AI INSIGHTS
Expert insights into artificial intelligence, machine learning, and beyond
Recent AI Insights
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AI transforms insurance: See 8 examples of how it worksUsing AI in insurance can boost value for customers, insurance companies and stakeholders alike. Examples range from stronger fraud detection and improved customer service to optimized underwriting processes and competitive advantage. Learn more about how AI is transforming the industry.
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What is AI modeling?AI modeling involves creating programs that use one or a combination of algorithms to allow computers to think, learn and predict outcomes. Much like a human brain, AI models absorb input data – numbers, texts, images, video, sound – to learn how to predict outcomes or solve specific tasks without explicit instructions at every step.
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Understanding digital twin technologyLearn how digital twin technology can change industries from health care to manufacturing, and shape the future of data modeling and process improvements.
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What is synthetic data? And how can you use it to fuel AI breakthroughs?There's no shortage of data in today's world, but it can be difficult, slow and costly to access sufficient high-quality data that’s suitable for training AI models. Learn why synthetic data is so vital for data-hungry AI initiatives, how businesses can use it to unlock growth, and how it can help address ethical challenges.
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Unlocking a strategic approach to data and AIAI is only as good as the data that powers it – this is a fundamental truth about data and AI that defines the limits of what’s possible with artificial intelligence. It may seem surprising, but it's rarely a bad algorithm or a bad learning model that causes AI failures. It's not the math or the science. More often, it's the quality of the data being used to answer the question.
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AI anxiety: Calm in the face of changeAI anxiety is no joke. Whether you fear jobs becoming obsolete, information being distorted or simply missing out, understanding AI anxiety can help you conquer it.
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Fraud detection and machine learning: What you need to knowMachine learning and fraud analytics are critical components of a fraud detection toolkit. Discover what you’ll need to get started defending against fraud – from integrating supervised and unsupervised machine learning in operations to maintaining customer service.
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Five AI TechnologiesDo you know the difference between artificial intelligence and machine learning? And can you explain why computer vision is an AI technology? Read our overview to understand these and other technologies behind the AI craze.
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What are AI hallucinations?Separating fact from AI-generated fiction can be hard. Learn how large language models can fail and lead to AI hallucinations – and discover how to use GenAI responsibly.
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What are chatbots?Chatbots are a form of conversational AI designed to simplify human interaction with computers. Learn how chatbots are used in business and how they can be incorporated into analytics applications.
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How AI and advanced analytics are impacting the financial services industryTop SAS experts weigh in on topics that keep financial leaders up at night – like real-time payments and digital identity. See how advanced analytics and AI can help.
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Shut the front door on insurance application fraud!Fraudsters love the ease of plying their trade over digital channels. Smart insurance companies are using data from those channels (device fingerprint, IP address, geolocation, etc.) coupled with analytics and machine learning to detect insurance application fraud perpetrated by agents, customers and fraud rings.
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4 strategies that will change your approach to fraud detectionAs fraudulent activity grows and fighting fraud becomes more costly, financial institutions are turning to anti-fraud technology to build better arsenals for fraud detection. Discover four ways to improve your organization's risk posture.
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Analytics leads to lifesaving cancer therapiesA long-shot treatment offers hope to 10-year-old Harrison after he learns the DNA profile of his cancer is resistant to chemo. Find out how data and analytics play a role in cancer research and cancer treatments that are saving lives.
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Analytics: A must-have tool for leading the fight on prescription and illicit drug addictionStates and MFCUs now have the analytics tools they need to change the trajectory of the opioid crisis by analyzing data and predicting trouble spots – whether in patients, prescribers, distributors or manufacturers. The OIG Toolkit with free SAS® programming code makes that possible.
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Detect and prevent banking application fraudCredit fraud often starts with a falsified application. That’s why it’s important to use analytics starting at the entrance point. Learn how analytics and machine learning can detect fraud at the point of application by recognizing the biggest challenge – synthetic identities.
