SAS IS A LEADER
IDC MarketScape: Worldwide Machine Learning Operations Platforms 2022
SAS Model Manager offers support for a wide variety of languages and platforms. It integrates with Git (including GitLab and GitHub), Python, R, MLflow, and Azure Machine Learning, as well as with container registries on Azure, AWS, GCP, and private Docker registries. Customers appreciated this flexibility and capability.
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E-Book
How to govern your AI strategy in a highly regulated worldIt’s no longer a case of “if” an organization adopts AI but “when.”
The technology is rapidly advancing and transforming the workplace and society at large, but it comes with risks. That’s where governance comes in. Governance is essential to the reliable, transparent and ethical performance of AI. But the clear lack of oversight of the technology is putting many organizations at risk of noncompliance with incoming regulations around AI, such as the EU AI Act.
This e-book will reveal:
· Why AI governance is so important and what successful governance looks like.
· The five key drivers for implementing AI governance today.
· The risks of poor governance and growing regulatory pressure.
· A practical approach to implementing AI governance.
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Технический документ
Boosting Tax Agency Productivity and Protection with AI and Generative AIGenerative AI (GenAI) technology is gaining momentum rapidly, not just in businesses and government agencies, but also among those trying to defraud them. Tax agencies have potentially valuable uses of GenAI in process productivity, taxpayer service, and staying ahead of fraudsters by augmenting fraud detection and threat simulation. Given the new and sometimes uneven capabilities of GenAI, agencies should be approaching it with both purpose and caution. To explore these opportunities and threats, IIA spoke with SAS global tax and revenue compliance experts Teya Dyan, Principal Industry Consultant, based in North America, Ensley Tan, Principal Industry Consultant, based in Asia Pacific, and Alexandre Negadi, Senior Industry Consultant, based in Europe.
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E-Book
Your journey to a GenAI future: A strategic path to success in health careGenAI is at the forefront of global health care innovation and is here to stay. Health care organizations at large are leaning into the promise of advanced technologies with the intent to streamline operations and deliver stronger health outcomes for patients all over the world. But in a highly regulated, protected and data-sensitive sector, how is this technology being used? And how will health care organizations keep patient data safe while implementing cutting-edge technologies like GenAI?
In this report, you’ll discover:
• How health care organizations are approaching GenAI adoption compared with other sectors.
• The specific areas where health care already sees GenAI drive results – and where they’re still navigating uncertainty.
• How GenAI investments in health care stack up against other sectors and where these industries are placing their bets.
• Practical strategies to overcome the challenges of GenAI implementation, ensuring you maximize your return on investment (ROI) and stay ahead of the curve.
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E-Book
Your journey to a GenAI future: A strategic path to success in life sciences and pharmaAs generative AI continues to make waves across both headlines and boardrooms, the life sciences industry is unlocking new possibilities that could reshape the future. This sector, known for managing vast, intricate data sets and safeguarding sensitive patient information, is poised to harness GenAI for groundbreaking advancements. In life sciences, GenAI isn’t just a buzzword – it’s a game changer with the potential to revolutionize innovation, productivity and patient care.
Our latest insights on GenAI come from a comprehensive survey of 1,600 organizations across the globe, offering a deep dive into how different industries are approaching GenAI. Specifically, we focused on the responses of 237 senior life sciences leaders who are at the forefront of shaping GenAI, data and analytics strategy.
In this report, you’ll discover:
• How the life sciences industry is leading or lagging in GenAI adoption compared with other sectors.
• The specific areas where the industry is already seeing GenAI drive results – and where it is still navigating uncertainty.
• How GenAI investments in life sciences stack up against other sectors and where the industry is placing its bets.
• Practical strategies to overcome the challenges of GenAI implementation, ensuring you maximize your return on investment (ROI) and stay ahead of the curve.
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Article
Пять технологий искусственного интеллектаОт машинного обучения до компьютерного зрения. Эти технологии подпитывают всеобщее помешательство на ИИ.
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Аналитический отчет
IDC MarketScape: Worldwide Machine Learning Operations Platforms 2024 -
Article
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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Article
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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Технический документ
Revealing the paths to 2040: four possible scenarios for insuranceFrom extreme weather events and natural disasters to geopolitical volatility and shifting demographics, insurers face increasing numbers and varieties of disruptions and uncertainties. At the same time, longstanding risk models are upended by rapid technological advances and evolving market needs. Opportunities abound – but the future is unclear.
This Economist Impact report, informed by expert interviews and an analysis of megatrends, presents insurers with four possible scenarios for the world in 2040. Each path forward describes a potential future, reflecting two main drivers of change:
– Pace of technological evolution.
– Level of global cooperation.
How will insurance evolve? Challenge your assumptions as you delve into these scenarios, considering along the way how you should prepare.
