Artificial intelligence (AI) is an evolving technology that is still growing, but it is undoubtedly getting better. 

For all we know, factories might not even need lights 20 years later, because most of them will be operated by AI. We see a lot of R&D happening within the AI framework, giving good results. Besides, we see newer frameworks coming in. 

AI-based visual inspection, too, has been growing by leaps and bounds, reshaping automotive inspection. It helps examine detailed defects in vehicles, providing automotive OEMs the opportunity for accuracy and cost-savings. 

One such company focusing on AI-based visual inspection is Lincode Labs, whose AI-backed visual inspection solution, Lincode Visual Inspection System (LIVIS), is its current focus. The company was started with complete research and understanding of the top challenges that manufacturers globally face. After interviewing close to 100 customers, 86 percent of them said that quality inspection happens to be their biggest challenge.

“We were intrigued by this and went to various quality inspection people and identified the technology they were using,” says Rajesh Iyengar, Founder and CEO, Lincode Labs, and goes on, “We went on to find out that the technology hasn’t changed for two decades and there were a lot of false calls in it. That’s when Lincode stepped in and built a product around specific challenges focused on the automotive industry.”

Automotive OEMs, too, look at specifically reducing these false calls and improving productivity, which Lincode has helped solve through its AI-backed visual inspection solution. “The industry standards were 150 to 200 false calls per million inspections. So, in our case, we are doing it in zero to four parts per million,” Iyengar cites.  

Iyengar further reveals that due to this, 80 percent of their customers are repeat orders. “That’s because they are completely happy with the inspection process and the way the inspection is automated,” he mentions.  

LIVIS
Traditional vision systems cannot catch up with AI, as Iyengar says. He avers, “LIVIS stands out because we have built it as a platform. The scalability becomes easier if you’re going to deploy it across multiple factories and locations. But also, the foremost important thing is that it is completely made as a product. Thus, AI is commoditised. With the LIVIS platform, we can bring the cost and time to deployment down.” 

Lincode’s role in the automotive industry
What’s interesting is that even if Lincode caters to the manufacturing industry as a whole, it first addressed the automotive industry. The company researched the market size of various manufacturing companies and the automotive industry took the top spot, with close to USD 542 billion of global value.  

“We started with the automotive industry but pivoted later,” Iyengar tells us and continues, “So, instead of looking at just the automotive or any other industry, we turned our attention to steel, metal, plastic, glass etc. We basically went to the surface and saw how steel and metal are produced today. Whether it’s a CNC machining or forging or casting process, these are major processes used for any industry across the globe involving steel and metal. We understood that steel and metal are dealt with in the same way globally. Therefore, it made sense to go to the surface and into these kinds of defects specifically, and then generalise that and start building a model towards it. This, plus making AI as a product, has made deployment easier across the globe.” 

R&D centre in Bengaluru
Lincode recently opened a new R&D centre in Bengaluru, which also has a significant role to play in deploying the company’s solution across the world.

Stressing on the fact that evolving models are important in AI, Iyengar states, “It’s a continuous process; it’s not that you just build a model and you’re set. We have a big roadmap in the product development, and the Bengaluru R&D centre is going to play a major role in that. We are going to conduct deep research with various data collected across the globe and do various testing with that.” 

Staying ahead
What’s more, Lincode recently closed a funding round in December last year. Catering to a constantly evolving industry like the automotive, Lincode, too, strives to make sure that its visual inspection solution stays ahead and is put to use. “There are about more than 600 parts in a car and each part is segregated – like the structure, wiring, engine components etc.,” Iyengar shares and continues, “These segregations are made so that we can target the sector of the product. For example, when it comes to engine blocks, there is a specific model with a huge data set around engine blocks. This is how we stay ahead of competition.” Iyengar also adds that their trials with various use cases made them understand that inspection alone is not important but also the way the inspection is done. 

Essential skill sets for AI vision systems
Leveraging AI-based visual inspection solutions in the automotive industry is bound to increase productivity, and the cost of labour will also come down because of automation. “Today, most manufacturers use secondary inspection, which can be cut off straight away. This will improve their productivity and also reduce the risk of delays,” Iyengar enlightens. 

