US Customs and Border Protection (CBP) recently awarded Pangiam, a leading trade and travel technology company, a prime contract for developing and implementing Anomaly Detection Algorithms (ADA).
Pangiam, in collaboration with West Virginia University, aims to bring cutting-edge artificial intelligence (AI), computer vision, and machine learning expertise to enhance CBP’s border and national security missions, the company announced in a press release.
“In the study, we demonstrate how artificial intelligence can be used to carry out fundamental theoretical physics that addresses the behavior of fluids and other complex soft matter systems,” says Prof. Dr. Matthias Schmidt, chair of Theoretical Physics II at the University of Bayreuth.
Scientists from Bayreuth have developed a new method for studying liquid and soft matter using artificial intelligence. In a study now published in the Proceedings of the National Academy of Sciences, they open up a new chapter in density functional theory.
We live in a highly technologized world where basic research is the engine of innovation, in a dense and complex web of interrelationships and interdependencies. The published research provides new methods that can have a great influence on widespread simulation techniques, so that complex substances can be investigated on computers more quickly, more precisely and more deeply.
In the future, this could have an influence on product and process design. The fact that the structure of liquids can be excellently represented by the newly formulated neural mathematical relationships is a major breakthrough that opens up a range of possibilities for gaining deep physical insights.
Google thinks that there’s an opportunity to offload more healthcare tasks to generative AI models — or at least, an opportunity to recruit those models to aid healthcare workers in completing their tasks.
Google has unveiled MedLM, a new family of generative AI models designed to tackle healthcare-related tasks.
When it comes to spurring the development of cutting-edge technologies, the Chinese government is rather pragmatic in its policymaking process. In the field of autonomous driving, the country has made some big strides in defining the parameters and limitations for service providers, removing regulatory ambiguity and granting industry players the freedom to test the nascent technology.
The trial guidelines, unveiled by the Ministry of Transport recently, target AV services like robotaxis, self-driving trucks and robobuses. The release arrived about 16 months after the department began seeking public opinions on the regulatory framework, and policymakers have reached a consensus that self-driving vehicles are subject to rigorous surveillance measures to ensure utmost safety.
Prior to the introduction of the nationwide guidelines, policymaking for AVs in China had been playing out in a more decentralized fashion, with local governments formulating their own rules for service providers on their turf. Major tech clusters like Beijing, Shenzhen and Guangzhou, for example, have been frontrunners in allowing companies to test AVs with minimum human interference.
Perplexity.ai’s co-founder and CEO discusses the looming challenges in AI research and product development.
Google has released a new Pro model of its latest AI, Gemini, and company sources say it has outperformed GPT-3.5 (the free version of ChatGPT) in widespread testing. According to performance reports, Gemini Ultra exceeds current state-of-the-art results on 30 of the 32 widely-used academic benchmarks used in large language model (LLM) research and development. Google has been accused of lagging behind OpenAI’s ChatGPT, widely regarded as the most popular and powerful in the AI space. Google says Gemini was trained to be multimodal, meaning it can process different types of media such as text, pictures, video, and audio.
Insider also reports that, with a score of 90.0%, Gemini Ultra is the first model to outperform human experts on MMLU (massive multitask language understanding), which uses a combination of 57 subjects such as math, physics, history, law, medicine and ethics for testing both world knowledge and problem-solving abilities.
The Google-based AI comes in three sizes, or stages, for the Gemini platform: Ultra, which is the flagship model, Pro and Nano (designed for mobile devices). According to reports from TechCrunch, the company says it’s making Gemini Pro available to enterprise customers through its Vertex AI program, and for developers in AI Studio, on December 13. Reports indicate that the Pro version can also be accessed via Bard, the company’s chatbot interface.
