Artificial Intelligence, often described as “Thor’s Hammer”, is simply getting into everything these days.
Various leading publications including Forbes, Wall Street Journal, and Fortune have called 2017 “The Year of AI”, for the major breakthroughs tech giants made in artificial intelligence space this year.
The milestones in AI comprised Microsoft’s record-breaking 12% accuracy level for recognizing words in a conversation and human transcribers, IBM’s advanced AI features through Watson and investment of $240 million in MIT-IBM Watson AI Lab, AWS’s DeepLens and SageMaker, to name a few.
Along with the technology firms, the research universities and organizations (Oxford, Massachusetts General Hospital and GE’s Avitas Systems) too show interest in AI, and invested heavily in deep learning supercomputers.
According to a recent report from Avendus Capital, the revenue of organizations working in AI space might reach around $3.06 billion by 2024.
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The leading researchers and industry thought leaders across the globe have predicted where AI is heading in the coming year.
1. Transformation of engineering simulation and design
The engineering and manufacturing simulation is primarily focused on structural performance needs of products, while design services are used for development of new products and enhanced performance of existing products.
“2018 will be the year deep learning starts a revolution in engineering simulation and design. Over the next three to five years, deep learning will accelerate product development from years to months and weeks to days to create a new paradigm of rapid innovation in product features, performance and cost,” said Marc Edgar, senior information scientist, GE Research.
2. Biometrics capabilities
Biometrics, the technology for identification and access control, is going to replace credit cards and driving licenses.
“Thanks to AI, the face will be the new credit card, the new driver’s license and the new barcode. I can see a near future where people will no longer need to stand in line at the store,” said Georges Nahon, CEO, Orange Silicon Valley.
3. AI for Medicine
AI will become real for medicine, generating solutions for population health, hospital operations and a wide range of clinical specialties.
“By the end of next year, I think around half of leading healthcare systems will have adopted some form of AI within their diagnostic groups,” said Mark Michalski, executive director, Clinical Data Science.
4. AI for content creation
Nvidia expects that AI will be able to create new personalized media, like music service which not only plays existing songs but also generates new songs according to the taste of user.
5. Continuous AI adoption
According to Accenture, AI will comprise over 25% of the total investments in technology.
6. Innovation in deep learning techniques
“Deep learning will significantly increase the quantitative content of radiology reports. There will be much fewer concerns about deep learning being a ‘black box,’ as new techniques will help us understand what DL is ‘seeing.’” – Bradley J. Erickson, Mayo Clinic.
7. AI accessible on smartphones
Mobile apps will run deep neural networks to enable AI.
“Friendly robots will start to emerge as more affordable and rise as the new platform at home. They will start to bridge vision, language and speech in such a way that the users will not be conscious about the difference between these communication modalities.” – Robinson Piramuthu, chief scientist for computer vision, eBay.
8. AI more integrated into daily life
The deep learning techniques of AI are already used by Google Photos to group images of people using facial recognition, Yahoo for chatbots, Alibaba to find a handbag matching the one whose photo is uploaded on shopping site, etc.
The new AI integrations will make the daily lives easier. For example, AI will know the choices of user regarding pantries, foods, groceries, etc. and will keep those things ready when he reaches home.
Also read: Microsoft powers Office 365 with AI and online tools
AI is going to open a new field of research in contemporary astrophysics, to enable more people from various background to utilize AI.
