Using technology is a fundamental right that all people have. That’s not a pronouncement of law, a fundamental truth, or even a declaration of de facto general public understanding. The consensus is that this is the case. In the last three articles of the series dedicated to AutoML, we highlighted the technical aspects of the …
We hope that the first two articles of our AutoML series would have given you a good idea about AutoML, its workflow, pros and cons and the way it add value to a business’s deployment of AI technology and business model. This article will take you through the same in terms of practical use cases …
In the first article of our series dedicated to AutoML, we explored what AutoML is all about and how it works; however, the way AutoML lets businesses upscale the AI is another important aspect to discover for AutoML learners, deployers, experts and professionals. In this article, we will highlight what is meant by democratizing AI …
According to Forrester’s recent research, 61 percent of data and analytics business decision makers who deployed AI, stated that they had either implemented or are in process of implementing AutoML software. This is because AutoML has the potential to up-scale the AI at any business. When machine learning algorithms are automated, the results are more …
Here are Four Companies That Are Using or Trying to Incorporate Data Mesh 1. Intuit Zhamak Dehghani’s data mesh concept caught the eye of Intuit, a global tech platform that creates business software for individuals, accountants, and small businesses. As such, the company has endeavored to apply its own data mesh strategy to its data …
Before fully embracing data mesh for your organization, take note of a few key considerations. In this article, we’ll discuss the things you should take into account, as well as share real-life examples of companies that are leveraging the capabilities of data mesh. Four Key Considerations Prior to Implementing Data Mesh Within Your Organization 1. …
Data Mesh Primer – Part 3: Key Considerations Before Implementation Read More »
In part one of this series, we gave a general introduction to Data Mesh and why should organizations consider using this new technology. Today, we’ll continue exploring. Data Mesh vs. Data Fabric A data fabric is one approach to data integration that allows for data orchestration, while a data mesh follows a decentralized data architecture …
Data is a key driver of progress and innovation. In an ideal setting, it should be scalable and accessible. As organizations expand their operations, there’s also a growing need to better manage and utilize all your available data. However, your current data architecture may be preventing you from effectively and efficiently utilizing data and making …
AI systems are evolving at neck-breaking speeds. They aren’t just handling human tasks more efficiently, they also take on responsibilities that we can’t do. Such roles include providing relevant and instant recommendations to consumers or reviewing and approving hundreds of bank transactions at once. Moreover, there’s a growing need for automated systems to help industries …
Strategies for Trustworthy AI Selection and Building Team Trust Read More »
Traditional AI solutions are built on models that learn how to handle data in a certain way for real-world applications. Models generally consist of a training channel for collecting and grouping data and a prediction channel that establishes patterns as it analyzes these data. However, these models are fixed or static, so they either become …
