Things to Do in L.A. Tim Walz isn't the only governor plagued by fraud. Minnesota Gov. Tim Walz said he would not seek a third term amid attacks over a fraud scandal involving child care funding. This is read by an automated voice. Please report any issues or inconsistencies here . California has lost billions to cheats in the last few years, leaving Newsom vulnerable to the same sort of attack that took down Walz.

Recent advancements in robotics, including applications like self-driving cars, unmanned systems, and medical robots, have had a significant impact on the job market. On one hand, big robotics companies offer training programs based on the job requirements. However, these training programs may not be as beneficial as general robotics programs offered by universities or community colleges. On the other hand, community colleges and universities face challenges with required resources, especially qualified instructors, to offer students advanced robotics education. Furthermore, the diverse backgrounds of undergraduate students present additional challenges. Some students bring extensive industry experiences, while others are newcomers to the field. To address these challenges, we propose a student-centered personalized learning framework for robotics. This framework allows a general instructor to teach undergraduate-level robotics courses by breaking down course topics into smaller components with well-defined topic dependencies, structured as a graph. This modular approach enables students to choose their learning path, catering to their unique preferences and pace. Moreover, our framework's flexibility allows for easy customization of teaching materials to meet the specific needs of host institutions. In addition to teaching materials, a frequently-asked-questions document would be prepared for a general instructor. If students' robotics questions cannot be answered by the instructor, the answers to these questions may be included in this document. For questions not covered in this document, we can gather and address them through collaboration with the robotics community and course content creators. Our user study results demonstrate the promise of this method in delivering undergraduate-level robotics education tailored to individual learning outcomes and preferences.

LLMs are increasingly powerful and widely used to assist users in a variety of tasks. This use risks the introduction of LLM biases to consequential decisions such as job hiring, human performance evaluation, and criminal sentencing. Bias in NLP systems along the lines of gender and ethnicity has been widely studied, especially for specific stereotypes (e.g., Asians are good at math). In this paper, we investigate bias along less studied, but still consequential, dimensions, such as age and beauty, measuring subtler correlated decisions that LLMs (specially autoregressive language models) make between social groups and unrelated positive and negative attributes. We ask whether LLMs hold wide-reaching biases of positive or negative sentiment for specific social groups similar to the ``what is beautiful is good'' bias found in people in experimental psychology. We introduce a template-generated dataset of sentence completion tasks that asks the model to select the most appropriate attribute to complete an evaluative statement about a person described as a member of a specific social group. We also reverse the completion task to select the social group based on an attribute. Finally, we report the correlations that we find for multiple cutting-edge LLMs. This dataset can be used as a benchmark to evaluate progress in more generalized biases and the templating technique can be used to expand the benchmark with minimal additional human annotation.

This paper presents a work-in-progress on a learn-ing system that will provide robotics students with a personalized learning environment. This addresses both the scarcity of skilled robotics instructors, particularly in community colleges and the expensive demand for training equipment. The study of robotics at the college level represents a wide range of interests, experiences, and aims. This project works to provide students the flexibility to adapt their learning to their own goals and prior experience. We are developing a system to enable robotics instruction through a web-based interface that is compatible with less expensive hardware. Therefore, the free distribution of teaching materials will empower educators. This project has the potential to increase the number of robotics courses offered at both two- and four-year schools and universities. The course materials are being designed with small units and a hierarchical dependency tree in mind; students will be able to customize their course of study based on the robotics skills they have already mastered. We present an evaluation of a five module mini-course in robotics. Students indicated that they had a positive experience with the online content. They also scored the experience highly on relatedness, mastery, and autonomy perspectives, demonstrating strong motivation potential for this approach.

