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The potential of Artificial Intelligence is enormous and in fact a 2013 study by Oxford University estimated that Artificial Intelligence could take over nearly half of all jobs in the United States in the near future. Artificial Intelligence’s most common application is about finding patterns in enormous quantities of data. This allows companies to automate and improve complex descriptive, predictive and prescriptive analytical tasks.
All the major tech companies are working on developing Artificial Intelligence solutions, ranging from Google, Facebook and Twitter and they are working hard to crack AI. As such Google recently acquired UK Artificial Intelligent Startup DeepMind for over $ 500 million. But there are quite a few more Artificial Intelligent startups working hard to create big ideas.
There is Quill, developed by Narrative Science, which is an artificial intelligence engine that generates, evaluates and gives voice to ideas as it discovers them in the data. Also Rocket Fuel, which had very successful IPO in 2013, uses AI to deliver a programmatic media-buying platform to improve marketing ROI in digital media across web, mobile, video, and social channels. Expertmaker uses AI to transform search, discovery and recommendation, and enable broad deployment of intelligent solutions. Finally there is Path Intelligence that maps 3D visitor journeys to generate data-driven insights into visitor and customer behaviour using Artificial Intelligence. These are of course just a few of the Big Data Startups focusing on AI, as there are many more.
Artificial Intelligence basically offers a solution for any organisation or industry that deals with massive amounts of data. Companies are investing billions to create applications in areas as wide as robotics, business intelligence systems, intelligent search, translators and many more. Such AI applications are intend to reduce costs, improve customer satisfaction and productivity and increase revenues. Some examples of use cases are:
1. Predicting human behaviour and as such assist in decision-making. AI algorithms can find patterns in factors that influence human behaviour and decisions. As such, it provides consumers as well as decision-makers guidance in making their decision because it can better predict the future outcome. A great example is the App RedLaser. An App that has been downloaded over 27 million times and provides users with recommendations by analysing store deals and user behaviour.
2. Making operations within your organisation more efficient and effective by minimizing human intervention. The Artificial Intelligence startup CogniCor has developed an automated complaint resolution service for call centres, which minimizes human intervention in resolving complaints.
3. Improving customer satisfaction by bringing down response times, fewer redundancies, a reduced time to market for new products and a more personalized approach. Artificial Intelligence helps organisations improve customer interactions resulting in more loyal customers. IBM’s Watson for example has developed a financial services assistant that can provide better advice on financial products based on market conditions, life events, client’s past decisions and available offerings.
4. Improving knowledge workers’ productivity within your organisation thanks to algorithms that learn from interactions among your employees. AI helps to understand associations between different information flowing through your company and can suggest relevant information to the right person at the right moment. As such, companies who use QlikView, a business discovery platform, allowing for associative data exploration, show 34% increase in employee productivity.
So there are many different benefits to be achieved with Artificial Intelligence, but it is not all hallelujah. Artificial Intelligence has already made promises for decades and only recently we are seeing some, significant, results. There are many challenges involved in creating truly intelligent software and machines. We are still very far away and currently the best AI, the ConceptNet 4 Artificial Intelligence, is said to be as smart as a four-year-old. Big Data startups working on AI solutions therefore require a lot of time to improve the applications. Venture capital firms investing in these companies thus need to have a very long investment horizon. Although of course the acquisition of DeepMind by Google suggests otherwise.
In addition, for companies being able to fully benefit of Artificial Intelligence they would need to have a good understanding of the data generated by their own organisation. AI requires vast amounts of data and such a lack of knowledge about the available data slows down the acceptance of AI applications. Apart from the fact that AI applications are often rather disruptive technologies, which always require time before becoming mainstream.
However the potential of Artificial Intelligence for organisations is enormous and if the projections turn out to be true and in the coming years the AI market will grow to a multiple billion dollar market, doing business can take up a whole new meaning. Resulting in fewer employees required while significantly improving your bottom line results.
With our lives becoming datafied, and more and more aspects of our lives and work that generate vast amounts of data, it also becomes more predictable. From travel information to customer satisfaction and to how much money new movies will generate. Big Data offers great insights and quite often this is thanks to Artificial Intelligence (AI). AI has to do with the study and development of intelligent software and machines and it is a branch of computer science that is highly technical. The focus of this research is on creating software that can gather knowledge, reason, learn, plan intelligently, communicate, perceive and manipulate objects. The market for AI-based tools and applications is growing rapidly and according to a research document by the EU, the global market for AI is set to grow from € 700 million in 2013 to € 27 billion in 2015. Artificial Intelligence has many applications and advantages but also quite a few challenges.
轉貼自: smartdatacollective
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