Moreover, AI vision systems come with their share of essential skill sets to bring out the best in the automotive industry. Iyengar states that, in general, skilling is required for the factory people. “This could be at various levels,” he puts across and adds, “It could be for the operators, the IT administrator or even the software development team. Hence, deep training is required, which can be somewhat cumbersome because it could be a bit challenging for the operator. So, an IT person might be needed in order to help the operator every time there is a downtime.” 

Covid-19 and AI-backed visual inspection
Such training or skills could certainly come in handy, because Iyengar claims that the need for AI-backed visual inspection solutions in the automotive industry has increased since the Covid-19 pandemic. “Unplanned shutdowns happened during Covid, because of which employees could not report and manufacturing could not continue properly,” he responds and adds, “Hence, a lot of investments are happening because of this. In fact, even now, a lot of employees are still not reporting and the labour problem has become global. It has become tough to get skilled workers. This has led to the adoption of autonomous manufacturing for automotives, where AI is going to play a big role.”

Meeting industry requirements
For an industry that is an economic force globally, AI-based visual inspection is certainly meeting the high-quality requirements of the customers of the automotive sector. Plus, we already see companies like Volvo using the technology. Safety surpasses any requirement, and this requirement can be fulfilled if quality is top-notch. And quality will be at its best if automotive manufacturers can perform production quality inspections in the most efficient way. (MT)

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Infineon Technologies has announced a technology agreement with Qualcomm Technologies, Inc. to integrate a microcontroller-based design pattern into Qualcomm's Snapdragon Ride reference platforms for high-performance computing and in-vehicle Artificial Intelligence (AI).

The initiative combines Qualcomm's systems-on-chip (SoC) with Infineon's hardware and software components for safety management, connectivity and memory handling to support centralised architectures in Software-Defined Vehicles (SDVs). The development will be highlighted ahead of the electronica trade fair in Munich.

The subsystem is built around an Infineon AURIX microcontroller and OPTIREG integrated circuits for power management, operating alongside Qualcomm's Snapdragon Ride and Ride Flex platforms to monitor system health, coordinate safety mechanisms and provide real-time control.

The architecture is supported by a dedicated software package designed to pre-integrate firmware and connect with vehicle networks such as Ethernet and CAN. In addition to the microcontroller subsystem, Infineon contributes BRIGHTLANE Automotive Ethernet and USB connectivity devices alongside SEMPER NOR Flash memory qualified for the Snapdragon Ride ecosystem.

Peter Schiefer, President of the Automotive Division, Infineon, said, "With Qualcomm Technologies’ Snapdragon Ride, we enable the automotive industry to build and scale a new generation of car computers that combine tremendous computing and AI capabilities with the reliability required on the road. Our collaboration reflects a fundamental approach to centralised vehicle computing, which combines a powerful SoC with a set of specialised components around it, including a safety microcontroller, power management, connectivity and memory devices. All these components need to work together seamlessly to help enable safe vehicle operation. Infineon provides essential functional building blocks and integration expertise for building the trust foundation for software-defined vehicles that leverage the power of AI."

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LG Energy Solution has announced the launch of the Battery Innovation Contest 2026 (BIC 2026), inviting universities and research institutions globally to submit research proposals between 29 October and 6 December 2026 via its online open innovation platform, BRIDGE.

Now in its 10^th year, the program aims to identify and fund research concepts with potential for commercialisation across the battery industry. BIC 2026 incorporates two application streams: a thematic call addressing specific development topics identified by LG Energy Solution across materials, cells, battery management systems and artificial intelligence; and an open-topic call permitting researchers to submit original proposals.

To safeguard intellectual property, the contest uses a two-stage evaluation process requiring a brief concept proposal during the initial review before shortlisted applicants submit detailed submissions.

Since 2017, the Battery Innovation Contest has supported approximately 50 research projects. Select projects with verified feasibility have been expanded into longer-term initiatives at the company's Frontier Research Laboratory joint research centres. Previous outcomes include patent filings for physics-based battery management models and research on room-temperature all-solid-state batteries published in academic journals.

