Tag Archives: Autonomous

Xpeng Engineer Guilty Of Stealing Apple Car Secrets!

XPeng Engineer Guilty Of Stealing Apple Car Secrets!

An XPeng engineer just pleaded guilty to stealing trade secrets from the Apple Project Titan self-driving car program!

Here is what we know so far…

 

XPeng Engineer Guilty Of Stealing Apple Car Secrets!

A former Apple engineer who joined Xpeng – the Chinese electric vehicle maker, just pleaded guilty to the criminal charge of stealing trade secrets from the Apple self-driving car program!

Zhang Xiaolang initially pleaded not guilty to the charges, but he reached a plea deal with prosecutors and changed his plea to guilty, according to court documents released on Monday, August 22, 2022.

The plea deal is sealed, so the details are unknown. Zhang’s attorney, Daniel Olmos, confirmed the plea agreement but declined to comment on the details. Sentencing however is set for November 2022.

Zhang faces a maximum sentence of 10 years in prison, and a $250,000 fine. With this plea deal, he should serve a much shorter sentence.

In addition to Zhang, US federal prosecutors also charged Chen Jizhong with stealing secrets from the Apple self-driving car program. Chen, however, continues to plead not guilty, and will have his day in court on August 29, 2022.

Chen is also represented by the same lawyer as Zhang – Daniel Olmos.

Recommended : Did China Make 7nm Chips In Spite Of US Sanctions?!

 

How XPeng Engineer Stole Apple Car Secrets!

Zhang Xiaolang worked on the Apple Project Titan autonomous vehicle program as a hardware engineer between 2015 and 2018, during which he designed and tested circuit boards.

He travelled to China during his paternity leave in 2018, and on returning in April 2018, he told his boss at Apple that he was leaving to work for XPeng (Guangzhou Xiaopeng Motors Technology) in China.

XPeng, also known as XMotors in the United States, is a Chinese electric car startup backed by Alibaba, Foxconn and IDG Capital. It has developed electric cars like the XPeng G3 and XPeng P5.

His boss felt that Zhang was “being evasive” during the meeting. There was also increased network activity and visits to his office, before he resigned. All that led to an internal Apple investigation of his two company-issued phones and laptop.

That’s when they discovered that Zhang had been downloading confidential files from the Apple lab during his time away. He was also caught on CCTV removing circuit boards and a Linux server from their lab.

Zhang’s network activity was found to consist of “both bulk searches and targeted downloading copious pages of information from the various confidential database applications“.

Recommended : US Mil Contractor Admits Selling Aviation Secrets To China!

Zhang was arrested at the San Jose airport in July 7, 2018, before he could board a last-minute, one-way flight to China aboard Hainan Airlines.

In an interview with Apple’s security team, Zhang admitted that he downloaded the data online, and removed hardware from its labs. He also admitted to the FBI that he stored the files he downloaded on his wife’s laptop.

The FBI described the data he stoled as “largely technical in nature, including engineering schematics, technical reference manuals, and technical reports“.

The files – about 24 GB worth – include a 25-page document containing engineering schematics of a circuit board, as well as technical manuals and PDFs related to the Apple self-driving car prototype.

The other Apple engineer to be charged with stealing secrets of its autonomous car project – Chen Jizhong – was accused of stealing stolen thousands of sensitive documents, as well as 100 photos taken inside its self-driving facility – all discovered in a hard disk drive he owned.

Chen was also arrested when he attempted to board a flight to China, ostensibly to visit his ill father.

Recommended : TikTok Leak : China Repeatedly Accessed Private User Data!

 

XPeng Denies Involvement In Theft Of Apple Car Secrets!

XPeng said in a Weibo post that it was aware of the plea agreement from media reports, but it was “not clear about the details, nor involved in further investigation conducted by US law enforcement“.

It has been more than four years into the case, and we are not aware of the specifics of the case and have not been involved in the follow-up investigation of the case by the US judiciary.

