DeepMind's New AI Tracks Serengeti Herds from Images Alone DeepMind, the U.K.-based AI research subsidiary acquired by Alphabet in 2014 for $500 million, today detailed ecological research its science team is conducting to develop AI systems that'll help study the behavior of animal species in Tanzania's Serengeti National Park. They extend the popular BERT architecture to a multi-modal two-stream model, processing both visual and textual inputs in separate streams that interact through co-attentional transformer layers.

Artificial intelligence-powered tools are rapidly becoming more accessible, including for people in the more remote corners of the globe. This is good news for smallholder farmers, who can use handheld technologies to run their farms more efficiently, linking them to markets, extension workers, satellite images, and climate information. The technology is also becoming a first line of defense against crop diseases and pests that can potentially destroy their harvests. A new smartphone tool developed for banana farmers scans plants for signs of five major diseases and one common pest. In testing in Colombia, the Democratic Republic of the Congo, India, Benin, China, and Uganda, the tool provided a 90 percent successful detection rate. This work is a step towards creating a satellite-powered, globally connected network to control disease and pest outbreaks, say the researchers who developed the technology.

The oldest known knitting item dates back to Egypt in the Middle Ages, by way of a pair of carefully handcrafted socks. Although handmade clothes have occupied our closets for centuries, a recent influx of high-tech knitting machines have changed how we now create our favorite pieces. These systems, which have made anything from Prada sweaters to Nike shirts, are still far from seamless. Programming machines for designs can be a tedious and complicated ordeal: When you have to specify every single stitch, one mistake can throw off the entire garment. In a new pair of papers, researchers from MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) have come up with a new approach to streamline the process: a new system and design tool for automating knitted garments. In one paper, a team created a system called "InverseKnit," that translates photos of knitted patterns into instructions that are then used with machines to make clothing.

Artificial intelligence may still be in its infancy, but there's no question more people are beginning to feel its influence in their everyday lives. Tolga Kurtoglu, CEO of PARC, and award-winning tech journalist Kara Swisher sat down to discuss the current state of AI and how ethics can steer its future. Here are the key takeaways from their discussion. AI algorithms are now able to perform breast cancer screenings better than some medical professionals. It's become clear that AI isn't just another passing tech fad.

Using artificial intelligence, scientists created an easy-to-use tool to detect banana diseases and pests. Artificial intelligence-powered tools are rapidly becoming more accessible, including for people in the more remote corners of the globe. This is good news for smallholder farmers, who can use handheld technologies to run their farms more efficiently, linking them to markets, extension workers, satellite images, and climate information. The technology is also becoming a first line of defense against crop diseases and pests that can potentially destroy their harvests. A new smartphone tool developed for banana farmers scans plants for signs of five major diseases and one common pest.

Water scarcity – an increasingly important topic of conversation as countries across the Middle and East and Africa grapple with rising concerns around future water shortages, which not surprisingly often results in civil unrest. Currently the Middle East and North Africa is the most water-scarce region in the world, according to the United Nations. With at least 17 countries well below the water line, water is being consumed faster than it can be replenished. Only a year ago, the City of Cape Town was in the headlines with a forecasted Day Zero where the city's taps would be turned off in order to preserve the remaining water supply (13.5% of normal) for critical services. Fortunately, the city avoided Day Zero through a combination of water saving measures and well-timed rain.

Breast cancer is the most common cancer and is the leading cause of cancer death among women worldwide. Detection of breast cancer, while it is still small and confined to the breast, provides the best chance of effective treatment. Computer Aided Detection (CAD) systems that detect cancer from mammograms will help in reducing the human errors that lead to missing breast carcinoma. Literature is rich of scientific papers for methods of CAD design, yet with no complete system architecture to deploy those methods. On the other hand, commercial CADs are developed and deployed only to vendors' mammography machines with no availability to public access. This paper presents a complete CAD; it is complete since it combines, on a hand, the rigor of algorithm design and assessment (method), and, on the other hand, the implementation and deployment of a system architecture for public accessibility (system). (1) We develop a novel algorithm for image enhancement so that mammograms acquired from any digital mammography machine look qualitatively of the same clarity to radiologists' inspection; and is quantitatively standardized for the detection algorithms. (2) We develop novel algorithms for masses and microcalcifications detection with accuracy superior to both literature results and the majority of approved commercial systems. (3) We design, implement, and deploy a system architecture that is computationally effective to allow for deploying these algorithms to cloud for public access.

Priya Lakhani is an entrepreneurial adrenaline junkie. She has founded two successful companies, won numerous business awards, and acted as an advisor to the Department of Business, Innovation, and Skills. Her life's aim is to change the world for the better, and to that end she has funded meals in India, vaccinations in Africa, and her current project improves education for thousands of UK children. Remarkably, she has achieved all this despite a constant barrage of people telling her to "quit and go home". In this podcast Priya takes us through her astonishing career, from unloading boxes of sauce outside Victoria Street Station, to writing a book for preschoolers.

Language identification ("LI") is the problem of determining the natural language that a document or part thereof is written in. Automatic LI has been extensively researched for over fifty years. Today, LI is a key part of many text processing pipelines, as text processing techniques generally assume that the language of the input text is known. Research in this area has recently been especially active. This article provides a brief history of LI research, and an extensive survey of the features and methods used in the LI literature. We describe the features and methods using a unified notation, to make the relationships between methods clearer. We discuss evaluation methods, applications of LI, as well as off-the-shelf LI systems that do not require training by the end user. Finally, we identify open issues, survey the work to date on each issue, and propose future directions for research in LI.

Global AI Machine Learning market, a new research report that examines the current and futuristic growth of this market. This report offers a detailed study about the market which is tremendously propelling in the present market situation. The key driving factors like drivers, restraints and opportunities which are capable of the primary and secondary research, which allows the players to have a strong understanding of the overall market. The ongoing market trends of AI Machine Learning market and the key factors impacting the growth prospects are elucidated. With increase in the trend, the factors affecting the trend are mentioned with perfect reasons. Top manufactures, price, revenue, market share are explained to give a depth of idea on the competitive side.