• UberPeople.NET - Independent community of rideshare drivers. It's FREE to be a person and enjoy all the benefits of membership. JOIN US! CLICK HERE

AI genius leaves Princeton lab to beat Uber, Google, and Intel

Maven

Well-Known Member
Business Insider - March 18 2017 - In the spring of 2016, Dr. Jianxiong Xiao — affectionately known among students and staff as "Professor X" — said goodbye to his plum professorship at Princeton and his post as the founding director of the school's Computer Vision and Robotics Labs.

By the fall of that same year, Xiao, known as something of a risk-taker, had moved himself and his family from New Jersey to Silicon Valley, and raised some modest seed funding for his new startup focused on self-driving cars.

His startup, dubbed AutoX, has done its best to stay under the radar to date — apart from a filing with the California DMV to test self-driving vehicles.

The filing officially put the professor's mysterious startup in the company of giants, such as Tesla, Waymo (formerly the Google self-driving car project), Uber, and numerous other big auto companies testing self-driving cars.

But Xiao isn't worried about getting run over by the giants, saying that his small team of academics possesses the kind of expertise in computer vision that big corporations just can't match. Exhibit A: after only six months on the job, Xiao says he's already developed a prototype vehicle that can do the same things as the cars made by his deep-pocketed rivals, at a fraction of the cost.

AutoX gave a first peek at its creation on Friday, with a debut video showing its prototype system in action. The car itself isn't anything special in terms of style (it's basically just a regular 2017 Lincoln MKZ that's been rigged with AutoX technology), but it deftly navigates residential streets near San Jose, seeming to handle driving situations such as cloudy days and night-time, historically a challenge for self-driving cars, with ease.

As noted in the video, AutoX's system doesn't rely on the LIDAR laser arrays or other expensive sensors that most self-driving cars, including Waymo's and Uber's, require to function. Instead, AutoX uses advanced artificial intelligence to "see" through cameras mounted on the car and steer the car accordingly.

Better yet, Xiao tells Business Insider that the cameras that power this AutoX prototype were purchased at Best Buy for $50 a pop. "It could not be cheaper than that," he says.

From Xiao's standpoint, that's a crucial point: While future iterations of AutoX technology will support ultrasonic sensors and LIDAR and all that stuff for the sake of enhancing driver safety, the startup is currently focused on building the cheapest and most accessible system for self-driving cars that it possibly can.


While Waymo's self-driving cars sport cameras to "see" around them, they mostly rely on LIDAR laser arrays and other radar sensors to function. Waymo; Business Insider/ Skye Gould

To Xiao, self-driving cars have the potential to benefit society, from cutting down on traffic, to providing more autonomy for the disabled, to making long-distance trucking safer and more efficient. The next step for AutoX is building out a fleet of test cars, so it can test the technology with a variety of different vehicles types.

"Self-driving [cars] shouldn't just be a luxury, but be available to every citizen," Xiao says.

Purely academic
A thoughtful speaker, Xiao says he got the nickname Professor X because some of his peers at Princeton found his actual name "very complicated" (his personal web page includes a link to hear a sound of how his name is pronounced).

The term for Xiao's specific field of study is "computer vision," a branch of artificial intelligence that's just as applicable to self-driving cars as it is to Snapchat puppy filter selfies.

For Xiao, it's been a long-time area of interest. Over the years, he's won recognition from the likes of Google and Amazon for his and his team's advancements in the field of computer vision. In 2013, Xiao received his PhD from MIT, right before he went to Princeton.

The impetus for going from academia to Silicon Valley was simple, he says: He had long seen self-driving cars as a huge potential market for computer vision. After consulting with his network of computer vision and autonomous driving experts in academia, he decided the time was right to take a big leap and go into business.

This readout from an Uber self-driving car shows how it uses a LIDAR laser array to "sense" the world around it. AutoX just uses ordinary cameras in its current form.Uber

It's that academic pedigree that gives AutoX an advantage, Xiao says, as it "enables us to to tap into the academic research network." With artificial intelligence experts in such high demand in Silicon Valley, it helps with recruiting that Xiao and his team already have personal relationships with many of the best and brightest in the field.

"We've known these people in person for many years," Xiao says.

Nowadays, Xiao says, AutoX is about 20 people strong, almost all engineers, with PhD-level computer vision talent that had previously worked at companies like Apple, Magic Leap, and Microsoft.

And with all that brainpower on board, Xiao says that they were able to build their prototype from scratch in only six months, without using anyone's technology. With the Waymo/Uber self-driving car IP lawsuit rocking Silicon Valley, that's a huge plus.

Xiao says the shift from academia to startup has required a subtle change in how he approaches problems. In academia, you tend to flit from one project to the next. At a private company like AutoX, you "actually make things work, actually get things done" in service of one big idea. In this case, self-driving cars.

Driven to success
While Xiao stresses this system is still a prototype, he does say it indicates the way he wants to see AutoX go, with a focus on building real self-driving technology that can handle every situation, versus more limited driver-assist features like Tesla's autopilot, which can only be engaged on freeways.

