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Category: robotics/AI – Page 910

Given the rise of chat gpt and its volumes of knowledge bases there is a new chat bot that is aiding mental health care and therapy 😀

When it comes to mental health, the main focus is on the patient and how to provide the best care possible. But with the rising demand for mental health services, it’s increasingly difficult for clinicians to address the individual needs of their patients and meet the growing demand for mental health services. This is where ChAT-GPT, or Conversational Artificial intelligence-based Therapy for Generalized Psychological Treatment, comes in.

Chat-GPT is an AI-based therapy that uses natural language processing (NLP) and conversational AI to help therapists provide more personalized and effective mental health care and therapy. This new technology allows mental health professionals to provide real-time and personalized care to their patients in a way that is tailored to their needs and preferences. In this article, we will discuss the key features of Chat-GPT and how it is helping improve mental health care and therapy.

Chat-GPT is a type of AI-based therapy developed by researchers at Albert Einstein College of Medicine. It is a conversational AI-based therapy designed to help clinicians diagnose mental health issues. Chat-GPT uses natural language processing (NLP) to understand the patient’s conversations and provide personalized care and therapy.

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Researchers from the University of Aberdeen develop an AI algorithm to detect planetary craters with high accuracy, efficiency, and flexibility.

A team of scientists from the University of Aberdeen has developed a new algorithm that could revolutionize planetary studies. The new technology enables scientists to detect planetary craters and accurately map their surfaces using different data types, according to a release.

The team used a new universal crater detection algorithm (CDA) developed using the Segment Anything Model (SAM), an artificial intelligence (AI) model that can automatically identify and cut out any object in any image.

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For the first time in human history, doctors will transplant a human bladder from a deceased person to an alive patient using surgery robots.

A team of urologists at Keck Medicine of the University of South California (USC) is conducting a clinical trial that will soon lead to the first-ever bladder transplant operation in humans. The doctors are currently in the process of selecting participants for their trials.

If successful, such operations would provide relief to millions of people around the globe who live with bladder-related disorders.

Georgiy Datsenko/iStock.

Continue reading “World’s first bladder transplant will be performed by both human and robot surgeons” | >

The Colombian protests began on April 28, 2021, sparked by a tax reform opposed by the working class and middle-class Colombians.

Amnesty International’s use of AI generated images to commemorate the second anniversary of Colombian protests has sparked a debate over the credibility of advocacy groups and media organizations in their coverage of war-inflicted zones.

Amnesty’s Norway regional account posted three images in a series of tweets. The first depicted a crowd of armor-clad police officers; the second featured a police officer with a red splotch on his face, and the third of a protester being dragged away by police officials.

Amnesty International/Twitter.

Continue reading “Amnesty uses AI-generated images to portray Colombian protests, draws criticism” | >

Neural networks are distributed computing structures inspired by the structure of a biological brain and aim to achieve cognitive performance comparable to that of humans but in a much shorter time.

These technologies now form the basis of machine learning and that can perceive the environment and adapt their own behavior by analyzing the effects of previous actions and working autonomously. They are used in many areas of application, such as speech and image recognition and synthesis, autonomous driving and augmented reality systems, bioinformatics, genetic and molecular sequencing, and high-performance computing technologies.

Compared to conventional computing approaches, in order to perform complex functions, neural networks need to be initially “trained” with a large amount of known information that the network then uses to adapt by learning from experience. Training is an extremely energy-intensive process and as computing power increases, the neural networks’ consumption grows very rapidly, doubling every six months or so.

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In light of these changes, there is growing concern about the future of employment worldwide. Surveys suggest that one-fourth of all jobs are at risk of being automated, which understandably makes people worry about job security. However, there is evidence to suggest that the impact of automation may not be as dire as some may fear.

Contrary to popular belief, the automation of jobs is not necessarily synonymous with the elimination of jobs. Instead, it is likely to change the nature of occupations by taking over easy and repetitive tasks, which will free up employees to focus on work that requires higher-level interpersonal skills. This shift is expected to create a demand for workers who are skilled in areas such as communication, problem-solving, and critical thinking.

In conclusion, the nature of labor is evolving at an unprecedented pace due to the rise of technology. Automation and AI are transforming the types of jobs available in many industries, creating new opportunities for workers with higher-level skills. Although there may be concerns about job security, the impact of automation is expected to change rather than eliminate occupations, providing a chance for workers to develop new skills and remain relevant in an ever-changing job market.

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Using a strategy that mimics the encoding of information in our brains, a trio of researchers in China has proposed a new platform for artificial intelligence (AI) that could be far more robust than existing architectures. The approach, which has yet to be implemented in the lab, exploits the inevitable non-uniformity of artificial neurons that are a result of defects in real magnetic materials.

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The research was done by Zhe Yuan, Ya Qiao and Yajun Zhang at the Center for Advanced Quantum Studies and Department of Physics at Beijing Normal University.

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