We also have no relevant dispute with Apple and have no connection with the case. We strictly abide by relevant laws and attaches great importance to intellectual property protection.

Zhang joined XMotors in May 2018, but the company quickly distanced itself from its employee, stating on July 11, 2021 :

There is no indication that he has ever communicated any sensitive information from Apple to XMotors.

XMotors always has strictly abided by the laws of China and the United States and takes protection of intellectual property rights seriously.

Company spokesperson Isabel Jiang also stated that once they were notified in late June 2018 that US authorities were investigating Zhang, they secured his computer and office equipment and denied him access to his work. They subsequently fired him.

XPeng also said that Zhang signed an intellectual property compliance document on the day he joined, and that there was “no record that he reported any sensitive and illegal situations” to the company.

 

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KasperskyOS : First Successful Automotive ECU Integration!

Kaspersky just announced the first integration of their new automotive KasperskyOS into the ECU of an advanced driver assistance system by AVL SFR. Here are the details…

 

Automotive KasperskyOS : What Is It?

Modern vehicles are complex systems, which makes it hard to manage the security of its components.

KasperskyOS for automotive ECUs combines a secure microkernel operating system, with a security policy enforcement engine (Kaspersky Security System), and a trusted channel encrypted framework.

It is designed to secure onboard systems and communications, ensuring safer OTA updates, fleet management and safer autonomous driving.

 

KasperskyOS Integration Into AVL ADAS ECU

The new AVL Software and Functions GmbH (AVL SFR) ADAS ECU features two high-performance SoCs (system-on-a-chip), and a safety controller..

This new ECU platform also supports Controller Area Network, and automotive Ethernet standards, allowing for secure communications between devices in the vehicle – including cameras and LIDARs.

The integration of KasperskyOS into the ECU guarantees that undeclared functionality – either unnoticed at launch, or inserted through system updates – cannot be exploited. This is especially important in the safety of autonomous vehicles.

All interactions between electronic components is controlled by the Kaspersky Security System, the security policy engine within KasperskyOS. It monitors the launch of processes, as well as communications between those components and the operating system.

This new ADAS ECU by AVL SFR is ready for prototyping projects by OEMs and Tier-1 suppliers.

 

Kaspersky Automotive Adaptive Platform for KasperskyOS

Kaspersky is also a new associate partner of AUTOSAR, a consortium aimed at developing mutual standards for automotive software architecture.

To that effect, they developed a software development kit (SDK) called Kaspersky Automotive Adaptive Platform.

With this SDK, AVL SFR can develop applications for automated and even driverless vehicles – such as delivering auto-piloting features, controlling safety systems and monitoring their health.

This set of libraries also allows for other software to be adopted, which follow AUTOSAR Adaptive requirements, and work on KasperskyOS without additional changes.

Kaspersky Automotive Adaptive Platform is ready to be delivered and AVL SFR is showcasing its auto-piloting application to several automotive customers.

 

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NVIDIA DRIVE Deep Neural Networks : Access Granted!

NVIDIA just announced that they will be providing the transportation industry access to their NVIDIA DRIVE Deep Neural Networks (DNNs) for autonomous vehicle development! Here are the details!

 

NVIDIA DRIVE Deep Neural Networks : Access Granted!

To accelerate the adoption of NVIDIA DRIVE by the transportation industry for autonomous vehicle development, NVIDIA is providing access to the NVIDIA DRIVE Deep Neural Networks.

What this means is autonomous vehicle developers will now be able to access all of NVIDIA”s pre-trained AI models and training code, and use them to improve their self-driving systems.

Using AI is central to the development of safe, self-driving cars. AI lets autonomous vehicles perceive and react to obstacles and potential dangers, or even changes in their surroundings.

Powering every self-driving car are dozens of Deep Neural Networks (DNNs) that tackle redundant and diverse tasks, to ensure accurate perception, localisation and path planning.

These DNNs cover tasks like traffic light and sign detection, object detection for vehicles, pedestrians and bicycles, and path perception, as well as gaze detection and gesture recognition within the vehicle.

