Dans un monde où la sécurité routière est d'une importance capitale, Kilmanger Inc. se distingue comme un pionnier avec sa technologie de pointe de siège intelligent. En parfaite adéquation avec les strictes exigences de la nouvelle Réglementation Générale sur la Sécurité des Véhicules, le siège intelligent de Kilmanger Inc. se positionne comme une solution incontournable pour répondre aux principales préoccupations en matière de sécurité tout en améliorant l'expérience de conduite globale.

A Game-Changer by Kilmanger Inc.

Embracing the ethos of emotional AI, Kilmanger Group Inc. delves into the psyche of drivers, analyzing cognitive behaviors to implement real-time interventions when necessary. The company's approach extends beyond the cold mechanics of technology, acknowledging the human factor in the transportation equations.

En intégrant la technologie de gestion des risques de fatigue, Kilmanger Group Inc. ouvre de nouvelles perspectives, non seulement sur les routes, mais aussi dans les cieux. Les pilotes d'avion peuvent bénéficier de cette avancée majeure pour assurer leur vigilance, minimisant ainsi les risques liés à la fatigue. Une révolution dans la sécurité aérienne qui s'étend au-delà des routes.

Embark on a transformative journey in road safety with Kilmanger's innovative Intelligent Seating System, an unprecedented breakthrough that establishes new standards for driver well-being and transportation security. This comprehensive solution integrates cutting-edge technologies, including Deep Reinforcement Learning, Emotional AI, Multilayer Perceptron (MLP), and  Photoplethysmography. Dive into our exploration of the dynamic interplay between heart health and driver performance, optimizing sleep , mitigating fatigue,  vehicle speed impact, and advancing alcohol detection protocols. Through real-time data analysis and strategic partnerships , we harness the potential of 5G technology and remote driver assistance to prevent accidents and cultivate a safer road environment. Join us on the path to a safer future, as we blend transformative technologies and collaborative innovation to redefine road air transport safety.  

Engineering Evolution Redefined

Improving the efficiency of algorithms for fundamental computations can have a widespread impact, as it can affect the overall speed of a large amount of computations. Matrix multiplication is one such primitive task, occurring in many systems—from neural networks to scientific computing routines. The automatic discovery of algorithms using machine learning offers the prospect of reaching beyond human intuition and outperforming the current best human-designed algorithms. However, automating the algorithm discovery procedure is intricate, as the space of possible algorithms is enormous. Here we report a deep reinforcement learning approach based on AlphaZero1 for discovering efficient and provably correct algorithms for the multiplication of arbitrary matrices. Our agent, AlphaTensor, is trained to play a single-player game where the objective is finding tensor decomposition within a finite factor space. AlphaTensor discovered algorithms that outperform the state-of-the-art complexity for many matrix sizes. Particularly relevant is the case of 4 × 4 matrices in a finite field, where AlphaTensor’s algorithm improves on Strassen’s two-level algorithm for the first time, to our knowledge, since its discovery 50 years ago2. We further showcase the flexibility of AlphaTensor through different use-cases: algorithms with state-of-the-art complexity for structured matrix multiplication and improved practical efficiency by optimizing matrix multiplication for runtime on specific hardware. Our results highlight AlphaTensor’s ability to accelerate the process of algorithmic discovery on a range of problems, and to optimize for different criteria.

By José D. Martín-Guerrero I Lucas Lamata 

University of Zurich 

Songqiao Han I Xiyang Hu