Self-driving cabs "turnip fast run" in Wuhan, Hubei Province, landing, quickly sparked heated debate. The price ranges from 4 yuan to 16 yuan per 10 kilometers, attracting many people to queue up for a taste.It has also made more people realize that autonomous driving is coming a little sooner than expected.
The groundbreaking experiment that landed on the ground was both a test run of the technology's footprint and an impact of the technology on the existing labor structure and industrial landscape.
In addition to stakeholders
The public's attitude has reached a delicate equilibrium
I'm afraid that self-driving won't come.
And I'm afraid of the self-driving mess.
New technologies that free up hands, increase efficiency, and conserve attention will surely lead to social progress and an increase in total wealth. But what about the future of those who depend on driving for their livelihood? How should this account be calculated? This is not a question of choosing "technology" to give up "people".
Sock knitting machine, sock knitter, how to choose?
Today's Turnip Shockwave.
With more than 200 years of
The "Luddite movement" is similar.
One day in the 19th century, the first batch of fast and good sock knitting machines entered a factory in England, and without a word of greeting, a group of sock knitters were on the verge of being "optimized". Struggling to make ends meet, the sock knitters turned their wrath on the machines and entered the factories to destroy them.
Sock loom, sock knitter, what's the choice? History gives the answer. Britain, which chose the sock loom, took the lead in the first industrial revolution and completed its primitive accumulation far ahead of other countries. Today.Instead of expanding unemployment, the sock loom, a new technology born more than 200 years ago, has given inventors of all kinds of machines the opportunity to be bold and creative, and has given us all more beautiful, warmer socks.
There have been countless such choices over the past century or two, and history has made them all one by one. We neither threw away the noodles because of the chef's bowl; we didn't call off takeout because of the noodle maker's bowl; we didn't call off the car because of the coachman's bowl; we banned cameras from smartphones because of Nikon's and Canon's bowls, and that's how we came to have a more and more colorful modern life.
subocular (medicine)
Artificial Intelligence Every Step of the Way
It's all on the public's mind.
See "radish fast running" the first experience passengers share "7 kilometers 5 yuan" order screenshots, we can not help but sigh: "still shaking what number ah"". Shared bicycle is just like that"...... and for the operating company, the dividends of automatic driving is even more needless to say: not only can work continuously, but also do not want to five insurance and one gold, work overtime at any time and any place, known as "the king of cost-effective".
Just as smashing a machine is the sock weaver's stress reaction to seeing a sock loom, people who see autopilot as a beast of prey really don't have to.
"The Radishes lead the way to human self-mastery.
Today, the fast-running "turnip" has its own journey.
The complexity of autonomous driving from pilot to commercial closure tests the technology's availability, reliability and control.
Wuhan residents who experienced the unmanned cab called the Turnip Express "camas radish". In Hubei, the word "camphor" means "stupid": "When it gets stuck in a traffic jam, even in the middle of a busy road, it will brake and stop sharply, very camphorish." A Wuhan resident said after the experience.
This means that at this stage, human drivers still have the advantage of agility, and there are many more skill points that the radish needs to refine.An autopilot closed loop is realized by solving three clear questions: where am I? Where am I going? How to get there?
As a special class of "robots", mobile "automotive robots", autonomous driving requires precise perception, analysis and execution. Sensors, like human eyes, are responsible for collecting information about the external environment while the car is traveling. When the information is passed to the computing unit, the in-vehicle chip, which is like a human brain, utilizes decision-making algorithms to give appropriate control strategies. Then based on the control strategy of the analysis layer, the on-board chip controls the gas pedal, brake, and steering wheel of the car to complete the acceleration, deceleration, steering, and other actions to complete the movement.
This process is simple and clear. However, to realize "real-time" and "accurate", it calls for a technology ecosystem that affects the whole body and "hardware has to be hard and software has to work".
Currently, the evolution of autonomous driving is bound up with the capabilities of artificial intelligence. Recognition, analysis, decision-making, and control, each of which cannot be separated from the sophistication of AI algorithms.
High-order smart driving, which requires high-order algorithms, relies on high-quality data. The problem is that traffic accidents often occur in black swan events with extremely low probability, but it is these extreme scenarios that have the most important data but are the most difficult to obtain. The current high-performance end-to-end models that new energy forces are competing to put on their cars are even more dependent on a large amount of high-quality data.Modeling capabilities will remain a key factor in the direction of the self-driving endgame for the foreseeable future.
So, does practicing modeling fix everything? It's not that simple.On the diagonal of Vehicle-Road Collaboration also stands the player of Bicycle Intelligence.Vehicle-road collaboration has many environmental requirements and high thresholds, while single-vehicle intelligence requires only one vehicle. This route is more promising to reach a wider place once it matures.
If the maturity of single-vehicle intelligence still takes a long time, autonomous driving under the route of vehicle-circuit coordination has the opportunity to move from intelligence to sharing, which will in turn disrupt the travel market and reshape the pattern of automobile consumption.
When a higher percentage of car purchases come from travel platforms
Instead of every family
Then the design, production, sale and insurance of vehicles
It's gonna be a different story.
Industry chain discourse, bargaining power
It is an artificial intelligence business,
OEMs, travel platforms
Or a new character yet to be born?
Leaving the Cave for the Promised Land.
Automatic driving is not the first application of artificial intelligence to face the subject of "sock loom and sock knitter", let alone the last one. Unmanned supermarkets, unmanned warehouses have begun to realize, unmanned distribution, unmanned mines, unmanned airports, unmanned farms will also be realized in the future.Change is only getting bigger and faster. The unstoppable efficiency revolution has made the windfalls all but fleeting.
Similar range to new energy vehicles
Humanity will also enter the "Long Mileage Era".
The "long" is not just the length of life.
More representative of the long-term perspective
Before insecurity strikes, one might as well ask one's own next generation: will they really want to continue to drive online cars? Are they going to repeat the life of the previous generation, just as they had to knit socks with their hands in the age of machines, hold on to carriages in the age of automobiles, and dive into the sea in the age of ships? Will the next generation have their new dreams?
Technology never stops to wait for anyone.Even without autopilot, the Netflix track is too crowded. Netjob drivers are getting more and more saturated as far as the naked eye can see. Order-taking rates are even lower, and the price per passenger is dropping.
If in such a trend, still hold the "refusal to change" obsession, cut off the technology "to make a bigger cake" possibility, it is like the delay out of the cave of the primitive man, although avoided the wind and frost outside the cave, but also missed the beautiful water and grass and the wider world.
