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Amazon's Alexa becomes a better conversationalist and can now ask you questions, too – TechCrunch

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At its annual hardware event, Amazon today announced new capabilities for its Alexa personal assistant that will allow it to become more personalized as it can now ask clarifying questions and then use this personalized data to interact with the user later on. In addition, Alexa can now join a conversation, too, starting a mode where you don't have to say'hey Alexa' all the time. With that, multiple users can interact with Alexa and the system will chime in when it's appropriate (or not -- since we haven't tested this yet). As Amazon VP and head scientist Rohit Prasad noted, the system for asking questions and personalizing responses uses a deep learning-based approach that allows Alexa to acquire new concepts and actions based on what it learns from customers. Whatever it learns is personalized and only applies to this individual customer.


NLP - Natural Language Processing with Python

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NLP - Natural Language Processing with Python Learn to use Machine Learning, Spacy, NLTK, SciKit-Learn, Deep Learning, and more to conduct Natural Language Processing Bestseller What you'll learn Welcome to the best Natural Language Processing course on the internet! This course is designed to be your complete online resource for learning how to use Natural Language Processing with the Python programming language. In the course we will cover everything you need to learn in order to become a world class practitioner of NLP with Python. We'll start off with the basics, learning how to open and work with text and PDF files with Python, as well as learning how to use regular expressions to search for custom patterns inside of text files. Afterwards we will begin with the basics of Natural Language Processing, utilizing the Natural Language Toolkit library for Python, as well as the state of the art Spacy library for ultra fast tokenization, parsing, entity recognition, and lemmatization of text.


Ask the Oxford Professors: The interplay between Machine Learning and Semantic Reasoning

Oxford Comp Sci

Artificial intelligence (AI) is a widely used term that conjures notions of fantasy, the future, or even threat. This is not surprising considering the multitude of movies which dramatise the role of artificial intelligence and what it may become. In reality, artificial intelligence is a branch of computer science which aims to "understand and build intelligent entities by automating human intellectual tasks". These processes have contributed to numerous technological advances across various industries, for example. It is now quite common to see articles about the latest AI development -- check out these robots which flip burgers!


Webinar: Introduction of NVIDIA A100 GPU on E2E Cloud

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The NVIDIA A100 Tensor Core GPU delivers unprecedented acceleration at every scale for AI, data analytics, and high-performance computing (HPC) to tackle the world's toughest computing challenges. As the engine of the NVIDIA data center platform, A100 can efficiently scale to thousands of GPUs or, with NVIDIA Multi-Instance GPU (MIG) technology, be partitioned into seven GPU instances to accelerate workloads of all sizes. And third-generation Tensor Cores accelerate every precision for diverse workloads, speeding time to insight and time to market. Pallab Maji is a "Senior Solutions Architect – Deep Learning" at NVIDIA working with System Integrators & Cloud Service Providers. His research interest lies in design and development of perception modules for autonomous systems, focusing mostly on Computer Vision, Natural Language Processing and Machine Learning.


How Artificial Intelligence and Machine Learning Can Help Insurers - Agency Nation

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The insurance industry is reliant on a strong digital presence and detailed analytics, whether for marketing, risk analysis or the prediction of future events. An insurer who can adopt Artificial Intelligence (AI) and Machine Learning (ML) will gain an advantage over their competitors that will last for years to come. Artificial Intelligence involves using computers to complete tasks such as learning and problem solving that traditionally require human intelligence. Machine Learning is an application of artificial intelligence that provides the ability to automatically learn from the environment and applies that learning to make better decisions. If we take the first example of marketing AI, and in this case, Natural Language Processing (NLP) is able to extract social media posts, reviews and threads that surround your company and your competitors.