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E-Book
A Comprehensive Approach to Trustworthy Data and AI GovernanceAI is revolutionizing human life and unlocking a whole new world of innovation. As AI becomes more prevalent, it will affect nearly every aspect of society from our professional to personal lives. Organizations that can demonstrate responsible and ethical use of AI are more likely to be commercially successful. This is where Trustworthy AI – a system designed to ensure safety, reliability and ethical practices – can help.
Trustworthy AI is an AI system designed, developed and deployed with human-centricity in mind. These systems incorporate appropriate levels of accountability, inclusivity, transparency, completeness and robustness to promote human agency and prevent human harm.
In this eBook you will discover:
The business need for ethics in AI
Why you should embrace Trustworthy AI
How to establish Trustworthy AI governance
The 6 SAS principles to guide your Trustworthy AI strategy
How the SAS Data Ethics Practice supports Trustworthy AI
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E-Book
Five reasons developers hit a productivity wall – and what to do about itDevelopers, when you hit a wall, you hit it hard. And it’s often the same five obstacles getting in the way of productivity over and over again. Do these issues sound familiar?
“I don’t have my own space to experiment with models before sharing them.”
“It takes too long to develop a model.”
“The infrastructure we need costs too much.”
“It’s too hard to keep track of version updates.”
“Everybody’s getting different results from the same data sets.”
This e-book from SAS and AWS takes a closer look at each of these obstacles and how you can overcome them with the help of SAS® Viya® Workbench. Make productivity blockers a thing of the past.
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Технический документ
Solving the public services productivity puzzleIn Global Government Forum’s survey, 91% of public service respondents said they face a productivity challenge, with 56% characterizing it as significant or very significant.
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E-Book
Data-driven health careThe use of technology and data in the health care ecosystem continues to evolve. An extreme emphasis has been placed on digital health, AI, and the need for interoperability across various stakeholders in the healthcare ecosystem. Interoperability of different health care systems and devices to seamlessly exchange information is crucial to provide stronger health outcomes and patient engagement opportunities, enhance patient safety and operational efficiency, and reduce duplicated effort and potential for error.
Discover how health care powered by data and technology will be the springboard to the future.
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E-Book
Marketers and GenAI: Diving Into the Shallow EndMarketers are leading in GenAI use, but it’s only surface level. What’s needed to take the next step?
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Article
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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E-Book
Your journey to a GenAI future: An insurer’s strategic path to successThe insurance industry is rapidly embracing generative AI technology, recognizing its extraordinary capabilities through high rates of personal and organizational usage. Overwhelmingly, insurance companies around the globe plan to invest in GenAI over the next year, and most have a dedicated budget in place. Yet many lack sufficient budgeting for GenAI governance, and most governance frameworks are still in development.
Recent research compiled survey results from 1,600 global organizations across a wide range of sectors. In this report, we drilled down to the 236 respondents who are senior decision makers in GenAI strategy or data analytics in the insurance sector.
Read the results to understand insurance firms’ unique perspectives on GenAI – including how the industry compares to other sectors, how you can proactively prepare for implementation challenges, what the most promising business opportunities are, and which issues are the top concerns.
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E-Book
Your journey to a GenAI future: A strategic path to success for governmentAs generative AI (GenAI) accelerates into the mainstream, organizations of every kind are seeing the transformative potential of the technology. Many government organizations handle huge data sets, hold sensitive personal information and synthesize details about entire populations. For government, GenAI could create a paradigm shift in productivity and capability.
Our research findings are based on a new survey of 1,600 organizations from a wide range of sectors worldwide. To better understand the unique perspectives that government organizations have about GenAI, we examined the responses from the 237 senior leaders who are responsible for making decisions on GenAI strategy or data analytics.
This report uncovers:
• How governments are implementing GenAI compared to other sectors.
• Which areas governments are already seeing the benefits of GenAI and where they feel less confident.
• How government investment stacks up against other sectors and where it’s being spent.
• How you can proactively prepare for the challenges of implementing GenAI to ensure a strong ROI
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Аналитический отчет
IDC MarketScape: Worldwide Decision Intelligence 2024 -
E-Book
Public service of the futureNever before have governments been asked to do so much, so fast, while facing considerable pressures – rising customer service expectations, fiscal constraints, overstretched organizations and workforce fatigue.
Technologies like AI and generative AI are shifting the limits of what is possible – enabling fresh ideas about how public sector organizations can deliver services and helping to rethink what services are offered. From national to local government, law enforcement to health and defense to education, great strides are being made to deliver better outcomes and experiences.
In this e-book, you will discover six considerations for improving productivity and ensuring public servants have the time to focus on what matters. Here's a sneak peek:
· How do different demographics engage with public services and how do you serve everyone?
· Are traditional processes meeting your organization’s needs? Would updating and modernizing help you achieve increased operational efficiency?
· How AI is a catalyst for organizational transformation.
