This year, Paris Mondial de l’Auto has regained more manufacturers, more visitors than previous edition. People still seems to love cars, they make kids to seniors dreaming. We could feel electricity on the air because it is everywhere. A lot of new models from French brands on super design booths. Chinese cars almost occuped one of the four pavillons of Paris convention center, with more sedan’s than city cars, even exentric premiums.
Paris Mondial will return in october 2026.
After seeing AI companies attract more and more money (article here), there is an increasing financial investments by American tech giants – Microsoft, Google and Amazon – who are positioning themselves for the future by choosing nuclear energy.This move is particularly strategic because nuclear energy stands out as an energy source that does not produce CO2 emissions while providing a reliable and constant supply of electricity.As the computing requirements of the AIs they develop continue to increase, these companies are committing billions of dollars to meet their energy needs. Those who do not have access to sufficient energy resources could suffer in the competitive landscape of AI development.
Milan Kovac, VP Head of Engineering Optimus at Tesla shared a couple of news after 10/10 event held at Warner Bros. studios in California.
Here a summerize:
Tesla Bot recently held an event where it showcased the progress of its Optimus robots. About 20 active robots chatted with visitors for about four hours at the 10/10 event. The robots demonstrated impressive balance and mobility, and there was only one minor incident. Highlights included the unveiling of a new generation of hand and forearm that greatly improves dexterity and sense of touch.
Work continues, and marks advances in the robot’s autonomy: Optimus is now able to visually navigate indoors using its 2D cameras. It can avoid obstacles, navigate autonomously, carry payloads, and dock to recharge. Efforts to improve autopilot technology, used in both cars and robots, have contributed to these improvements.
Additionally, Optimus is being trained to interact with humans and respond to gestures and voice commands to give them snacks and drinks. There is certainly still a lot of work to be done, but there is optimism by Elon Musk’s teams about future developments.
For the second time, after 2022, PFA (Platform of French Automotive) organise its Summit during the Paris Mondial at Paris Convention Center, Porte de Versailles in Paris.
Concern and determination are the two impressions that were revealed by the various top leaders’ interventions (see list below)
The European automotive industry is facing a drop in sales on the old continent that is multifactorial:
– General economic slowdown
– Increase in energy prices
– Demographic decline of potential buyers
– Arrival of Chinese vehicles
– Cut-throat regulation that could worsen the situation
But the manufacturers, tier one suppliers and side players, back to the wall, want to be combative. They have the collective will to organize themselves on several items:
– Innovation (batteries, Software Defined Vehicle, ADAS, AI)
– Industrial collaboration at a European scale
– Alliances with Asian players
– The call to EU political bodies for support adapted to current and future realities of sector
Introduction by Luc Chatel President of PFA
Keynotes :
Luca de Meo, CEO Renault Group
Oliver Zipse, CEO BMW Group
Christophe Perillat, CEO Valeo
John Bozzela, President of the International Organization of Motor Vehicle Manufacturers (OICA), president and CEO Alliance for Automotive Innovation (USA)
Carlos Tavares, CEO Stellantis
Interview :
Patrick Pouyanné, CEO TotalEnergies
Christel Heydemann, CEO Orange Group
Closing : Antoine Armand, Minister of Economics, Finance and Industry of France
Luc Chatel, President Platform of French Automotive
Use-Case that described a common situation leading to many accidents:
Pedestrian crossing partly masked by a bus, a pedestrian surrounds from behind the bus.
As the vehicle is approaching the pedestrian crossing, it slows down slightly (a prudence function is activated at the crossing, which can be disabled if you believe your customers prefer that, similar to other Prudence Functions in the tool). We could also incorporate contextual information to determine if the area is urban or peri-urban. The vehicle detects the parked bus, geolocates it, and recognizes that it is partly masking the view of the pedestrian crossing, prompting a reduction in speed even if no pedestrian is currently visible. When the pedestrian does appear, the vehicle can stop at a deceleration of 0.5 g, avoiding the activation of the Automatic Emergency Braking (AEB) system.
Please note that we cannot calculate the potential collision with a pedestrian because potential pedestrian is masked by the bus.
The pilot system is a PID (you can utilize your existing pilot).
Understand Vehicle HMI:
See video : simulation with AURELION (dSpace)
The vehicle is driven by SafetyNex, on a real pathway around Nexyad office (digital twin).
« Who Is That You Are Chatting With? Oh, Just ChatGPT.
The artificial intelligence chatbot’s Advanced Voice Mode feature has delighted some users and weirded out others.
