Tesla, the leading electric vehicle manufacturer, made exciting announcements regarding their advancements in artificial intelligence (AI) and robotics during their Annual Shareholder Meeting held earlier today. The company aims to revolutionize autonomous technology and expand into new frontiers. Here are the key highlights from the event:
Multiple fully Tesla-made Bots now walking around & learning about the real world 🤖
Join the Tesla AI team → https://t.co/dBhQqg1qya pic.twitter.com/3TZ2znxkfd
— Tesla Optimus (@Tesla_Optimus) May 16, 2023
Tesla Bot: In an ambitious move, Tesla revealed plans to develop a groundbreaking humanoid robot called the Tesla Bot. This autonomous robot is designed to perform repetitive, mundane, and hazardous tasks, freeing humans from such labor-intensive work. Tesla envisions the Tesla Bot as a general-purpose robot capable of executing various duties. To achieve this, Tesla will focus on developing the necessary software stacks for balance, navigation, perception, and interaction with the physical world. The company is actively seeking skilled engineers specializing in deep learning, computer vision, motion planning, controls, mechanical engineering, and general software development to join this exciting project.
AI Chips for Full Self-Driving (FSD): Tesla is committed to enhancing its Full Self-Driving (FSD) capabilities by developing specialized AI inference chips. These chips will power the FSD software and undergo rigorous improvements to optimize performance and energy efficiency. Tesla’s dedicated team will conduct comprehensive testing, implement drivers, and ensure mass production readiness for seamless integration into their vehicles.
Advanced AI Training with Dojo: Another major development is the creation of AI training chips for Tesla’s Dojo system. These chips will leverage cutting-edge technology to enhance performance, throughput, and bandwidth. The Dojo system represents Tesla’s next-generation machine learning compute infrastructure, and it will be designed in-house to meet the company’s unique requirements. Tesla will develop compilers, drivers, and comprehensive validation methods to optimize power and performance for their neural networks. The Dojo system aims to revolutionize AI training capabilities and accelerate progress in autonomous technology.
Tesla Vision powers most of our active safety features.
8 cameras + deep neural networks + learnings from our fleet of 4M+ cars enable greater levels of reliability vs classical vision processing techniques pic.twitter.com/veqlZVwH15
— Tesla (@Tesla) May 16, 2023
Enhancing Neural Networks: Tesla employs state-of-the-art research techniques to train deep neural networks. These networks play a crucial role in perception and control tasks. By analyzing raw camera images, Tesla’s neural networks enable semantic segmentation, object detection, and monocular depth estimation. The company’s innovative approach involves gathering data from their vast fleet of vehicles in real-time, capturing the most diverse and complex scenarios. The training process for Tesla’s Autopilot neural networks involves a comprehensive system of 48 networks, generating 1,000 distinct predictions at each timestep.
Advancing Autonomy Algorithms: Tesla is continuously developing core algorithms to power their autonomous vehicles. These algorithms create highly accurate representations of the surrounding world, enabling precise trajectory planning. Tesla leverages data from its sensors to create large-scale ground truth datasets. By employing cutting-edge techniques, Tesla aims to build a robust planning and decision-making system that can operate seamlessly in real-world situations, even under uncertain conditions. The evaluation process for these algorithms is conducted at the scale of Tesla’s entire vehicle fleet, ensuring constant improvement and innovation.
Tesla’s commitment to optimizing code and evaluation: Tesla recognizes the critical importance of code optimization and evaluation in delivering top-notch autonomous technology. The company focuses on throughput, latency, correctness, and determinism as the main metrics for code optimization. Tesla builds its Autopilot software from the ground up, integrating tightly with its custom hardware. This approach ensures efficient data capture from sensors and seamless distribution across multiple processing units.
With these groundbreaking initiatives, Tesla aims to redefine the future of transportation and revolutionize AI and robotics technology. Elon Musk and the Tesla team remain committed to pushing the boundaries of innovation, ultimately creating a safer, more sustainable, and autonomous future for everyone.