ChatGPT-maker Open AI said Friday it has pushed out its co-founder and CEO Sam Altman after a review found he was “not consistently candid in his communications” with the board of directors.ChatGPT-maker Open AI said Friday it has pushed out its co-founder and CEO Sam Altman after a review found he was “not consistently candid in his communications” with the board of directors.Business[#item_full_content]

In August 2020, following a period of prolonged drought and intense rainfall, a dam situated near the Seomjin River in Korea experienced overflow during a water release, resulting in damages exceeding 100 billion won (USD 76 million). The flooding was attributed to maintaining the dam’s water level 6 meters higher than the norm. Could this incident have been averted through predictive dam management?In August 2020, following a period of prolonged drought and intense rainfall, a dam situated near the Seomjin River in Korea experienced overflow during a water release, resulting in damages exceeding 100 billion won (USD 76 million). The flooding was attributed to maintaining the dam’s water level 6 meters higher than the norm. Could this incident have been averted through predictive dam management?Engineering[#item_full_content]

In the last year, large language models (LLMs) have come into prominence for boasting a suite of ever-expanding capabilities including text generation, image production, and, more recently, highly descriptive image analysis. The integration of artificial intelligence (AI) into image analysis represents a significant shift in how people understand and interact with visual data, a task that historically has been reliant on vision to see and knowledge to contextualize.In the last year, large language models (LLMs) have come into prominence for boasting a suite of ever-expanding capabilities including text generation, image production, and, more recently, highly descriptive image analysis. The integration of artificial intelligence (AI) into image analysis represents a significant shift in how people understand and interact with visual data, a task that historically has been reliant on vision to see and knowledge to contextualize.[#item_full_content]

In the last year, large language models (LLMs) have come into prominence for boasting a suite of ever-expanding capabilities including text generation, image production, and, more recently, highly descriptive image analysis. The integration of artificial intelligence (AI) into image analysis represents a significant shift in how people understand and interact with visual data, a task that historically has been reliant on vision to see and knowledge to contextualize.In the last year, large language models (LLMs) have come into prominence for boasting a suite of ever-expanding capabilities including text generation, image production, and, more recently, highly descriptive image analysis. The integration of artificial intelligence (AI) into image analysis represents a significant shift in how people understand and interact with visual data, a task that historically has been reliant on vision to see and knowledge to contextualize.Computer Sciences[#item_full_content]

A new algorithm that can enhance covert communication without compromising data integrity is reported in the International Journal of Autonomous and Adaptive Communications Systems.A new algorithm that can enhance covert communication without compromising data integrity is reported in the International Journal of Autonomous and Adaptive Communications Systems.[#item_full_content]

Four years ago, UC Santa Cruz’s Jason Eshraghian developed a Python library that combines neuroscience with artificial intelligence to create spiking neural networks, a machine learning method that takes inspiration from the brain’s ability to efficiently process data. Now, his open source code library, called “snnTorch,” has surpassed 100,000 downloads and is used in a wide variety of projects, from NASA satellite tracking efforts to semiconductor companies optimizing chips for AI.Four years ago, UC Santa Cruz’s Jason Eshraghian developed a Python library that combines neuroscience with artificial intelligence to create spiking neural networks, a machine learning method that takes inspiration from the brain’s ability to efficiently process data. Now, his open source code library, called “snnTorch,” has surpassed 100,000 downloads and is used in a wide variety of projects, from NASA satellite tracking efforts to semiconductor companies optimizing chips for AI.[#item_full_content]

Four years ago, UC Santa Cruz’s Jason Eshraghian developed a Python library that combines neuroscience with artificial intelligence to create spiking neural networks, a machine learning method that takes inspiration from the brain’s ability to efficiently process data. Now, his open source code library, called “snnTorch,” has surpassed 100,000 downloads and is used in a wide variety of projects, from NASA satellite tracking efforts to semiconductor companies optimizing chips for AI.Four years ago, UC Santa Cruz’s Jason Eshraghian developed a Python library that combines neuroscience with artificial intelligence to create spiking neural networks, a machine learning method that takes inspiration from the brain’s ability to efficiently process data. Now, his open source code library, called “snnTorch,” has surpassed 100,000 downloads and is used in a wide variety of projects, from NASA satellite tracking efforts to semiconductor companies optimizing chips for AI.Computer Sciences[#item_full_content]

President Joe Biden and other global leaders have spent the past few days melding minds with Silicon Valley titans in San Francisco, their discussions frequently focusing on artificial intelligence, a technology expected to reshape the world, for better or worse.President Joe Biden and other global leaders have spent the past few days melding minds with Silicon Valley titans in San Francisco, their discussions frequently focusing on artificial intelligence, a technology expected to reshape the world, for better or worse.Machine learning & AI[#item_full_content]

According to data from 2010, around 1.8 million people in the U.S. can’t eat on their own. Yet training a robot to feed people presents an array of challenges for researchers. Foods come in a nearly endless variety of shapes and states (liquid, solid, gelatinous), and each person has a unique set of needs and preferences.According to data from 2010, around 1.8 million people in the U.S. can’t eat on their own. Yet training a robot to feed people presents an array of challenges for researchers. Foods come in a nearly endless variety of shapes and states (liquid, solid, gelatinous), and each person has a unique set of needs and preferences.Robotics[#item_full_content]

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