Artificial intelligence is on the verge of changing the world, so much so that Port Technology has made it a key theme for its Container Terminal Automation Conference in 2018.
This year may not see the technology start to affect our daily lives, but important companies in the supply chain have already started investing in its development.
One of the biggest stories to land on PTI’s news desk was the joint venture between A.P. Moller – Maersk and IBM, which will provide more efficient and secure methods for conducting global trade using blockchain technology and other cloud-based open source technologies including AI, IoT and analytics.
We recently found out from Dr. Yvo Saanen, Commercial Director and Founder of TBA — an industry-leading consultancy, simulation and software specialist for ports, terminals and warehouses, that the quality of data in the shipping industry will hinder its adoption of AI technologies.
But, to find out what may come in 2018, read an extract below from best-selling author and keynote speaker on business, technology and big data, Bernard Marr, who has shared his AI predictions for the year — first published by Forbes.
1. Less hype and hot air about AI – but more action
With any breakthrough technology comes hype. As the arrival of functional and useful AI is something that has been predicted for centuries, it’s hardly surprising people want to talk about it, now it’s here.
All the indicators show that investment into the development and integration of AI and, in particular machine learning, technology is continuing to increase in scale.
And importantly, results are starting to appear beyond computers learning to beat humans at board games and TV game shows.
I expect 2018 to provide a continuous stream of small but sure steps forward, as machine learning and neural network technology takes on more routine tasks.
2. More money will pour into AI enterprise projects than ever before
Spurred on by the successes achieved by innovators and market leaders in 2017, more and more businesses will launch initiatives involving AI.
With self-driving cars and ships, as well as life-saving medical advances on the horizon, it seems likely that the speed of technological change is only going to increase as the decade draws to a close. For many CEOs and CTOs, acting on the potential for change that has become available is an increasingly urgent priority.
3. A lot of AI projects will fail, in a costly manner
This is a sad fact about many projects involving new and often untested technology and has existed down the ages. In some cases it’s down to the risks accepted by every pioneer.
When working on a new frontier the only certainty is that there will be unforeseen difficulties. Machine learning algorithms may be great at thinking of new ways around problems, and may even seem able to predict the future, they are unlikely to foresee or react to many of the internal and external factors which could influence success.
These could include management and workforce buy-in, legal, political or economic developments, the activities of competitors and the ability of business and data-centric teams to cooperate.
A vagueness or lack of focus around the aims and expectations of an AI initiative is often a cause of failure. The hard truth is that AI is tough, and often expensive. A trend towards “plug and play”, as-a-service solutions may have opened the floodgates for organizations with less than global-scale resources to think about integrating AI.
However, it also risks encouraging a “one-size-fits-all” or templated approach to data science, which may not be appropriate for every organization’s aims.
The initiatives and projects most likely to succeed are those which are envisaged from the start with a clear strategy, and with results clearly tied to bottom-line KPIs such as revenue growth and customer satisfaction scores.
4. The way we interact with machines will continue to shift towards voice
Just as Echo and Alexa have invaded our homes, conversational interfaces will become increasingly common when it comes to interacting with technology in a business environment.
According to one report, next year 20% of firms will look to add voice enabled interfaces to their existing point-and-click dashboards and systems.
After all it’s the way most of us communicate most naturally – we can generally structure any query in a matter of seconds. As computers have become more adept at understanding us, there’s less need for us to spend time learning their complicated mathematical languages.
Natural language generation and natural language processing algorithms are constantly learning to become better at understanding us, and talking to us in a way we understand.
Throughout 2018 this will continue to improve and we should get used to robots which we can converse with, within limited parameters, just as we would with another human.