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Технический документ
Pioneering Ethical AI: The Crucial Role of Property and Casualty InsurersInsurers have long been global leaders in addressing risks and protecting people and businesses. As artificial intelligence continues to revolutionize how business gets done, it is redefining how insurers can deliver on their promises. Read this paper to learn from industry veterans and AI experts alike about:
• The state of AI regulations globally.
• The multifaceted role insurers can play in developing AI ethics.
• Why insurers are uniquely qualified to use AI (and GenAI) – and how they’re using these technologies today.
• An approach to an ethical AI framework that any insurer can follow to establish their own AI narrative.
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E-Book
On the Road to Accelerating Claims AutomationMore than ever, insurance companies need to provide customers with seamless interactions that save them time, minimize hassle, and make them feel seen, understood, and cared for. Many are also exploring the use of AI for claims prevention – for example, by creating new risk mitigation services. All of this requires investment in digital technologies that work together to enable intuitive, Amazon-like customer experiences. This ebook explores how insurers can make the leap to digitally transformed, intelligent claims processes that customers love and increase operational efficiency and reduce costs.
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Аналитический отчет
SAS is a Leader in The Forrester Wave™: AI Decisioning Platforms, Q2 2023.The Forrester Wave™: AI Decisioning Platforms, Q2 2023 recognizes SAS for seamlessly integrating world-class analytics for decisioning.
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Технический документ
How to realize value from cloud analytics faster — and with less cost and riskIn just a few years’ time, analytic and AI models have gone from being on-premises “pet projects” and proofs of concept to high-volume mission-critical technologies developed and deployed in the cloud to support business decisions at scale. But as Foundry’s survey reveals, most IT departments haven’t evolved how they will support and enable the new world of cloud analytics at scale.
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Article
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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Технический документ
Top 5 insurance problems – and AI isn’t one of themAs all players in the insurance ecosystem know – insurers to reinsurers, GSIs and regulators – the industry faces a multitude of daunting business problems today. In this paper, we discuss five of the most pressing insurance problems, how they affect communities around the world, and obstacles that can get in the way of solving those challenges. Read the paper to learn how insurers can use AI to identify and solve far-reaching issues. And learn why it will take the entire insurance ecosystem to course correct on business results, climate risk, AI safety and governance, and more.
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E-Book
Intelligent decisioning in governmentGovernments can incorporate AI-driven decisioning into existing business processes to take advantage of digital transformation benefits. Through automated processes, deeper insights and the ability to act quickly, governments can innovate service delivery, drive efficiency and help build a better future.
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E-Book
Government navigating an uncertain worldHow governments can harness data,
advanced analytics, and trustworthy AI to
prepare for the unexpected—and respond
faster to protect and improve citizens’ lives.
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Article
Fraud detection and machine learning: What you need to knowМашинное обучение является важной частью инструментария обнаружения мошенничества. Вот что вам нужно для начала работы.
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Article
Fraud detection and machine learning: What you need to knowМашинное обучение является важной частью инструментария обнаружения мошенничества. Вот что вам нужно для начала работы.
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Технический документ
Generative AI in Health Care: Opportunities and CautionsLearn how GenAI will affect all aspects of health care, from cost containment to patient care., and the importance for organizations to recognize both the potential and the limits of this new technology and be alert to how it’s being used to perpetrate fraud.
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Article
Shut the front door on insurance application fraud!Как выявить, что вас обманывают агенты и страхователи, а также распознать первые признаки будущего мошенничества.
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Article
How to improve your AI marketing skillsMarketing teams can use current AI capabilities to enhance their efforts around campaign automation, dynamic pricing based on forecasting models, and by providing more relevant, real-time customer offers.
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E-Book
Detect and halt risky payments across the life sciences supply chainCut fraud, waste, error and abuse with a data-driven approach to payment integrity
It’s estimated that 4.57% of the total annual procurement spending in the private sector is lost to fraud and error. What would be the impact to life sciences organizations if you could stop that flow of cash out of the business? Even for smaller organizations, improving payment integrity could free up significant capital for strategic investments. In R&D, for example, it could free up funds for strategic acquisitions or returning cash to shareholders.
In this e-book, we’ll look at how a smarter, more data-driven approach to payment integrity helps life sciences companies gain faster and deeper visibility into their spending across R&D, manufacturing and distribution. A data-driven approach also helps highlight potential anomalies in real time for investigation by human experts.
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E-Book
The insurance data and AI revolutionInsurers face continual disruptions these days as they respond to price sensitivity, the push for sustainable practices, evolving regulations, climate change issues and all types of heightened risks. How should they respond?
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Аналитический отчет
IDC Spotlight: Looking Beyond the AI Model to Improve the Value of Computer Vision in Manufacturing OperationsThis IDC Spotlight explores the increasing adoption of computer vision (CV) by manufacturers, and how in order to succeed, they must focus on more than just model development, validation and deployment. SAS delivers a comprehensive portfolio of tools, software and resources – integrated into SAS Viya – to develop and deploy CV solutions.
