Discrete integration is a fundamental problem in computer science that concerns the computation of discrete sums over exponentially large sets. Despite intense interest from researchers for over three decades, the design of scalable techniques for computing estimates with rigorous guarantees for discrete integration remains the holy grail. The key contribution of this work addresses this scalability challenge via an efficient reduction of discrete integration to model counting. The proposed reduction is achieved via a significant increase in the dimensionality that, contrary to conventional wisdom, leads to solving an instance of the relatively simpler problem of model counting. Building on the promising approach proposed by Chakraborty et al, our work overcomes the key weakness of their approach: a restriction to dyadic weights. We augment our proposed reduction, called DeWeight, with a state of the art efficient approximate model counter and perform detailed empirical analysis over benchmarks arising from neural network verification domains, an emerging application area of critical importance. DeWeight, to the best of our knowledge, is the first technique to compute estimates with provable guarantees for this class of benchmarks.

Automakers and tech developers testing and deploying self-driving and advanced driver assistance features will no longer have to report as much detailed, public crash information to the federal government, according to a new framework released today by the US Department of Transportation. The moves are a boon for makers of self-driving cars and the wider vehicle technology industry, which has complained that federal crash reporting requirements are overly burdensome and redundant. But the new rules will limit the information available to those who watchdog and study autonomous vehicles and driver assistance features--tech developments that are deeply entwined with public safety but which companies often shield from public view because they involve proprietary systems that companies spend billions to develop. The government's new orders limit "one of the only sources of publicly available data that we have on incidents involving Level 2 systems," says Sam Abuelsamid, who writes about the self-driving vehicle industry and is the vice president of marketing at Telemetry, a Michigan research firm, referring to driver assistance features such as Tesla's Full Self-Driving (Supervised), General Motors' Super Cruise, and Ford's Blue Cruise. These incidents, he notes, are only becoming "more common."

After more than a year of hearing people talk about artificial intelligence (AI) and co-pilots, I finally tried one on a small project. I even paid for the privilege of doing so, figuring that the paid version would be superior to the free one. But what I have found confuses me, and I am wondering if you too have tried any of these tools. From your previous columns, it seems you might not be focused on the latest tools in our industry. So, maybe you have just continued to use vim and Makefiles.

Not only has China's largest EV maker BYD unveiled good, better, and best tiers for its advanced driver-assistance system (ADAS), it announced last week that the tech--marketed somewhat immodestly as "God's Eye"--will now be fitted as standard to 21 of BYD's 30 cars split across four brands. Even the 9,500 Seagull hatchback, the cheapest of BYD's EVs, will ship with the base level of God's Eye at no extra cost, while the 233,500 Yangwang U9 electric supercar will get the top-tier iteration. However, BYD's ADAS system could be as misleadingly named as Tesla's Full Self-Driving (FSD). Including ADAS for free will no doubt rile BYD's smaller rivals in China's innovative but cutthroat auto market. Comparatively low-tech Toyota, VW, and Nissan may weaken further, and Tesla--which has yet to gain permission for FSD in China--could also struggle.

In 2022, ChatGPT was released to the general public by OpenAI, a company that does artificial intelligence (AI) research and development. Anybody with a device and internet connectivity may use ChatGPT for free, making it broadly accessible, especially for students who are currently all digital natives. OpenAI ChatGPT, also known as GPT (Generative Pre-trained Transformer) is a large-scale language generation model developed by OpenAI. It uses machine learning algorithms to understand and respond to natural language input from users in a conversational way. GPT is based on a transformer architecture that was first introduced by researchers…...

Boundary conditions (BCs) are important groups of physics-enforced constraints that are necessary for solutions of Partial Differential Equations (PDEs) to satisfy at specific spatial locations. These constraints carry important physical meaning, and guarantee the existence and the uniqueness of the PDE solution. Current neural-network based approaches that aim to solve PDEs rely only on training data to help the model learn BCs implicitly. There is no guarantee of BC satisfaction by these models during evaluation. In this work, we propose Boundary enforcing Operator Network (BOON) that enables the BC satisfaction of neural operators by making structural changes to the operator kernel. We provide our refinement procedure, and demonstrate the satisfaction of physics-based BCs, e.g. Dirichlet, Neumann, and periodic by the solutions obtained by BOON. Numerical experiments based on multiple PDEs with a wide variety of applications indicate that the proposed approach ensures satisfaction of BCs, and leads to more accurate solutions over the entire domain. The proposed correction method exhibits a (2X-20X) improvement over a given operator model in relative $L^2$ error (0.000084 relative $L^2$ error for Burgers' equation).

There are more than 30 species of dolphins in the world, the Māui dolphin, which lives off the west coast of the North Island, New Zealand, faces a threat of extinction. To save this rarest of the world's dolphins, a nonprofit organization has been formed called MAUI63 (Marine Animal Unmanned Identification, with 63 representing the estimated number of Māui dolphins when this initiative began in 2018). The team's scientists and conservationists use an AI-powered drone to locate, track, identify, and ultimately protect these and Hector's dolphins. The Māui dolphin population has declined further since the project began, as a 2021 survey counted only 54. Hector's and Māui dolphins are small coastal dolphins found only in New Zealand.

The retail business is getting back on track and has been witnessing steady growth after the dismal impact of the third wave. There has been buoyancy in the market with the removal of lockdown restrictions. After a long time of distress and uncertainty, things are getting back to normalcy as businesses have started taking pertinent steps to resume operations and focus on sales, marketing, and inventory management. The realization of digital transformation coupled with the indispensable role of artificial intelligence (AI) has been one of the major outcomes of Covid-19 implications on the retail sector and the vast possibilities and opportunities it can create with such transformations. With the emergence of e-commerce, buyers experienced the first crucial shift that successfully made it possible for them to buy things from anywhere at any time.

Machine Learning has wholly integrated into our everyday life. Naturally, many aspiring would-be analysts want to learn the magic behind ML. However, the application of the machine learning process in analyzing data involves a framework of collecting data, creating/choosing a model, preparing, and training the data until predicting the outcome. All of which makes the entire process appear too technical, challenging, and laborious, leaving those who aren't fluent in software development feeling overwhelmed. However, No-code Machine Learning is changing this status quo.

AI platforms are a boon for businesses who are constantly looking to improve their output. Artificial intelligence platforms allow businesses to maximize their efficiency and provide many benefits such as taking over redundant tasks, providing deeper insight into data for better decision making, providing data management capabilities and more. AI-powered platforms are a boon for businesses that are constantly looking for ways to reduce their output. This article lists the 10 most popular AI platforms in 2022. C3 AI is one of the most popular AI platforms.