Sengupta: Thank you so much for having me today. I'm really excited to be in San Francisco. I don't get to come here that often, which is strange because I live in Los Angeles, but I do like to come whenever I can. For my talk today, I'm going to talk about the future of transportation, specifically on the things that I worked on that I think are kind of the up and coming thing, the thing that I'm working on now and what's going to happen in the future. I think part of my career has always been about just doing fun and exciting new things and all my degrees are in aerospace engineering, ever since I was a little kid, I loved science fiction. I actually am a Star Trek person versus a Star Wars person, but I knew since I was a little kid that I wanted to be involved in the space program, so that's why I decided to go the aerospace engineering route and I wanted to build technology. I got my Ph.D. in plasma propulsion systems. Has anyone heard of the mission called Dawn that's out in the main asteroid belt? My Ph.D. research actually was developing the ion engine technology for that mission. It actually flew and got it to a pretty cool place out in the main asteroid belt looking at Vesta and Ceres. I did that for about five years and then I kind of felt like I had done everything I could possibly do on that front, from a research perspective. My management asked me if I wanted to work on the next mission to Mars. There's very few engineers in the space program who'd be like, "No, I'm just not interested in that." And they're like, "We want you to do the supersonic parachute for it."

In today's landscape, the AI space is one of the fastest growing sectors in technology. And there's no shortage of companies searching for the best solution to solve problems using artificial intelligence and machine learning. Despite their best intentions, many young people remain skeptical of AI and how it might affect them in terms of automation and job loss. One company that strongly believes AI can be developed to do good and make a positive change in the world is California-based startup Halfcode. We caught up with its 17-year-old founder and chief executive Richard Black shortly after the company announced its seed funding round to find out what being a social entrepreneur means to him and what his plans for the future are.

Estonia is a pioneer in digital initiatives. The Estonian government-initiated AI strategy counts with over 20 machine learning-based solutions live in the Estonian public sector. In Estonia, citizens are always the owners of their own data. None of this comes as a surprise, though, in a country which has been named the most advanced digital society in the world by many. Below, the opening to the third annual Tallinn Digital Summit that took place on September 16 - 17.

A US firm is flogging facial-expression software to analyse job candidates' performance in video interviews and make initial selections for companies including Unilever. The Marmite and Persil maker has previously used facial recognition software to analyse shoppers' reactions to in-store displays of products, and is now turning to algorythms to help in choosing its workforce. Hirevue software claims to analyse facial expressions and language to select the best candidates. Job seekers sit in front of a laptop or mobile phone and complete an automated video interview. This is analysed and compared against results from candidates who have already proved to be good at the job, according to The Telegraph.

PerimeterX is a provider of scalable, behavior-based threat protection technology for the web, cloud, and mobile. By analyzing the behavior of humans, applications, and networks, PerimeterX catches in real-time automated attacks with unparalleled accuracy. Its security service PerimeterX Bot Defender accurately protects commerce, media, and enterprise websites from all types of automated or non-human attacks, at any scale. The company was listed in the Top 5 Cybersecurity Startups Of 2019 by Business Computing World and was ranked in the 100 most promising private artificial intelligence companies in the world by CBInsights. PerimeterX was founded in 2014 and is based in San Mateo, California and has raised $91.5M in total.

Former Infosys CEO Vishal Sikka, who has announced a new AI startup with USD50 million fund, believes India has the potential to become a world leader in artificial intelligence but the key to this is integrating AI into the country's education system in a massive way. India is at "an inflection point" when it comes to AI or artificial intelligence, Mr. Sikka said. Over the next 20-25 years, AI is going to be "a very, very big disruptor" for the Indian society because what one is seeing now in terms of automation and job losses is just the beginning, said Mr. Sikka, who announced his startup Vianai Systems last week. "But on the other hand, if we are able to bring AI education, the ability to build AI systems to India at a very large scale, and I'm talking about like billion plus people, then India can really leap frog and become the world's leader in artificial intelligence, in AI skill and AI talent," Mr. Sikka told PTI in an exclusive interview. Doing that requires working on multiple dimensions in parallel, he said.

Yesterday, we talked about how Facebook has decided to monitor political speech. Today, we want to tell you about an area where Facebook is boldly going forward - dating. Facebook recently launched this new feature in the U.S. after testing it overseas. We wanted to know how people should feel about trusting Facebook in this particularly sensitive area since the company has long been under scrutiny for the way it handles users' data, so we've called Lisa Bonos. She writes about dating and relationships for the Washington Post.

In this paper, we study problems at the interface of two important fields: \emph{submodular optimization} and \emph{online learning}. Submodular functions play a vital role in modelling cost functions that naturally arise in many areas of discrete optimization. These functions have been studied under various models of computation. Independently, submodularity has been considered in continuous domains. In fact, many problems arising in machine learning and statistics have been modelled using continuous DR-submodular functions. In this work, we are study the problem of maximizing \textit{non-monotone} continuous DR-submodular functions within the framework of online learning. We provide three main results. First, we present an online algorithm (in full-information setting) that achieves an approximation guarantee (depending on the search space) for the problem of maximizing non-monotone continuous DR-submodular functions over a \emph{general} convex domain. To best of our knowledge, no prior approximation algorithm in full-information setting was known for the non-monotone continuous DR submodular functions even for the \emph{down-closed} convex domain. Second, we show that the online stochastic mirror ascent algorithm (in full information setting) achieves an improved approximation ratio of $(1/4)$ for maximizing the non-monotone continuous DR-submodular functions over a \emph{down-closed} convex domain. At last, we extend our second result to the bandit setting where we present the first approximation guarantee of $(1/4)$. To best of our knowledge, no approximation algorithm for non-monotone submodular maximization was known in the bandit setting.

The invasive and expensive diagnosis process of bladder cancer, which is one of the most common and aggressive cancers in the United States, may be soon helped by a novel non-invasive diagnostic method thanks to advances in machine learning research at the San Diego Supercomputer Center (SDSC), Moores Cancer Center, and CureMatch Incorporated. Research scientists Igor Tsigelny and Valentina Kouznetsova have been working on the development of a machine-learning (ML) model that looks at a patient's metabolites and their chemical descriptors. The model accurately classifies the stages of bladder cancer in a patient, according to the researchers. Tsigelny is the lead author on a recently published study in the Metabolomics journal called'Recognition of Early and Late Stages of Bladder Cancer using Metabolites and Machine Learning'. When a patient experiences early symptoms of bladder cancer (e.g., blood in urine, pain during urination, etc.), the current method of diagnosis is often a painful, invasive series of tests.

Today's leading minds talk AI with host Byron Reese Listen to this episode or read the full transcript at www.VoicesinAI.com Byron Reese: This is Voices in AI, brought to you by Gigaom and I am Byron Reese. Today, our guest is Hilary Mason. She is the GM of Machine Learning at Cloudera, and the founder and CEO of Fast Forward Labs, and the Data Scientist in residence at Accel Partners, and a member of the Board of Directors at the Anita Borg Institute for Women in Technology, and the co-founder of hackNY.org. That's as far down as it would let me read in her LinkedIn profile, but I've a feeling if I'd clicked that'More' button, there would be a lot more.