11 Oct, 2017
For 250 years or so, innovations in technology have been the fundamental drivers for growth in the economy, especially the general-purpose technologies like the steam engine, electricity, internal combustion engine, internet, telephone, etc. These are referred to as general purpose technologies as each is catalysts for complementary innovations and opportunities.
Now, Artificial Intelligence, especially machine learning (ML), is one of the most important general-purpose technology of this era. The ability of machines to keep learning and improving its performance without any human intervention is creating breakthrough innovations in all business verticals today. In the past few years, machine learning has become very effective and also widely available. We can now build systems that learn how to perform tasks on their own.
This advancement in ML is very important as we can now automate things that we were not able to previously, like facial recognition and voice recognition. This advancement has drastically improved and we can make real-time decisions now. Another important advancement in ML systems is that they are excellent learners in a wide range of tasks such as detecting fraud and diagnosing disease. Excellent digital learners are being deployed across the economy and their impact will be profound.
Today, AI has made huge advancements in areas of perception and cognition. In areas of perception, the most practical advances have been made in relation to speech. Voice recognition is still far from perfect, but millions of people are now using it like iPhone Siri, Amazon Alexa, Microsoft Cortana, and Google Assistant. The speech recognition is now much faster than typing on a cell phone. The error rate is dropping drastically in short periods of time, now to 4.9%. Image recognition, too, has improved dramatically. You may have noticed that Facebook and other apps now recognize many of your friends’ faces in posted photos and prompt you to tag them with their names. The new iPhone 10 has face recognition even in the dark. If you search for face recognition apps you will find many today. Vision systems, such as those used in self-driving cars today, are errorless, often less than one in millions of frames. According to HBR, the error rate for recognizing images from a large database called ImageNet, with several million photographs of common, obscure, or downright weird images, fell from higher than 30% in 2010 to about 4% in 2016 for the best systems.
AI can have a transformational impact on businesses and has already had great success in in thousands of companies around the world. Companies like Domino’s, McDonald’s, Harley Davidson, and many small businesses are using AI driven Personal Assistants, Chat Bots, etc. But we are just scratching the surface and real opportunities have not yet been tapped into.
The effects of AI will be magnified in the coming decade as manufacturing, retailing, transportation, finance, healthcare, law, advertising, insurance, entertainment, education, and virtually every other industry transform their core processes and business models to take advantage of AI.
Companies have to put AI first strategy. This year, all the major tech companies are talking about their AI first strategy. So, companies need to have AI first, Mobile first, and Cloud first strategies in order to be competitive and create value. The most important thing in the strategy is that it needs to be customer-centric, and employee-centric.
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