BRN - Mercedes

[equanimous]

Is Mercedez F1 team utilizing Akida??

How Formula 1 uses machine learning to spice up races

To help make racing safer for drivers, yet more exciting for viewers, Formula One has turned to cloud computing.

www.afr.com

How Red Bull plans to take AI in F1 to the next level

www.motorsport.com

Instead, the most exciting aspect for both the team and its partner was in how they both planned to drive forward the use of AI and ML in F1.

Neuromorphic Computing for Autonomous Racing

With the rise of successful uses of artificial intelligence (AI) and machine learning (ML) for a wide variety of applications in the last decade, there has been a corresponding increase in interest in applying AI and ML methods to develop intelligent autonomous systems

Algorithm: EONS For training and designing an SNN for this task, we use Evolutionary Optimization for Neuromorphic Systems (EONS) [22]. EONS is based on evolutionary algorithms and trains SNNs for deployment to neuromorphic hardware

We use the LIDAR sensor as the observation, and we utilize information about distance traveled, collisions, and laps completed as part of our fitness evaluation

SUMMARY AND FUTURE WORK Here, we demonstrate a workflow for training a neuromorphic SNN in simulation targeting a particular hardware platform. We demonstrate the success of that workflow on an autonomous racing task. Our next step is to deploy the SNN shown in Figure 4 to 𝜇Caspian and integrate 𝜇Caspian onto the physical car shown in Figure 1.

Neuromorphic Computing for Autonomous Racing (Conference) | OSTI.GOV

The U.S. Department of Energy's Office of Scientific and Technical Information

www.osti.gov

 

[equanimous]

Navigating Driver Privacy and Safety of Electric Vehicles, Self-Driving Vehicles - insideBIGDATA​

A growing number of connected electric vehicles, as well as the evolution of self driving and automated vehicles are putting a greater demand on processing power. New technologies are advancing rapidly with the introduction of new processing methods, according to experts at BrainChip Holdings...

insidebigdata.com

Navigating Driver Privacy and Safety of Electric Vehicles, Self-Driving Vehicles​

August 15, 2021 by Editorial Team Leave a Comment

A growing number of connected electric vehicles, as well as the evolution of self driving and automated vehicles are putting a greater demand on processing power. New technologies are advancing rapidly with the introduction of new processing methods, according to experts at BrainChip Holdings Ltd (ASX: BRN), (OTCQX: BRCHF), a leading provider of ultra-low power high performance artificial intelligence technology.
These automotive systems rely heavily on Artificial Intelligence and Machine Learning (AI/ML) to train an increasing number of sensors, components, image and video processors in each vehicle. Autonomous vehicles and near-autonomous vehicles are predicted to generate 12-15 terabytes (1014) of data for every two hours of driving, and all this data has vulnerabilities as it is uploaded to the cloud. Consumer advocates have raised alarms about operator and passenger privacy, including location data, driver health, speed, and more with the dependence on the cloud.

“Many of the concerns about driverless cars and driver assist systems can be addressed with improved AI/ML operations and internal components,” said BrainChip Founder and CEO Peter van der Made. “Safety is a particularly salient one, but energy efficiency, privacy and security are critical considerations for the automotive industry and their supply chain to address.”

Notable ways that improved technology “under the hood” will reduce accidents, protect data, and conserve energy include:
Real-time learning
Improved chips can perform “incremental learning,” and add to their knowledge of the world as they are confronted with new information. Object recognition is one situation when real-time learning is impactful – a car needs to “see” whether an object in the road is a rock, an animal, or a plastic bag and be able to recognize the differences of each to react accordingly. Under current AI/ML processing methods, all are viewed as obstacles.
“Real-time incremental learning, sometimes called one-shot learning, makes it possible to train a chip within a fraction of a second, and trigger corrective action,” said van der Made. “As this is widely adopted, the safety improvements will be enormous.”
On-chip learning
Traditional microprocessors are too slow to perform the type of calculations that are required to recognize objects. A large array of parallel operating cells, each operating according to the same principle as brain cells, perform rapid computations in the vehicle, rather than sending data to a cloud / data center and then waiting for instructions. Not only does this reduce latency so decisions are made faster, it removes the need for internet connectivity, so the vehicle continues to operate even when there is no internet available. And, by retaining data within the vehicle itself, instead of transmitting it to a remote location, security and personal data privacy is vastly improved.

