Often the best way to learn a language is to immerse yourself in an environment where people speak it. The constant exposure, along with the pressure to communicate, helps you swiftly pick up and practice new vocabulary. But not everyone gets the opportunity to live or study abroad. In a new collaboration with IBM Research, Rensselaer Polytechnic Institute (RPI), a university based in Troy, New York, now offers its students studying Chinese another option: a 360-degree virtual environment that teleports them to the busy streets of Beijing or a crowded Chinese restaurant. Students get to haggle with street vendors or order food, and the environment is equipped with different AI capabilities to respond to them in real time.
According to the report, global AI in agriculture market was valued at around USD 545 million in 2017 and is expected to reach approximately USD 2,075 million by 2024, at a CAGR of slightly above 21% between 2018 and 2024. New York, NY, July 11, 2019 (GLOBE NEWSWIRE) -- Zion Market Research has published a new report titled "AI in Agriculture Market by Technology (Machine Learning and Computer Vision), by Component (Hardware, Software, and Services), and by Application(Agriculture Robots, Agricultural Drones, Driverless Tractors, Facial Recognition, Crop Health Monitoring, and Automated Irrigation Systems): Global Industry Perspective, Comprehensive Analysis, and Forecast 2017-2024''. According to the report, global AI in agriculture market was valued at around USD 545 million in 2017 and is expected to reach approximately USD 2,075 million by 2024, at a CAGR of slightly above 21% between 2018 and 2024. Availability of numerous equipment and modern day technologies such as intelligent monitoring system, drones, and robots has made agriculture industry a cusp of technological revolution. Browse through 84 Tables & 28 Figures spread over 144 Pages and in-depth TOC on "Global AI in Agriculture Market 2017: By Technology, Size, Share, Trends, Applications, Analysis and Forecast to 2024".
Considering various factors such as the research areas, research focus, courses offered, duration of the program, location of the university, honors, awards and job prospects, we came up with the best universities to help you in your choosing process. This article is most suited for individuals who'd like to pursue a PhD with a focus in machine learning and need some guidance on their decision making. Feel free to jump to the end if you are looking for only the names of the Universities. Note: The universities mentioned below are in no particular order.
The AI in Finance Summit is returning to New York due to popular demand, this time accompanied by the AI in Insurance Summit. Across 2 days, 400 attendees will come together to learn from over 60 speakers about the most cutting edge advancements in the application of AI in the financial and insurance industries. Topics covered will include investment, fintech, financial compliance, financial forecasting, fraud detection, responsibility, deep learning and more. As the discussions around regulation, cybersecurity and ethics increase, these topics will take centre stage across both tracks at the summit. Sessions will focus on the explainability of algorithms used within the financial industry, and there will be presentations for business leaders and decision makers specifically as well to compliment the technical sessions.
At the turn of the twentieth century, the swelling populations of newly arrived immigrants in New York City's Lower East Side reached a boiling point, forcing the City to pass the 1901 Tenement House Act. Recalling this legislation, New York City's Mayor's Office recently responded to its own modern housing crisis by enabling developers for the first time to build affordable micro-studio apartments of 400 square feet. One of the primary drivers of allocating tens of thousands of new micro-units is the adoption of innovative design and construction technologies that enable modular and flexible housing options. As Mayor de Blasio affirmed, "Housing New York 2.0 commits us to creating 25,000 affordable homes a year and 300,000 homes by 2026. Making New York a fairer city for today and for future generations depends on it."
"While most organisations recognise that AI is a transformational technology with huge potential impact, their approach to adoption has been cautious. The survey data and white paper demonstrate how to harness the power of AI and successfully increase its adoption by first establishing a clear strategy and framework," said Michael Tae, head of strategy for Broadridge. "At Broadridge, we are focused on what we call'the ABCDs of innovation': AI, blockchain, the Cloud, digital and beyond. This is how we define our continued commitment to driving the innovation roadmap; helping our clients understand and apply next-generation technologies to transform business, optimise efficiency and generate growth.