When you think of what a voice programmed by artificial intelligence would sound like, you might picture something robotic and stilted, with a staccato cadence incapable of capturing the inflections, speed and emotion required to sound even somewhat human. But this is 2024, and the robots have gotten a serious upgrade. Now they can imitate voices, accents and intonation to an almost creepy degree — for better or worse. »
For better or worse ? The both of course.
This could probably be nice for a typical user looking for information, ordering a meal, or making a doctor’s appointment, and even support for a single person who no longer communicates with others. But it also risks generalizing deep fake vocals.
When cavemen banged stones on top of twigs to warm themselves with fire, it was a great innovation, a step forward for the human kind. And then they discovered other less positive uses…
Nexyad’s innovation, BYOD* SafetyNex, in its informative driving assistance mode for fleets and/or insurance companies, consists of warning drivers on board when they are not being prudent behind the wheel in real time. SafetyNex can then launch simple messages by anticipation such as: « slow down » or even contextualized « slow down dangerous bend », etc.
Our tool enhanced with ChatGPT-type technologies could then launch alerts such as « Honey, please slow down » in your wife’s voice, or « Daddy, go slower » in your child’s voice.
In this combination, our 100% positive innovation will make the vocal imitation for the better way. *Bring Your Own Device
It takes time in science to estimate the scope of important work.Finally, John Hopfield born in 1933 and Goeffrey Hinton in 1947, have just jointly obtained the 2024 Nobel Prize in Physics for their work carried out since the 80’s on machine learning.
Goeffrey Hinton is known for his applications:
Backpropagation in machine learning is a gradient estimation method commonly used for training neural networks to compute the network parameter updates.
Boltzmann machine, a statistical physics technique applied in the context of cognitive science.
Deep learning (considered as one of the godfathers) is a subset of machine learning methods based on neural networks with representation learning.
Capsule neural network (CapsNet) is a machine learning system that is a type of artificial neural network (ANN) that can be used to better model hierarchical relationships. The approach is an attempt to more closely mimic biological neural organization.
John Hopfield developed :
Hopfield network (or associative memory) is a form of recurrent neural network, or a spin glass system, that can serve as a content-addressable memory.
Modern Hopfield networks(also known as Dense Associative Memories) are generalizations of the classical Hopfield networks that break the linear scaling relationship between the number of input features and the number of stored memories.
Andrej Karpathy joins Sarah and Elad in this week of No Priors. Andrej, who was a founding team member of OpenAI and the former Tesla Autopilot leader, needs no introduction. In this episode, Andrej discusses the evolution of self-driving cars, comparing Tesla’s and Waymo’s approaches, and the technical challenges ahead. They also cover Tesla’s Optimus humanoid robot, the bottlenecks of AI development today, and how AI capabilities could be further integrated with human cognition. Andrej shares more about his new mission Eureka Labs and his insights into AI-driven education and what young people should study to prepare for the reality ahead.
Complexity Reduction Technology, Gain of Time and Money
SafetyNex by Nexyad is a technology that reduces with 100 factor (at least) complexity of development, test and validation for Highly Automated vehicle or HAV.
We do not use Petaoctets of recorded data for treatment in computers farms large as malls. Nexyad worked on a new paradigm based on experience of prudent professional drivers, experts on road safety, and info from insurers, building a metric of prudent driving. Ordinary PC runs our technology using 5% of CPU.
SafetyNex doesn’t identify scenarios, but works on separated elements or events that make up scenarios. We associate a PRUDENCE FUNCTION to each detected element/event in parallel. Prudence functions are dynamic as elements/events are. We fusion them in real time with knowlegde-based, fuzzy logic and possibility theory AI. Doing so, SafetyNex replicates the way humans manage prudence/risk.
Use-Cases Simulation Video of Safetynex
The road, shown in video below, really exists in France near Nexyad office. AI SafetyNex is interfaced with RTMaps of Intempora dSPACE Company in simulation sensors tool AURELION by dSPACE. We just changed trees and houses, but alignment of the road is the same than real world. The legal speed limit is 80 km/h or 50 mph all the way.
Nexyad SafetyNex controls longitudinal and lateral of vehicle. HMI of autonomous vehicle on video shows legal speed sign, current speed on the left, square of prudence (green, yellow or red) with next speed to apply at tapering given distance, and the reason by road sign. Just below, the prudence target accepted: here we have set the threshold of driving prudence at 50% (range from 0 to 100). This corresponds to an occasional driver, not very experienced.
