Imagine having a magic ball to foresee things about your business. What would you do?

Maybe you’d like to know exactly what your users are looking for, so you could better serve them. Or, you’d want to know what prices will bring you the most profit on a given day. Perhaps, you’d like to catch the ill-intentioned users even before they do any harm to you and others on your platform.

What if I tell you it is possible? Shared economy leaders use machine learning for eCommerce and p2p marketplaces to do these and many other great things that have a direct impact on their success.

Robots will never displace humans in the ability to be empathic and passionate. And actually, we do not need them to do this. Let’s save emotions for humans and delegate routine work of systematization, search and calculation to computers, while we focus on extraordinary tasks that need all our involvement, communication talent, analytical abilities, and understanding of feelings.

Charity and nonprofit organizations, on the one hand, work to appeal to people’s real feelings (caused by their needs and deeds) and, on the other hand, need to complete the quite ordinary tasks of collecting donations, keeping documentation, sending out emails. Here we’ll discuss how automation can improve nonprofit.

Are you tired of routine in your charity organization? Ready to change it?

“When you think about recommending something to someone, there’s a real business reason why you might want to do that.” - Jack Chua, Director of Data Science at Expedia.

Machine learning recommendation systems are not just a trendy feature of online stores. It is a mighty tool that can propel your business to the next level if used strategically. No wonder Jack Chua suggests always having “a great tie-in to the underlying KPI of what you want to drive”. For example, increase sales, customer retention, cross-selling, and so on.

If you’re still hesitating on how exactly to use recommendations to invigorate your business, we invite you to learn from the experience of those who already made it work brilliantly!

We collected the best examples of machine learning implementation in recommenders (including our own development projects) and explain in plain English how to build a machine learning recommender system from scratch. Are you in?

The healthcare sector, despite being the largest repository of data in the world, lags significantly behind other industries in adopting artificial intelligence (AI) technologies. This gap presents a substantial opportunity for innovation and investment.

According to Statista, the AI healthcare market, which was valued at $11 billion in 2021, is expected to soar to an impressive $187 billion by 2030. This rapid growth indicates a shift in the operations of medical providers, hospitals, pharmaceutical companies, and biotech firms, making now an opportune time for startups to engage with this technology.

In this article, we will explore practical AI use cases in healthcare, identify key challenges, and provide insights into the AI healthcare app development process. Whether you're developing new tools or improving existing ones, we will help make your idea real.

What do Google, IBM, Unilever, and IKEA have in common, besides being market leaders? They, along with a handful of others, are trailblazers that have been applying artificial intelligence in human capital management for years already, and they have done so successfully!

Regardless of whether you believe in the ‘Terminator’ scenario or not, right now machine learning can give your company a real competitive edge in talent management.

In the business world, keeping up with new trends is like catching a train - you need to go really fast to make it. So let’s learn how to become one of the pioneers in ChatGPT plugin development. We, at Greenice, have experience in working with different GPT technologies and are ready to help you tame them. So let’s begin!