Whilst progress in AI is rapid, the majority of society are overestimating the speed at which drastic changes will happen, imagining a world run by robots where everyone is unemployed.
Contrary to what people think, scientific progress is slow and continuous, but social and economic impact can be disruptive - there’s no doubt that we will reach human level AI but we don’t know how long it’s going to take. We need to make sure that AI and society will bloom for the benefit of all. - Yoshua Bengio, Deep Learning Summit, Montreal, 2017
Breakthroughs, whilst impactful, are subtle and transformative to specific elements of industries, rather than industries as a whole. As AI continues its progression into the mainstream, we’re looking at some of the breakthroughs over the last 6 months.
As of March this year, by using machine learning on POWER9 with NVIDIA Tesla V100 GPUs, IBM technology can now predict the likelihood of a user clicking online advertisements 46x faster than previous published results. In a benchmark by IBM Research, it was demonstrated how Snap Machine Learning (AI technology) can be used to train ML models for massive data sets from financial records to weather forecasting to online marketing. The result for customers is lower cloud costs and faster time to insight.
The insights derived from data are where real business value is—and getting those insights is a tall order when it is time- and cost-consuming to evaluate even relatively simply datasets. Speed is critical for scaling insights, and IBM is optimizing IT infrastructure to achieve that speed.
In the video game Dota 2, OpenAI’s software achieved a milestone in computer science by beating five highly skilled human players.
The achievement puts San Francisco-based OpenAI, whose backers include billionaire Elon Musk, ahead of other AI researchers in developing software that can master complex games combining fast, real-time action, longer-term strategy, imperfect information and team play. Dota 2 is a multiplayer science-fiction fantasy video game created by Bellevue, Washington-based Valve Corp. The tournament version pits two competing five-player teams.
The London based team have created an AI algorithm to enable a computer to analyze optical coherence tomography (OCT), a high resolution 3D scan of the back of the eye. The computer was asked to give a diagnosis in the cases of 1,000 patients whose clinical outcomes were already known. It was asked to make one of four referrals: urgent, semi-urgent, routine and observation only.
The algorithm did not miss a single urgent case. The model identified serious conditions such as wet age-related macular degeneration (AMD), which can lead to blindness unless treated quickly. The team used two neural networks to mimic the way the brain operates, and inputted thousands of eye scans. They divided the eye into anatomical areas and were able to classify whether disease was present. The DeepMind algorithm provides a visual map of where the disease is, allowing clinicians to check how the AI has come to its decision, which is crucial if doctors and patients are to have confidence in its diagnoses.
A team of Microsoft researchers have created the first machine translation system that’s capable of translating news articles from Chinese to English with the same accuracy as a person. The company says it’s tested the system repeatedly on a sample of around 2,000 sentences from various online newspapers, comparing the result to a person’s translation in the process – and even hiring outside bilingual language consultants to further verify the machine’s accuracy.
The sample set, called newstest2017, was released just last fall, so it’s surprising how quickly the researchers were able to achieve this milestone – especially given that machine translation is a problem people have been trying to solve for decades.
“Hitting human parity in a machine translation task is a dream that all of us have had,” said Xuedong Huang, a technical fellow in charge of Microsoft’s speech, natural language and machine translation efforts, in Microsoft’s blog post. “We just didn’t realize we’d be able to hit it so soon.”
Digital learning solutions equipped with artificial intelligence are making revolutionary changes to the way education is imparted in students with varied interests and capabilities. Education sets the foundation of human behaviour. Educational ecosystem is formed by knowledge base, teaching skills and experience, learning capability, and evolving teaching methods. Digital learning solutions equipped with artificial intelligence are making revolutionary changes to the way education is imparted in students with varied interests and capabilities. Here are some facets of education where we can feel the difference created by artificial intelligence: personalised learning, elevating the role of teachers as facilitators/motivators, objectively assessing students, creating smart content.