AI

What’s a data mart and why data scientists should use onePhoto by Dima Valkov from PexelsAs a data scientist, you can spend up to 80% of your time cleaning and transforming data in order to generate actionable insights and build machine learning models to create business impact. Now imagine a world where you can spend more time on analysis and model development instead of cleaning data. This can become a reality by having a data mart defined as a subset of data within a data warehouse developed for a specific group of…

Artificial intelligence (AI) has opened new capabilities for businesses with a diverse set of use cases across sectors. To achieve the best results in tackling complex business problems, companies often combine different AI with other analytical techniques. Composite AI, also known as multidisciplinary AI, is the emerging term for integrating different AI technologies into a single solution in a systematic way to approach complex business problems holistically. What is composite AI? Composite AI is an approach to solve…

As the applications of artificial intelligence (AI) start to affect our everyday life from self-driving cars to product recommendations, it can become easy to be misled by myths and misconceptions about the technology. These myths can lead to a reluctance to adopt AI technologies in businesses or to unrealistic expectations from AI applications. We list five popular myths and the realities behind them: Myth 1: Artificial intelligence, machine learning, and deep learning are the same things AI refers to a broad class of…

Claims processing is one of the most important insurance operations. 87% of customers say that the effectiveness of claims processing influences their decision to choose a vendor (see Figure 1). Figure 1: Claims processing influence on customers Source: EY Before the introduction of AI/ML models, most claims processing tasks were done manually. As a result, insurance companies spend too much time and labor on this process. In addition, human labor is prone to errors and is not capable of working 24/7. Therefore,…

As the figure above illustrates, the number of parameters (consequently the width and depth) of the neural networks increase, which indicates greater model size. To derive meaningful results from existing… The post Top 10 AI Chip-makers of 2022: In-depth Guide first appeared on AIMultiple: High Tech Use Cases & Tools to Grow Your Business. As the figure above illustrates, the number of parameters (consequently the width and depth) of the neural networks increase, which indicates greater model size. To derive…

Both the number of parameters and size of models (see Figure 1) that refers to width and depth of the neural networks is skyrocketing.  Richer data means better predictive capabilities for businesses to anticipate customer preferences, trends, fraud, the climate – anything, really. But to analyze the data more effectively, companies need more computing power. Accelerated computing provides the computing power businesses need. In this article, we will introduce accelerated computing and its challenges in detail. Figure 1.…

Customers have more options than ever due to increasing competition and the quality of customer service has become one of the key factors for businesses to stay ahead of the competition. According to studies: A third of customers would walk away from a brand they love after a single bad experience.70% of customers would recommend the brand to others after a positive experience. AI applications in customer services such as chatbots and personalization help businesses to understand their customers better and improve…

Introduction Natural Language Processing (NLP) offers a plethora of use cases that your business can benefit. As a cutting-edge research field, methods to improve NLP models and use cases are constantly being developed. If you come across to one of those methods called data augmentation, you may hear many positive comments about it but resources to understand what this method actually does may still sound too technical. In this article, we will break down this technical concept into a simple definition, how it can be…

Web scraping has transformed many business processes, but it also has many technical challenges. The end-to-end process of collecting web data can be demonstrated as in Figure 1. Figure 1: Technical steps of web scraping in a snapshot When the number of pages and the complexity of websites to be scraped increase, each of these steps face with unique challenges. Artificial intelligence methods help web scraping to overcome the unique challenges of each step. In this article, we will introduce you the top 3 ways that AI…

AI has numerous applications in the healthcare industry, and it continues to grow with technology advancements. However, this field also has some limitations that hold AI back from being integrated into the current healthcare systems. We will explore how you can overcome these challenges to boost healthcare with AI. Understand how and why AI comes up with specific results AI models become more complicated to deliver better outcomes. This complexity causes AI to work in a “black-box,” where it becomes harder to understand…