AutoX isn't much interested in manufacturing cars and going head-to-head with Tesla, Xiao says. He's equally uninterested in following the controversial Comma.ai into helping people give their existing cars limited self-driving features.

Instead, Xiao says, he's looking to partner up with auto manufacturers for their future vehicles. AutoX provides the core technology, almost like an operating system, that car companies can then take, customize to their exact needs, and use as the basis for their own autonomous systems.

Residential streets can present a challenge for self-driving cars. Waymo

Additionally, Xiao says that AutoX is similarly looking to license out its software to trucking companies, factory operators, and the like.

Xiao also wants to distinguish between AutoX and the technology from companies like Mobileye, which Intel bought for $15 billion this week — Mobileye helps self-driving car systems gather the data, but other software has to step in to interpret that data and help guide the car accordingly. AutoX is the whole package, says Xiao.

"We're building the brains for self-driving vehicles," Xiao says.
 

RamzFanz

Well-Known Member
This is one thing I think a lot of people are missing in their predictions. There's probably far more brain power in self driving cars right now than all of the space agencies combined. JMHO.
 

Jesusdrivesuber

Well-Known Member
Lol, they weren't using AI to begin with or was it that badly coded compare to the guy's strings?

I thought all companies were using AI, this guy is going to make a killing once he gets his software to gold.
 

tohunt4me

Well-Known Member
This is one thing I think a lot of people are missing in their predictions. There's probably far more brain power in self driving cars right now than all of the space agencies combined. JMHO.
What a waste of talent.

Business Insider - March 18 2017 - In the spring of 2016, Dr. Jianxiong Xiao — affectionately known among students and staff as "Professor X" — said goodbye to his plum professorship at Princeton and his post as the founding director of the school's Computer Vision and Robotics Labs.

By the fall of that same year, Xiao, known as something of a risk-taker, had moved himself and his family from New Jersey to Silicon Valley, and raised some modest seed funding for his new startup focused on self-driving cars.

His startup, dubbed AutoX, has done its best to stay under the radar to date — apart from a filing with the California DMV to test self-driving vehicles.

The filing officially put the professor's mysterious startup in the company of giants, such as Tesla, Waymo (formerly the Google self-driving car project), Uber, and numerous other big auto companies testing self-driving cars.

But Xiao isn't worried about getting run over by the giants, saying that his small team of academics possesses the kind of expertise in computer vision that big corporations just can't match. Exhibit A: after only six months on the job, Xiao says he's already developed a prototype vehicle that can do the same things as the cars made by his deep-pocketed rivals, at a fraction of the cost.

AutoX gave a first peek at its creation on Friday, with a debut video showing its prototype system in action. The car itself isn't anything special in terms of style (it's basically just a regular 2017 Lincoln MKZ that's been rigged with AutoX technology), but it deftly navigates residential streets near San Jose, seeming to handle driving situations such as cloudy days and night-time, historically a challenge for self-driving cars, with ease.

As noted in the video, AutoX's system doesn't rely on the LIDAR laser arrays or other expensive sensors that most self-driving cars, including Waymo's and Uber's, require to function. Instead, AutoX uses advanced artificial intelligence to "see" through cameras mounted on the car and steer the car accordingly.

Better yet, Xiao tells Business Insider that the cameras that power this AutoX prototype were purchased at Best Buy for $50 a pop. "It could not be cheaper than that," he says.

From Xiao's standpoint, that's a crucial point: While future iterations of AutoX technology will support ultrasonic sensors and LIDAR and all that stuff for the sake of enhancing driver safety, the startup is currently focused on building the cheapest and most accessible system for self-driving cars that it possibly can.


While Waymo's self-driving cars sport cameras to "see" around them, they mostly rely on LIDAR laser arrays and other radar sensors to function. Waymo; Business Insider/ Skye Gould

To Xiao, self-driving cars have the potential to benefit society, from cutting down on traffic, to providing more autonomy for the disabled, to making long-distance trucking safer and more efficient. The next step for AutoX is building out a fleet of test cars, so it can test the technology with a variety of different vehicles types.

"Self-driving [cars] shouldn't just be a luxury, but be available to every citizen," Xiao says.

Purely academic
A thoughtful speaker, Xiao says he got the nickname Professor X because some of his peers at Princeton found his actual name "very complicated" (his personal web page includes a link to hear a sound of how his name is pronounced).

The term for Xiao's specific field of study is "computer vision," a branch of artificial intelligence that's just as applicable to self-driving cars as it is to Snapchat puppy filter selfies.

For Xiao, it's been a long-time area of interest. Over the years, he's won recognition from the likes of Google and Amazon for his and his team's advancements in the field of computer vision. In 2013, Xiao received his PhD from MIT, right before he went to Princeton.

The impetus for going from academia to Silicon Valley was simple, he says: He had long seen self-driving cars as a huge potential market for computer vision. After consulting with his network of computer vision and autonomous driving experts in academia, he decided the time was right to take a big leap and go into business.

