Avalue EMX-PTLP – A thin mini-ITX motherboard powered by up to an Intel Core Ultra 7 358H Panther Lake-H SoC
#artificialintelligenceai
STMicroelectronics Stellar P3E quad-core Arm Cortex-R52+ automotive MCU features Neural-ART AI accelerator
Mimiclaw is an OpenClaw-like AI assistant for ESP32-S3 boards
Can Anthropic Control What It's Building?
Qualcomm IPQ5424 embedded router board supports 22 Gbps tri-band Wi-Fi 7 and dual 10GbE networking
reComputer Jetson AGX Orin Developer Kit GMSL Bundle features 8x GMSL2 camera interfaces, 10GbE networking
A driverless car without steering wheel, pedals, or gear shift
http://www.youtube.com/watch?v=CqSDWoAhvLU
What does a built-from-the-ground-up Google Self-Driving Car Project look like? Well, you start by taking away all the things that allow you to actually drive the thing — you take away the steering wheel and pedals that give a driver control.
Two Seats — No Back Or Front
There’s no steering wheel, pedals, or gear shift. Instead, just push a button and they’ll take you where you want to go!
Stay updated on Telegram with latest updates from Google Home/Assistant ecosystem.
Safety First
The car has about two feet worth of foam in the front to dampen any collision, and a plastic windshield instead of shatterable glass.
The self-driving car is part of a bigger vision for re-envisioning the transportation environment. If you look at people who are too old, too young, or disabled, and can’t get around, that’s a big challenge for them. Just imagine, how could this change transportation for them. Expect to see about 100-200 prototypes by end of this year on road.
Google wants to reinvent the car by replacing the whole idea of driving
The next stage of Auto Industry will be a paradigm shift as an ultimate driverless machine rather than a marginal gain.
Automakers are taking an incremental approach, where they let the car drive itself in the situations it can handle and turn control back over to the human driver when the car encounters something it can’t handle. Google says that won’t work, and has data to prove it. The problem is that the carmakers’ approach requires that the human “driver” remain ready and alert at all times, doing all of the mental work of driving so that if called upon to take over they know what’s going on and what needs to be done. Given how many people don’t pay adequate attention to their driving even when they are in sole control of the vehicle, this is clearly insane.
Google tested it by giving 100 employees semi-automated cars and then recording the results. Even though the employees knew the technology was a prototype, as soon as they saw it working well they immediately put far too much confidence in it, proceeding to ignore the road for large amounts of time. These employees were skilled engineers with a deep understanding of automation and much better able to judge what the car can or cannot do than the general population.and their judgment terrified the skilled engineers who built the vehicles. That is why it is extremely tough to get from incremental improvement to full self-driving.
Stay updated on Google News with the latest updates from Google Home/Assistant ecosystem.
So, Google Self-Driving Car Project believes in an all or nothing approach: either the car must be able to handle the job entirely on its own or it’s not ready for real-world deployment. At a minimum, if the car encounters a situation it can’t handle it must be able to give the human driver plenty of notice before he or she has to take over. Expecting the driver to be ready to take over at any instant simply will not work.
Of course, what’s even better is if we simply remove human driving from the equation entirely. Get the car to the point where it can really handle anything that can come up, and remove the human controls. That is what Google is working towards.
Google is attempting autonomy in city driving, a challenge, at a different order of magnitude from what BMW and most of the rest are aiming for. In some ways this is primarily a mapping challenge. There is a kind of ambitious genius in what Google is aiming for – and of course the implications, positive and negative, are debatable – but the spirit of it seems to go against the grain of what people are ready for.
Interested in learning more about the Google Assistant and Smart Home? Subscribe to WAV newsletter via Email.
A car from the future, people are willing to get inside today. The future’s coming a lot faster than we thought.
Things you can do from here:
- Subscribe to this blog on Feedly, or Google News, or via RSS.
- Keep the conversation going, Join 60000+ users in our Community
- Follow Deepak(Author), on Medium or Twitter or Quora
- Do click Like button below or share it to other interested readers.
#ArtificialIntelligenceAI #EmergingTechnology #SelfDrivingCar
Fusion HAT+ Review – Adding AI voice and servo/motor control to Raspberry Pi for robotics, Smart Home, or education
Trump’s Profiteering Hits $4 Billion
M5Stack AI-8850 LLM Accelerator M.2 Kit offers an alternative to Raspberry Pi AI HAT+ 2
Jupiter 2 – RVA23-compliant SBC features SpacemiT K3 octa-core RISC-V AI SoC, up to 32GB RAM, 256GB UFS
UP Xtreme PTL Edge – Intel Core Ultra X5 338H/X7 358H Panther Lake AI mini PC features 40-pin GPIO header, RS232/RS485 COM ports
Congatec conga-TCRP1 COM Express Type 6 module features AMD Ryzen AI Embedded P100 SoC with 50 TOPS NPU
AI Unlocks Hundreds of Cosmic Anomalies in Hubble Archive https://science.nasa.gov/missions/hubble/ai-unlocks-hundreds-of-cosmic-anomalies-in-hubble-archive/ #NASA #ArtificialIntelligenceAI #Astrophysics #AstrophysicsDivision #Galaxies #GoddardSpaceFlightCenter #GravitationalLensing #HubbleSpaceTelescope #IrregularGalaxies #OriginEvolutionOfTheUniverse #TheUniverse
MaixCAM2 modular 4K AI camera is based on Axera AX630 SoC with 3.2 TOPS NPU (Crowdfunding)
Raspberry Pi CM5-based outdoor PoE security camera features 12.3 MP IMX500 sensor, IP66 enclosure
Innodisk EXEC-Q911 COM-HPC Mini kit is powered by a Qualcomm Dragonwing IQ-9075 Edge AI SoC
Lanner EAI-I351 – An NVIDIA Jetson Thor Edge AI computer with 100GbE QSFP28 port and 8x GMSL2 camera
Hiwonder WonderLLM – An ESP32-S3 smart chat module with 2-inch touch display, 2MP camera, and dedicated voice chip
NASA AI Model That Found 370 Exoplanets Now Digs Into TESS Data http://dlvr.it/TQVdwj #AmesResearchCenter #ArtificialIntelligenceAI #Exoplanets
Client Info
Server: https://mastodon.social
Version: 2025.07
Repository: https://github.com/cyevgeniy/lmst