The Bosch Center for Artificial Intelligence (BCAI) serves as Bosch’s center of excellence, dedicated to integrating cutting-edge AI technologies into the company's products and services to create solutions truly “Invented for life.” By leveraging Bosch's vast domain expertise and world-class AI methods, BCAI actively spearheads applied AI projects from initial concept to implementation, bridging the gap between fundamental research and real-world applications. With a strong focus on skills, agility, and openness, BCAI teams, comprising domain experts, data professionals, and software engineers from diverse international backgrounds, are at the forefront of AI research and application.

The 2026 revision of the Current Procedural Terminology (CPT) codes for lower extremity revascularization introduces important changes that are intended to better align code selection with contemporary endovascular practice.1 In this article, I highlight several key updates and illustrate how I applied the revised codes to a case of chronic limb-threatening ischemia (CLTI) in the setting of multilevel occlusive peripheral artery disease (PAD).

We believe intelligence that cannot act in the physical world is incomplete. The next frontier of AI is not only to understand information, but to operate safely and intuitively in the real world. It will be defined by systems that can perceive, reason, learn, and make decisions safely in dynamic physical environments. Systems that understand uncertainty, causality, motion, interaction, and consequence.That requires a different set of problems to be solved: world models that support action, representations grounded in space and physics, policies that adapt under uncertainty, and learning systems that improve through interaction with reality rather than passive observation alone.This is the challenge of embodied AI.

The autonomous vehicle market is poised for transformative growth through 2030, with projections indicating a global market value reaching $2.1 trillion. Industry experts anticipate a robust compound annual growth rate of 22-25% from 2024 to 2030, driven by technological advancements in artificial intelligence, machine learning, and sensor technology. By 2030, approximately 60% of newly sold vehicles are expected to feature Level 2 autonomy capabilities. This expansion presents substantial opportunities across automotive manufacturing, software development, insurance, and logistics sectors. Businesses should strategically position themselves by establishing partnerships with autonomous vehicle technology providers, investing in research and development, and developing complementary services in smart infrastructure and fleet management. Companies that fail to engage with this technological shift risk competitive disadvantage in an increasingly autonomous-focused automotive landscape.

This week in autonomous vehicle news highlights significant regulatory developments shaping the industry's future. Federal investigators are probing crashes involving autonomous vehicle startup Avride in Texas, underscoring heightened scrutiny of safety performance and deployment practices as AV operations expand beyond controlled pilot programs. Meanwhile, Washington DC's Metro system is exploring full automation of its Red Line trains, potentially representing one of the first large-scale driverless heavy-rail transit deployments in the United States. Transit officials suggest automation could enhance train frequency, operational consistency, and reliability while reducing costs. Additionally, Alaska is advancing autonomous vehicle legislation. These developments collectively demonstrate how federal oversight and regulatory frameworks are increasingly shaping operational standards across passenger and delivery-focused autonomous systems as the technology matures.

California's Department of Motor Vehicles finalized comprehensive autonomous vehicle regulations on April 28, 2026, establishing the state's first pathway for testing and deploying heavy-duty autonomous vehicles exceeding 10,000 pounds. The regulations introduce rigorous permitting, safety-case, reporting, and enforcement requirements for all AV manufacturers while maintaining separate requirements for robotaxi operators. Though heavy-duty passenger transport AVs remain prohibited, the rules represent a significant milestone for AV trucking companies seeking access to California's substantial market. The framework provides industry clarity through detailed compliance requirements and tiered permitting for testing and commercial deployment. However, legal challenges from the California Teamsters and opposition from state and federal policymakers threaten implementation, potentially influencing AV regulatory approaches nationwide.

While they may not represent the revolution many predicted, autonomous taxi fleets are rolling out in more cities and becoming a promising urban mobility option. A BCG analysis estimates that the global robotaxi fleet could range between 700,000 to 3 million vehicles by 2035 and that fares in some markets will be lower than traditional ride-hailing services.The speed of deployment will be influenced by the costs of entering new markets, the time needed to scale up, consumers’ willingness to embrace robotaxis, and the degree to which they capture share from other transportation modes. To win in this increasingly competitive market, operators will need patience and years of substantial investment. They’ll also need to navigate complex regulatory, operational, and technological challenges.

