January 18, 2023
- LEAD ARTICLE: For AI, Synthetic Data Is Anything but Fake News
- FEATURE ARTICLE: Artificial Intelligence, Part 1: Understanding Data
- FEATURE ARTICLE: Artificial Intelligence (AI) Use Cases
- NEWS HIGHLIGHT: Businesses Plan to Invest in Tech in 2023, Despite Economic Headwinds
- NEWS HIGHLIGHT: IBM Launches New Way to Partner Through IBM Partner Plus
- WHITE PAPER: 2022 IBM i Marketplace Survey Results
- EVENT: 5 IBM i Security Quick Wins
AI apps must be trained to evaluate data. However, some data uses are restricted by law or the logistics of gathering it. These difficulties created a need for synthetic data, and the market is providing it.
By John Ghrist
To most people, “synthetic data” sounds like a paradox, or at least a contradiction in terms. Synthetic is something made up, and data is presumed to be a collection of facts. In the realm of AI, though, synthetic data is not only real, it has become a critical tool. In fact, it is becoming so important that it may actually surpass the use of real data for training AI apps by the end of this decade, according to at least one prediction. Any enterprise that plans to use AI at some point will have to embrace this concept with the confusing name, if not become an outright consumer of synthetic data.
This article series is designed to provide you with an introduction to the basic concepts of artificial intelligence (AI), machine learning (ML), and deep learning (DL), as well as introduce you to some of the terminology that is frequently used in discussions regarding this technology. This is not a deep dive into AI, ML, and DL but rather a “dictionary” of AI, ML, and DL topics and terms.
By Roger Sanders
The information provided is NOT intended to make you an AI, ML, or DL expert. Nor will it show you how to build, train, and deploy ML and DL models. Instead, it will give you a good foundation in AI, ML, and DL and help you understand some of the terminology you are likely to encounter in discussions, presentations, papers, and books on the subject.
This article series is designed to provide you with insight on the ways artificial intelligence (AI), machine learning (ML), and deep learning (DL) can be (or already are being) utilized in a variety of industries.
By Roger Sanders
Although artificial intelligence (AI), machine learning (ML), and deep learning (DL) have been around for more than half a century, we still aren’t anywhere close to being able to create complex machines that possess all the characteristics of human intelligence. However, we have learned how to get computers to perform certain tasks – especially repeatable tasks – as well as, or in some cases, better than human beings. And, we have learned how to embed AI, ML, and DL into business processes to generate insights that can have a profound impact on the way an organization sets themselves apart from their competitors.
Explore the main considerations you should be aware of before embarking on a (migration or modernization) project. Take a deeper dive into business motivations and factors that could potentially influence your decision to migrate or modernize your existing IT platform and its risks.
More than ever, there is a demand for IT to deliver innovation.
Your IBM i has been an essential part of your business operations for years. However, your organization may struggle to maintain the current system and implement new projects.
The thousands of customers we've worked with and surveyed state that expectations regarding the digital footprint and vision of the companyare not aligned with the current IT environment.
Have you been wondering about Node.js? Our free Node.js Webinar Series takes you from total beginner to creating a fully-functional IBM i Node.js business application.
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In addition to background information, our Director of Product Development Scott Klement will demonstrate applications that take advantage of the Node Package Manager (npm).
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Technology spending is expected to remain steady in the coming year, despite ongoing concerns about the global economy. That’s the theme that emerged from a recent survey that IBM commissioned from Morning Consult. The report dives into the investment strategies of 4,000 global business leaders and found that more than three-quarters plan to prioritize or invest in technology in the next 12 months, a steady pace from 2022.
By Kathryn Guarini | CIO
Heading into 2023, technology buyers have clear directives and holistic plans to invest in infrastructure, build AI services on top of that infrastructure for a better employee and customer experience, secure their entire digital ecosystem, and make their entire business more sustainable and resilient.