In the following video (eagle & cockpit views), in two use-cases, elements/events are:
a) use-case Winding Curves (prudence function)
b) use-case Curve (prudence function 1) with No Visibility (prudence function 2) In the second use case (curve with no visibility) two prudence functions are merged*.
So AI SafetyNex manages autonomous driving, reading and analysing a map thru eHorizon and detects winding curves ahead in use-case a, deciding prudent speed at n meters.
Then use-case b, curve (prudence function 1) with no visibility (prudence function 2) is detected both on map (Here Technologies) and by Aurelion sensors (camera). SafetyNex reduces speed anticipating possible object hidden ahead. In this example there a very slow truck on the road. Once truck detected, SafetyNex turns red and decides to brake. Notice that collision was avoided because of the previous slowing down of prudence functions 1 and 2. With the legal speed of 80 km/h or 50 mph, car would have ended up in the truck or in the scenery.
Nexyad SafetyNex Use-Case Curve with No Visibility – Reality and Simulation
Look at this simple seemingly use-case and think how it can be imagined and recorded in this particular context (this type of curve there) by classical method of scenarios…
*if you want to challenge SafetyNex, and see several prudence functions merged to make a complex situation in urban area for example, contact us.
Money for AI, whereas Open AI creator of ChatGPT raises new $ 6,6 billion, Startup Poolside that aims to create AI capable of “human-level intelligence” in software developmentpockets $ 500 million at B serie, and HPC-AI Tech specializing in AI software infrastructure and video generation gets a first round of $ 50 M.
We have developed an AI technology for vehicle fleets (trucks, cars, two-wheelers) that measures driver prudence in real time. Where our competitors measure possible indirect consequences of poor driving, such as harsh braking, we offer a real prudence metric. This metric was developed through 12 research programs co-financed by the French government, and is currently being deployed in India. The company MOTIV AI from Coimbatore has in fact developed a smartphone App based on our technology SafetyNex.
Thanks to this App, fleets reduce the number of accidents and therefore reduce their operating costs. They can also train their drivers to be more careful.
Stellantis Chief Software Officer Yves Bonnefont, interviewed by S&P Global Mobility about Software-Defined-Vehicle technology.
Yves Bonnefont, Stellantis Chief Software Officer
Challenges, Issues and Strategy.
– Key factors driving Stellantis to develop SDVs.
– SDV architecture transformations and their potential impact on vehicle operations
– The division of software development between Stellantis and suppliers?
– Developing more software in-house that supports more of the platform, API and parent stack, or even deepening the software stack
– Organizational challenges related to SDV development
– Situations where hardware upgrades can be performed in the field
– Development of SDVs for the entire product portfolio or mainly for BEV platforms or the premium segment
– Security precautions, especially for SDVs that have deeper cloud connections
This year, the European New Car Assessment Program (NCAP) — an independent and respected safety body by the automotive industry – decided to introduce new rules in January 2026 that will require the vehicles it assesses to have physical controls in order to receive a full five-star safety rating. Car manufacturers in Europe are being encouraged to stop using touchscreens for basic functions such as indicators and windscreen wipers to make driving safer.
The trend for bare dashboards apart from a screen was started by Tesla. It was a kind of revolution, then followed by almost every manufacturers.
But for some time now, Enhance Automotive, a Bulgarian company (yes, you read that right) founded by Dimitar Stoimenov, has been offering what it calls sexy buttons. And these sexy buttons that are stuck within reach around the driver, but why not also the passengers (for functions that are not related to driving) are enjoying some success and are really transforming Elon Musk’s cars with command shortcuts and more to see their Website.
Nexyad is working on a feature that will soon be activated by a sexy button.
Stay tuned.
A NEW PARADIGM FOR AUTONOMOUS VEHICLE : reduce development, test/validation times by at least a factor 100.
When we want to automate the driving of a vehicle, it is natural to contact automation engineers. Their approach is to list the use cases. Each use case is a scenario, for example: a red vehicle follow another one blue approaching a roundabout with also a bicycle traveling in front.
The events building this scenario are: presence of a roundabout, presence of blue vehicle located in front, presence of a bicycle located in front.
Depending on the relative and absolute speed of these vehicles and their position as well as that of the roundabout (N scenarios built from these events), we deduce the desired behavior for our red vehicle to be automated.
Each desired behavior is obtained by a control law which generally includes 6 parameters. We therefore obtain 6 x N parameters just for this simple use case.
This is to be multiplied by the number of use cases. In practice, we quickly end up with a few hundred or even a few thousand parameters, which is very difficult to adjust or even impossible. And the run time of such a system requires strong embedded CPUs. It is difficult to scale.