Robotaxi networks are experiencing significant expansion into additional cities as commercial operations advance across the United States. This growth reflects increasing confidence in autonomous vehicle technology and its market viability. Companies are scaling their fleet operations to serve broader geographic regions, marking a pivotal moment in the transportation industry's evolution. As robotaxi services become more accessible, they promise to reshape urban mobility, reduce transportation costs, and address congestion challenges. The expansion demonstrates that autonomous vehicle technology has progressed from experimental phases into practical, revenue-generating operations that attract substantial investment and consumer interest.

Stellantis has announced a strategic five-year collaboration with Microsoft to accelerate its digital transformation and AI-driven innovation. The partnership will focus on co-developing over 100 AI initiatives spanning sales, customer care, and operations across the automotive company's global ecosystem. Key initiatives include strengthening cybersecurity defenses with AI-powered analytics to protect vehicles and operations, and modernizing cloud infrastructure to reduce datacenter footprint by 60% by 2029. By combining Stellantis' automotive engineering expertise and multi-brand scale with Microsoft's cloud and AI capabilities, the collaboration aims to enhance customer experiences and drive operational agility across the organization.

Software-Defined Vehicles represent a fundamental paradigm shift in automotive design, transitioning from hardware-centric to software-centric platforms capable of dynamic adaptation and continuous evolution. This comprehensive survey examines SDV architectures, enabling technologies, and operational frameworks, tracing the evolution from distributed electronic control units to centralized computing platforms. The paper reviews critical technologies including service-oriented software architectures, middleware, artificial intelligence, and cloud-based infrastructures, while introducing a structured taxonomy organizing SDV technologies across functional hardware, electrical-electronic architectures, software frameworks, automation mechanisms, and distributed infrastructure. Additionally, the study explores the Software-Defined Internet of Vehicles paradigm, integrating software-defined networking with edge and fog computing to enable scalable vehicular communication, while addressing cybersecurity and interoperability challenges inherent to modern connected vehicles.

The International Energy Agency examines the symbiotic relationship between artificial intelligence and electric vehicle development. AI and advanced computing capabilities are disproportionately benefiting EVs, particularly in autonomous driving and integrated vehicle control systems. The stable, high-voltage power supply inherent to EV batteries creates an ideal environment for sensor and chip integration. While AI benefits extend beyond EVs to hybrid vehicles and general automotive design optimization, autonomous vehicle advancement fundamentally depends on machine learning algorithms and computational power. Modern autonomous vehicles employ diverse sensor arrays including cameras, radars, and lidars to create comprehensive environmental awareness, leveraging sophisticated AI techniques and neural networks that can navigate real-world driving complexity far beyond the limitations of earlier rule-based systems confined to test tracks.

Digital twin technology has emerged as a critical infrastructure component in autonomous systems development, serving essential functions throughout design, validation, and operational phases. A digital twin represents a continuously synchronized virtual replica of a physical autonomous platform, encompassing sensors, actuators, control logic, and environmental interactions. Originally formalized by NASA in 2012, this technology spans multiple classification types, including geometric and kinematic twins for collision modeling and path planning, as well as physics-based twins for simulating complex behaviors and predictive maintenance. Digital twins directly support simulation, testing, safety certification frameworks, and real-time operational intelligence across ground, air, and industrial autonomous systems. By enabling continuous synchronization between virtual and physical platforms throughout the system lifecycle, digital twins facilitate enhanced validation procedures, reduce operational risks, and optimize maintenance strategies across diverse autonomous applications.

Samsung is advancing solid-state battery technology with an innovative silver-carbon composite anode designed to address critical limitations of conventional lithium-ion batteries. The company's breakthrough involves a five-micrometer silver-carbon nanocomposite layer that suppresses dendrite formation—needle-like lithium structures that cause battery degradation and safety issues. This silver-stabilized architecture enables Samsung's "anode-less" design, achieving significantly enhanced performance metrics including 900 Wh/L energy density, 600-mile vehicle range, and nine-minute fast charging capabilities. With mass production targeted for 2027, this development signals a transformative shift in energy storage technology and introduces silver as a critical material in the evolving EV supply chain, positioning Samsung SDI as a leading innovator in next-generation battery solutions.