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E-Book
5 Steps to Accelerate Value From Your Industrial IoT Data This e-book features five steps industrial leaders can follow to get more value from IIoT data. It describes how to craft a comprehensive IIoT strategy, what to look for in an edge-to-enterprise analytics solution, and how to evaluate IIoT solutions.
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Аналитический отчет
SAS is a Leader in The Forrester Wave™: Digital Intelligence Platforms, Q4 2022SAS is a Leader in The Forrester Wave™: Digital Intelligence Platforms, Q4 2022.
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Аналитический отчет
Gartner® Top Strategic Technology Trends for 2024: AI Trust, Risk and Security ManagementLearn why IT leaders must adopt an AI TRiSM to protect their organizations and improve their business outcomes from AI models.
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Customer Story
French national rugby team boosts performance with AI and analyticsThe French Rugby Federation counts on intelligence gleaned from SAS Viya on Microsoft Azure to guide coaching decisions and enhance player performance.
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Технический документ
Artificial Intelligence for ExecutivesThis paper outlines the SAS approach to AI and explains key concepts. It also provides process and implementation tips if you are considering adding AI technologies to your business and analytical strategies.
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Аналитический отчет
IDC MarketScape: Worldwide Responsible Artificial Intelligence for Integrated Financial Crime Management Platforms 2022 Vendor AssessmentLearn why SAS is positioned in the Leaders category in the 2022 IDC MarketScape for worldwide responsible artificial intelligence for integrated financial crime management platforms.
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Article
Operationalizing analytics: 4 ways banks are conquering the infamous ‘last mile’Here are four examples across the banking industry that show how these leading organizations followed a clearly defined path to conquer the infamous 'last mile' of analytics.
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Аналитический отчет
Matrix: Leading Fraud & AML Machine Learning PlatformsSAS is a best-in-class vendor in the most recent Datos Insights report, Matrix: Leading Fraud & AML Machine Learning Platforms.
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Технический документ
Machine Learning With SAS® Enterprise Miner™Learn how SAS modelers prepared data and applied different machine learning techniques to create and identify the most accurate model for predicting churn using KDD Cup data.
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Технический документ
The Machine Learning LandscapeThis paper, for novice and intermediate data scientists, talks about the four widely recognized machine learning styles and their common uses, data and modeling methodologies, and popular algorithms for solving machine learning problems.
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Технический документ
Machine Learning Use Cases in Financial CrimesLearn 10 proven ways machine learning can boost the efficiency and effectiveness of fraud and financial crimes teams – from data collection to detection to investigation and reporting.
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Технический документ
Machine learning and artificial intelligence in a brave new worldMachine learning in the last few decades has given way to an AI revolution. From self-driving cars to virtual assistants, learn more about the endless possibilities for these developing technologies.
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Аналитический отчет
SAS Inside Intelligence 2023 ConferenceThis IDC Link focuses on SAS' responsible innovation initiative and the importance of building trust, transparency and information privacy in machine learning and AI life cycle technologies and applications.
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Технический документ
Improve Customer Experience with Actionable Artificial Intelligence While more marketers turn to artificial intelligence technologies, this new territory also raises more questions. This paper offers a detailed look into how AI works, and explores the opportunities and challenges it presents.
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Технический документ
The Next Analytics Age: Machine LearningWhat management and leadership challenges will the next wave of analytic technology bring? This SAS-sponsored Harvard Business Review Insight Center on HBR.org went beyond the buzz to talk about how machine learning will change companies and the way we manage them.
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Аналитический отчет
IDC MarketScape: Worldwide MLOPs Platforms 2022 Vendor AssessmentSAS is positioned in the Leader's category in the 2022 IDC MarketScape for worldwide machine learning operations platforms.
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Customer Story
Customer engagement enhanced with cloud-based analytics and AI1-800-FLOWERS.COM, Inc. helps customers express, connect and celebrate with SAS Viya on Azure.
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Технический документ
How to Do Deep Learning With SAS® Get an introduction to deep learning techniques and applications, and learn how SAS supports the creation of deep neural network models.
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Технический документ
Data Management for Artificial IntelligenceWhen machines learn from exposure to data, the truism of “garbage in, garbage out” for data is truer than ever. Now is the time for executives, particularly the chief data officer, to establish the data management strategy, technology and best practices to ensure success with machine learning.
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Технический документ
The 3 R’s of AI Adoption: Refactor, Reinvent, ReimagineLearn how organizations are using AI to refactor, reimage and reinvent business as usual. Understand the relative impacts on business process, analytics and data practices, and DevOps at each level of adoption.
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Аналитический отчет
Artificial Intelligence In Retail: What Now?This RSR Benchmark Report examines retailers’ attitudes about AI/ML technology and whether it can be used to turn data into insights and help retailers better understand the environments they operate in.
