The road to fully autonomous vehicles is paved with AI! With machine learning algorithms, self-driving cars are learning how to navigate traffic, recognize pedestrians, and make life-saving decisions in real time. Waymo, Google's self-driving car project, has completed over 20 million miles of testing! The more data these systems gather, the smarter they get – and soon enough, your next road trip might be hands-free. #AI #AutonomousVehicles #TechTrends #Innovation

On Day 8 of our **12 Days of AI**, we’re diving into the future of transportation. From autonomous cars to optimised logistics, AI is steering us into a safer, more efficient world. Read the blog here: https://buff.ly/41mK29y #AIinTransportation #12DaysOfAI

𝐀𝐈 𝐅𝐮𝐧 𝐅𝐚𝐜𝐭: 𝐃𝐢𝐝 𝐲𝐨𝐮 𝐤𝐧𝐨𝐰? AI is driving the future of transportation with autonomous vehicles. These vehicles use AI algorithms to navigate roads, detect obstacles, and make split-second decisions, leading to safer and more efficient transportation systems. This application of AI not only transforms how we travel but also highlights the immense potential of AI to revolutionize industries.  #AIinTransportation

As part of the ROADVIEW project, which aims to improve autonomous vehicle driving performance in adverse weather conditions, we present some of our results in this video. Autonomous vehicles, ideally designed to operate without a human driver, must also contend with weather challenges, just like traditional drivers. To integrate these vehicles into our streets in the future, numerous tests are necessary, especially in difficult weather conditions such as heavy rain or dense fog. Since we cannot control the weather, the ability to simulate precise weather conditions greatly facilitates these tests. Additionally, simulating these conditions increases the amount of data available for algorithm training. Here, I present the initial results of my work on simulating adverse weather conditions, which are detailed in an article with the S.T.I team at Cerema. We propose a new training method for CycleGAN, called Group2Group, which significantly reduces artifacts. #roadview #cerema #roadview_eu #ArtificialIntelligenceMachineLearningDataScienceRobotics #generativeai #generativemodels #ai #machinelearning #neuralnetwork

Find out how self-driving cars use big data and AI, and learn about the five levels of self-driving cars. Discover how much data an autonomous car can generate and how Quobyte provides an efficient solution to handle the load. https://buff.ly/3VCBfvH #SDS #SoftwareDefinedStorage #SoftwareStorage #SelfSrivingCars #AI #AutonomousVehicles #AIDataStorage

Stepping Into the Future of Transport: Dive into an intriguing article that explores the evolving landscape of autonomous vehicles through a ride in Waymo's self-driving car around San Francisco. Discover how Waymo is enhancing passenger comfort and trust with advanced features like personalized greetings and real-time visual route displays. It’s an eye-opening look at the strides being made towards integrating these technologies into our daily lives! What are your thoughts on the future of autonomous travel? https://www.rfr.bz/l9ab432 #AutonomousVehicles #FutureOfTransport #TechInnovation #SmartMobility #Waymo #SelfDrivingCars #TransportationTechnology #AI #AutomotiveInnovation

One of the most critical parts of making vehicles fully autonomous: simulators, which require huge volumes of data to be representative of the real world. Whether it's a pedestrian jaywalking or unpredictable weather conditions, these simulators must be able to mirror rare events for vehicles to reduce the risk of accidents and become fully autonomous. Waymo Co-CEO Dmitri Dolgov is focused on scaling their powerful simulation tool to build the world's most trusted driver. Join him in the latest AI Revolution conversation with Growth general partner David George on how they are uniquely positioned to shape the future of AI.

#AI Needs #Data, and Lots of It! To capture the complexities of the real world, AI models require vast amounts of data: -Text: Training advanced language models takes over 570 GB—equivalent to around 45 million books. -Images & Video: AI relies on databases with over 14 million images and thousands of hours of video. Enter #DataCenters: With data demand skyrocketing, datacenters are the backbone of AI, powering the processing and storage of this immense information. As AI grows, #efficient and #scalable datacenters are more crucial than ever. The future of tech is here, and it’s data-driven.

Join the Live Learning session on AutoAuto Virtual Cars, where you can explore the fascinating world of self-driving cars. Feel free to ask questions while working on the lessons, and dive deep into the future of autonomous vehicles. #LiveLearning #SelfDrivingCars #AutoAuto #AI #ComputerScience #knowledgehubdubai Learn more: https://lnkd.in/gsGDk2_T

I recently watched a thought-provoking video by Ankur Warikoo where he predicts that by 2050, we may no longer be behind the wheel. Instead, AI could be driving our cars, transforming how we navigate the roads. Intrigued by this, I immediately searched how far we are on the journey to autonomous cars. I found that San Francisco is already deploying such technology with autonomous vehicles being tested and used in certain areas! It’s fascinating to see how far cars have come already. Newer models feature advanced driver assistance systems (ADAS) like lane-keeping, collision detection, automatic parking, and even adaptive cruise control that adjusts to traffic conditions. These features point us in the direction of a fully autonomous future. However, I do believe that many people will still want to drive for the sheer joy of it. That said, the general scenario might shift, especially with new policies like California’s proposal to tax drivers just for using the road. I’m curious to hear from you! Do you believe we’ll still be driving in 25 years, or will AI fully take over? What are your thoughts on the current advancements in this space? #FutureOfTech #AI #AutonomousDriving #Innovation #2050Predictions #TechTrends