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Archive for the ‘information science’ category: Page 10

Jan 5, 2024

Paper page — Towards Truly Zero-shot Compositional Visual Reasoning with LLMs as Programmers

Posted by in category: information science

Join the discussion on this paper page.

Jan 5, 2024

Leveraging Artificial Intelligence to Improve Accuracy of Lung Cancer Screening

Posted by in categories: biotech/medical, health, information science, robotics/AI

How can artificial intelligence help to improve the accuracy of lung cancer screening among people at high risk of developing the disease? Read to find out.


Lung cancers, the vast majority of which are caused by cigarette smoking, are the leading cause of cancer-related deaths in the United States. Lung cancer kills more people than cancers of the breast, prostate, and colon combined. By the time lung cancer is diagnosed, the disease has often already spread outside the lung. Therefore, researchers have sought to develop methods to screen for lung cancer in high-risk populations before symptoms appear. They are evaluating whether the integration of artificial intelligence – the use of computer programs or algorithms that use data to make decisions or predictions – could improve the accuracy and speed of diagnosis, aid clinical decision-making, and lead to better health outcomes.

Jan 3, 2024

New insight into how brain adjusts synaptic connections during learning may inspire more robust AI

Posted by in categories: biological, information science, robotics/AI

How the brain adjusts connections between #neurons during learning: this new insight may guide further research on learning in brain networks and may inspire faster and more robust learning #algorithms in #artificialintelligence.


Researchers from the MRC Brain Network Dynamics Unit and Oxford University’s Department of Computer Science have set out a new principle to explain how the brain adjusts connections between neurons during learning. This new insight may guide further research on learning in brain networks and may inspire faster and more robust learning algorithms in artificial intelligence.

The essence of learning is to pinpoint which components in the information-processing pipeline are responsible for an error in output. In , this is achieved by backpropagation: adjusting a model’s parameters to reduce the error in the output. Many researchers believe that the brain employs a similar learning principle.

Continue reading “New insight into how brain adjusts synaptic connections during learning may inspire more robust AI” »

Dec 31, 2023

Anne M. Andrews and Paul S. Weiss Public Lecture: Nanotechnology Meets Neuroscience and Medicine

Posted by in categories: biotech/medical, information science, nanotechnology, neuroscience

In their public lecture at Perimeter on May 1, 2019, neuroscientist Anne M. Andrews and nanoscientist Paul S. Weiss outlined their scientific collaboration and explained the importance of communicating across disciplines to target significant problems. \
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Dec 30, 2023

NEW Alter 3 GPT4 AI Robot w/ 43 Axes (DEMOS SEVERAL NEXT GEN ABILITIES)

Posted by in categories: information science, robotics/AI, transportation

Alter 3 has just been unveiled by the University of Tokyo and its powered by GPT-4, capable of human-like activities and interpreting verbal instructions. Researchers at the Technical University of Munich developed a self-aware robot with proprioception, enhancing its movement and interaction capabilities. The University of Southern California introduced RoboCLIP, an algorithm that trains robots to perform tasks in new environments with minimal instruction. Intel Labs and partners created advanced motor control for robots using hierarchical generative models, significantly improving their ability to perform complex tasks.\
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Deep Learning AI Specialization: https://imp.i384100.net/GET-STARTED\
AI Marketplace: https://taimine.com/\
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AI news timestamps:\
0:00 Alter 3 GPT4 powered AI robot\
1:31 Robot self awareness\
3:30 RoboCLIP\
5:22 Motor control for autonomous robots\
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#ai #robot #technology

Dec 29, 2023

The Equation That Explains (Nearly) Everything!

Posted by in category: information science

Check Out Rogue History On PBS Origins: https://youtu.be/xuT35ud41QQPBS Member Stations rely on viewers like you. To support your local station, go to: http:/…

Dec 28, 2023

The secrets of Einstein’s unknown equation — with Sean Carroll

Posted by in categories: cosmology, information science, space travel

Did you know that Einstein’s most important equation isn’t E=mc^2? Find out all about his equation that expresses how spacetime curves, with Sean Carroll.

Buy Sean’s book here: https://geni.us/AIAOUHn.
YouTube channel members can watch the Q&A for this lecture here: • Q&A: The secrets of Einstein’s unknow…

Continue reading “The secrets of Einstein’s unknown equation — with Sean Carroll” »

Dec 28, 2023

Ep. 20: J. Storrs Hall — Bringing Back A Future Past With Flying Cars, Nano-Robots and Multi-Level Cities By Nurturing A Techno-Optimist Culture and a Unleashing Second Nuclear Age

Posted by in categories: bioengineering, economics, genetics, information science, nanotechnology, robotics/AI

An interview with J. Storrs Hall, author of the epic book “Where is My Flying Car — A Memoir of Future Past”: “The book starts as an examination of the technical limitations of building flying cars and evolves into an investigation of the scientific, technological, and social roots of the economic…


J. Storrs Hall or Josh is an independent researcher and author.

Continue reading “Ep. 20: J. Storrs Hall — Bringing Back A Future Past With Flying Cars, Nano-Robots and Multi-Level Cities By Nurturing A Techno-Optimist Culture and a Unleashing Second Nuclear Age” »

Dec 27, 2023

Physicists Designed an Experiment to Turn Light Into Matter

Posted by in categories: information science, physics

It would be a tangible demonstration of Einstein’s famous E = mc^2 equation.

Dec 26, 2023

Testing the biological reasoning capabilities of large language models

Posted by in categories: biotech/medical, information science, robotics/AI

Large language models (LLMs) are advanced deep learning algorithms that can process written or spoken prompts and generate texts in response to these prompts. These models have recently become increasingly popular and are now helping many users to create summaries of long documents, gain inspiration for brand names, find quick answers to simple queries, and generate various other types of texts.

Researchers at the University of Georgia and Mayo Clinic recently set out to assess the biological knowledge and reasoning skills of different LLMs. Their paper, pre-published on the arXiv server, suggests that OpenAI’s model GPT-4 performs better than the other predominant LLMs on the market on reasoning biology problems.

“Our recent publication is a testament to the significant impact of AI on biological research,” Zhengliang Liu, co-author of the recent paper, told Tech Xplore. “This study was born out of the rapid adoption and evolution of LLMs, especially following the notable introduction of ChatGPT in November 2022. These advancements, perceived as critical steps towards Artificial General Intelligence (AGI), marked a shift from traditional biotechnological approaches to an AI-focused methodology in the realm of biology.”

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