Collaborating Authors


Pinaki Laskar on LinkedIn: #selfdrivingcars #autonomousdriving #autonomouscars


AI Researcher, Cognitive Technologist Inventor - AI Thinking, Think Chain Innovator - AIOT, XAI, Autonomous Cars, IIOT Founder Fisheyebox Spatial Computing Savant, Transformative Leader, Industry X.0 Practitioner What do you think of the update to the SAE's levels of autonomous driving? Do you find these levels helpful when it comes to knowing what an AV can do? What's the difference between driver support features and automated driving? Society of Automotive Engineers (SAE) recognise that levels 0-2 are better defined as'driver support features.' Level 3 and above encompass what they would now refer to as'automated driving features.' a six degrees of automated driving: from zero automation to full automation.

How Deep Learning has completely changed the entire self-driving car industry 🚗


So now, without any further ado let's dive into the how the self-driving car industry looked like 15–20 years ago! Unless you are living under a rock, you probably know that the self-driving car industry has become one of the hottest industries in the last 5–10 years. Some of the world's biggest companies like Google, Tesla, GM are working on self-driving cars. These companies have spent more than 120 billion dollars on self-driving car R&D just in 2020 alone! The CEOs of these companies are saying that they are on the verge of creating the driverless cars that we all imagine when we think about our future cities(the ones where you can just fall asleep in to get the extra hour of sleep).

Robo-taxis are headed for a street near you

MIT Technology Review

In the coming years, mobility solutions--or how we get from point A to point B--will bridge the gap between ground and air transportation--yes, that means flying cars. Technological advancements are transforming mobility for people and, leading to unprecedented change. Nand Kochhar, vice president of automotive and transportation for Siemens Software says this transformation extends beyond transportation to society in general. "The future of mobility is going to be multimodal to meet consumer demands, to offer a holistic experience in a frictionless way, which offers comfort, convenience, and safety to the end consumer." Thinking about transportation differently is part of a bigger trend, Kochhar notes: "Look at few other trends like sustainability and emissions, which are not just a challenge for the automotive industry but to society as a whole." The advances in technology will have benefits beyond shipping and commute improvements--these technological advancements, Kochhar argues, are poised to drive an infrastructure paradigm shift that will bring newfound autonomy to those who, today, aren't able to get around by themselves. Kochhar explains, "Just imagine people in our own families who are in that stage where they're not able to drive today. Now, you're able to provide them freedom." Laurel Ruma: From Technology Review, I'm Laurel Ruma, and this is Business Lab, the show that helps business leaders make sense of new technologies coming out of the lab and into the marketplace. Our topic today is the future of mobility. In 2011, Marc Andreessen famously said, "Software is eating the world."

The 25-year-old billionaire building the future of self-driving cars


Austin Russell is the 25-year-old founder and CEO of Luminar, a startup in Silicon Valley that makes LIDAR sensors for self-driving cars. LIDAR technology had been used for short-distance mapping, but Luminar claims to have a functioning LIDAR that works at 250 meters, which is a breakthrough. Luminar recently went public, making Austin today's youngest self-made billionaire. And when it comes to self-driving cars, youth is definitely an advantage -- Austin told me we're still years if not decades away from fully self-driving cars, and there's a lot of work to be done to make them safe, effective, and ubiquitous. That work is racing ahead -- Luminar has deals with Volvo, Audi, Toyota, and others -- but building a complete self-driving car is still a long-term project. This transcript has been lightly edited for clarity. I'm very excited to talk to you. You are, as far as the last thing I read, the youngest self-made billionaire in America, your company just went public in a SPAC [special purpose acquisitions company]. And come Pi Day, 26. You were born on Pi Day? So, Luminar, it's a company that makes LIDAR sensors. You have a number of deals to supply LIDAR sensors to major automakers. I want to talk about all of that. One thing that I always get frustrated by in origin stories is no one ever really talks about act two. In 2012 you were at Stanford, you had this idea to do LIDAR sensors. I want to talk about act two for a little bit. Just that middle part of going from "I've got a great idea," to "This company is actually up and running and functional." So give me a sense of, at the beginning you were a student at Stanford, you got a Thiel Fellowship from Peter Thiel. What was the next step? Did you sit down and build a LIDAR sensor?