Neuromorphic computing, which aims to replicate the brain's neuro-synaptic systems through hardware design, is emerging as a promising alternative to traditional computing architectures. Though still in early development, this technology is garnering significant interest from technology companies, scientists, and researchers across multiple sectors, including artificial intelligence, robotics, energy systems, and defence. The concept, originally introduced by Carver Mead at Caltech in the 1980s, involves creating electronic circuits that mimic the analogue behavior of neurons and synapses. However, considerable technical and commercial challenges must be resolved before determining the technology's practical applications and optimal deployment contexts.

Nissan is implementing significant restructuring across its European operations, cutting approximately 900 jobs—roughly ten percent of the region's workforce—as part of its broader Re:Nissan programme targeting 20,000 global job reductions. The majority of cuts affect white-collar and warehouse positions across the UK, France, and Spain, with production roles at the Sunderland plant protected despite consolidating from two manufacturing lines to one. The facility, operating at approximately fifty percent capacity, will maintain its status as an electric vehicle hub while streamlining operations to improve profitability. Additional measures include partial closure of Barcelona's parts warehouse and transition to importer-led distribution in Nordic markets. Spanish unions have strongly opposed the cuts, with negotiations expected to reduce Spain's allocation from the planned five hundred positions.

Nissan announced the closure of its production line at its Sunderland facility in the United Kingdom, resulting in the elimination of approximately 900 jobs across Europe. The Sunderland plant, which manufactures the Qashqai, Juke, and Leaf models, represents a significant shift in Nissan's European operations. This decision reflects broader challenges within the automotive industry, including manufacturing pressures and market dynamics. The closure is expected to have considerable implications for the UK automotive sector and Nissan's European workforce, marking a notable restructuring effort by the Japanese automaker.

Uber et la start-up Pony.ai lancent des essais de voitures autonomes destinées au marché européen. Ce partenariat vise à explorer le potentiel des robotaxis sur le continent, une étape stratégique pour l’essor de la mobilité sans conducteur en Europe.

La singularité technologique de Wayve réside dans sa pile logicielle « AV2.0 », qui s’appuie sur un modèle d’IA généralisée end-to-end. Contrairement aux approches classiques (architecture « sense-plan-act »), l’algorithme de conduite autonome traite directement les données brutes des capteurs (caméras, radars, voire LiDAR) pour piloter le véhicule. Concrètement, cela permet à un robotaxi équipé du système Wayve d’apprendre à circuler dans des environnements urbains variés sans recourir systématiquement à des cartes HD ou à une phase d’entraînement longue et locale.

L'usine, ouverte en 1937 par Ford, fut le haut lieu de Simca avant d'être reprise par PSA à la fin des années 1970, lorsqu'elle employait près de 27.000 salariés. Elle ne fermera pas ses portes pour autant. D'une part car elle accueillera toujours le « Green Campus » dédié à la R&D, aux fonctions support et aux activités de siège de Stellantis en France. D'autre part car le groupe va y localiser une palette d'activités pour « se consacrer aux différentes vies des véhicules », a-t-il indiqué. Pour cela, une enveloppe approchant les 100 millions d'euros sera mobilisée.

Un mois après la présentation du nouveau plan stratégique, c'est la soupe à la grimace pour les syndicats et les salariés de Renault. La direction du constructeur a annoncé vendredi à l'occasion d'un comité de groupe que 15 % à 20 % des postes de l'ingénierie seraient supprimés dans les deux ans à venir au niveau mondial.Selon des chiffres fournis par l'entreprise, Renault compte aujourd'hui près de 12.000 ingénieurs dans ses effectifs, dont la moitié hors de France. Le groupe compte également des centres d'ingénierie (des RTX dans le langage interne) en Roumanie, en Corée du Sud, en Inde, ou encore au Brésil et au Maroc.