“On-chip learning is likely the single biggest breakthrough for the automotive industry, because this alone addresses critical concerns like response times and data privacy,” said van der Made. “A car travelling at 110 km/h does 50 meters in one second. A one-second, or even a fraction of a second delay in receiving data from the cloud could be fatal.”

Greener processing
Today’s luxury cars contain many microchips. In the future, more advanced self-driving cars will have so many on-board computing systems that their power consumption will have a major impact on the car’s performance. Smaller, light weight, energy-efficient chips will reduce this impact. Ultra low power brain-like processors that can deliver high performance object recognition and an overall higher range of efficiency, so the car’s battery performance or overall power consumption is maximized.

“Combined with on-chip learning, power-efficient processors will also save vast amounts of energy versus transmitting data via the cloud,” said van der Made. “A back-of-the-envelope calculation suggests a 97% energy savings over current technologies, which not only improves the efficiency of the car, it reduces the data center’s energy use.” Each instance that runs on a remote data center is contributing to its huge carbon footprint.

Mechanical monitoring
Advanced AI processing can be used to monitor the health status of the vehicle for early diagnostics through real-time analysis of sensor data. Sensors can identify sounds, vibrations, even odors to identify upcoming problems or failures. This is a safety feature that also eliminates human error, reduces labor and maintenance costs, and prevents machinery deterioration.
Operator monitoring
Future systems will be capable of “seeing” the driver to gauge attention, to verify their identity to ensure they are authorized to operate the vehicle, and alert drowsy or distracted drivers instantly.

“There are valid reasons to question the safety and security of self-driving cars, but the largest and most dangerous threat is the processing limitation of present technologies,” said van der Made. “Less capable processors are the real obstacle, especially if corners are cut. It is critical that all data is processed within the car itself, that the data be protected from leak or attack, and that these developments do not come at a greater cost to people or even our planet.”

BrainChip’s Akida™ brings artificial intelligence to the edge in a way that is different from existing technologies. The solution is high-performance, small, ultra-low power and enables a wide array of edge capabilities. The Akida AKD1000 and its intellectual property can be used in applications including Smart Home, Smart Health, Smart City and Smart Transportation. These applications include but are not limited to home automation and remote controls, industrial IoT, robotics, security cameras, sensors, unmanned aircraft, autonomous vehicles, medical instruments, object detection, sound detection, odor and taste detection, gesture control and cybersecurity

 

[Ian]

 

[equanimous]

Convolutional Spiking Neural Networks for Detecting Anticipatory Brain Potentials Using Electroencephalogram

[2208.06900] Convolutional Spiking Neural Networks for Detecting Anticipatory Brain Potentials Using Electroencephalogram

 

[equanimous]

Convolutional Spiking Neural Networks for Detecting Anticipatory Brain Potentials Using Electroencephalogram

[2208.06900] Convolutional Spiking Neural Networks for Detecting Anticipatory Brain Potentials Using Electroencephalogram

Now who do we know who has a Convolutional Spiking Neural Network chip already commercially available:

View attachment 14268



VI. CONCLUSION AND FUTURE WORK This paper explored the use of a CSNN as a classifier for detecting features in EEG data that predict braking intention, which occurs before the actual physical activity. The EEG data for the classification experiment was collected via an in-house experiment using a pseudo-realistic testbed with the participant operating a remote-controlled vehicle using a live video feed. The CSNN performance was compared to a standard CNN and three GNN models using a 10-fold cross-validation scheme with the CSNN achieving the highest performance and with more consistency. In addition, the effect of converting the floating-point EEG data into spike trains prior to training the CSNN was studied. The best results were obtained using a threshold of 0.5, which were similar to those obtained using floating-point data, suggesting that spike train transformation might be possible with acceptable levels of performance degradation. Future work includes assessing the performance of the CSNN in different environments, particularly when the cognitive functions of the participants are stressed because of, for example, fatigue or distractions. In addition, the ability of the CSNN to decode the participant’s intention in other EEG control signals in BCI applications, such as P300, motor imagery, motor-related cortical potentials and steady-state evoked potentials would be of interest. Implementation of the CSNN on a neuromorphic platform to study energy efficiency is another area of future research.

https://arxiv.org/pdf/2208.06900.pdf

 

[Deleted member 118]