 

Advanced NVIDIA DRIVE Tools

In addition to providing access to their DRIVE DNNs, NVIDIA also made available a suite of advanced NVIDIA DRIVE tools.

These NVIDIA DRIVE tools allow autonomous vehicle developers to customise and enhance the NVIDIA DRIVE DNNs using their own datasets and target feature set.

  • Active Learning improves model accuracy and reduces data collection costs by automating data selection using AI, rather than manual curation.
  • Federated Learning lets developers utilise datasets across countries, and with other developers while maintaining data privacy and protecting their own intellectual property.

  • Transfer Learning gives NVIDIA DRIVE customers the ability to speed up development of their own perception software by leveraging NVIDIA’s own autonomous vehicle development.

 

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DiDi Adopts NVIDIA AI + GPUs For Self-Driving Cars!

At GTC China 2019, DiDi announced that they will adopt NVIDIA GPUs and AI technologies to develop self-driving cars, as well as their cloud computing solutions.

 

DiDi Adopts NVIDIA AI + GPUs For Self-Driving Cars!

This announcement comes after DiDi spliced out their autonomous driving unit as an independent company in August 2019.

In their announcement, DiDi confirmed that they will use NVIDIA technologies in both their data centres and onboard their self-driving cars :

  • NVIDIA GPUs will be used to train machine learning algorithms in the data center
  • NVIDIA DRIVE will be used for inference in their Level 4 self-driving cars

NVIDIA DRIVE will fuse data from all types of sensors – cameras, LIDAR, radar, etc – and use numerous deep neural networks (DNNs) to understand the surrounding area, so the self-driving car can plan a safe way forward.

Those DNNs (deep neural networks) will require prior training using NVIDIA GPU data centre servers, and machine learning algorithms.

Recommended : NVIDIA DRIVE AGX Orin for Autonomous Vehicles Revealed!

 

DiDi Cloud Computing Will Use NVIDIA Tech Too

DiDi also announced that DiDi Cloud will adopt and launch new vGPU (virtual GPU) cloud servers based on NVIDIA GPUs.

The new vGPU licence mode will offer more affordable and flexible GPU cloud computing services for remote computing, rendering and gaming.

 

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NVIDIA DRIVE AGX Orin for Autonomous Vehicles Revealed!

NVIDIA just introduced the DRIVE AGX Orin – a new software-defined platform for autonomous vehicles and robots!

Here is a quick primer on NVIDIA DRIVE AGX Orin, including its key capabilities and specifications!

 

NVIDIA DRIVE AGX Orin for Autonomous Vehicles + Robots

At GTC China 2019, NVIDIA unveiled the DRIVE AGX Orin – the culmination of a four-year development process.

The NVIDIA DRIVE AGX Orin is a new system-on-a-chip (SoC) designed to drive a software-defined platform for automatous machines.

The Orin is designed to handle large numbers of applications and deep neural networks simultaneously, while achieving systematic safety standards like ISO 26262 ASIL-D.

Built as a software-defined platform, the NVIDIA DRIVE AGX Orin can be used to develop architecturally-compatible platforms that are scalable from Level 2 to Level 5 (full self-driving) vehicles.

Since both Orin and Xavier are programmable through Open CUDA and TensorRT APIs and libraries, developers can work on both, leveraging their investments across both product lines.

Recommended : DiDi Adopts NVIDIA AI + GPUs For Self-Driving Cars!

 

NVIDIA DRIVE AGX Orin Performance

With 17 billion transistors, the Orin combines Arm Hercules CPU cores with NVIDIA GPU cores, as well as new deep learning and computer vision accelerators.

According to NVIDIA, the DRIVE AGX Orin delivers an aggregate performance of 200 trillion operations per second (200 TFLOPS) – almost 7X faster than the previous generation NVIDIA DRIVE Xavier SoC.

Recommended : NVIDIA DRIVE Deep Neural Networks : Access Granted!

 

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