This readout from an Uber self-driving car shows how it uses a LIDAR laser array to "sense" the world around it. AutoX just uses ordinary cameras in its current form.Uber

It's that academic pedigree that gives AutoX an advantage, Xiao says, as it "enables us to to tap into the academic research network." With artificial intelligence experts in such high demand in Silicon Valley, it helps with recruiting that Xiao and his team already have personal relationships with many of the best and brightest in the field.

"We've known these people in person for many years," Xiao says.

Nowadays, Xiao says, AutoX is about 20 people strong, almost all engineers, with PhD-level computer vision talent that had previously worked at companies like Apple, Magic Leap, and Microsoft.

And with all that brainpower on board, Xiao says that they were able to build their prototype from scratch in only six months, without using anyone's technology. With the Waymo/Uber self-driving car IP lawsuit rocking Silicon Valley, that's a huge plus.

Xiao says the shift from academia to startup has required a subtle change in how he approaches problems. In academia, you tend to flit from one project to the next. At a private company like AutoX, you "actually make things work, actually get things done" in service of one big idea. In this case, self-driving cars.

Driven to success
While Xiao stresses this system is still a prototype, he does say it indicates the way he wants to see AutoX go, with a focus on building real self-driving technology that can handle every situation, versus more limited driver-assist features like Tesla's autopilot, which can only be engaged on freeways.

AutoX isn't much interested in manufacturing cars and going head-to-head with Tesla, Xiao says. He's equally uninterested in following the controversial Comma.ai into helping people give their existing cars limited self-driving features.

Instead, Xiao says, he's looking to partner up with auto manufacturers for their future vehicles. AutoX provides the core technology, almost like an operating system, that car companies can then take, customize to their exact needs, and use as the basis for their own autonomous systems.

Residential streets can present a challenge for self-driving cars. Waymo

Additionally, Xiao says that AutoX is similarly looking to license out its software to trucking companies, factory operators, and the like.

Xiao also wants to distinguish between AutoX and the technology from companies like Mobileye, which Intel bought for $15 billion this week — Mobileye helps self-driving car systems gather the data, but other software has to step in to interpret that data and help guide the car accordingly. AutoX is the whole package, says Xiao.

"We're building the brains for self-driving vehicles," Xiao says.
We can't cure cancer,but we can spend all of this money on self driving cars .
What an achievement . . . . .
 

RamzFanz

Well-Known Member
What a waste of talent.
As compared to what? Going to the moon? How many lives and injuries did that save?

The moon missions were all about being superior and proving what we already knew. Not worthless, not unworthy of the effort for science and technology, but a huge expenditure to show we were better.

We can't cure cancer,but we can spend all of this money on self driving cars .
What an achievement . . . . .
I agree in principle. In reality, massive amounts of money are spent on curing cancer which is mostly self induced. Avoid sugar, carbs, and smoking and you're pretty much golden with proper screening.
 

Maven

Well-Known Member
  • Thread Starter Thread Starter
  • #6
...We can't cure cancer,but we can spend all of this money on self driving cars ...
The 1971 "War on Cancer" spent huge amounts of money with only limited success. "Cancer" is a vague term that applies to 100s of widely different disease pathologies. While progress was made on some, others proved far more difficult to find a treatment, let alone a cure. Implementing self-driving cars, while undeniable difficult and expensive, is likely to prove far easier and cheaper than curing cancer.
As compared to what? Going to the moon? How many lives and injuries did that save? The moon missions were all about being superior and proving what we already knew. Not worthless, not unworthy of the effort for science and technology, but a huge expenditure to show we were better. I agree in principle. In reality, massive amounts of money are spent on curing cancer which is mostly self induced. Avoid sugar, carbs, and smoking and you're pretty much golden with proper screening.
Like implementing self-driving cars, going to the moon, while undeniable difficult and expensive, has already been proven to be far easier and cheaper than curing cancer.

You have great suggestions about minimizing sugar, carbs, smoking, and having regular screenings. However, that does not account for the growing rate of cancers and other health problems caused by environmental contaminants. Every passing year, we learn that something we thought was safe is not. The steering wheel cover that I recently bought (and all the other I looked at) had a warning saying wash your hands after touching to minimize lead contamination. The number and variety of environmental contaminants is growing and accelerating. Modern medicine cannot keep pace.
 
Last edited:

RamzFanz

Well-Known Member
The 1971 "War on Cancer" spent huge amounts of money with only limited success. "Cancer" is a vague term that applies to 100s of widely different disease pathologies. While progress was made on some, others proved far more difficult to find a treatment, let alone a cure. Implementing self-driving cars, while undeniable difficult and expensive, is likely to prove far easier and cheaper than curing cancer.

Like implementing self-driving cars, going to the moon, while undeniable difficult and expensive, has already been proven to be far easier and cheaper than curing cancer.

You have great suggestions about minimizing sugar, carbs, smoking, and having regular screenings. However, that does not account for the growing rate of cancers and other health problems caused by environmental contaminants. Every passing year, we learn that something we thought was safe is not. The steering wheel cover that I recently bought (and all the other I looked at) had a warning saying wash your hands after touching to minimize lead contamination. The number and variety of environmental contaminants is growing and accelerating. Modern medicine cannot keep pace.
Good point. Same goes for processed food ingredients.
 
Top