Amid the wave of artificial intelligence, many young people are achieving financial freedom through innovative means. 18-year-old Zach Yadegari and 23-year-old Blake Anderson are among the standout examples, having successfully launched a calorie tracking app called Cal AI, utilizing ChatGPT's no-code development capabilities, and generating an astonishing $56 million in revenue in just one year. The core feature of Cal AI is its ability to identify food calories through photo recognition, making it easy to use.
Recently, Chengdu Huayi revealed on its interactive platform that it has successfully developed a specialized AI chip for the edge computing field. This chip boasts an AI computing power of up to 16 Tops and is currently undergoing limited trial use among several clients in specific industries. The new chip not only offers robust computing power but also demonstrates excellent performance in video encoding and decoding, supporting video processing capabilities of up to 8K resolution. This represents a significant technological advancement for applications such as video surveillance and smart homes.
In today's digital world, the use of short text has become central to online communication. However, these texts often lack common vocabulary or context, posing numerous challenges for Artificial Intelligence (AI) during analysis. In response, Justin Miller, an English Literature graduate student and data scientist from the University of Sydney, proposed a novel approach that utilizes Large Language Models (LLMs) to gain deeper understanding and analysis of short texts. Miller's research focuses on how to analyze a vast array of short texts, such as social media profiles,