Considering the Safety and Quality of Artificial Intelligence in Health Care

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The role of machine learning and artificial intelligence (AI) in the health care sector is rapidly expanding. This expansion may be accelerated by the global spread of COVID-19, which has provided new opportunities for AI prediction, screening, and image processing capabilities.1 Applications of AI can be as straightforward as using natural language processing to turn clinical notes into electronic data points or as complex as a deep learning neural network performing image analysis for diagnostic support. The goal of these tools is not to replace health care professionals, but to enable better patient experience and better inform the clinical decision-making process to improve the safety and reliability of clinicians. Clinicians and health systems using these new tools should be aware of some of the key issues related to safety and quality in the development and use of machine learning and AI. The performance of a chatbot on a shopping website poses little harm to users, but AI used in health care, particularly clinical decision supports or diagnostic tools, can have significant impact on a patient's treatment.


Women Leaders in AI - 2020 - NASSCOM Community

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The excitement of using Artificial Intelligence has not dwindled from the time it has been unfolded. In KPMG study on “living in the AI world 2020: achievements and challenges of AI across 5 industries (retail, financial service, healthcare, transportation, and technology), revealed that 92% of respondents agreed that leveraging the spectrum of AI technologies will make their companies run more efficiently. Amidst the admiration towards AI, IBM created the Women Leaders in AI program in 2019. This was a way to acknowledge the women leading in AI and encourage females to lend a hand in the field of AI. Through this IBM, planned to make the efforts of the honourees more visible to the world. 2020 IBM women leaders were honoured for outstanding leadership in the AI space. Here is the list of women leaders in AI 2020 honorees:- Aarthi Fernandez Who is a Global head of Trade Operations and SEA Trade COO at Standard Chartered Bank? She is a C-suite executive with deep insight on how digitalization can positively disrupt US$17 trillion global trade. She is into deploying AI/Machine learning to make trade financing simple, faster, and better for corporate clients and mitigate compliance risk. Piera Valeria Cordaro She is a commercial Operations Innovation Manager, Wing Tre S.p.A., Italy. She is a speaker, advocating the use of AI in customer operations. Along with her team and with support by IBM Watson, implemented two chatbots, to improve customer experience. Both bots have made it possible to handle a million queries efficiently. Amala Duggirala Who is the enterprise Chief operation and Technology officer, Regions Bank, United States. To handle customers’ inquiries she deployed IBM Watson’s assistant- virtual banker persona, ”Reggie”. From the time of its implementation 4.3 million customer calls have been answered, with 22% of them being handled by AI. Mara Reiff Vice President, Strategy and Business Intelligence, Beli Canada, Canada. She used AI to improve operations, loyalty, and brand. She worked with IBM to install Watson studio Local using Red Hat open shift. This resulted in smarter, fast decision-making with improved customer experience leading to increased sales. Mara suggests everybody to “Make sure to stop and smell the roses. Take each opportunity to learn something new and embrace change”. Amy Shreve- McDonald She is lead Product Marketing Manager for Business Digital experience, AI&T, USA. EVA (Enterprise Virtual Agent) was launched in February 2019, to improve customer chat experience, it uses Watson assistant. This system has been able to handle 45% chats on its own, resulting in reduced costs and expanding 24/7 support. She also received AT&T’s 2019 Visionary Award for her work advocating EVA. Ryoko Miyashita Manager, customer service department, customer service section JACCS CO., LTD Japan. She launched a Watson-enabled operator onboarding tool, that resulted in reduced new operator training period by 30%. The tool has increase customer satisfaction. Her advice to the younger self is “It is important to believe in yourself, but it is equally or more important to believe in people around you. I would encourage myself to have many experiences and garner knowledge to objectively evaluate things, not blindly accept or exclude others’ opinions”. Carol Chen She is Vice President for Global Marketing, Global Commercial, Royal Dutch Shell, United Kingdom. Along with her team, Carol is partnering is planning for digital transformation with the creation of “Oren”- a Smart Minning Platform, by partnering with IBM. This platform will offer an innovative and creative experience for users in the sector to deliver connectivity and integration across the ecosystem. To use AI, she advice commencing with analyzing the business outcome that one wants and customer pain points that one can cater to. The next step would be to determine how to leverage AI and data to solve the problem. Rosa Martinez Cognitive Project Manager, CiaxaBank, Spain. For those who consider using AI, her advice to them is ‘first to understand the business case as it may take time more than expected. This phase can result in a non-AI project example a ‘software as usual’. But moving further with the project there can be more AI application for sure to work on’. Lee- Lim Sok Know Deputy Principal, Temasek Polytechnic, Singapore. Under the leadership of Sok Keow, The higher education institution in Singapore ‘Temasek Polytechnic’ launched the “Ask TP” chatbot in January 2018. The chatbot helped current as well as prospective students to get answers to the questions asked about Temasek and also gave personalized course advice. In the 1st two weeks of 2020, ‘Ask’ TP’ responded to more than4,351 questions. She suggests everybody “deeply appreciate ‘people’ as they are the most critical asset in an organization, and a leader must develop a team”. Itumeleng Monale Executive Head of Enterprise Information Management Personal and Business Banking, Standard Bank of South Africa, South Africa. By deploying many analytical tools in her organization, she can uplift the revenue of the company. Through models of analytics relationships, bankers are experiencing a 40% revenue uplift when comparing to their peers. She sees AI as a tool through which business delivery can be accelerated, value could be added to human capital and relationships can build further. With this AI era, Research has postulated that corporate giants still have less percentage of women in the technical department. Facebook’s diversity report suggests that there are 22 % of women in the technical department and 15 per cent of women work in the AI research group. Similarly, Google’s diversity report suggests that only 10% women are working on  “machine intelligence”. There is a need to encourage women participation as there are many more women around the world, stepping out of the pre-existed sheathe and going beyond the walls to shape the future. Opening up the AI platform for all will fetch us more talented beings which can help us celebrate the use of AI in different fields and different ways. Reference:- https://www.ibm.com/watson/women-leaders-in-ai/2020-list https://advisory.kpmg.us/content/dam/advisory/en/pdfs/2020/technology-living-in-an-ai-world.pdf   About the author:- Kirti Kumar is a budding HR professional currently pursuing PGDM in HR and Marketing at New Delhi Institue of Management. She looks forward to opportunities that can hone her skills. She is agile in her attitude with versatility in her action


