Artificial Intelligence is disrupting and transforming every industry it touches. From business operations and efficiency to innovative means of customer service, medical research breakthroughs, smarter transport systems and targeted advertising campaigns, it’s an inescapable reality of today’s world. Businesses unwilling to adopt AI will fall behind, and it’s predicted that the revenue generated from both the direct and indirect application of AI software will grow from $1.38 billion in 2016 to $59.75 billion by 2025. (Tractica, 2017)
“As machines become smarter, consumers will expect flawless customer service around the clock, and by 2025 AI will drive 95% of all customer interactions, with consumers unable to differentiate bots from human workers via online chats as well as over the phone.”(Servion, 2017)
At the Applied AI Summit in Houston this November 29 - 30, we'll be exploring real-life AI applications, case studies, business insights & results from leading companies leveraging AI to solve problems in the enterprise, so in advance of the Summit, we're exploring the areas where AI can transform businesses of all shapes and sizes.
Thanks to the availability of huge amounts of data and increasingly intelligent algorithms, machines can learn, speak, make informed decisions and carry out complex tasks in an increasingly effective manner. Not only is this driving research breakthroughs, but implementation in industry is demonstrating the huge potential impact that real-world applications of AI can have on businesses across all industries from retail and advertising, to healthcare, sales and marketing, transport, travel and tourism amongst others.
"It is machine learning, and in particular neural networks, that seem right now to hold huge promise; but the history of artificial intelligence warns us not to assume we can accurately predict what will work, or when." (Ed Newton-Rex, Jukedeck)
"Depending who you talk to, you usually find two definitions: one where AI aims to embed human intelligence into a machine, and another where AI aims at discovering possibly super-human levels of intelligence. If interpretability of the AI system is important, we might prefer an intelligence that's closer to the humans. But if we wish to design the best AI system that detects diseases in patients, we would be happy if it were better than a human doctor." (Hugo Larochelle, Google Brain)
"AI is the simulation of intelligence in computers: behaviour exhibited by non-biological systems that we would consider intelligent if exhibited by humans. A more recent approach, is ‘machine learning’ where the computer learns how to complete tasks by being exposed to large datasets." (Ed Newton-Rex, Jukedeck)
ML is always held back by limitations in the amount of computation we can use. These advances are able to have very apparent impacts on real-world problems, and Ian Goodfellow explained:
"The May 2017 announcement of the new generation of Google TPUs is huge. The new Google TPU helps bridge the gap between the amount of computation we can leverage in DL experiments and the amount of computation used in a biological nervous system. The previous generation was available only to Google engineers, but the new one will be available to Cloud customers, and researchers can apply to get access for free."
As more companies are able to implement AI models in their businesses through the availability of cloud platforms (for instance from Google, Amazon, Microsoft), AI technology will continue to become more accessible to both industry and society at large. There is no need for any particular industry to get left behind, and industries across the board are being positively disrupted by AI advancements (Hugo Larochelle, Google Brain). Business intelligence tools are able to source, analyse, transform and report on data to provide valuable customer insights and allow businesses to invest their time and money in the right areas. Companies striving to build emotional connections with their users will see increased customer satisfaction through emotional AI, after all ‘in real life situations, people are actually pretty bad at emotional intelligence’, causing us to end up in pointless fights, dismiss good arguments because they go against our biases, and judge people based on stereotypes. Once AI can be trained without bias it should be able to provide more rational responses than its human counterparts (Mikko Alasaarela, Inbot, Oct 2017).
Across multiple industries we see mind-boggling results due to deep learning in data preparation, speech recognition, text understanding, computer games, cybersecurity, etc. Deep learning has provided the greatest leap in performance in the history of AI (and arguably, in the history of computer science), and has rendered many traditional methods obsolete. As a result, within the next decade any company that will not heavily rely on deep learning will be left behind (Eli David, CTO, Deep Instinct).
Find out if you should be using AI in your business by downloading RE•WORK’s White Paper here, and learn from the likes of Google Brain, Deep Instinct and Jukedeck at RE•WORK’s summits. Save 25% on any summit when you register before September 7 using the code SUMMER.