Mercedes to Develop Autonomous Vehicles

The automaker has teamed with Tencent Cloud Computing to develop self-driving cars

www.iotworldtoday.com

 

[Deleted member 118]

IDEMIA pioneers mass-scale connectivity fleet swap with Mercedes-Benz | Frontier Enterprise

IDEMIA, the France-based identity technologies firm, has completed the first-of-its-kind mass-scale remote SIM provisioning campaign in the automotive industry with its Automotive Connectivity Manager platform. The group worked with Mercedes-Benz to transfer over 700,000 vehicles from one...

www.frontier-enterprise.com

 

[supersonic001]

Mercedes-Benz AG on LinkedIn: #mercedesbenz #eqssuv #leadinelectric #futuremobility #ai #mbux… | 32 comments

Fewer operating steps thanks to artificial intelligence The second generation of our MBUX system is also used in the EQS SUV. With adaptive software, the… | 32 comments on LinkedIn

www.linkedin.com

 

[supersonic001]

Second Gen already, exciting, things moving quickly in tech, and the SUV no less !!

 

[Terroni2105]

As part of its first Automotive Investor Day today, Qualcomm announced a pair of new partnerships with Mercedes-Benz and Red Hat.

The latest announcements are focused on the software defined vehicle area. Mercedes-Benz will be adopting Qualcomm Snapdragon cockpit chips to power next-generation infotainment and connectivity systems. This marks a shift away from Nvidia which Mercedes has used in its current MBUX system. The first Mercedes vehicles with Qualcomm digital cockpit will launch in 2023.

Qualcomm Announces New Automotive Partnerships With Mercedes-Benz And Red Hat

As part of its first Automotive Investor Day today, Qualcomm announced a pair of new partnerships with Mercedes-Benz and Red Hat.

www.forbes.com

i watched the Qualcomm Auto investor day posted in the Qualcomm thread, where Qualcomm CEO states they have been working with Mercedes for 3 years.

 

[toasty]

As part of its first Automotive Investor Day today, Qualcomm announced a pair of new partnerships with Mercedes-Benz and Red Hat.

The latest announcements are focused on the software defined vehicle area. Mercedes-Benz will be adopting Qualcomm Snapdragon cockpit chips to power next-generation infotainment and connectivity systems. This marks a shift away from Nvidia which Mercedes has used in its current MBUX system. The first Mercedes vehicles with Qualcomm digital cockpit will launch in 2023.

Qualcomm Announces New Automotive Partnerships With Mercedes-Benz And Red Hat

As part of its first Automotive Investor Day today, Qualcomm announced a pair of new partnerships with Mercedes-Benz and Red Hat.

www.forbes.com

i watched the Qualcomm Auto investor day posted in the Qualcomm thread, where Qualcomm CEO states they have been working with Mercedes for 3 years.

To me this is sufficient information to deduce that we are now part of the Qualcomm world..........

My opinion only

 

[Build-it]

Since Mercedes is being discussed in the BRN Discussion thread, here's a link revive the earlier Mercedes thread :

cosors​

Regular​

• Apr 20, 2022
• Add bookmark
• #163

I just had a quick look at the new EQS. The Akida also takes control of parts of the MBUX and display controls. Do I understand this correctly?

"There is much to discover in the digital interior of the new EQS SUV: For example, the optional MBUX Hyperscreen, whose displays self-learn to adapt to your habits, and the large head-up display with augmented reality."

Dio,
Not sure if this answers your question however I believe where in the drivers seat so to speak.

https://www.news.com.au/technology/motoring/luxury/2022-mercedesbenz-eqs-suv-new-car-review/news-story/abf628a70584c5a31846db32145c75b2

And this line is interesting also..

There will soon be a new pinnacle of electric luxury from Mercedes-Benz: the made-in-America EQS SUV.

Edge Compute.

 

[Build-it]

Dio,
Not sure if this answers your question however I believe where in the drivers seat so to speak.

https://www.news.com.au/technology/motoring/luxury/2022-mercedesbenz-eqs-suv-new-car-review/news-story/abf628a70584c5a31846db32145c75b2

And this line is interesting also..

There will soon be a new pinnacle of electric luxury from Mercedes-Benz: the made-in-America EQS SUV.

