The New York Institute of Finance (NYIF) and Google Cloud announced a new Machine Learning for Trading Specialization available exclusively on the Coursera platform. The Specialization helps learners leverage the latest AI and machine learning techniques for financial trading. Amid the Fourth Industrial Revolution, nearly 80 percent of financial institutions cite machine learning as a core component of business strategy and 75 percent of financial services firms report investing significantly in machine learning. The Machine Learning for Trading Specialization equips professionals with key technical skills increasingly needed in the financial industry today. Composed of three courses in financial trading, machine learning, and artificial intelligence, the Specialization features a blend of theoretical and applied learning.
In this AI Podcast, Serkan Piantino from Spell describes how his company is making machine learning easier. Piantino, CEO of the New York-based startup and former director of engineering for Facebook AI Research, explained to AI Podcast host Noah Kravitz how he's bringing compute power to those that don't have easy access to GPU clusters. We want to empower and transform the global workforce by making deep learning and artificial intelligence accessible to everyone. We believe that as organizations and individuals can harness the power of machine learning, our world will change quickly. Our mission is to make sure the technology driving this change is not mysterious and locked away but open and available for everyone.
The most well-funded US artificial intelligence startup is Nuro, with just over $1B in disclosed equity funding, including a $940M Series B from SoftBank in February 2019. The California-based startup is developing autonomous vehicles, with a focus on last-mile delivery. Nuro is followed by New York's UiPath ($1B in disclosed equity funding) and Illinois' Avant ($655M). There are 9 unicorn startups on our map: robotic process automation vendor UiPath ($7.1B valuation), autonomous vehicles software provider Argo AI ($7B), agtech startup Indigo Agriculture ($3.5B), Nuro ($2.7B), alternative lending startup Avant ($1.9B), AI-powered predictive sales platform InsideSales.com The startup with the least funding on the list is Rhode Island's The Innovation Scout, a SaaS platform that connects enterprises with startups, accelerators, and more.
Below you will find the articles on economics, investing, and finance that we found most interesting for the week. Google chief Sundar Pichai says artificial intelligence needs to be regulated. Natural gas drops below $2 and the industry is on its knees. Is there an opportunity lurking? The Blevinator ruthlessly keeps Apple's supply chain costs down.
The vehicles still drive with a safety driver and a software operator. Optimus Ride, an MIT spinoff, has started operating its autonomous vehicles at Paradise Valley Estates in Fairfield, California. The shuttles, which have been carrying passengers for a couple of months now, follow deployments at the Seaport District in Boston, the Halley Rise mixed-use district in Reston, Virginia, and the Brooklyn Navy Yard in New York, a 300-acre industrial park. At the moment, the vehicles still drive with two people from the company on board, a safety driver and a software operator, but the goal of the company is to be fully driverless later this year. We caught up with the company recently -- check out the video below.
Meeting strangers off the internet is inherently dangerous, and Tinder reportedly wants to do something about it. The popular dating app is beefing up its user security options, offering a panic alarm for when casual meet-ups or dates take a turn for the worst, the Wall Street Jourrnal reports. Tinder, which is owned by Match, will start testing a panic button in the U.S. by the end of this month, the publication said on Thursday. The offering is brought about through Match's purchase of the personal safety app Noonlight. Match will extend the feature to its other dating apps like OkCupid, Match and Hinge this year.
Tinder is adding a'panic button' to its app that will allow people to alert the police if they feel unsafe while out on a date. It will be rolled out to users of the dating service from the end of January in the USA, according to a Wall Street Journal report. They will use a technology that tracks the location of users and notifies authorities of any safety issues that is built by company Noonlight. Tinder has not said when or if the service will be rolled out to the rest of the world. 'You should run a dating business as if you are a mom,' Mandy Ginsberg, CEO of Tinder parent company Match Group, told the Wall Street Journal.
The AI Youth Lab is an initiative by 1M1B in collaboration with the United Nations Sustainable Development Goals (SDGs) for the year 2030. The organisation, because of its association with the various UN bodies, has also been able to take the students it works with to UN headquarters in New York to attend, as well as address, international intra-governmental sessions. Manav Subodh, the co-founder of 1M1B, who is currently out in the countryside, working with the program's rural schools, says, "We've been working with youth around the country for the last four years, and while previously we encouraged our student participants to work on projects which can positively impact the lives of at least 10 people (no small thing in itself), we realised that by using Artificial Intelligence, we could scale up that impact by multiple factors." Subodh intends to set up over 50 labs in schools across India and abroad over the course of 2020, saying, "We provide the infrastructure, training, and all other facilities for our partner schools, so that it doesn't cost them anything. This is especially an important factor for rural schools. In fact, we're also organising mobile AI labs, which can travel between hard-to-reach villages, so as to have maximum reach."
Artificial intelligence burst onto Wall Street several years ago, to fanfare and hope. Unfortunately, AI-based investing strategies have struggled to live up to some of the more inflated expectations for their performance. There is no denying these strategies' theoretical promise. By being able to sift through otherwise prohibitively large amounts of data, and then "learn" from it, AI is supposed to be able to discover profitable patterns that were previously invisible to mere mortals.