Model drift refers to the phenomenon that occurs when the performance of a machine learning model degrades with time. This happens for various reasons, including data distribution changes, changes in the goals or objectives of the model, or changes to the environment in which the model is operating. There are two main types of model drift that […]
2023 Predictions: Breakthroughs Incoming for AI and Data Science
Surprising though it may sound, most AI business applications remain rudimentary. Some industry spectators believe the market is flush with cutting-edge AI breakthroughs. But in truth, many providers mislabel rules-based tools – including robotic process automation (RPA) – as AI and ML. Seasoned DevOps teams and software engineers know that RPA – although useful in […]
AI and Machine Learning Trends to Watch in 2023
This article highlights 10 of the biggest trends triggered by technological advancements in artificial intelligence (AI) and machine learning (ML). These trends have collectively revolutionized the way businesses approach everything from education and economics to the environment. The broad AI and machine learning trends include the provisioning of cloud platforms for data activities – accelerating the use […]
What to Expect from AI, Data Science, and Wearables in Health Care in 2023
AI and data science have remained areas of focus in the last year and will continue to be top of mind for many tech companies in the coming year. Wearables, especially those with health monitoring capabilities, have also grown abundant as medical and consumer companies alike ramp up their offerings in response to increased demand. […]
Understanding the Five Tenets of Intelligent Automation
Data-driven decision-making is a critical aspect of modern business operations, with most organizations leveraging enterprise applications to execute their business processes easily and effectively. However, the users of these tools have historically needed to make a majority of their decisions manually, outside the software, creating inefficiencies that have a negative impact on operations. Businesses are […]
How Federated Learning Is Helping to Overcome Obstacles in Machine Learning
Federated learning is a machine learning technique that allows multiple parties to train a model without sharing their data. It is being used across several industries, from mobile device keyboards to health care to autonomous vehicles to oil rigs. It is particularly useful in situations where data sharing is limited by regulation, or is sensitive or proprietary, […]
Goodbye Dashboards: How Modern BI Tools Are Being Used to Analyze Data
Not all that long ago, the only way for businesses to readily access their data was through dashboards. And, even then, these predefined and static dashboards provided data that was restricted only to citizen data scientists and data analysts. Standalone, static dashboards also inadvertently distract users and force them to shift their focus from their typical tasks […]
2023 Predictions for AI, Machine Learning, and NLP
It’s been an exciting year in AI, machine learning, and NLP, with text-to-image generators and large language models delivering some very impressive results and a lot of promise for the future – while noting all of the important caveats about their shortcomings including mitigating societal biases, the possibility of them being used to generate “fake […]
Semantic Technology Trends in 2023
The trends of semantic technology are based on the desire to improve the computer’s understanding of data. The goal of combining semantic technology with a computer system is to discover relationships within the data. Semantic technology can be described as tools and methods that can process, categorize, and find patterns in the data. Semantics is […]
Merging Fast and Slow Data for a Full View of Human Intent
The digital industry has evolved massively and consistently over the years, often taking off in surprising directions. But one thing has remained constant: The role that data plays in driving business success has only grown. Looking toward the future, data-driven decision-making is an increasingly complex process, involving more and varied sources of data to stay ahead of […]