lodge, Georgetown, was on Friday brought before the courts where he faced a murder charge in connection with the shooting death of a Bourda Market cheese vendor.Chief Magistrate Ann McLennan read the charge to Nya John, which stated that on August 15, 2018 at Robb Street, Bourda, Georgetown, he murdered Troy Ramalho.John was represented by Attorney George Thomas. The case will continue on January 18, 2019.John’s two alleged accomplices – Akeem Morris and George Paton – were also charged for the murder of Ramalho.According to Police, on the day of the incident, the now dead man had already packed up his stall and was awaiting transportation to take him home. However, he was confronted by three gun-toting bandits, who held him at gunpoint and demanded that he hand over cash and other valuables.Ramalho allegedly refused to comply with the bandits’ demands, and one of the armed men discharged a round that hit the vendor to his chest.As he fell to the ground, the two other men relieved him of his valuables and made good their escape. It was reported that the incident happened in plain sight of two on-duty City Constables.The deceased was rushed to the Georgetown Public Hospital Cooperation where he died while receiving medical attention. read more
The next goal would come at 8:32 remaining in the period, as Chase London would score a goal, with a double assist from Justin Brownlee and Thomas Loewen, making the Trackers’ score 2-0 over Peace River. By the end of the second frame, the score would be 7-2 in favour of the Trackers. Throughout the period, the Trackers would manage to score a total of five goals on the Royals.Advertisement There would be no more scoring throughout the remainder of the game, so the Trackers would win the game 7-2 over the Royals. FORT ST. JOHN, B.C. – The Northeast B.C. Yukon Midget Trackers were home on Sunday, December 15, as they were host to the Peace River Royals. – Advertisement -Then with 7:44 left in the period, the Royals would score a goal on the Trackers which would make the score 2-1 as they headed into the second frame. In the second period, a lot of action would take place as the Trackers would begin to go on a strong scoring streak. At 9:32 into the game, Connor Brown would score on the Royals, with assists by Kurtis Lee and Kaden Arberry, making the score 1-0. Up next, the Trackers are on the road this coming weekend, December 20 to the 22, as they get three more games in before the Christmas break. read more