Je-Young Kim, CTO, LG Energy Solution, said, "By joining forces, industry and academia can drive innovation across the battery industry. Building on our differentiated technological competitiveness, LG Energy Solution will continue to accelerate its growth in the battery market."

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Wayve, NVIDIA and Stellantis have announced a joint collaboration alongside the French government at the Assises du Véhicule Autonome to support the deployment of autonomous vehicles in France and across the European Union.

The initiative combines Stellantis’ L4-Ready Platforms with the Wayve AI Driver system, integrating NVIDIA Halos OS on the NVIDIA Hyperion compute and sensor architecture. The collaboration aims to establish an autonomous vehicle value chain in France, spanning silicon development, software integration and vehicle manufacturing.

Local transport partners will engage with trade unions, municipal authorities, and mobility stakeholders to address regulatory alignment, safety requirements, and operational deployment.

Philippe Tabarot, French Minister of Transports, said, "I am pleased to see this collaboration between Wayve, NVIDIA and Stellantis launched at the Autonomous Vehicle Forum in France. France is committed to adapting its regulatory framework to accelerate the development of autonomous vehicles while maintaining strict safety and data sovereignty requirements. By bringing together trade unions, city authorities, and mobility stakeholders, this collaboration embodies the collaborative spirit of the Assises du Véhicule Autonome, as well as the approach required to transition from trials to real-world deployment."

Kaity Fischer, VP Autonomous Mobility & Operations, Wayve, said, "France is leading the way in preparing for autonomous vehicles, and we’re proud to enter this collaboration at such an important moment. By working directly with the French Government and our partners, we can help shape how this technology is deployed safely and responsibly and accelerate its development across the country and entire EU."

Anne Laliron, SVP of Technology Research, Stellantis, said, "This collaboration will help accelerate the delivery of autonomous driving technologies that make mobility safer and more convenient for customers. While its impact is global, France is one of Stellantis’ key centres for engineering and technology development, making it a natural home for advancing the future of AI-powered mobility."

Ali Kani, VP of Automotive, NVIDIA, said, "Bringing safe autonomous mobility to Europe requires deep collaboration across AI, computing and vehicle engineering. NVIDIA Hyperion platform, combined with Wayve’s embodied AI and Stellantis’ automotive expertise, provides a foundation for that ambition. Together with the French Government and local partners, we can help build an ecosystem that brings the benefits of autonomous driving to communities across France and Europe."

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German luxury carmaker Audi has introduced third-generation digital OLED rear lighting technology on the Q91, marking the production debut of three-dimensionally curved digital OLED panels in the automotive industry.

The lighting system incorporates carrier glass measuring 0.1 millimetres in thickness, allowing a bend radius of up to 200 millimetres to match the vehicle's body contours. The Q91 uses six digital OLED panels housing 512 individual segments, including an outer curved panel with 99 segments.

The curved positioning extends light visibility to wider lateral angles and incorporates warning symbols within the communication light system to alert surrounding traffic to breakdowns, emergency braking or accidents. Up to eight digital light signatures are available across static, active and semi-active display settings.

The vehicle also features digital Matrix LED headlights utilising a 13-millimetre micro-LED module containing 25,600 individual micro-LEDs. The headlight system projects high-resolution lane lighting, orientation paths and dynamic turn signal graphics directly onto the road surface to assist lane centring and indicate directional changes to pedestrians and other vehicles.

Audi first introduced OLED technology on the TT RS in 2016, followed by segmented digital OLEDs on the Q5 in 2020 and second-generation panels on the Q6 e-tron in 2024.

Stefan Berlitz, Head of Lighting Development at AUDI AG, said, "At Audi, light means safety first and foremost – seeing and being seen. Digitalisation opens up entirely new possibilities for further enhancing road safety. The curved digital OLED technology in the Audi Q91 impressively demonstrates this technology’s potential. It combines design freedom, personalization, and communication with the vehicle’s surroundings at a new level. Our vision is to gradually transform light into an intelligent means of communication that makes interaction between the vehicle and its surroundings even safer and more intuitive."

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