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Аналитический отчет
Advanced Analytics Excellence In Discrete Manufacturing -
Аналитический отчет
ARC Insights: Maximizing Innovation in Digitally Maturing Process ManufacturingLearn why manufacturers that can leverage analytics tools to better problem solve will be capable of applying expertise in a way and at a speed the competition cannot.
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Технический документ
What You Need to Know About Data & Digital TransformationCompanies need to know how to use data to meet client needs, hire the right talent, measure performance and communicate their brand’s promise. This collection will cover how to adopt and analyze data and use it as part of your digital transformation.
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Технический документ
The Artificial Intelligence of Things We’re living in a world that has more connected devices than humans. See how AI amplifies the value and potential of this fast-growing Internet of Things.
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Технический документ
AIOT: How IoT Leaders Are Breaking Away (IDC Market Report / AIoT Survey 2019)Read the results of a global study conducted by IDC, which revealed that AI and the IoT are having a bigger-than-expected impact – and leaders report that the AIoT is becoming the key to competing effectively.
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Технический документ
Statistics and Machine Learning at ScaleDiscover how machine learning can be applied to a variety of applications, and learn about the techniques required to help computers learn from massive amounts of data.
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Технический документ
Redefine Your Analytics Journey With Interactive Data Exploration and Predictive AnalyticsWhat if your analytics journey were easier? It can be, in five easy steps. Learn how SAS Visual Analytics and SAS Visual Statistics together can provide a fast, fun way to explore data, build models and find the best performer.
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Технический документ
Get the most from your AI investment by operationalizing analyticsAnalytics needs to take a page from application development (DevOps) and embrace ModelOps – a practice that puts in place the culture, process and technology to operationalize analytics faster and more efficiently. ModelOps ensures maximum business impact from analytics, automates repeatable tasks, builds collaboration between stakeholders and streamlines the flow of analytics into decision making processes.
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Технический документ
AI for the CIO: 10 Tips for SuccessThis paper offers 10 tips for the CIO who is knee-deep in digital transformation projects that require deploying AI models at an enterprise scale.
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Технический документ
Building the Data-Intelligent Enterprise: Tap the Power of Technology and PartnersThe value of an intelligent enterprise is clear, but operationalizing analytics can be a long and complex journey. There is no magic bullet or singular solution. Rather, it takes the support of strategic partnerships to create a cohesive strategy and deployment road map that will accelerate deployment and maximize value from analytics investments.
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E-Book
How to Take AI Projects From Start to WinThe four pillars of starting a successful AI program and examples of how other organizations have taken their AI projects from start to finish.
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Технический документ
How AI Changes the RulesReaping the benefits of AI will require changes in workplace structures, technology strategies and technology governance. Read on to learn more about the changes that leaders must prepare for to successfully implement trusted AI.
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Технический документ
AI Momentum, Maturity & Models for Success: Focus on SingaporeAdvances in data and analytics have enabled early adopters of AI to grow beyond experiments and quick hits and provide examples for paths to success with AI.
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E-Book
Operationalizing AnalyticsExplore how to overcome difficulties related to data and operationalizing analytics. We’ll also look at how one industry – banking – has been able to realize the full benefit of its analytics investment.
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E-Book
Mastering Model Lifecycle OrchestrationThis interactive guide describes the stages of the model life cycle and explains why organizations should embrace different programming languages, tools, techniques and runtime environments when developing and deploying models.
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E-Book
Accelerate and improve business outcomes with AIoTOrganizations across multiple industries are using AIoT to improve quality, maximize equipment performance, improve efficiencies and more. Download this e-book to find out how you can reap the same benefits.
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E-Book
Formidable ForecastsWith artificial intelligence capabilities and traditional forecasting processes, it’s possible to create efficiencies by automating the production of large-scale time-series analyses and hierarchical forecasts.
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E-Book
Fearless Decision? The most successful banks of the future will be those who can see their customers as individuals, appreciate their unique journeys and make decisions accordingly — across all associated business functions.
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Технический документ
Adopting AI: The Impacts of AI on ManagementThe AI revolution is no longer the stuff of science fiction – it’s corporate reality. Harvard Business Review’s AI Adoption Insight Center articles on management discuss the reality of AI execution in businesses today and what we’re learning as AI advances.
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Технический документ
Adopting AI: Strategic Takes on AI AdoptionA successful AI implementation requires a strong strategy from the beginning. Knowing how and where to fit AI into your business to gain the most benefits is crucial to drive growth.
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Технический документ
Adopting AI: Industry PerspectivesFrom self-driving cars to supply chain jobs, detecting crime and changing healthcare, AI promises to transform our business world. The promise of AI is no longer speculative—it’s today’s reality.
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Технический документ
Adopting AI: Linchpins of AI Success - Data Scientists and Their Algorithms The Harvard Business Review’s AI Adoption Insight Center focuses on the the human faces behind the computational and automation advancements that are carrying our world into exciting, uncharted territory.
