The hottest Autonomous Vehicles Substack posts right now

And their main takeaways
Category
Top Technology Topics
Fight to Repair 19 implied HN points 12 Oct 22
  1. Stellantis, parent company of Jeep and others, aims to generate over $2 billion in revenue by 2030 through its Circular Economy Business Unit focusing on reman, repair, reuse, and recycle.
  2. The battle over Massachusetts right-to-repair law shows significant disagreements between automakers and the Attorney General regarding key terms, cybersecurity, and data-sharing timelines.
  3. Big agriculture's emphasis on bushels per acre over profits may harm farmers as they overspend on inputs to achieve higher yields, benefiting companies more than the farmers themselves.
The Gradient 24 implied HN points 12 Mar 24
  1. Apple terminated its Project Titan autonomous electric car project and shifted focus to generative AI, impacting hundreds of employees.
  2. Challenges faced by Project Titan included leadership changes, strategic shifts, and difficulties in developing self-driving technology.
  3. Research proposes RNN-based architectures Hawk and Griffin that compete with Transformers, offering more efficiency for language models.
Apperceptive (moved to buttondown) 32 implied HN points 27 Oct 23
  1. The self-driving car industry had many startups aiming for a piece of the autonomous car market.
  2. Waymo and Cruise were seen as leading the race for self-driving vehicles, but had vastly different approaches and challenges.
  3. Cruise faced difficulties transitioning from testing to deploying revenue taxi service while still grappling with technical challenges.
Exasperated Infrastructures 7 implied HN points 20 Dec 23
  1. The 11th edition of the MUTCD addresses the need for updated road safety measures but lacks clear accountability processes.
  2. The controversial '85th percentile speed trap' rule in the MUTCD has received criticism for rewarding law-breaking behavior.
  3. The new version of the MUTCD includes factors like pedestrian activity in speed limit determinations, but lacks clear definitions and enforcement mechanisms.
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Data Science Weekly Newsletter 19 implied HN points 27 Oct 16
  1. Self-driving cars are not fully ready for everyday use yet, so we should be cautious when thinking about how they will change transportation.
  2. Artificial intelligence has the potential to transform various industries, similar to how electricity changed the world.
  3. Data is becoming a vital part of decision-making in many areas, including sports like basketball, changing how teams operate.
Global Community Weekly (GloCom) 0 implied HN points 11 Feb 24
  1. A crowd in San Francisco's Chinatown attacked a Waymo robotaxi, setting it on fire, prompting an investigation by authorities.
  2. The incident damaged the autonomous vehicle, leading to concerns of potential similar actions during festivities like the Super Bowl.
  3. City officials, including Supervisor Aaron Peskin, are taking measures to ensure safety, with police presence boosted for potential security threats.
Joshua Gans' Newsletter 0 implied HN points 28 Mar 17
  1. Training for AI, like pilots or cashiers, is essential for machines to learn and improve in performance.
  2. Determining what is "good enough" for machine intelligence involves considering the trade-offs in terms of error tolerance and level of in-house vs on-the-job learning.
  3. The decision of when to deploy AI systems into the real world for learning involves balancing the need for data with the potential risks to brand and customer safety.
Joshua Gans' Newsletter 0 implied HN points 25 Jul 16
  1. Elon Musk's new strategy for Tesla involves moving beyond the traditional car market and focusing on reconfiguring cities, energy systems, and environmental impact.
  2. Tesla's approach to building electric cars involved designing the vehicles from a clean slate, integrating software and hardware in a new architecture.
  3. Musk's plan to merge Tesla with SolarCity aims to create an integrated company that can innovate in clean energy solutions, including combining electric cars with solar power for reduced carbon footprint.
Joshua Gans' Newsletter 0 implied HN points 29 Dec 15
  1. Ownership and control of a car's software is a complex issue, especially in the context of autonomous vehicles.
  2. The debate boils down to whether third parties like manufacturers or governments should have the power to restrict user's ability to alter software for safety reasons.
  3. Maintaining transparency and user control over software modifications may be crucial to balance safety and individual liberties in the era of autonomous vehicles.
Cybernetic Forests 0 implied HN points 19 Dec 21
  1. Artificial Intelligence can be thought of as a living system like a compost heap, breaking down and reorganizing to produce something new.
  2. Metaphors play a crucial role in how we perceive and design AI, shifting from brain-centric models to organic and dynamic models like compost intelligence.
  3. Compost intelligence could offer benefits like data decomposition freeing up energy, designing for self-regulation, and emphasizing emergence and nurturing in creating richer outcomes.
Robots & Startups 0 implied HN points 12 Nov 21
  1. In October 2021, there were 58 funding rounds for robotics and autonomous vehicle companies, raising a total of $1.7B.
  2. 6% of the funding rounds in October were Seed rounds, showing a mix of early-stage and later-stage investments.
  3. SciFounders launched an accelerator program and fund that provides scientist founders with control over voting rights, emphasizing support for founders in the industry.
Sector 6 | The Newsletter of AIM 0 implied HN points 09 Oct 23
  1. Tesla's self-driving cars are not fully autonomous; they are at Level 2, meaning drivers still have to be ready to take control anytime.
  2. Wayve, a UK company, has achieved Level 5 technology, where cars can drive themselves completely without human intervention.
  3. Wayve's system uses a new approach called GAIA-1 that combines video, text, and actions to create realistic driving scenarios.
Cobus Greyling on LLMs, NLU, NLP, chatbots & voicebots 0 implied HN points 23 Apr 24
  1. Large Language Models (LLMs) can help autonomous vehicles predict if other cars will change lanes and explain those predictions clearly.
  2. It's important for these predictions to be quick, ideally under 500 milliseconds, so cars can respond fast in traffic.
  3. Integrating LLMs can improve trust in self-driving cars by making their decision-making process clearer and easier to understand.