How startups and enterprises can leverage AI for innovation and growth
Artificial Intelligence (AI) has not been getting preference for the consumer market since it directly does not touch personal lives. Virtual reality (VR) on other hand is getting mass attention. But one can expect AI to come out to the mainstream as many companies are leveraging their version of artificial intelligence (AI) soon.
Many people are already using AI routinely. Crystal, an AI application attempts to teach users about crafting emails based on recipient’s likes and dislikes. There are countless opportunities to use AI and businesses now are paying attention.
The Race for AI adoption
For example, Facebook Inc. recently rolled out a new feature, which is termed as VoiceOver, that makes use of AI technology for oral descriptions of FB photos meant for visually-impaired users. A further resounding win for AI happened when Alphabet’s AI program AlphaGo beat the world champion in Go—a game that was touted to be far complex for a computer to play better than any human. One can expect that in the future whichever company controls AI could steer the industry for many years to come.
Amazon, Facebook, Alphabet and Microsoft Corp. are all vying for the top spot in AI offerings while IBM’s AI service, is already on its way to boost its customer base to almost double the present figures. Some companies are though not interested in AI tools. They want to deliver with their own algorithms. For example Atomwise, a company which successfully raised $6 million, is using the algorithms for revving up drug research. It researches side effects of known drugs and then uses them to solve multiple medical issues.
After an estimated $5 billion spent on acquisitions in the past two quarters, IBM is soon unveiling plans of revenue monetization of its AI engine, Watson. This AI offering concentrates on front-office services leveraging a potential $150 billion market of the future. IBM is monetizing Watson through personal data accessibility, user subscriptions, shared value with partners, overall revenue and licensing fees.
Japan’s SoftBank Group Corp. and Johnson & Johnson have already joined forces with IBM for training Japanese language to the AI and thus explore multiple ways to enhance its cognitive capabilities, through different channels like mobile, tablets and even robots. IBM and Johnson & Johnson even announced collaborative plans last year for introducing intelligent virtual coaching solutions and healthcare applications that can transform patient experience as part of Watson’s health unit.
Amazon’s AI Offerings
Amazon launched a cloud service in April that helps companies choose the right predictive models with the help of existing data. The service lets professionals using huge data sets to make use of statistical modeling for making accurate predictions. The service uses the data to train algorithms to deliver the result that the company needs. It can now predict one or two possible outcomes or even predict one of three possible outcomes based on the likelihood of each one. It also predicts using regression method and also resorts to find and research complex concepts.
Google’s Translation Service
Real-time translation without any human intervention is a dream envisioned by Google and the company has spent lot of time improving its translation services with the help of machine learning. Google Translate API, lets one build dynamic translation services at a nominal cost. Instead of adding words that mean differently in other languages, Google Translate uses machine learning for understanding every word meaning and even scour through idioms. Words relating to each other are understood with proper reasons.
AI ventures by Facebook and Microsoft
Facial recognition is one of prime importance for people at Facebook and Nest along with Microsoft who have built AI tools to recognize people’s faces. While machine learning fails to identify a person in the photos, it can reveal if a person in one photo is the same as any other person in any other photo or video. By linking a limited name field, systems can identify the people. These facial recognition efforts are intrinsic part of the computer vision research that are being introduced in self-driving cars.
As its core part, machine learning is trying to unravel troves of digital information that is being generated every day. One can let computers do more work, while letting humans focus on tasks that they excel in. As companies grapple with AI and its after-effects, rest assured, one can leverage technology for getting trivial tasks completed easily.