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) …
Continuing off a basic introduction to AI & Machine Learning, we will explore common algorithms of Machine Learning such as linear regression or classification and defining how they work and when to use them. Afterwards, we will go through an example on using Watson Studio and AutoAI, which automates the workload of data scientists, to best choose the correct machine learning algorithm for your problem.
Banks lost about $4 billion to account takeover (ATO) fraud attempts last year and the losses are set to further increase as this year progresses. ATO and other fraud methods that rely on using stolen credit card numbers or other personal information are becoming decidedly popular with bad actors, who are employing increasingly sophisticated technologies to execute their scams. The majority of ATO attacks are automated, meaning that fraudsters are becoming more comfortable utilizing advanced learning tools such as deep learning, artificial intelligence (AI) and machine learning (ML) to target financial institutions (FIs) and their customers. About 40 percent of all ATO attacks now count as high-risk, meaning banks of all shapes and sizes must reexamine how they think about data protection, security and the tools they use to guard against emerging threats. In the latest Digital Banking Tracker, PYMNTS analyzes the ways in which FIs are working to keep fraudsters from accessing customer information and funds on their mobile and digital channels.
In our previous tutorial, we learned how to use models which were trained for Image Classification on the ILSVRC data. In this tutorial, we will discuss how to use those models as a Feature Extractor and train a new model for a different classification task. Suppose you want to make a household robot which can cook food. The first step would be to identify different vegetables. We will try to build a model which identifies Tomato, Watermelon, and Pumpkin for this tutorial.
Taiwanese electronics giant Delta Electronics, Inc. (TPE:2308) has announced a partnership with Microsoft (NasdaqGS:MSFT) for the former's digital transformation, according to local outlet the Taipei Times. In addition to the digital transformation, Delta Electronics chairman Yancey Hai said the company is "also planning future collaborations with Microsoft in areas such as machine deep learning at its robotics arm with the aim of improving the industrial automation business". "We have set up two AI [artificial intelligence] projects with Microsoft's headquarters in the US... One is aimed at improving the efficiency and noise cancelation of our ultra-thin fans, the other is focused on developing a product quality management system." Virtusa Corporation (NasdaqGS:VRTU) has joined the Stanford Artificial Intelligence Laboratory (SAIL) as an Affiliate Member.
The federal and Quebec governments have announced the creation of a Montréal-based international centre of expertise for the advancement of artificial intelligence as part of the Global Partnership on AI (GPAI), which was recently discussed at the G7 Leaders' Summit. "Montréal was ideally suited to host this centre of expertise." The federal government will invest up to $10 million over five years to support the activities of the centre once it commences operations. This commitment is in addition to a $5 million grant previously committed by Quebec, and awarded to Montréal International, to create or attract an international AI organization, bringing total government investment to $15 million over five years. "The Montréal ecosystem is recognized as a leader in AI," said Navdeep Bains, minister of innovation, science, and economic development.
"Business is going to change more in the next five years than it has in the last twenty" Is this book for you? Are you looking to start up an automation Centre of Excellence (CoE) in your company to start building automation solutions, or perhaps you want your new CoE to mature and grow. Read industry best practices and insights, to get high-level steps on how to best implement Intelligent Automation. This will improve your awareness on what's been happening in the industry and what may be to come in the near future. This will help you understand the dos, don't, myths, challenges, and benefits of automating your business processes, and give you a picture of what your team is doing …or should be doing.
Find practical recommendations for the use of AI technology for both clinical and nonclinical applications. The Ethics of Medical Data Donation features essays that combine academic argument with practical application of ethical principles. Innovative research that will inform future practice directed at changing health behavior through improved communication, networking, and social capital published in Journal of Healthcare Informatics Research. Addresses the gaps in the understanding of how health IT impacts on clinical workflows and provides insights for practitioners in designing, implementing, and evaluating workflow changes in the context of health IT adoption and use. Provides detailed practical guidelines on how to develop an efficient pathological brain detection system, reflecting the latest advances in the computer-aided diagnosis of structural magnetic resonance brain images.
Tableau announced the general availability of Explain data that brings a new set of AI capabilities to its analytics platform. Founded in 2003, Seattle-based, Tableau is the leading provider of the analytics platform. The company was successfully IPO(ed) in 2013 and later acquired by Salesforce in an all-stock deal amounting to $15.7 billion in transaction. It analyzes available data and explains relevant factors for the given data point. Earlier, to derive the cause of data point, manual validation of explanations is required.
It seems like artificial intelligence is taking over the world, leaving many of us non-techies feeling terrified. Yet when you stop to think about it, we all use artificial intelligence (AI) every day. When we Google something, use Siri on our smart phones or ask Alexa a question, we are using AI. Wikipedia states artificial intelligence, sometimes called machine intelligence, is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans. Colloquially, the term "artificial intelligence" is often used to describe machines (or computers) that mimic "cognitive" functions that humans associate with the human mind, such as "learning" and "problem solving."
This robot, Pepper, welcomes people to the store. Artificial Intelligence (AI) and machine learning (ML) applications are growing and expanding into all industries and functions. From ranking sales leads (Einstein) to chatting with customers (Bold 360) artificial intelligence seems to be popping up everywhere. However, many of the of the boldest claims for artificial intelligence have not yet come to fruition. AI is not yet curing cancer and Amazon's recruiting tool acted with just as much bias as a normal human recruiter.