Nexyad has developed a new approach based on a prudence metric that makes the solution scalable and which uses automation only to modulate the comfort parameters. This approach does not work on scenarios but on events: we assign to each event a « prudence function ». In our case mentioned above, we will characterize the following events; a roundabout, a vehicle in front, a bicycle in front. This makes a total of 3 « prudence functions » (instead of N scenarios). Once these 3 events have been characterized in terms of prudence, we take into account the current scenario by combining the « prudence functions » with fuzzy logic and theory of possibilities. All possible scenarios for combining these three events are taken into account in a logical manner.
We keep only one parameter which is the « lack of prudence target », which characterizes the sportiness of the vehicle.
Prudence function are independent functions that can be tunes separately. This new paradigm reduces times of development and test/validation by a factor 100 at least.
It calculate prudence of automated vehicles (from predictive ACC to level 4). This prudence is a KPI of the vehicle.
It is an eXplainable Artificial Intelligence (XAI).
This system runs with only 5% of the CPU of a conventional PC type computer. The autonomous vehicle can at least be scalable and adjustable. This technology is called SafetyNex, to learn more: Autonomous Cars & Autonomous Trucks driven by Prudence (nexyad.net)
California Governor Gavin Newsom vetoes US’s first bill Safe and Secure Innovation for Frontier Artificial Intelligence Models Act. California with Silicon Valley is home to some of AI’s biggest players including: OpenAI, Anthropic, Google, or Meta.
AI is more than ever a subject of lively controversy in the USA and in the rest of the world, with its defenders and its detractors.
On the other side of the Atlantic, there is already an EU AI Act, but there is no AI giant companies.
After amazing olympic games this summer, Paris continue to welcome guests from the world with Paris Motor Show 2024. Cars lovers will be delighted with a return of that seems to be great this year. Alsmost major brands will be present. We notice a serious landing of Chinese companies, numerous suppliers and technology providers.
Come in large numbers at Porte de Versailles Convention center in Paris, 15th arrondissement.
NxNeural by Nexyad is a new AI Tool integrated into Excel in the form of a menu, ready for use. Nx Neural uses all the power of Excel for data management and its graphics for display. Data Scientists can easily analyse Data on Excel without coding with Python or C++, for Data Manipulation function and neural processing function.
An article by Steffen Hoffmann, Managing Director at Bosch UK:
People shouldn’t fear AI but should instead learn how it works in the background to benefit society.
Public perceptions of artificial intelligence (AI) are evolving and many use cases demonstrate the positive benefits that it can bring to society across the globe.
It’s a technology that promises to reshape our world in unprecedented ways and this revolutionary potential partly explains why some people are cautious about AI’s impact.
In the Western world, less than half of the respondents agreed that “AI technologies will change the world for the better,” with the perception being much more positive in Eastern countries with 75% in India and 82% in China.
This is the new concept of Artificial Intelligence described for the first time in 2007. Of course, as usual for some analysts, this AGI could surpass human intelligence, like generative intelligence and AI at all. The principle would be that these systems could have a kind of understanding and control of themselves, or a conscience, with the capacity to modify their code without human intervention. Link to article below.
In 2001: A Space Odyssey, we understood that HAL 9000, the AI of the Discovery One ship, had a sort of birth, then a laborious apprenticeship like a child, to bring it to a level of cognition equivalent to, or even superior to, human members of the crew. Finally, HAL 9000 having its own assessment of the mission to be accomplished, comes into conflict with the astronauts and kills the most of them.
Another aspect of Stanley Kubrick’s film sets that human intelligence involves the duality of good and evil for reasons of survival at all costs, power and control. This intelligence transposed to machines could lead to the same consequences.
HAL 9000
Azimov initially solves this problem with his three laws of robotics. But later, some robots amend these simple laws to place the safety of humanity before that of the individual.
This reminds us of the questions posed by AIs controlling autonomous vehicles. In extreme cases, will they choose to hit the group of little girls? The senior couple? Or will they drive into a wall, endangering the vehicle’s passenger(s)?
Nexyad’s AI, SafetyNex, is based on the knowledge of road safety experts, professional drivers, traffic police, and insurers. It is designed to help robotized driving systems according to the context they encounter, for safety of their passengers and that of other road users. SafetyNex analyzes prudent driving according to the road context 20 times per second and reduces speed as soon as prudence decreases, to always respect the traffic rules code and safe driving recommendations. The mission of our AI is to save lives and it anticipates risky situations so as not to have to make value judgment choices.
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