The Ten Most Dangerous Roads In The World, And How Self-Driving Cars Would Fare


Will self-driving cars be able to cope with highly dangerous roads? Let's talk about dangerous roads. In a moment, I'll provide you with a recently published list of the presumed Top Ten most dangerous roads in the world. For some of you, the odds are that you'll be happy that you've never had a cause to try and traverse these bad-to-the-bone roads, while others of you are probably going to put these alarming roads on your bucket list of places you have to go and give a whirl someday. Do you prefer roads that are calm, easy to navigate, and present little or no qualms?

The 2018 Survey: AI and the Future of Humans


"Please think forward to the year 2030. Analysts expect that people will become even more dependent on networked artificial intelligence (AI) in complex digital systems. Some say we will continue on the historic arc of augmenting our lives with mostly positive results as we widely implement these networked tools. Some say our increasing dependence on these AI and related systems is likely to lead to widespread difficulties. Our question: By 2030, do you think it is most likely that advancing AI and related technology systems will enhance human capacities and empower them? That is, most of the time, will most people be better off than they are today? Or is it most likely that advancing AI and related technology systems will lessen human autonomy and agency to such an extent that most people will not be better off than the way things are today? Please explain why you chose the answer you did and sketch out a vision of how the human-machine/AI collaboration will function in 2030.

Supercomputing on a chip AutoSens Conference


In Grenoble, France, one company is aiming to make an impact in the field which is so visibly dominated by multi-billion dollar corporations. We caught up with the company's Business Unit Director responsible for introducing their products to the Automotive market, Stéphane Cordova, to find out more, ahead of their attendance at AutoSens Detroit in May. The company's approach to "Supercomputing on a chip" has evolved from a the business origins providing components and software services to data centres, where high speed and reliability as well as low power consumption and significantly reduced heat generation were all key factors in processor component design. What helped you decide to commit to exhibiting at AutoSens again? Kalray's technology will be at the heart of autonomous driving.

The biggest problem with autonomous driving has nothing to do with AI AndroidPIT


Choose "I don't think so." or "Yes, I think so.". In many ways, we are on the brink of this new mobility tech becoming mainstream. Just this month, Waymo was granted the go-ahead to test fully driverless cars in California. In the US, twenty-nine states have already enacted legislation related to autonomous vehicles. In places like Arizona, the cars are already on roads.

How Autonomous Vehicles Will Upend Transportation - Knowledge@Wharton


Autonomous vehicle technology is advancing rapidly, and hard-core promoters contend that driverless cars could soon be the norm rather than the exception. Many other knowledgeable analysts, however, say widespread adoption of fully autonomous cars is many years -- perhaps decades -- away. The chief reason for the delay is the years it will take to generate the vast amount of data required to make self-driving cars fully safe. But whenever it finally takes over, driverless technology will do much more than ease daily commutes: It will also have a profound impact on the world's economy, notes Lawrence Burns, a former corporate vice president of research, development and planning for General Motors who supervised and encouraged GM's development of robotic driving technology. His new book with Christopher Shulgan is titled, Autonomy: The Quest to Build the Driverless Car -- And How It Will Reshape Our World. He joined the Knowledge@Wharton show on SiriusXM to talk about how a driverless world will map out. An edited transcript of the conversation follows.

Anticipating the next move in data science – my interview with Thomson Reuters


Thomson Reuters has a series, AI experts, where they interview thought leaders from different areas - including technology executives, researchers, robotics experts and policymakers - on what we might expect as we move towards AI. As part of that series I recently spoke to Paul Thies of Thomson Reuters, and here are the excerpts from the interview: Anticipating the next move in data science Thomson Reuters: For timely information concerning developments in data science, data mining and business analytics, KDnuggets is widely regarded as a leading outlet in the field. Created in 1993 by founder, editor and president Gregory Piatetsky-Shapiro, it is frequently cited as one of the top sources of data science news and influence by various industry watchers. Thomson Reuters: What are some use cases of data science that you find to be particularly valuable to organizations in this age of Big Data? GREGORY: Where people typically apply data science, probably not surprisingly, are in the areas of customer relationship management (CRM) and consumer analytics.