If you thought that mobile communications and the Internet have drastically changed the world, just wait. Coming years will prove to be even more disruptive and mind-blowing. Over the last few years, cloud computing has been lauded as the next big disruption in technology and true to the fact it has become a mainstream element of modern software solutions just as common as databases or websites; but is there a next phase for cloud computing? is it an intelligent cloud?
Artificial intelligence (AI) is the type of technology with the capacity to not only enhance current cloud platform incumbents but also power an entirely new generation of cloud computing technologies. AI is moving beyond simple chat applications like scheduling support and customer service, to impact the enterprise in more profound ways; as automation and intelligent systems further develop to serve the purpose of critical enterprise functions. AI is bound to become ubiquitous in every industry where decision-making is being fundamentally transformed by ‘Thinking Machines’. The need for smarter and faster decision making and the management of big data is the driving factor behind the trend.
Remember Moore’s Law? In 1965, Intel’s co-founder, Gordon Moore observed that the transistors per square inch on integrated circuits had doubled in number each year since their invention. For the next 50 years, Moore’s Law was maintained. In the process, multiple sectors like robotics and biotechnology saw remarkable innovation because machines that ran on computers and computing power all became faster and smaller with time as the transistors on the integrated circuits became more efficient. Now, something even more extraordinary is happening. Accelerating technologies such as big data and artificial intelligence are converging to trigger the next major wave of change. This ‘digital transformation’ will reshape every aspect of the enterprise, including cloud computing.
Artificial intelligence (AI) is expected to burgeon in the enterprise in 2017. Several IT players, including today’s top IT companies, have heavily invested in the space with plans to increase efforts in the foreseeable future.
Despite the fact that AI has been around since the 60’s, advances in networking and graphic processing units, along with demand for big data, have put it back at the forefront of several companies’ minds and strategies. Given the recent explosion of data from Internet of Thing (IoT) and applications, and the necessity for quicker, real-time decision making, AI is well on its way to becoming a key differentiator and requirement for major cloud providers.
In a market that has for the longest time been dominated by four major companies – IBM, Amazon, Microsoft, and Google –an AI first approach has the potential to disrupt the current dynamic.
“I think we will evolve in computing from a mobile-first to an AI-first world.”
-Sundar Pichai, Chief executive of Google
The consumer world is not new to AI-based systems; products like Siri, Cortana and Alexa have been making our lives easier for a while now. However, the enterprise applications for AI are completely different. An AI first enterprise approach should be designed to allow business leaders and data professionals to organize, collect, secure and govern data efficiently so they can gain the insights they require to become a cognitive business. In order to maintain a competitive advantage, businesses today have to get insights from data; however, acquiring those insights is complex and requires work from skilled data scientists. The ability to predict strategic and tactical purposes has evaded enterprises due to prohibitive resource requirements.
Cloud computing solves the two largest hurdles for AI in the enterprise; abundant, low cost computing and a means to leverage large volumes of data.
Today, this new breed of Platform as a Service (AIaaS) can be applied on all the data that enterprises have been collecting. Major cloud providers are making AI more accessible “as-a-service” via open source platforms. For enterprises with an array of complex issues to solve, the need for disparate platforms working together can’t be ignored. This is why making machine learning and other variations of AI applications and technology available via open source is critical to the enterprise. By leveraging AI-as-a-service, businesses can innovate solutions that solve infinite problems.
As machine learning becomes more popular as a service, organizations will have to decide the level at which they want to be involved. While the power of cognitive intelligence is undeniably high, wanting to use it and being able to use it are two completely different things. For this reason, most companies will opt to use a PaaS vendor to manage their entire cycle of data intelligence as opposed to an in-house attempt, allowing them to focus on powering and developing their applications. When looking for an AI provider, you have to ask the right questions. The ideal vendor should be in a position to elucidate both how they handle data and how they intend to solve your specific enterprise problem.
There are multiple digital trends that have the potential to be disruptive; the only way to guarantee smarter business processes, more agility, and increased productivity is by planning ahead for the change and impact that is coming. The main differentiating factor between competing vendors in this space will be how the technology is applied to improve business processes and strategies.
Author: Gabriel Lando
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