Smart Video surveillance systems have become important recently for ensuring public safety and security, especially in smart cities. However, applying real-time artificial intelligence technologies combined with low-latency notification and alarming has made deploying these systems quite challenging. This paper presents a case study for designing and deploying smart video surveillance systems based on a real-world testbed at a community college. We primarily focus on a smart camera-based system that can identify suspicious/abnormal activities and alert the stakeholders and residents immediately. The paper highlights and addresses different algorithmic and system design challenges to guarantee real-time high-accuracy video analytics processing in the testbed. It also presents an example of cloud system infrastructure and a mobile application for real-time notification to keep students, faculty/staff, and responsible security personnel in the loop. At the same time, it covers the design decision to maintain communities' privacy and ethical requirements as well as hardware configuration and setups. We evaluate the system's performance using throughput and end-to-end latency. The experiment results show that, on average, our system's end-to-end latency to notify the end users in case of detecting suspicious objects is 5.3, 5.78, and 11.11 seconds when running 1, 4, and 8 cameras, respectively. On the other hand, in case of detecting anomalous behaviors, the system could notify the end users with 7.3, 7.63, and 20.78 seconds average latency. These results demonstrate that the system effectively detects and notifies abnormal behaviors and suspicious objects to the end users within a reasonable period. The system can run eight cameras simultaneously at a 32.41 Frame Per Second (FPS) rate.

Millions of students attend community colleges every year, with almost 1,300 schools located in every corner of the United States. With their large student bodies, community colleges are a massive source of potential for expanding the artificial intelligence (AI) workforce, but employers and policymakers alike sorely underestimate their potential. If the United States aims to maintain its global lead and competitive advantage in AI, it must recognize that community colleges hold a special spot in our education system and are too important to be overlooked any longer. As detailed in a recent study I co-authored as part of Georgetown University's Center for Security and Emerging Technology (CSET), community colleges have the potential to support the country in its mission for superiority in AI. Community colleges could create pathways to good-paying jobs across the United States and become tools for training a new generation of AI-literate workers.

The partnership will create a consortium offering support and infrastructure so that community college students can receive artificial intelligence training affordably and with fewer barriers. Intel and Dell have partnered with the American Association of Community Colleges to launch artificial intelligence incubators throughout the country. The 18-month initiative will utilize the expertise of both companies along with the knowledge and industry connections of the nation's community colleges. Because the demand for training in AI far outstrips higher education supply, community colleges could provide a critical link in the talent pipeline. The partnership will create a consortium offering support and infrastructure so that students can receive instruction affordably and with fewer barriers.

Remember surround sound home theater & 3D TV? The promise was real but the technology was premature. Unlike my younger Millennial cohorts, I can remember a time before the Internet took off. Al Gore may have invented it (or not) before my lungs first cried "Hello, World!" but like all nascent technologies, the Internet took a while to develop & fan out. A few years before the awful sound of dial-up modems became commonplace, my first experience with this new thing called the Internet was at my mom's workplace - the local community college.

Over the years, this biweekly letter has provided me with the opportunity to fully and fairly document just how much free time college students can have if they try. My college roommates tried really hard. They found time to make prank calls to the campus literary magazine, create enough frost in our fridge to throw snowballs out the window on 90-degree days, leave old pizza in the entryway for the stated purpose of growing penicillin for a roommate who couldn't afford antibiotics, and organize campus recruiting events for fake investment banks. When these time-wasting activities required a fake identity, the persona of choice was John W. Moussach Jr., an alumnus turned successful Midwestern industrialist. Last week I looked online for remnants of John W. Moussach Jr. and came upon neither the Wikipedia page my roommates built after graduating nor the Moussach aphorism that somehow made it onto Wikiquote ("We have all heard the Will Rogers quote'I never met a man I did not like.' In my youth, I met a World War I veteran who had met Will Rogers. The veteran told me, 'I never met a man I did not like until I met Will Rogers'"), but rather an article on something called Study Sive which purports to feature higher education news.

TechRepublic's Karen Roby spoke with Carlos Contreras, AI and digital readiness director for Intel, about addressing the artificial intelligence skills gap with the AI for Workforce Program. The following is an edited transcript of their conversation. Karen Roby: We talk a lot about the tech skills gap. It seems like AI and cybersecurity are the two we tend to talk about a lot, that we need more people ready to fill those roles. But at Intel, you guys are building on a program to help change this and bridge the gap.