Current evaluations of commonsense reasoning in LLMs are hindered by the scarcity of natural language corpora with structured annotations for reasoning tasks. To address this, we introduce KnowLogic, a benchmark generated through a knowledge-driven synthetic data strategy. KnowLogic integrates diverse commonsense knowledge, plausible scenarios, and various types of logical reasoning. One of the key advantages of KnowLogic is its adjustable difficulty levels, allowing for flexible control over question complexity. It also includes fine-grained labels for in-depth evaluation of LLMs' reasoning abilities across multiple dimensions. Our benchmark consists of 3,000 bilingual (Chinese and English) questions across various domains, and presents significant challenges for current LLMs, with the highest-performing model achieving only 69.57\%. Our analysis highlights common errors, such as misunderstandings of low-frequency commonsense, logical inconsistencies, and overthinking. This approach, along with our benchmark, provides a valuable tool for assessing and enhancing LLMs' commonsense reasoning capabilities and can be applied to a wide range of knowledge domains.

While tech giants across the world work on materializing the idea of having a generative artificial intelligence (AI) to aid humans in their daily lives, the risk of the nascent technology going rogue remains imminent. Considering this possibility, Tesla and Twitter chief Elon Musk reminded the people of AI's potential to destroy civilization. On March 15, Musk's plan of creating a new AI startup surfaced after the entrepreneur was reportedly assembling a team of AI researchers and engineers. However, Musk continues to highlight the destructive potential of AI -- just like any other technology -- if it goes into the wrong hands or is being developed with ill intentions. According to Musk, AI can be dangerous. In a FOX interview, he said that AI can be more dangerous than mismanaged aircraft design or production maintenance, for example.

She's upset that he refused to watch Twilight with her on the weekend:

Add Jack in the Box to the list of fast food chains experimenting with robots. The company is launching a pilot program that will test Miso Robotics' Flippy 2 (frying) and Sippy (drink-prepping) robots in a San Diego restaurant. Jack in the Box wants to see how much help the automatons can offer to busy staff who may want to spend more time with customers and less time in the kitchen. The companies didn't say how long the pilot might last. Jack in the Box said it was open to "further integration" in coming months, however.

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A robot-building lab and contest was held at the Eleventh National Conference on Artificial Intelligence. Teams of three worked day and night for 72 hours to build tabletop autonomous robots of legos, a small microcontroller board, and sensors. The robots then competed head to head in two events. The contest was a chance to learn about building machines that operate in the real world. The lab was in a roped-off area of the main exhibition area.

To use language one must be able to make inferences about the information which language conveys. This is apparent in many ways. For one thing, many of the processes which we typically consider "linguistic" require inference making. For example, structural disambiguation: (1) Waiter, I would like spaghetti with meat sauce and wine. You would not expect to be served a bowl of spaghetti floating in meat sauce and wine. That is, you would expect the meal represented by structure (2) rather than that represented by (3).