Traffic simulation is essential for autonomous vehicle (AV) development, enabling comprehensive safety evaluation across diverse driving conditions. However, traditional rule-based simulators struggle to capture complex human interactions, while data-driven approaches often fail to maintain long-term behavioral realism or generate diverse safety-critical events. To address these challenges, we propose TeraSim, an open-source, high-fidelity traffic simulation platform designed to uncover unknown unsafe events and efficiently estimate AV statistical performance metrics, such as crash rates. TeraSim is designed for seamless integration with third-party physics simulators and standalone AV stacks, to construct a complete AV simulation system. Experimental results demonstrate its effectiveness in generating diverse safety-critical events involving both static and dynamic agents, identifying hidden deficiencies in AV systems, and enabling statistical performance evaluation. These findings highlight TeraSim's potential as a practical tool for AV safety assessment, benefiting researchers, developers, and policymakers. The code is available at https://github.com/mcity/TeraSim.

TypeScript and Python are two programming languages that support optional type annotations, which are useful but tedious to introduce and maintain. This has motivated automated type prediction: given an untyped program, produce a well-typed output program. Large language models (LLMs) are promising for type prediction, but there are challenges: fill-in-the-middle performs poorly, programs may not fit into the context window, generated types may not type check, and it is difficult to measure how well-typed the output program is. We address these challenges by building OpenTau, a search-based approach for type prediction that leverages large language models. We propose a new metric for type prediction quality, give a tree-based program decomposition that searches a space of generated types, and present fill-in-the-type fine-tuning for LLMs. We evaluate our work with a new dataset for TypeScript type prediction, and show that 47.4% of files type check (14.5% absolute improvement) with an overall rate of 3.3 type errors per file. All code, data, and models are available at: https://github.com/GammaTauAI/opentau.

As one of the largest North American automotive suppliers, Bosch develops Driver Assistance functions like Adaptive Cruise Control (ACC), Predictive Emergency Brake Systems (PEBS), Lane Departure Warning/Keeping Systems (LDW, LKS), Predictive Pedestrian Protection, Road Sign recognition, head light control, Advanced Parking Assistance, and many more. For these functions Bosch has all necessary sensors in our portfolio (e.g. In our offices in Plymouth, MI and Palo Alto, CA we develop state of the art systems as well as advanced features leading to partly/highly automated driving. Join us to become part of the exciting and growing field of Driver Assistance. We are on the mission to turn latest technology into outstanding Bosch products and services.

As one of the largest North American automotive suppliers, Bosch develops Driver Assistance functions like Adaptive Cruise Control (ACC), Predictive Emergency Brake Systems (PEBS), Lane Departure Warning/Keeping Systems (LDW, LKS), Predictive Pedestrian Protection, Road Sign recognition, head light control, Advanced Parking Assistance, and many more. For these functions Bosch has all necessary sensors in our portfolio (e.g. In our office in Plymouth, MI, we develop state of the art systems as well as advanced features leading to partly/highly automated driving. Join us to become part of the exciting and growing field of Driver Assistance. In our team we are developing the perception of the next generation of automatic parking systems.

The CIO's primary focus during this pandemic-induced work-from-home stretch has been to keep hardware healthy and data safe. But in America's factories, warehouses and distribution centers, where "work from work" is almost always the only option, the technology directives understandably center on protecting human capital. You might think the recipes for success between the two scenarios are very different. But it might surprise you to learn that many of the ingredients are very similar. Fortunately for Trilogy Health Services, which runs 28 senior living facilities across four midwestern states, the company already had nearly 80 percent of its 15,000 employees on its internal communication app when the virus hit.