A school district in western New York is launching a first-of-its-kind facial recognition system, generating new privacy concerns about the powerful but controversial technology. The Lockport city school district is beginning implementation of the Aegis facial recognition system this week, officials said, with the technology expected to be fully up and running in time for the new school year in September. "Much to our dismay, school shootings continue to occur in our country. In many cases, these shootings involve students connected to the schools where these horrific incidents occur," superintendent Michelle Bradley said in a message to parents. "The Lockport city school district continues to make school security a priority."
San Francisco supervisors approved a ban on police using facial recognition technology, making it the first city in the U.S. with such a restriction. Facial recognition has enrolled in school. On Monday, a New York school district became one of the first in the U.S. to roll out facial recognition technology on campus using its students' faces as an added layer of security. The system of cameras can also be used to identify guns or flagged persons, such as expelled students and sex offenders, according to the school district. The Lockport City School District will pilot its Aegis system over the summer and will expand the technology to each of its eight schools before classes resume in the fall.
Some 9,000 people, about one-third of Goldman's staff, are computer engineers." Artificial Intelligence is causing massive paradigm shifts across many industries, but its biggest impacts is felt in financial services sector. Simply put, artificial intelligence provides unfair advantage in the financial markets. Nonetheless, AI has limited capability as exemplified in the chess game between Russian chess grandmaster and IBM Deep Blue computer. This piece provides insight into why algorithm trading won't necessarily render human traders useless on Wall Street. In recent years, technology has made it possible to'teach' computers how to trade. Yet day traders continue to remain an integral part of the stock trading markets globally. Apart from specialist niche trading sections where corporations engage in high frequency trading, day trading by robots fails time and time again. But the stock markets behavior constantly changes. Savvy traders can adjust themselves to changes, while adjusting algorithms is too expensive, and time consuming. For that reason and others, day traders still do a better job than any day trading algorithm. Computers are facilitating many of the trades happening on the floor of exchanges globally; yet, the actual task of the algorithms is often limited to analyzing and predicting market trends. The final decision to buy or sell an asset is still often determined by a human. In some instances, the human hits the buy/sell button and in most instances, the human instructs the algorithm to buy X when the price/profit/loss reaches a certain threshold or sell Y when certain parameters are met. Interestingly, Meir Barak, author of The Market Whisperer: A New Approach to Stock Tradingand founder of Tradenet observes that there will always be a place for human traders because the stock market is fluid and dynamic. The fact that humans don't consistently act rationally suggests that computers won't necessarily be adept in the face unexpected market performance. "Let's say a chess grandmaster plays against the best computer in the world.
Investment banking is seeing its historical profit centers eroded by technology and regulations. Core processes are being automated or commoditized. From IPOs, to M&A, to research and trading, investment banks are getting smaller, leaner, and scrambling to keep up with innovations. In 2006, investment banks were at the top of the finance world. With torrential growth and return on investment (ROI) driven largely by the trading of complex financial instruments, Lehman Brothers, Bear Stearns, Goldman Sachs and others achieved record profits and awarded unprecedented bonuses. Over the next two years, everything fell apart. Download the free report to learn how core processes of this financial service are being automated or commoditized. After the collapse of Lehman and Bear Stearns and the global financial crisis that ensued, the business models of the world's biggest investment banks needed to change. In the US, legislation emerged to forbid investment banks from prop trading, or trading with their own capital, and forcing them to keep more capital on hand. This regulation reduced trading profits and created a need to cut costs, spurring investment banks to spin off unprofitable divisions or eliminate them entirely. While the rules against prop trading have more recently been loosened, the restriction has still changed how investment banks operate. Moreover, as more and more companies raise large equity rounds they're also choosing to delay public offerings. And even when major tech companies do decide to go public, some, like Spotify and Slack, are doing so mostly without the help of banks. As a result, banks are facing dropping IPO profits: they generated just $7.3B in revenue in 2017 from equity capital markets, which includes IPOs, down an inflation-adjusted 43% since 2000's peak, according to the Wall Street Journal. At the same time, financial upstarts have built technologies that could eventually cut into the relationship-driven work that investment banks are used to doing. Instead of working with a bank to make an acquisition, you can use Axial -- the so-called "Tinder of M&A," for its algorithm-based approach to matching companies with potential buyers. In 2015, 26% of $1B mergers and acquisitions took place without the help of external financial advisors, up 13% from the year before, according to Dealogic.