One goal of AI work in natural language is to enable communication between people and computers without resorting to memorization of complex commands and procedures. Automatic translation – enabling scientists, business people and just plain folks to interact easily with people around the world – is another goal. Both are just part of the broad field of AI and natural language, along with the cognitive science aspect of using computers to study how humans understand language.
Artificial Intelligence and Machine Learning (AI & ML) and Sentiment Analysis are said to "predict the future through analysing the past" – the Holy Grail of the finance sector. They can replicate cognitive decisions made by humans yet avoid the behavioural biases inherent in humans. Processing news data and social media data and classifying (market) sentiment and how it impacts Financial Markets is a growing area of research. The field has recently progressed further with many new "alternative" data sources, such as email receipts, credit/debit card transactions, weather, geo-location, satellite data, Twitter, Micro-blogs and search engine results. AI & ML are gaining adoption in the financial services industry especially in the context of compliance, investment decisions and risk management.
Before building and deploying chatbots, there are some basic practices to follow in separating your chatbot from the others in the market. Fortunately for business owners, launching a quality Chatbot isn't hard, as long as you follow the guidelines below. Before thinking about adopting a chatbot for your business, you should first understand why individuals might want to converse with chatbots rather than a real human being. Whether you are planning to deploy a chatbot for customer support on your website or creating a lead capturing bot, it's time to read the guidelines of Chatbot design and development. The below-compiled guide will help you in building a Chatbot that's engaging and effective enough to drive 4X growth for your business.
Australian IBM cybersecurity engineers have developed an artificial intelligence (AI) system to analyse network connections and employee communications at an enterprise scale. The model detects changes in users' behaviour and can automatically triggers investigations even if the changes occur across multiple platforms. IBM research found the root cause for 52 per cent of data breaches in Australia was malicious or criminal attacks which often use methods like phishing and social engineering. The new IBM solution, developed in the company's Gold Coast cybersecurity lab as part of a hackathon, uses AI to monitor changes in employee behaviour and flags indicators of compromise. It was debuted to the industry at last week's Australian Cyber Conference in Melbourne as a way of showing what can be done but the solution is not something that can be bought directly from IBM. Currently known as "QRadar Insider Threat Detector with Watson" it uses IBM's AI model, Watson, to analyse user generated content – like emails, Word documents, and Slack messages – to detect both the tone of content and employees' typical behaviour or "personalities".
Artificial Intelligence (AI) is already re-configuring the world in conspicuous ways. Data drives our global digital ecosystem, and AI technologies reveal patterns in data. Smartphones, smart homes, and smart cities influence how we live and interact, and AI systems are increasingly involved in recruitment decisions, medical diagnoses, and judicial verdicts. Whether this scenario is utopian or dystopian depends on your perspective. The potential risks of AI are enumerated repeatedly.
There's a real contender emerging in the digital marketing arena and it's threatening to put the reigning champion, the Email Drip Campaign down for the count. With the release of Facebook chatbots back in 2016, marketers began to realize the awesome potential of chatbot funnels to transform the way we market to our target audiences. Email drip campaigns present problems in delivering targeted content to consumers that chatbot funnels seamlessly address. Chatbots are AI-driven programs that allow marketers to automate customer interactions, nurturing leads through the marketing funnel without any actual human intervention. Another benefit of AI chatbots sure to bring email drips to their collective knees is that they--much like human salespeople--organically learn and evolve with each interaction, that is, they build upon each previous interaction, improving their ability to interact naturally with customers and to address customer needs with each and every conversation.
Artificial intelligence (AI) is rarely out of the headlines these days, due in large part to a steady stream of controversies from many of the major tech players. Facial recognition software is increasingly permeating society without much regard for ethics or accuracy. And crashes and near-misses blighted the recent launch of Tesla's new Smart Summon feature, which allows drivers -- in theory -- to remotely beckon their vehicle in parking lots. There is a strong case for the suggestion that AI, in its current form at least, is more artificial stupidity than anything else. Nonetheless, AI is here and here to stay.
What have been the highs and lows so far? Have you moved the needle on CSAT scores and NPS? Has the customer experience fundamentally improved? But perhaps more importantly: did you get that chatbot up-and-running? After all, Gartner made some bold predictions. In 2018, it was that over 50 percent of medium to large enterprises will have deployed them by 2020.
Spooky jokes, eerie noises, and popular costume ideas--if you're looking for help celebrating Halloween on Thursday, Oct. 31, your smart speaker has your back. We've rounded up some of the top skills and ways Alexa and Google Assistant help you celebrate the creepiest day of the year. To enable these Halloween skills on your Echo, open the Amazon Alexa app, which is available for download on iOS and Android devices, tap "Skills and Games" in the menu, and search for the skill you want. For Google Home, you can find these actions in the Google Assistant app, which is also available for iOS and Android devices. From recipes ideas to trivia games, here are eight ways Alexa and Google Assistant can help you celebrate Halloween.
Chitchat dialogue is a very difficult NLP task to master. However, creating a dialogue system (chatbot) with a simple LSTM Seq2Seq model with controls can deliver relatively good performance. Below, we've deployed a chatbot with two control features (conditional training [CT] and weighted decoding [WD] in order to control four attributes in chitchat dialogue: repetition, specificity, response-relatedness and question-asking. The chatbot leverages a baseline twitter dataset that was fine-tuned on the PersonaChat ConvAI2 dataset found here. In addition, we've also added a transformer based chatbot called Poly-Encoder.
Artificial Intelligence (AI) is the mantra of the current era. The phrase is intoned by technologists, academicians, journalists, and venture capitalists alike. As with many phrases that cross over from technical academic fields into general circulation, there is significant misunderstanding accompanying use of the phrase. However, this is not the classical case of the public not understanding the scientists--here the scientists are often as befuddled as the public. The idea that our era is somehow seeing the emergence of an intelligence in silicon that rivals our own entertains all of us, enthralling us and frightening us in equal measure. There is a different narrative that one can tell about the current era.