Artificial intelligence diagnoses Alzheimer's with more than 95% accuracy

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An artificial intelligence (AI) algorithm has produced another significant breakthrough using attention mechanisms and a convolutional neural network to accurately identify tell-tale signs of Alzheimer's. The AI tool developed by the Stevens Institute of Technology is said to be able to explain its conclusions, thus enabling human experts to check the accuracy of its diagnosis by up to 95%. AI has made huge strides in the medical sector and this latest news is further evidence that the speed at which the technology is moving shows no signs of ceasing any time soon. The algorithm is trained to identify subtle linguistic patterns previously overlooked by using texts composed by both healthy subjects and known Alzheimer's sufferers. The team of researchers then converted each sentence into a unique numerical sequence, or vector, representing a specific point in a 512-dimensional space.


Why Is Python Used for AI(Artificial Intelligence) & Machine Learning - eSparkBiz

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Artificial Intelligence and Machine Learning have been making our lives easier for quite some time. Today, we're going to talk about Python For AI & Machine Learning. Though the community keeps discussing the safety of its development, at the same time it is working relentlessly to grow the capacity and abilities of AI and ML. The demand for AI is at its peak, as it is highly used in analysing and processing large volumes of data. Due to the high volume and intensity of this work, it cannot be handled and supervised manually. AI is used in analytics for data-based predictions that enable people to come up with more effective strategies and strong solutions. FinTech applies AI in investment platforms to conduct market research and make predictions about where to invest funds for greater profits. The travel industry utilises AI to launch chatbots and make the user journey better. Python Web App Examples are proof of that. Due to such high processing power, AI and ML are absolutely capable of providing a better user experience, that is not only more apt but also more personal, making it more effective than ever.


How To Migrate Your Chatbot From IBM Watson Assistant To Rasa

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IBM Watson Assistant (WA), at its core has a basic intent and entity structure. Intents are as minimalist as can be. During the intent creation process, there are two features which aid in the defining of intents. Bot of these features translate into better defined intents, and translates nicely into the JSON export file. Hence the leverage these functions lend to the intent creation process is not lost.