As more businesses are incorporating AI and ML into their strategy to reduce costs and create better products, they are gaining a competitive advantage over those holding on to traditional means of operation. Employed effectively, AI and ML will provide tide-turning returns for companies. If you’re looking to introduce AI into your business strategy, how do you choose the most effective business cases? How do you measure the empirical value?
As AI is increasingly adopted globally, it is vital to consider how AI can bolster your business. Gartner predicts that by 2020, 85% of customer interactions will be managed without a human. While AI is no silver bullet, when applied effectively, it can enable businesses to tune their customer interaction, marketing, and product design to competitive levels.
Most people have heard of blockchain in conjunction with cryptocurrencies such as Bitcoin or smart contracts like Ethereum. While these applications demonstrate blockchain’s disruptive power, its decentralized, trustless technology has the power to do so much more for businesses and brands everywhere .
Testing is the most critical step of any successful machine learning project. It demonstrates whether your algorithms, weights, biases, and labels are correct or need to be improved. Read our white paper to learn the 10 critical steps to ensure successful testing of your machine learning application.
You have likely felt the buzz in the business community about artificial intelligence (AI) – how it is transforming every business process from sales and marketing to customer service and throughout the entire supply chain. But despite all the talk, only one in five executives have deployed an AI solution to support core aspects of their business. The best place to start is find the right partner who has the experience, team and confidence to overcome the barriers.
Having grown up as Generation Y and watching technology grow at what seems like hyper speed, I can’t describe just how interesting it has been watching each generation interact with new technology, new devices and how much the latest generation (Millennials) has influenced the rapid request for change across many industries.
Machine Learning is creeping into companies of all sizes and I’ve found that many of those who want to implement it are those who aren’t in IT. Business clients are able to explain the results of machine learning within an application or set of applications, yet have trouble understanding exactly what machine learning actually is, how it works and why it takes longer than they think to get the results they want.