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Engage all areas of the marketing brain to improve the CXIn an increasingly competitive marketplace, and in recent months, in particular, digital channels and capabilities have been critical to success. Organisations need to engage all three areas of the corporate brain: customer intelligence, human intelligence and artificial intelligence.
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AI is a practical tool to help Marketers gain insightsMarketers are not scientists, and technologies like AI have become more important to help Marketers understand customer data and insights. With AI, Marketers are able to focus on the bigger picture - improving experiences for customers and driving revenue for the business.
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The impact of the CMO in the coming yearsThe past couple of months for CMOs have seen them thrown into the fire and stress-tested to keep not only the business alive, but also their relationship with their consumers. With this climate, the future role and impact of CMOs has irrevocably changed.
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AI optimises campaign performance at WWF and drives ROIIn its mission to advocate for endangered species and for the environment, the World Wide Fund faces challenges familiar to all brands. By optimising its marketing through the smart use of machine learning and AI the WWF was able to address the issues of cost and purpose successfully.
Artificial Intelligence: The Basics
Exactly how intelligent is artificial intelligence? And how closely can machines mimic human intelligence? We explore these questions, and review the ways artificial intelligence is improving our world. From digital assistants to automated X-ray readings, artificial intelligence can be found in many industries.
- Select a topic
- Deep Learning
- Natural Language Processing
- Machine Learning
- Predictive Analytics
- Computer Vision
- Neural Networks
- Generative AI
- AI Ethics
What is deep learning?
If you've ever held a conversation with Siri, you've used deep learning. Systems such as Siri, Alexa and Cortana are driven in part by deep learning, a type of machine learning that trains a computer to complete human-like tasks. Speech recognition, image recognition and natural language processing are all powered by deep learning, which trains a computer to learn on its own by recognising patterns. How can you use it? And how will it affect your industry.
What is natural language processing (NLP)?
Who would have guessed 10 years ago that you could hold a conversation with your phone or tell your thermostat to turn up the heat? Today, it's not uncommon to ask for a weather report, add to your grocery list and play your favourite music by voice command – and get immediate results.
Natural language processing is the central technology behind these advancements. But how do your devices understand language? And how can these same technologies be used in a business setting? From text mining to natural language processing and natural language understanding, find all the answers here
What is machine learning?
Machine learning isn’t new. But now it's high-powered. And that’s giving this decades-old mathematical science new momentum in the world of big data.
Self-driving vehicles? That's machine learning in action. Email spam filters and online shopping recommendations? That's machine learning for everyday life. Fraud detection? One of the more obvious – and important – uses in our world today. Discover how machine learning can help you find answers to complex problems.
What is predictive analytics?
So you’ve embraced the power of collecting and analysing data. That’s a great first step, but it just scratches the surface. To get the most out of your data, you need to anticipate the future, not just analyse the past.
Whether you want to attract new customers, assess payment risk, identify fraud or forecast energy demand, predictive analytics can provide answers to your most complex questions.
What is computer vision?
Find out how a computer goes from "seeing" an image as a series of pixels to interpreting what's in the image and what it means. You'll learn how image segmentation, feature matching and object detection all play a role in this process – and how computer vision is used for everything from detecting cancer to assessing insurance claims.
What are neural networks?
Neural networks are computer programs designed to imitate how the human brain learns and searches for patterns. Often referred to as artificial neural networks (ANNs), they are ideally suited to solving real-world problems in different fields. Much like a human brain, they can be trained over time to improve their interpretations of data.
Generative AI: The Basics
What is generative AI and how does it work? Consider generating computer code or synthetic data. Creating a business strategy with help from a conversational AI chatbot based on a large language model. Or using a digital twin to spot supply chain disruptions. See how generative AI started, who’s using it, and which underlying technologies make it work.
What is AI Ethics?
Artificial intelligence technology gives machines the ability to mimic human decision-making and automate tasks intelligently. In a world filled with AI technology, the implications of ethics in relation to AI tech are broad. We need clear guidelines to ensure our AI systems are designed in accordance with human principles of right and wrong, from the start – including considerations around privacy, fairness, transparency and more.
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