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Технический документ
AI Momentum, Maturity and Models for SuccessSAS, Intel and Accenture, working with Forbes Insights, surveyed business leaders and interviewed thought leaders around the world to identify early adopters and uncover emerging best practices for AI. Find out what they had to say.
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Технический документ
TDWI Checklist Report Six Best Practices to Ignite the Customer Experience with IoTcustomer data, IoT
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Технический документ
The Autonomous Grid in the Age of the Artificial Intelligence of ThingsExplore how AI and IoT work together to deliver everything from improved threat detection to better customer engagement for utilities.
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Технический документ
Artificial Intelligence in Banking and Risk ManagementGlobal Association of Risk Professionals (GARP) and SAS survey drew more than 2,000 responses from across the financial services industry to answer questions about the current and future state of AI in risk.
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Технический документ
Data, Analytics & AI: How Trust Delivers ValueThe annual Data and Analytics Global Executive Study with MIT Sloan Management Review looks at how 2,400 global business leaders make decisions based on analytics insights.
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Технический документ
Combining Robotic Process Automation and Machine LearningLearn how you can make robotic process automation smart by adding machine learning to it.
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Технический документ
The Risks and Rewards of AIExploring the rise of AI, Harvard Business Review has published a collection of articles assessing the opportunities and pitfalls that could evolve, with discussions on the innovative uses of data and analytics, industry adoption, impacts to human work, and the factors of business change.
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Технический документ
Advanced Analytics: Moving Toward AI, Machine Learning, and Natural Language Processingadvanced analytics, artificial intelligence, machine learning, natural language processing
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Технический документ
TDWI Navigator Report: Predictive AnalyticsPredictive Analytics
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E-Book
Powering Health Innovation with AIThere is no doubt: AI has the potential to transform health care. The most recent SAS Hackathon showcased how the transformative power of analytics can spark health care innovation. The Hackathon was entirely conducted on a Microsoft Azure cloud infrastructure to facilitate the agile analysis and visualization of big data.
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Технический документ
ModelOps with SAS and MicrosoftThis paper explores how SAS and Microsoft have built integrations between SAS Model Manager and Microsoft Azure Machine Learning.
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E-Book
The Innovator's Flight Plan to AIAs an emerging technology, AI is naturally associated with innovation. Many organizations are using AI to develop new products and business models, and to improve their business processes.
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E-Book
Augmented Analytics: The secret ingredient to better business intelligenceAugmented analytics breaks down the limitations of
business intelligence (BI) and brings forward insights
from data using AI and machine learning.
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Customer Story
Advanced analytics can detect and prevent insurance fraud before losses occur | SAS -
Article
Аналитика как инструмент для борьбы с зависимостью от рецептурных сильнодействующих препаратов и незаконно приобретенных наркотических веществШтаты и подразделения Medicaid, осуществляющие мошеннический контроль, теперь имеют аналитические инструменты, необходимые для изменения траектории кризиса опиоидов путем анализа данных и прогнозирования проблемных точек - будь то у пациентов, врачей, дистрибьюторов или производителей. Инструментарий от УГИ с бесплатным программным кодом SAS® делает это возможным.
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Customer Story
IoT-данные с искусственным интеллектом сокращают время простоя, помогают дальнобойщикам продолжать грузоперевозкиVolvo Trucks и Mack Trucks используют данные датчиков и решения SAS на основе ИИ для минимизации незапланированных простоев.
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Article
An executive’s guide to cognitive computingCognitive computing is the latest buzzworthy term that everyone seems to be talking about in the technology industry. But can machines really think?
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Customer Story
Уменьшение внутрибольничных инфекций с помощью искусственного интеллекта Больницы в регионе Южной Дании стремятся повысить безопасность пациентов, используя аналитические решения и искусственный интеллект SAS.
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Вебинар
ModelOps: операционализация моделей машинного обученияНа этом вебинаре мы расскажем о том, как подход ModelOps позволит вашим моделям пройти ‘последнюю милю аналитики’. В рамках этого подхода у вас появиться универсальный и прозрачный регламент управлениям моделями, включающий этапы разработки, валидации, внедрения и мониторинга.
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Customer Story
Бразилия борется со страховым мошенничеством с помощью ИИ и аналитики.CNSeg полагается на SAS, чтобы препятствовать мошенникам, и повышает точность оповещения на 67%
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Article
Почему менеджерам стоит позаботиться о качественном инструменте для прогнозированияТеперь, когда COVID-19 стал частью нашей реальности, жизненно важно планировать каждый аспект бизнеса. Мы наблюдаем бурный рост спроса на решения для прогнозирования, которые гарантируют последовательность, автоматизацию и повышенную точность.
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Customer Story
Using artificial intelligence to decode dance patterns of beesAmesto NextBridge and Beefutures use visual analytics and machine learning to help protect and support healthy bee populations.
