In January, IBM announced that it was merging the artificial intelligence [AI] tools of fellow tech powerhouse, Google, with its own cognitive computing technologies.
The aim of the move is to allow its deep-learning systems to more accurately come up with answers for thorny questions.
Meanwhile, also at the turn of the year, Apple became the latest tech company to sign up to the Partnership on AI alliance, joining rivals such as Google, IBM, Microsoft, and Facebook to help advance research and development of AI technologies.
Such high-level cooperation among traditional competitors illustrates just how important this capability has become in the modern IT market.
Deep-learning, AI, machine learning – whatever you want to call it – is making its way into the mainstream technology mix, both in the consumer world and the enterprise.
This technology is already all around us.
You know those annoying live chat windows that pop up on some websites to ask you if you need help? Yep, the chatbots behind those are often powered by machine learning technology.
Do you have a personal assistant on your phone? If you’ve got an Apple iPhone or a Google Android- powered phone, you do. Those are driven by various forms of AI, machine learning, and cognitive platforms as well.
Many of these capabilities are now nestled in the cloud offerings of companies such as Google, IBM, Microsoft, Amazon Web Services (AWS), and Oracle, giving way to the emergence of the intelligent cloud.
The intelligent cloud, as it currently stands, comes in many shapes and sizes, with different aspects of cloud-based intelligent learning technology being presented in a variety of offerings that lend themselves to different applications and solutions.
Still early days
For many IT providers, cloud-based AI and machine learning represents a new frontier that promises to offer fresh opportunities as the market catches on to the technology. But it also requires a host of new skills and capabilities for partners to make the most of it.
For Rod Bryan, lead partner of KPMG Australia’s cognitive and AI business division, Solution 49x – which partners heavily with IBM for its Watson cognitive capabilities – it’s still early days for the technology.
“I think we’re at the beginning of a totally revolutionary timeframe,” Bryan said. “These technologies are so fundamental to the way organisations need to change, and some of the change will be good; it introduces efficiencies and capabilities we could only dream of a number of years ago.”
While Bryan concedes that many industries are still coming to grips with the impact of the intelligent cloud, and that its uptake is likely to lead to some social disruption, it’s growing quickly.
This serves as encouraging news for partners in a position to tackle this new technology, but a new approach may need to be adopted.
“It’s different to a typical IT or system integration implementation,” Bryan said. “This is more of a business transformation where IT is a true partner rather than an owner.
“And the reason it has to be that way is because these implementations are not like the fundamental provision of a core capability, like a billing system or a CRM system.”
At present, many intelligent cloud projects begin life as a proof-of-concept or an experimental trial. They often end that way, too, according to Bryan. The trick is in proving its value.
“The biggest challenge is in bringing the required skill-sets together to move it [the project] from trial into production in a way that demonstrates the robustness that any good IT shop and its business partners would expect.”
The likelihood that a project drawing upon cloud- based AI or machine learning will make it only as far as a proof-of-concept trial has, until recently, remained relatively high for Daryl Wilding-McBride, chief technology officer of AWS partner, DiUS.