Edge Compute.

https://www.google.com/url?sa=t&source=web&rct=j&url=https://group.mercedes-benz.com/company/north-america/mercedes-benz-usa.html&ved=2ahUKEwiv05TGm8D6AhWc4DgGHbRXBv0QFnoECBcQAQ&usg=AOvVaw2jT7US4uhbZY_-TPCiKqd1

A little digging into MB in the USA turned up some interesting info i was unaware of considering the current macro environment concerns for Europe manufacturering the lights should stay on in America.

 

[Pappagallo]

According to the article below this is the next generation Mercedes EQA due in 2025. It’s built on their new MMA platform and I think it’ll probably be the car that debuts the MB.OS operating system as well.

If I was a betting man I’d wager that this swoopy little electric sedan will be the first Merc with Akida riding shotgun (outside of Valeo applications of course).

EQAkida?

https://www.carsales.com.au/editorial/details/spy-pics-2025-mercedes-benz-eqa-sedan-steps-out-138734

 

[stuart888]

Sure hope all 1000 eyes at least knows about Luminar, the Orlando Florida Lidar company.

I have a strong suspicion that the Brainchip implementation-team focused on Mercedes knows them well.

Just akida dot collecting!

https://group.mercedes-benz.com/inn...omous-driving/articlepartnership-luminar.html

Why Orlando?​

There are many reasons why Luminar, the leading autonomous vehicle and lidar technology company for consumer cars and trucking, chooses Orlando as its headquarters, according to Luminar Chief Business Officer Scott Faris.

The primary one, however, is that the largest Department of Defense laser programs (Lockheed Martin, Northrop Grumman and L3 Communications) are all based in Orlando.

The region’s history in aerospace and defense has developed unparalleled expertise in the region for photonics technology. And the ability to leverage this powerful ecosystem allows Luminar to set the bar for high performance sensor technology that will ultimately make autonomous mobility safe and ubiquitous.

 

[BaconLover]

 

[stuart888]

Since Peter asked for some questions, just thinking. First, I would as a shareholder never surprise the BRN team with a question at the AGM or anywhere.

I would send it over and give them a heads up. They might not deem it the right time/place. They know stuff we do not, contracts being negotiated for instance. I am team Brainchip, as a stockholder.

If they let me ask a Question, I would like to be a setup for a winning answer:

Your 4-Bits Are Enough and other publishing's have highlighted your energy inference/ml efficicency. Is the industry in agreement enough where you can proclaim specific features like "keyword spotting" as Category Leading?

As a shareholder, I am not going to surprise Peter with any Linkedin questions, that he is not aware of. Again, from me, Team Brainchip.

I would love to set him up to embellish Akida versions now and upcoming in various Use Cases.

 

[Rise from the ashes]

Since Peter asked for some questions, just thinking. First, I would as a shareholder never surprise the BRN team with a question at the AGM or anywhere.

I would send it over and give them a heads up. They might not deem it the right time/place. They know stuff we do not, contracts being negotiated for instance. I am team Brainchip, as a stockholder.

If they let me ask a Question, I would like to be a setup for a winning answer:

Your 4-Bits Are Enough and other publishing's have highlighted your energy inference/ml efficicency. Is the industry in agreement enough where you can proclaim specific features like "keyword spotting" as Category Leading?

As a shareholder, I am not going to surprise Peter with any Linkedin questions, that he is not aware of. Again, from me, Team Brainchip.

I would love to set him up to embellish Akida versions now and upcoming in various Use Cases.

"If they let me ask a Question, I would like to be a setup for a winning answer:"
We call that a Dorothy Dixer.
Honestly I'm not a fan of them.

 

[Learning]

Forget Tesla. Mercedes is betting $45 billion it can become the king of luxury EVs

Mercedes-Benz Chief Executive Ola Källenius is putting his chips on rebuilding the electric-vehicle motor and outmaneuvering rivals on autonomous driving.

www.latimes.com

Learning 🏖

 

[buena suerte :-)]

Forget Tesla. Mercedes is betting $45 billion it can become the king of luxury EVs

Mercedes-Benz Chief Executive Ola Källenius is putting his chips on rebuilding the electric-vehicle motor and outmaneuvering rivals on autonomous driving.

www.latimes.com

Learning 🏖

Thanks Learning

I very much like the sound of that .... we wouldn't need Tesla!!!(would still be nice) but ..... Mercedes would be enough!!!