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Article
5 способов измерить здоровье улья с помощью аналитики и потоковых данныхТакой аналитический подход к пониманию здоровья пчелиных ульев может автоматически предупреждать пчеловодов об изменениях в весе улья, температуре, летной активности и многом другом.
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Customer Story
Revolutionizing marketing campaigns with AIAlliant relies on machine learning to create qualified marketing audiences for its clients.
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Вебинар
Новый всплеск страхового мошенничества после COVID-19Вебинар основан на богатом практическом опыте SAS в области создания Аналитических Антифрод-систем для российских и международных страховых компаний.
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Article
Гуманность в искусственном интеллектеЧто происходит, когда искусственный интеллект и люди работают вместе во имя решения глобальных проблем?
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Article
Внутренние ИТ-отделы становятся более значимыми для бизнесаИнновация – это вопрос данных. Это не секрет. Но как компания преобразовывает свои данные в бизнес-модели, чтобы стимулировать изменения?
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Article
Прохождение «последней мили» аналитики в три шагаВнедрение аналитических моделей в производство может быть самой сложной частью аналитического пути. Неудивительно, что эта последняя миля аналитики - внедрение моделей в развертывание - является самой сложной частью инициатив в рамках цифровой трансформации, которую должны освоить компании, потому что она считается наиболее важной.
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Article
Ускоряясь на пути внедрения искусственного интеллекта, подумайте о «качестве дорожного покрытия»ИИ-технология добилась огромных успехов за короткое время и готова к более широкому внедрению. Но поскольку организации наращивают усилия по ИИ, им необходимо проявлять особую осторожность, потому что, как скажет любой сотрудник полиции, даже небольшие выбоины могут создавать проблемы для транспортных средств, движущихся на высоких скоростях.
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Customer Story
Достижения в области здравоохранения, основанные на анализе ДНКВ генетическом исследовании на уровне сообществ для улучшения здоровья населения штата Невада используются машинное обучение SAS и искусственный интеллект.
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Article
Нереализованный потенциал в неструктурированном текстеТекст является крупнейшим источником данных, созданным человеком. Этот источник растет с каждым днем, когда мы публикуем посты в социальных сетях, общаемся с чат-ботами и цифровыми помощниками, отправляем электронные письма, ведем бизнес в Интернете, генерируем отчеты и, по сути, документируем наши повседневные мысли и действия с использованием компьютеров и мобильных устройств.
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Customer Story
Artificial intelligence and IoT analytics keep aircraft operational for crucial missionsLockheed Martin revolutionizes aircraft maintenance with the SAS Platform.
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Article
ModelOps: непрерывное управление жизненным циклом моделиModelOps – методика бесперебойной интеграции аналитических моделей в бизнес, когда модели, созданные командой аналитиков, реализуются в ИТ окружении компании в условиях внесения регулярных изменений и обновлений.
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Article
Машинное обучение и искусственный интеллект в дивном новом миреКак взаимодействует человек и машина в дивном новом мире с ИИ?
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Аналитический отчет
5 Pitfalls to Avoid When Designing an Effective Data and Analytics Organization In this research report, Gartner examines five major pitfalls that significantly inhibit the design of an effective data and analytics organization, then discusses practical steps that data and analytics leaders can take to avoid them.
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Аналитический отчет
Top Strategic IoT Trends and Technologies Through 2023In this report, Gartner examines 10 longer-term IoT technologies and trends that will be important in the 2018 through 2023 time frame.
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Аналитический отчет
SAS is a Leader in The Forrester Wave™: Streaming Analytics, Q3 2017Streaming analytics are critical to building contextual insights for IoT, mobile, web and enterprise applications. Read the report to learn more.
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Аналитический отчет
How Data Science Teams Leverage Machine Learning and Other Advanced AnalyticsGartner's 2017 customer reference survey for data science and machine learning platforms reveals how many organizations are undertaking data science initiatives.
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Article
Демо глубокого обучения для обнаружения опухолей печени при КТ-сканированииЭто пятый и последний пост в моей серии постов о модели глубокого обучения, которую я разработала для обнаружения опухолей в 3D КТ-сканировании печени. Эта статья посвящена точности модели и финальной демонстрации проекта.
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Article
Доработка модели глубокого обучения для обнаружения объектовЭто четвертый пост в моей серии публикаций о проекте компьютерного зрения, над которым я работала, чтобы идентифицировать опухоли печени при КТ-сканировании.
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Article
Построение передней части пайплайна компьютерного зренияЭто третий пост, описывающий проект компьютерного зрения, над которым я работала в SAS для выявления опухолей печени при КТ-сканировании. Сегодня я расскажу об обработке данных для данных изображений.
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Article
Как использовать ИИ для выявления ракаНедавно мне предоставили удивительную возможность поработать над проектом в области биомедицинской аналитики изображений в сотрудничестве с крупным университетским медицинским центром. Целью проекта была разработка системы компьютерного зрения, которая будет выявлять опухоли при компьютерной томографии печени.
