Tricks for using Zoom to have a more human connection in large meetings
Submitted by brad on Fri, 2020-05-29 12:15

I reported last week about Zoox shopping for a buyer. Now reports have surfaced that Amazon is in negotiations. It's a strange matchup but would still have big consequences. A big push into self-driving by Amazon could upend logistics and retail, but Zoox's efforts at a vehicle custom designed for taxi service might be wasted.
Read about it on Forbes.com at Match and Mismatch of Amazon buying Zoox
In a year when several other companies have slowed development and plans for full robocars, MobilEye's CEO this week indicated they were on track to deploy Robotaxi service in Israel in early 2022, and will follow on with France, Korea and China.
Analysis is at MobilEye reaffirms prediction of robotaxi service by 2022
Earlier I wrote about how EasyMile had to stop operations after a sudden stop in one of their vehicles gave minor injuries to a passenger.
Today they announced their plan to resume operations. It includes seatbelts and education. It's a start, but I wonder if the whole idea of "stops" is the problem. Stops are inherent in the 20th century thinking that surrounds public transit. Big vehicles need to make lots of stops picking up and dropping off passengers. But that's a problem if you expect the vehicle not to start until everybody has their seatbelt on!
Everybody shut down testing during the Covid crisis. It's not over but now Waymo and others are getting back on the road, testing vehicles with nobody inside, with one safety driver, and sometimes with two. Yes, delivery and rides are essential services, but what are the issues around this?
Read some thoughts at Forbes's site in Waymo and others resume testing
I've known Zoox since before it began and their vision has always been bold. In a possible hiccup, the downturn has led them to shop around for a potential buyer if they can't get more investment.
I analyse what this means in my story Zoox searches for a buyer on the Forbes site.
Zoox is the $1B funded startup trying to build a radical design self-driving car. Last week they released a video of an hour long drive through Las Vegas, going through pick-up zones in hotels and the airport. The car does a number of impressive things, but at the same time, showing these things and an hour of driving are only the tip of the iceberg of what you need to do, making the video unimpressive at the same time.
In this new article, I go into what goes on in the video, and what it means.
Ready to get on a 10 hour overseas flight, wearing an N95 mask, sharing bathrooms, in the middle seat between two coughing passengers? I didn't think so. With all the idle cruise ships out there, would you sail across the ocean like your grandparents in a private cabin if they followed good virus procedure? 4 days stuck in a room (kinda like now) to prove that your virus test is accurate to the country you're heading to.
Last year Tesla released "smart summon" which let you (very slowly) call your car to you from across a parking lot. It was cute but a bit of a dud, as it's not just very useful. Now Elon Musk promises "reverse summon" that will valet park your car for you. But if you have to watch it, it's not going to be very useful either.
Eventually, though, we'll get a robotic valet park that works without supervision. That will be very useful, allowing cheaper parking and better charging. Even today, the basic summon could allow slightly denser parking for cars that have it.
If you read my earlier report on efforts to convert CPAP machines into ventilators with new firmwware the good news is that the feared massive ventilator shortage seems (for now) to have been avoided.
Tesla doesn't want to use LIDAR. So they are hoping for success in a technique known as pseudo-LIDAR, where you train neural networks to look at images and calculate the distance to everything in the scene, as though you had a LIDAR. It's not here yet, but an interesting question is, should this succeed, is it better for Tesla or for their LIDAR using competitors who already have tons of experience using 3D point clouds?
Uber, Lyft, Scooters and Transit have all cratered in ridership. Will people be more likely to ride in self-driving taxis if they had them during a pandemic crisis? I discuss some of the Covid-19 issues around robotaxis in this new article.
It's found at Can robotaxis survive a pandemic?
Recently, Stefan Seltz-Axmacher, the founder of Starsky Robotics -- a startup doing self-driving and remove-driven transport trucks that I advised before they started going -- wrote a detailed and complex blog post about why he feels his company had to shut down. He goes into several issues, including failures of Deep Learning to meet hype, VC desires, strangeness of the trucking industry and lack of love for safety.
In my new article for the Forbes site, I dig into those reasons and whether he's right that nobody else will succeed soon, either.

I've been involved with delivery robots for a long time, and on my walk through empty streets yesterday, I noticed a certain irony. We have a desperate need for more delivery capacity, especially without humans handling packages, and teams have been working hard to make deliverbots safe enough to drive on our streets.
If we shut down public areas, we're going to need a lot of online shopping and home delivery. How can we do that in a virus-infected world? Here's some plans for how to make it happen even with gig workers (who aren't driving Uber and Lyft much any more.)
I outline some of the ways to make it work in this Forbes.com article.
An EasyMile made a sudden stop from 7mph and a seated passenger fell off her seat to minor injuries. Now NHTSA has ordered EasyMile to stop testing with passengers.
Transit shuttles don't usually have seatbelts, but maybe EasyMile needs them during the testing phase. But can it ever take them out?
This weekend I went to the finals of the GoFly prize, a Boeing sponsored contest for personal VTOL flying machines. Sadly, nobody was able to build one that could meet all the requirements in the rules, and only a few of the contestants could even fly. That was disappointing, but then so was the first Darpa Grand Challenge.
The California robocar disengagement reports are out. And everybody is now pointing out that they're not very useful because everybody uses different methods. So I have an article about what we do learn from the data, little as it is.
Read California Disengagement Reports aren't too engaging at Forbes.com
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