Today we look at the major impact that AI and robotics have had on diverse spheres, such as energy storage, manufacturing, wearables, VR, and big data from young entrepreneurs in Forbes “30 under 30”.
Many of the individuals on the list have been changing the world through their innovative products and strategies such as Prarthna Desai. She is Head of Operations at Zipline, a company which employs drones to deliver medicine in developing countries. In addition, Nishant Garg & Jimit Shah, co-founders of Flow Labs, have crafted a small wireless-enabled sensor that attaches to water pipes and measures the amount of water flowing through them — ideal for homes and businesses looking for ways to save water and save money. Finally, Anurag Garg, CEO of Dattus, has been hard at work transforming old manufacturing facilities into smarter factories.
Forbes’ “30 under 30″ list celebrates the achievements of 30 game changers in 20 different industries — 600 in total — of the brightest young entrepreneurs and innovators who are challenging conventional wisdom. The list highlights some interesting trends in robotics, AI, intelligence energy storage, and automation.
Hyperloop Transportation Technologies (HTT), a company working to make Elon Musk‘s dreams of a levitating, 700mph train a reality, is to open a test facility in France. To be built in Toulouse, known as “Aerospace Valley”, the development and testing facility will be used to produce Hyperloop-related technologies. As part of the agreement with HTT, Toulouse will provide a 3,000 square metre (37,674 sq ft) facility, along with “outdoor terrain” for various aspects of the Hyperloop to be tested on.
Chris Skinner outlines 11 fintech trends that you need to follow. They are: 1) Removing friction from the customer journey, 2) Rise of insurtech, 3) Rise of regtech, 4) PSD2 forces banks and fintech to partner, 5) Reform of the bank boardroom, 6) China and emerging markets focus, 7) Chatbots, machine learning, AI, 8) Fintech gets integrated with social media, 9) Fintech gets integrated with the Internet of Things, 10) Platforms, APIs, and open banking are key, 11) Blockchain moves out of the labs into the real world. Check out the blogpost for more details.
Their mission is to develop general AI (as fast as possible) to help humanity and understand the universe. They see general AI as the ultimate leverage in solving humanity’s direst problems and becoming better humans. To help accelerate the search for general AI, they are preparing a series of milestone challenges starting in early 2017 with prizes totalling at least $5mil. Their team opened the General AI Challenge up to public discussion at the Machine Intelligence Workshop at NIPS 2016 in Barcelona on December 9th. You can read more about the workshop here.
“Holiday Spirit” is claimed to be the world’s very first data-distilled rum and was created using IBM Watson. “In just six hours Watson was able to read 15 million posts on Facebook, Instagram and Twitter relating to holidays – and find the predominant emotions and concepts in those posts,” explained Joe Harrod, big data analyst and AI expert, who works closely with Watson. “Then Watson read 5,000 rum reviews from review sites around the web, matching emotions from the reviews with ingredients. For example, Watson picked out that cask-aged rums often tasted exciting and it already knew that excitement is a key ingredient in holidays – so the final recipe was for aged rum.”
Starting on Thursday, eight health-tech startups will begin an intensive 3 month boot camp at Cedars-Sinai in an attempt to transform the healthcare system. The startups will receive $120K in seed-money, along with support and mentoring from physicians and executives at the hospital. “We’re excited to pair these bright, motivated entrepreneurs with healthcare experts from Cedars-Sinai who together can rapidly accelerate the pace of innovation and transform healthcare in meaningful ways for our patients,” said Darren Dworkin, senior vice president and chief information officer at Cedars-Sinai.
Linkedin has added a chatbot feature to its new design. however, LinkedIn isn’t calling it a chatbot — and it doesn’t seem to have a snappy personalized name as of yet. For now, it’s a feature within LinkedIn’s larger online messaging service upgrade. Its functionality is reportedly a bit more limited than some of the chattier chatbots out there — but it’s a start. The new feature works to enable on-site conversations between professionals, suggesting icebreakers or even whom to contact to get started
and help schedule meetings by comparing users’ calendars.
Alpaca, a fintech startup which builds AI and database technology for financial trading, has announced the closing of a $1.75 million venture round. Yoshi Yokokawa, Alpaca’s co-founder and CEO, said: “We see an opportunity to offer a true value to casual stock traders like ourselves by providing trading contents in an easily digestible way, backed by real technology and science. We are excited to have received a huge amount of support from successful traders and technologists in the industry throughout this financing round.”
A newsurveyof 1,600 business and IT executives from Infosys points to AI’s potential beyond cold, hard job replacement, though it’s going to take inspired and entrepreneurial thinking to get past this early stage. So far, it appears AI is more a cost-cutting mechanism, versus a mind-expanding strategy.
At the same time, businesses at the forefront of AI say they’re not out to eliminate jobs. It’s a hopeful thought, as 80% of these AI adopters say they don’t intend to use AI to throw people out of work, but, rather, retain and retrain employees to fulfill more elevated capacities while AI systems take on the more routine grunt work aspects of their jobs.
The ability to accurately predict and simulate human driving behaviour is critical for the development of intelligent transportation systems. Traditional modelling methods have employed simple parametric models and behavioural cloning.This paper adopts a method for overcoming the problem of cascading errors inherent in prior approaches, resulting in realistic behaviour that is robust to trajectory perturbations.