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Embracing #ArtificialIntelligence across the Enterprise

2016 and artificial intelligence (AI) is the major focus and growth area in the world of technology. The latest market analysis forecasts a staggering 44.3% CAGR growth in the global artificial intelligence market over the next decade to $23.4 billion. Since 2010 almost a billion dollars has been invested in startups by the VC industry; multiplying 7 times in 2015. The tech giants Google, Microsoft, Apple and many others are investing in capability to embed ‘cognitive’ services across their platforms.

The term ‘artificial intelligence’ is broad; and often wrongly popularised in the press as a sentient (self-aware) robot machine set to replace humanity. In reality it encompasses a set of technologies that can mimic and act as human intelligence. The ‘mimic’ of human intelligence is quite specific; the Google AlphaGo ‘machine’ was dedicated to the pursuit of excellence in a board game which it achieved beating the human world champion 4-1. However to apply AlphaGo to another element of human intelligence would require a lengthy refocus and training period.
“Humans can learn to recognize patterns on a Go board — and patterns related to faces and patterns in language — and even patterns of patterns,” said Melanie Mitchell, a computer scientist at Portland State University and the Santa Fe Institute. “This is what we do every second of every day. But AlphaGo only recognizes patterns related to Go boards and has no ability to generalize beyond that — even to games similar to Go but with different rules.” Whereby scare stories proliferate in the media of machines becoming smarter than humans and taking over the world, the reality is they are bound by the information and instructions presented to them. The recent embarrassment of Tay, the #AI Twitterbot highlights the intelligence quotient; the ‘machine’ only deals with or reacts to the data presented to it; its understanding constrained by a set of instructions in its code. The level of ‘intelligence’ is restricted by the instruction programmed and the data presented to the software to ‘understand’. This is the ‘intelligence’ attracting the investment of the VC industry and the major global technology and consulting companies.

‘Artificial Intelligence’ today is being focussed on solving real world business problems; many of these created by the sheer scale of data being created in our increasingly digital world. These problems are new opportunities for businesses who are smart; who are seeking to embed ‘cognitive’ capability into their organisations to augment the efforts of their workforce. When ‘artificial intelligence’ is programmed to focus on and understand ‘data’ and to interpret and derive ‘insight’ it can do so at a speed and scale humans couldn’t imagine. Forget the ‘sci-fi’ view of AI; it is incredibly useful right now for helping us understand the increasingly data rich and complex environment we ourselves have created.

Back in 2014 Investor Daniel Darling put it very succinctly:

“The arrival of new sources of data is a gift. Just as Google gave us access to the web’s content, artificial intelligence will digest our increasingly data rich world to portray information we will come to rely on throughout our daily lives.”

This data rich world impacts a vast array of activities that humans currently do and to which artificial intelligence technology is being applied. The increase of data in these activities has rendered humans incapable of managing to make sense of it quickly enough; AI solves this problem. A ‘cognitive’ solution can consume as much data as you throw at it; applying ‘understanding’ based on what you have asked it to. Unlike a human the ‘cognitive’ solution doesn’t get tired, bored or restless; it will perform the task in front of it relentlessly. ‘Big data’ was the buzzword in the technology industry in the past few years; but the data just kept getting bigger; now we have data ‘lakes’ perhaps ‘oceans’ and AI has come into its own. This ‘cognitive’ computing understands the context; provides a level of reasoning based on this context and then learns from the patterns – together providing ‘insight’. This data driven ‘insight’ is what a smart enterprise business understands will deliver competitive advantage in the digital economy.

The utility of ‘artificial intelligence’ is going to be more practical than the ability to play a board game or interact on Twitter. It probably won’t grab the headlines as much as AlphaGo or Tay but it will be delivering actionable results that will have a material impact on the business operations and revenue.

The ‘use cases’ for AI are wide and varied at so many levels of an enterprise business but the machines will be created and driven by human creativity and imagination. They will perform their tasks with speed and scale; delivering insights and actionable information to truly liberate business from the shackles of ignorance.

The power behind ‘artificial intelligence’ is many years of research and development by data scientists who experimented with various methods and theories to achieve a contextual understanding of data. The commercialization of this research and development is set to reshape industries; a new startup cannot just ‘code’ a cognitive solution no matter how well funded they are; you need to have sound science embedded from years of effort.

Chatterbox Cognitive Engine delivers artificial intelligence, machine learning and natural language processing capability in one to provide mid level business analysts with the ability to create new cognitive products in days. Over 6 years of research and development by our PhD educated data scientists is embedded within the process and methods available to our partners creating new cognitive products for their clients.

For more information please visit our web site or contact Andrew Watson, VP Strategic Alliances,