Figures viewed best with zoom. MNIST [3] while SupSup achieves 94.91% accuracy after 250 permutations (see Table 5 in [3] vs. Table 7 in our work). Prior work is concise and clear . The most similar approach to SupSup is [4] and they are limited to scenario GG while requiring more storage. Thank you for highlighting the importance of transfer.

Figures viewed best with zoom. MNIST [3] while SupSup achieves 94.91% accuracy after 250 permutations (see Table 5 in [3] vs. Table 7 in our work). Prior work is concise and clear . The most similar approach to SupSup is [4] and they are limited to scenario GG while requiring more storage. Thank you for highlighting the importance of transfer.

Building the perfect neural network is Empirical Process which takes bit of a time and experiences to achieve it. But, now a days the Transfer Learning made it way faster and less hectic. So, What is…

In line with a PwC India report named "With AI's Great Power Comes Great Responsibility", a very sad 10 percent of Indian CEOs are pretty dependable and in confidence of the accuracy and authenticity of the Artificial Intelligence (AI) application software they put to use. This is a really alarming and an attention drawing scenario where in today's world and time, Indian business establishments lack the aid of the AI benefactor. This report brought to light the dire need to understand the'Responsible AI' system and the areas it can be made use in.

At least 10 new AI-based jobs are being created for every 100 positions made redundant in traditional technology, experts in the field have said. However, the new roles are not being created as quickly as the positions that are eliminated and companies are increasingly training talent to fill the gap in artificial intelligence skills, believes Sridhar Mitta, founder of digital technology services provider NextWealth Entrepreneurs. "I guess, training skills outside the industry requires a collective ecosystem and efforts across different companies," said Prakash Mallya, the head of Intel India. The global opportunity of AI was estimated at about $15.7 trillion by 2030, according to a PwC report last year. Technology services companies are increasingly using AI at the core, raising the demand for talent.

BENGALURU: At least 10 new AI-based jobs are being created for every 100 positions made redundant in traditional technology, experts in the field have said. However, the new roles are not being created as quickly as the positions that are eliminated and companies are increasingly training talent to fill the gap in artificial intelligence skills. This was the key takeaway from ET's recent conversation on Technology Talent Equilibrium with Sridhar Mitta, founder of digital technology services provider NextWealth Entrepreneurs; Prakash Mallya, the head of Intel India, and Supriyo Das, vice-president, Wipro Technologies. "If 100 jobs are cut, 10 jobs are created. The people who are losing jobs have different skills, and they're going away. People are getting new jobs on different skillsets," Mitta said.

Manual checking of expense claims and other business expenditure is too time-consuming to be effective in spotting issues. The advent of artificial intelligence is a cause of widespread concern in the industrial world. A key issue, of course, is the effect on employment, and there are wide-ranging discussions of whether the administrative-type jobs that are likely to be lost to AI will be made up for by the creation of new roles or whether there will be large-scale unemployment. But there are other areas that businesses need to consider before launching themselves into this brave new world - as is made clear in a report, Making AI Responsible - and Effective, which was published by the international business consultancy Cognizant earlier this month. Having said that, businesses can make huge gains by applying AI to certain parts of their operations.

The Gluon API specification is an effort to improve speed, flexibility, and accessibility of deep learning technology for all developers, regardless of their deep learning framework of choice. The Gluon API offers a flexible interface that simplifies the process of prototyping, building, and training deep learning models without sacrificing training speed. The Gluon specification has already been implemented in Apache MXNet, so you can start using the Gluon interface by following these easy steps for installing the latest master version of MXNet. We recommend using Python version 3.3 or greater and implementing this example using a Jupyter notebook. Setup of Jupyter is included in the MXNet installation instructions.

Artificial intelligence will come to the forefront this year in marketing departments across the world. But do marketers really understand what AI is in marketing and how to best implement it in their marketing strategies? A Demandbase and Wakefield Research AI survey asked just these kinds of questions of marketers and found some very interesting results. To understand the results of this survey at a deeper level, I spoke with Aman Naimat, SVP of Technology at Demandbase. Naimat has a very extensive background in data science.

A neuron is a nerve cell. The brain is made up of approximately 100 billion neurons. There are approximately 1 quadrillion synapses in the human brain. This is equal to about a half-billion synapses per cubic millimeter. What is behind the saying "We use only 10% of our brain?"