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Article
Как ИИ и углубленная аналитика влияют на отрасль финансовых услугВедущие эксперты SAS обсуждают темы, которые волнуют мошенников и не дают спокойно спать руководителям компаний.
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Article
ИИ в производстве: новые возможности для информационных и операционных технологийОпрос об ИИ показывает, что лидеры и первопроходцы в ИИ достигают значительных успехов, выявляют и расширяют возможности работы с ИИ, используя все больше и больше отделов в своих организациях.
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Article
Insights Page
Искусственный интеллект - Что это такое и почему это так важноИскусственный интеллект (ИИ) позволяет компьютерам обучаться на собственном опыте, адаптироваться к задаваемым параметрам и выполнять те задачи, которые раньше были под силу только человеку.
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Article
Машинное обучение для чайников (и не только)10 советов для тех, кто хочет преуспеть в области машинного обучения
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Article
ИИ в банковской сфере: опрос раскрывает факторы успехаЧто банковские руководители говорят о своем опыте работы с ИИ? На чем они сосредоточены сегодня? Что работает? Какие у них планы на будущее?
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Customer Story
Zeroing in on property values with machine learningArtificial intelligence improves assessment accuracy and productivity in Wake County.
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Customer Story
Поиск лучших клиентов с помощью аналитикиSeacoast Bank enhances customer value using AI and SAS Visual Analytics on SAS Viya.
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Article
Этика ИИ: 3 шагаБудет ли искусственный интеллект полезен человечеству или приведет к ряду нежелательных последствий? Этика ИИ может быть одним из гарантов использования искусственного интеллекта во благо.
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Article
Data Lineage делает искусственный интеллект умнееРазработайте стратегию управления данными с использованием Data Lineage и дайте возможность ИИ полностью раскрыть свой потенциал.
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Article
Чат-боты: что это такое?Чат-бот – это форма разговорного искусственного интеллекта, предназначенная для упрощения взаимодействия человека с компьютерами. Используя чат-ботов, компьютеры могут понимать и реагировать на приход человека через устную или письменную речь.
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Article
Гид: алгоритмы машинного обучения и их типыТермины «Машинное обучение» и «Искусственный интеллект» часто путают между собой. На самом деле, машинное обучение входит в область искусственного интеллекта. Ещё машинное обучение порой путают с прогнозной аналитикой (или предсказательным моделированием).
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Article
Инновационные технологии с помощью Интернета вещей и искусственного интеллектаКто знал, что анализуя данные Интернета вещей можно найти лучший способ пробурить скважину? Или найти более быстрый способ остановить мошенничество в сфере здравоохранения?
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Article
What do drones, AI and proactive policing have in common?Law enforcement and public safety agencies must wrangle diverse data sets to be effective in their operations. Intelligence analysts are using that data to apply machine learning and AI for more proactive policing.
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Вебинар What is the value of contextual customer engagement in telecommunications?
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Вебинар Machine learning, prediction and optimization techniques
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Вебинар Boost the value of your Call Center logs through Advanced Analytics
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Article
Student lands dream job with help from SASA strong partnership between the University of Alabama and SAS put Cameron Jagoe on a path that led to his dream job with US Bank.
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Вебинар Advancing Telecommunications with Artificial Intelligence
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Вебинар Using Machine Learning on raw transactional data to find customers’ moments of truth in Telco
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Article
Искусственный интеллект, машинное обучение, глубокое обучение, и что все это значитПонимание технологий искусственного интеллекта и того, как они ведут к созданию умных приложений
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Introduction to machine learning: Five things the quants wish we knewMachine learning is gaining momentum thanks to bigger, more complex data sets. How does it work? Kimberly Nevala from SAS Best Practices explains what it is by focusing on what it isn't.
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Article
Как API-интерфейсы изменят роль специалистов по data science?Интерфейсы прикладного программирования, или API-интерфейсы, способны коренным образом изменить лицо аналитики.
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Article
5 steps to sustainable GDPR complianceFollow these steps to achieve GDPR compliance by the May 2018 deadline – and get added benefits along the way.
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Article
Stopping the Zika virus: The potential of big data, analyticsHow do you stop global outbreaks? The answer may be in the data about the disease and how it spreads.
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Article
Ваш персональный data scientistImagine pushing a button on your desk and asking for the latest sales forecasts the same way you might ask Siri for the weather forecast. Find out what else is possible with a combination of natural language processing and machine learning.
IDC MarketScape vendor analysis model is designed to provide an overview of the competitive fitness of ICT suppliers in a given market. The research methodology utilizes a rigorous scoring methodology based on both qualitative and quantitative criteria that results in a single graphical illustration of each vendor’s position within a given market. The Capabilities score measures vendor product, go-to-market and business execution in the short-term. The Strategy score measures alignment of vendor strategies with customer requirements in a 3-5-year timeframe. Vendor market share is represented by the size of the icons.