Large Tabular Models Excel Where LLMs Fail
Researchers are developing specialized large tabular models to address the limitations of traditional large language models in analyzing structured data.
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Researchers are developing specialized large tabular models to address the limitations of traditional large language models in analyzing structured data.
Researchers have found that the step-by-step reasoning processes in advanced language models introduce vulnerabilities that attackers can exploit to slow down systems.
An experiment involving a real Claude Monet painting misidentified as AI-generated highlights the complex perceptions surrounding the value and authenticity of AI art.
Compact artificial intelligence models are increasingly being deployed in portable devices to solve localized challenges, such as detecting counterfeit pharmaceuticals in Africa.
The highly fluctuating power demands of modern AI data centers are presenting unique challenges to electrical grids beyond simple overall energy consumption.
The rising energy demands of artificial intelligence data centers are prompting collaborative engineering efforts in Melbourne to address system-level infrastructure challenges.
Industry experts are analyzing the feasibility and hype surrounding SpaceX's proposals to launch orbital data centers for space-based artificial intelligence processing.
Linguist Emily Bender reflects on the legacy and arguments of the influential 2021 paper regarding the limitations and risks of large language models.
A creative poetry piece published by IEEE Spectrum reflects on the life and legacy of inventor Nikola Tesla.
Researchers are exploring new hardware materials and computing methods to reduce the high energy consumption of artificial intelligence models.
Researchers have analyzed ConlangCrafter, an AI model designed to generate constructed languages.
This profile examines why financial institutions like Capital One are hiring top AI scientists to lead their technology initiatives.
An applied mathematician reflects on how the rise of automated AI tools is changing the nature of mathematical research.
Princeton researchers are using reinforcement learning and diffusion models to automate and accelerate the design of radio frequency integrated circuits.
Researchers are developing AI models capable of analyzing subtle physical and vocal cues to better understand human emotional states and context.
This article reflects on the seventy-year history of artificial intelligence since its formal establishment at the Dartmouth workshop in 1956.
IEEE has launched a virtual training course designed to teach engineers how to integrate large language models into their technical workflows.
A new study demonstrates that utilizing sound waves in neuromorphic devices can improve their energy efficiency and processing speed compared to electronic alternatives.
The article explores potential economic models and agreements that could allow musicians to receive compensation when their creative works are used to train generative AI models.
General Motors is shortening its vehicle development timelines to compete with rapid production cycles from Chinese electric vehicle manufacturers.
Researchers have utilized visual language models to train collaborative robots to interpret human emotions by analyzing facial expressions and contextual cues.