SecuRESafe (SRES)’s Post

Last week we had some great discussions during our AI Safety Week trainings, including topics around Responsible AI. In this latest blog SecuRESafe (SRES) delves into Explainable AI for autonomous vehicles.

Interesting stuff from Helm.ai Their approach to AI is transforming the training of machine learning models for self-driving vehicles and mobile robots. Their new generative AI model, VidGen-1, creates realistic driving scene videos, significantly reducing the labour-intensive process of data annotation and supervision. Leveraging their Deep Teaching technology and generative deep neural network architectures, Helm.ai enhances scalability and addresses complex corner cases where traditional supervised learning falls short. This generative AI model enables rapid, cost-effective simulation, closing the simulation-to-reality gap. Beyond automotive applications, VidGen-1’s potential extends to autonomous mining vehicles, drones, and more. https://lnkd.in/eJt-nDiJ

AI is the driving force behind autonomous driving (AD). Learn how some companies are using new AI technologies to overcome the complex challenges of AD in our blog post: https://bit.ly/3Rci5eD #AI

Waymo EMMA Powered by Gemini Showcases Multimodal Large Language Modelling https://lnkd.in/gHvN3JUu auto connected car newsFor over 15 years, Waymo has researched AI and machine learning within autonomous driving. Today, ,Waymo published its latest research paper on an End-to-End Multimodal Model for Autonomous Driving (EMMA). EMMA, powered by Gemini—a multimodal large language model from Google—uses a unified, end-to-end trained model to generate vehicle trajectories directly from sensor data. Developed and fine-tuned for autonomous driving, EMMA leverages Gemini’s vast world knowledge to better interpret complex on-road scenarios. The research highlights the benefits of multimodal models, like Gemini, in autonomous driving and evaluates the advantages and limitations of the end-to-end approach. It emphasizes the value of incorporating

Waymo EMMA Powered by Gemini Showcases Multimodal Large Language Modelling https://lnkd.in/g9HjC7nN auto connected car newsFor over 15 years, Waymo has researched AI and machine learning within autonomous driving. Today, ,Waymo published its latest research paper on an End-to-End Multimodal Model for Autonomous Driving (EMMA). EMMA, powered by Gemini—a multimodal large language model from Google—uses a unified, end-to-end trained model to generate vehicle trajectories directly from sensor data. Developed and fine-tuned for autonomous driving, EMMA leverages Gemini’s vast world knowledge to better interpret complex on-road scenarios. The research highlights the benefits of multimodal models, like Gemini, in autonomous driving and evaluates the advantages and limitations of the end-to-end approach. It emphasizes the value of incorporating

Embodied AI brings the extraordinary impact of AI into the physical world through robots like #AutonomousVehicles. 🤖 🚘 But why is autonomous driving the optimal path to #EmbodiedAI? Learn more here👇 https://lnkd.in/gFKvk7qB

🚘 🤖 Autonomous vehicles have come a long way, but they still struggle with something we take for granted: common sense. While humans effortlessly navigate complex scenarios, driverless cars often falter in unexpected situations. However, recent advancements in LLMs and multimodal systems are showing promise in bridging this gap. These AI models, capable of processing both visual and linguistic information, could potentially equip autonomous vehicles with human-like reasoning abilities. 🔗 https://lnkd.in/ddCUNdvy Share your thoughts! What do you envision for the future of AI-driven autonomous vehicles? #AIInnovation #AutonomousVehicles #FutureOfDriving #AICommonSense #DrivingEvolution

The journey towards fully #autonomousvehicles is accelerating. 🚗 Traditional methods of #AI training rely heavily on real-world data, but innovators are leveraging the power of unsupervised learning to train AI models more efficiently and effectively. This innovation not only reduces the need for extensive data labeling but also accelerates the path to safer, more reliable autonomous driving systems. As the automotive industry continues to evolve, integrating advanced AI solutions like these will be crucial in shaping the future of mobility. Read more: https://bit.ly/4cUW6AP #FutureOfDriving

Not all steps are equal. One step in your bedroom isn't the same as one step in the woods. Many machine learning consultants or solution providers don't acknowledge this fact when discussing the leap into machine learning with their clients. Asking a company to put its trust in a machine, however intelligent, isn't a small ask. To wit: 66% of drivers are still afraid of riding in autonomous vehicles. And the % is going up........ #Akkio #machinelearning #AI #dataanalytics