New technologies such as Artificial Intelligence (AI), Cloud Machine Learning, Satellite Imagery and advanced analytics are empowering small-holder farmers in India to increase their income through higher crop yield and greater price control, Microsoft India said. In a few dozen villages in Telengana, Maharashtra and Madhya Pradesh, farmers are receiving automated voice calls that tell them whether their cotton crops are at risk of a pest attack, based on weather conditions and crop stage. In Karnataka, the government can get price forecasts for essential commodities such as tur (split red gram) three months in advance for planning the Minimum Support Price (MSP). "Sowing date as such is very critical to ensure that farmers harvest a good crop. And if it fails, it results in loss as a lot of costs are incurred for seeds, as well as the fertilizer applications," Suhas P. Wani, Director, Asia Region, of the International Crop Research Institute for the Semi-Arid Tropics (ICRISAT), said in a Microsoft blog post.

We present an algorithm for the generation of prime implicates in equational logic, that is, of the most general consequences of formulæ containing equations and disequations between first-order terms. This algorithm is defined by a calculus that is proved to be correct and complete. We then focus on the case where the considered clause set is ground, i.e., contains no variables, and devise a specialized tree data structure that is designed to efficiently detect and delete redundant implicates. The corresponding algorithms are presented along with their termination and correctness proofs. Finally, an experimental evaluation of this prime implicate generation method is conducted in the ground case, including a comparison with state-of-the-art propositional and first-order prime implicate generation tools.

Unsupervised learning with generative adversarial networks (GANs) has proven hugely successful. Regular GANs hypothesize the discriminator as a classifier with the sigmoid cross entropy loss function. However, we found that this loss function may lead to the vanishing gradients problem during the learning process. To overcome such a problem, we propose in this paper the Least Squares Generative Adversarial Networks (LSGANs) which adopt the least squares loss function for the discriminator. We show that minimizing the objective function of LSGAN yields minimizing the Pearson $\chi^2$ divergence. We also present a theoretical analysis about the properties of LSGANs and $\chi^2$ divergence. There are two benefits of LSGANs over regular GANs. First, LSGANs are able to generate higher quality images than regular GANs. Second, LSGANs perform more stable during the learning process. For evaluating the image quality, we train LSGANs on several datasets including LSUN and a cat dataset, and the experimental results show that the images generated by LSGANs are of better quality than the ones generated by regular GANs. Furthermore, we evaluate the stability of LSGANs in two groups. One is to compare between LSGANs and regular GANs without gradient penalty. We conduct three experiments, including Gaussian mixture distribution, difficult architectures, and a new proposed method --- datasets with small variance, to illustrate the stability of LSGANs. The other one is to compare between LSGANs with gradient penalty and WGANs with gradient penalty (WGANs-GP). The experimental results show that LSGANs with gradient penalty succeed in training for all the difficult architectures used in WGANs-GP, including 101-layer ResNet.

In this work, we show the intrinsic relations between optimal transportation and convex geometry, especially the variational approach to solve Alexandrov problem: constructing a convex polytope with prescribed face normals and volumes. This leads to a geometric interpretation to generative models, and leads to a novel framework for generative models. By using the optimal transportation view of GAN model, we show that the discriminator computes the Kantorovich potential, the generator calculates the transportation map. For a large class of transportation costs, the Kantorovich potential can give the optimal transportation map by a close-form formula. Therefore, it is sufficient to solely optimize the discriminator. This shows the adversarial competition can be avoided, and the computational architecture can be simplified. Preliminary experimental results show the geometric method outperforms WGAN for approximating probability measures with multiple clusters in low dimensional space.

Sony has announced that it is strengthening its video and audio technologies through artificial intelligence (AI) and robotics by fusing its core offerings with the latest in technology.

An Australian man was taken into custody Saturday for allegedly acting as an economic agent for North Korea and attempting to sell missile parts, military intelligence and coal on the black market. The Australian Federal Police arrested Chan Han Choi, 59, in Sydney and charged him with brokering sales of weapons of mass destruction, according to the Australian Broadcasting Corporation. It is the first time a charge of this kind has been leveled against anyone in Australia. The sales would violate Australian and United Nations sanctions. "We believe this man participated in discussions about the sale of missile componentry from North Korea to other entities abroad as another attempt to try and raise revenue for the government in North Korea, again in breach of the sanctions," said Australian Federal Police Assistant Commissioner Neil Gaughan in a statement.

The animated face of prototype robot GRACE, Graduate Robot Attending Conference, is tested by Carnegie Mellon University computer scientist Reid Simmons, right, in the lab at the school in Pittsburgh Tuesday, July 9, 2002. It may have been the first bit of fake news in the history of the Internet: in 1984, someone posted on Usenet that the Soviet Union was joining the network. It was a harmless April's Fools Day prank, a far cry from today's weaponized disinformation campaigns and unscrupulous fabrications designed to turn a quick profit. In 2017, misleading and maliciously false online content is so prolific that we humans have little hope of digging ourselves out of the mire. Instead, it looks increasingly likely that the machines will have to save us.

Some of the hottest fields in business call for exactly the skills that the accounting profession offers, according to IBM's Leon Katsnelson. In a keynote address on artificial intelligence at CPA.com's 2017 Digital CPA conference, held in San Francisco in early December, Katsnelson, who is director and chief technology officer for strategic partnership for data science at IBM, introduced the accountants in attendance to two of the newest professionals on the block: data scientists and data engineers. Both of those jobs are only about five years old, he said, but are already in the top ranks in terms of compensation. "To be a data scientist, you need three things," explained Katsnelson. First are programming skills – not necessarily full coding capabilities, but a familiarity with the field.

In this contributed article, Sharmistha Sarkar of India based Progressive Markets, highlights a handful of compelling technology advancements that are helping to drive the evolution of artificial intelligence. Industry is expected to grow at a CAGR of 46.5% from 2017 to 2025. The market is growing fast due to improved productivity through AI, its diversified application areas, and big data integration drive....

There is no doubt that technology has made our lives better, convenient and easier. We are lucky to live in the era where the new emerging technologies like AR, VR and AI are offering an immersive digital experience through their products. From AI robot to unique VR headset, these creations are the next big thing in the tech world. Entrepreneur India spoke to few experts to know which sectors will be using AI in coming years. Distributing content to right people is of critical importance to attract high traffic.