The large language models that have increasingly taken over the tech world are not “cheap” in many ways. The most prominent LLMs, such as GPT-4, took some $100 million to build in the form of legal costs of accessing training data, computational power costs for what could be billions or trillions of parameters, the energy and water needed to fuel computation, and the many coders developing the training algorithms that must run cycle after cycle so the machine will “learn.”The large language models that have increasingly taken over the tech world are not “cheap” in many ways. The most prominent LLMs, such as GPT-4, took some $100 million to build in the form of legal costs of accessing training data, computational power costs for what could be billions or trillions of parameters, the energy and water needed to fuel computation, and the many coders developing the training algorithms that must run cycle after cycle so the machine will “learn.”Machine learning & AI[#item_full_content]
Recently, the research team led by Prof. Wang Hongqiang from the Hefei Institutes of Physical Science of the Chinese Academy of Sciences proposed a wide-ranging cross-modality machine vision AI model.Recently, the research team led by Prof. Wang Hongqiang from the Hefei Institutes of Physical Science of the Chinese Academy of Sciences proposed a wide-ranging cross-modality machine vision AI model.Computer Sciences[#item_full_content]
Japanese scientists have used artificial intelligence to uncover 303 new etchings in Peru’s Nazca desert—doubling the amount of known geoglyphs made some 2,000 years ago by a pre-Inca civilization.Japanese scientists have used artificial intelligence to uncover 303 new etchings in Peru’s Nazca desert—doubling the amount of known geoglyphs made some 2,000 years ago by a pre-Inca civilization.Machine learning & AI[#item_full_content]
A novel technology for real-time monitoring of tool wear in precision machining has been developed, utilizing smartphone sensors. This advancement is expected to enhance the quality of production by enabling proactive maintenance and timely tool replacement.A novel technology for real-time monitoring of tool wear in precision machining has been developed, utilizing smartphone sensors. This advancement is expected to enhance the quality of production by enabling proactive maintenance and timely tool replacement.Engineering[#item_full_content]
As the use of artificial intelligence is expands, more small firms say they’re harnessing AI to help their businesses.As the use of artificial intelligence is expands, more small firms say they’re harnessing AI to help their businesses.Business[#item_full_content]
A trio of AI researchers at ETH Zurich, Switzerland, has modified an AI-based, picture-processing model to solve Google’s reCAPTCHAv2 human-testing system.A trio of AI researchers at ETH Zurich, Switzerland, has modified an AI-based, picture-processing model to solve Google’s reCAPTCHAv2 human-testing system.Security[#item_full_content]
Artificial intelligence (AI) may reshape many industries, but the impact of the nascent technology on various jobs remains unclear. Daniele Quercia and colleagues used machine learning to investigate itself, by identifying patents for AI technologies that may impact various occupational tasks. The work is published in PNAS Nexus.Artificial intelligence (AI) may reshape many industries, but the impact of the nascent technology on various jobs remains unclear. Daniele Quercia and colleagues used machine learning to investigate itself, by identifying patents for AI technologies that may impact various occupational tasks. The work is published in PNAS Nexus.Business[#item_full_content]
Neural network pruning is a key technique for deploying artificial intelligence (AI) models based on deep neural networks (DNNs) on resource-constrained platforms, such as mobile devices. However, hardware conditions and resource availability vary greatly across different platforms, making it essential to design pruned models optimally suited to specific hardware configurations.Neural network pruning is a key technique for deploying artificial intelligence (AI) models based on deep neural networks (DNNs) on resource-constrained platforms, such as mobile devices. However, hardware conditions and resource availability vary greatly across different platforms, making it essential to design pruned models optimally suited to specific hardware configurations.Hardware[#item_full_content]
About 2.2 billion people, more than a quarter of the world’s population, lack access to safe, managed drinking water, and about half of the world’s population experiences severe water scarcity at some point during the year. To overcome these shortages, huge socioeconomic costs are being spent on sewer irrigation and alternative water sources such as rainwater reuse and seawater desalination.About 2.2 billion people, more than a quarter of the world’s population, lack access to safe, managed drinking water, and about half of the world’s population experiences severe water scarcity at some point during the year. To overcome these shortages, huge socioeconomic costs are being spent on sewer irrigation and alternative water sources such as rainwater reuse and seawater desalination.Engineering[#item_full_content]
Engineers working on Google’s DeepMind project have announced the development of two new AI-based robot systems. One called ALOHA Unleashed was developed to advance the science of bi-arm manipulation. The other, called DemoStart, was developed to advance the capabilities of robot hands that have multiple fingers, joints, or sensors.Engineers working on Google’s DeepMind project have announced the development of two new AI-based robot systems. One called ALOHA Unleashed was developed to advance the science of bi-arm manipulation. The other, called DemoStart, was developed to advance the capabilities of robot hands that have multiple fingers, joints, or sensors.Robotics[#item_full_content]
