2017 has been a year of significant hype for AI, with the Wall Street Journal calling it ‘the year of AI’, and this isn’t about to change as we head towards 2018. Yoshua Bengio said to us earlier this year ‘there’s no doubt that we will reach human level AI but we don’t know how long it’s going to take’, so we will see academic institutions and industry alike striving to push forward progressions to move closest to this goal. Whilst we’re not there yet, AI is already part of our everyday lives with AI assistants on our smart phones and in our homes, so what’s in store for 2018?
More and more businesses will realise the benefit of AI and will be implementing these technologies, augmenting human intelligence to improve efficiency. Most companies will be focusing on data-driven machines and ‘businesses will be turning to machine learning to process, trend, and analyze the information. Indeed, machine learning AI isn’t just a nice-to-have in 2018; it’s a must-have.’
Nikita Johnson, RE•WORK: In 2018 I expect to see the infiltration of smart automation into a wide variety of companies from traditional manufacturing organizations to retail, to utilities. With the continued increase in data collection and analysis, the need for an enterprise-wide automation system strategy will be vital. This will allow companies to invest in a longer-term plan for AI and to ensure it is a priority for future growth and efficiency.
Investment will continue as VCs from both tech and non-tech sectors continue to see the potential of AI - It’s the next step in our evolution to unleash and utilize full potential of data – whether sitting within an organization or connecting to external industry sources and macro-economic trends or data coming from sensors and devices. We expect insights from such data will be automated 70-80% of the time through training and learning. But it will require the right human skills and feedback loop aligned with technology advancements. Human expertise will continue to be required in this journey and we will see more focus shifted to strategic decision making—Subrata Chakrabarti, VP of Product Marketing and Strategy, Anaplan.
Gil Press, Forbes: ‘2018 is the year that AI becomes packaged and provided to the rest of us in ways that do not require a computer science degree’
AI Assistants will become more prominent in industry as well as in home devices as ‘humans simply can’t keep up with the speed at which technology—and customer demands—are moving.’ It’s estimated that 20% of business content will come from AI by 2018, and 75% of developer teams will use AI technology in one or more business applications or services by 2018. People will be able to offload their work to AI assistants to allow employees to focus their time and energy on the more creative aspects of their roles. This also includes the improved understanding that voice assistants such as Siri will have through both the improvement of NLP and far-field voice recognition.
Nathan Benaich has listed the 6 areas of AI and machine learning to watch closely as Reinforcement Learning, generative models, networks with memory, learning from less data and building smaller models, hardware for training and inference, and simulation.
The production and testing of autonomous vehicles will continue:
Healthcare is one of the industries that will be impacted most drastically by AI. Already there are products like the NHS’s ‘GP at Hand’ powered by Babylon Health, and we will see advances in medical imaging, diagnostics, drug production and disease prediction. Jasper Snoek from Google Brain explained how advances in medical image analysis will assist ‘experts to significantly improve morbidity detection rates. Deep learning methods are already enabling analysis that outperforms experts in applications such as the detection of diabetic eye disease and cancerous tumors.’
I want to highlight some developments that I think other people are likely to overlook:
I think we’ll start to see a good set of best practices recommendations for how to make machine learning algorithms fair, when they’re used to make decisions that strongly affect people’s lives (like parole decisions, mortgage applications, etc.)
I think we’ll start to see much stronger privacy guarantees, from techniques like differential privacy, federated learning, and maybe even homomorphic encryption.
I think we’ll start to see machine learning algorithms that are very difficult for attackers to intentionally fool, but I don’t think we’ll see any security guarantees in the form of mathematical proofs of strong protection claims.
I see a future with reduced congestion, improved mobility for those who have difficulty getting around today, greener cities, and increased access to public transit.
There is no doubt that recent advances in neural networks have lead to wonderful results in the areas of reinforcement learning and machine vision - I expect that progress to continue to accelerate. I'm looking forward to interesting products that may arise from these areas of research.
I am particularly excited at the progress in robotics so I do hope we make significant strides forward there, particularly, in generalisation of skills across different tasks and dexterity. Overall, I hope healthcare, public sector and government are affected positively as these are the places where most often important decisions are made and it would be ideal if there is a technology that can provide more insights into making an informed decision than a human can.
The AI research community is making breakthroughs everyday extending from beyond supervised learning to unsupervised and reinforcement learning. These advancements will enable enterprises of the future to build connected products and services as well as autonomous machines and robotics.
If you're keen to stay at the forefront of AI progressions throughout 2018, check out our calendar of events and join RE•WORK to learn about the most cutting edge advancements throughout the year. We are also hosting a webinar on Feb 9 where there will be the opportunity to discuss business applications of AI with leading minds in the space.