Unleashing AI: Machine Learning as a Service

Business

Business Access to new subscription AI tools to transform data science.

In the past, the data most companies dealt with was mostly structured and small in size, which meant it was relatively easy to analyze using simple business intelligence (BI) tools. Today, however, that’s no longer the case. Much of the data that organizations mine is unstructured or semi-structured, and this trend is growing; by 2020, more than 80% of enterprise data is expected to be unstructured. [1].

Moreover, the rate at which this data is being generated is only expected to increase in the future, with IDC predicting that the amount of data in the world will grow from 33 zettabytes (ZB) in 2018 to 175ZB by 2025. [2].

Simple BI tools are no longer able to handle this sheer volume and variety of data. Therefore, more advanced analytical tools and algorithms are required to deliver the meaningful, actionable insights that businesses need. To meet the demand for insights that drive faster, better decisions, data scientists are turning to artificial intelligence (AI), machine learning (ML), and cognitive computing technologies to take analytics to the next level.

No organization can afford to fall behind. As a result, IDC predicts that worldwide spending on AI and cognitive computing will reach $77.6 billion in 2022, more than triple what it was in 2018. [3]Meanwhile, total global business value from AI is predicted to reach $3.9 trillion over the same period, according to Gartner. [4].

Business The emergence of MLaaS

Implementing AI technologies such as ML is difficult: they require highly specific and in-demand skill sets, as well as specialized IT infrastructure and software tools, and can also require a sound data strategy — all of which translates into significant upfront investments that can be cost-prohibitive for many businesses.

To address this challenge, vendors have begun offering machine learning as a service.

As the name suggests, MLaaS is a subscription-based model that provides access to AI tools, much like many business applications are currently delivered in a Software-as-a-Service (SaaS) model. These AI services range from developer tools to data pre-processing and model training to fully trained, ready-to-use models that can be accessed via APIs and integrated into business workflows.

With the advent of MLaaS, instead of investing in creating their own AI resources, companies can rely on vendors to provide an easy, low-cost ecosystem that can be customized to fit their needs. This heralds a new era of data science, one in which AI tools are easier to use and available to a wider range of companies and roles within organizations. Click here to learn more. The full article is available on their website.

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