Scientists Press AI Researchers for Transparency #Sciencefather #professors #researchawards

An international group of scientists is demanding scientific journals demand more transparency from researchers in computer-related areas when accepting their reports for publication.

They also want computational researchers to include information about their code, models, and computational environments in published reports.

Their call, published in Nature Magazine in October, was in response to the results of research conducted by Google Health that was published in Nature last January.

The research claimed an artificial intelligence system was faster and more accurate at screening for breast cancer than human radiologists.

Google funded the study, which was led by Google Scholar Scott McKinney and other Google employees.

   

Criticisms of the Google Study

“In their study, McKinney et al. showed the high potential of artificial intelligence for breast cancer screening,” the international group of scientists, led by Benjamin Haibe-Kains, of the University of Toronto, stated.

“However, the lack of detailed methods and computer code undermines its scientific value. This shortcoming limits the evidence required for others to prospectively validate and clinically implement such technologies.”Scientific progress depends on the ability of independent researchers to scrutinize the results of a research study, reproduce its main results using its materials, and build upon them in future studies, the scientists said, citing Nature Magazine’s policies.

McKinney and his co-authors stated that it was not feasible to release the code used for training the models because it has a large number of dependencies on internal tooling, infrastructure, and hardware, Haibe-Kains’ group noted.

International Research Awards on New Science Inventions Join us for the International Research Awards on New Science Inventions, a premier event in the realm of research. Whether you're joining virtually from anywhere in the world, this is your invitation to explore and innovate in the field of research. Become part of a global community of researchers, scientists, and professionals passionate about advancing research. Visit Our Website 🌐: nesin.sciencefather.com Nomination👍: https://new-science-inventions.sciencefather.com/young-scientist-research-awards/ Contact us ✉️: nesinsupport@sciencefather.com #ScienceFather #researchawards #shorts #technology #researchers #labtechnicians #conference #awards #professors #teachers #lecturers #biologybiologiest #physicist #coordinator #business #genetics #medicine #labtechnicians #agriculture #bestreseracher #bestpaper Get Connected Here: ================== Twitter : twitter.com/ScienceInventi1 Pinterest : in.pinterest.com/scienceinventions/..... Tumblr : kayleerowan.tumblr.com..... Instagram : www.instagram.com/kaylee_rowan_ Linkedin : www.linkedin.com/feed/ Facebook : facebook.com/kaylee.rowan.92

The Role of Machine Learning and Artificial Intelligence in Robotics #Sciencefather #researchers #robotics

 

“Robotics are beginning to cross that line from absolutely primitive motion to motion that resembles animal or human behavior,” said J. J. Abrams. Fundamentally created in the early 1950s, robotics, today, is well-known as a self-operating machine with precisely trained and learned inputs, and its prevalence is omnipresent. The evolution of robotic intelligence shows a wide range of hierarchies since the time it was first created. Introduced to be deployed in factories for industrial use, it isn’t easy to find a sector where robotics is not used today. In the initial days of its advent, robots were merely designed to perform a trained set of repetitive tasks. However, with the role of artificial intelligence in robots, the scope of robotics has expanded. 

Now, robotics operates exclusively on artificial intelligence and machine learning. The 2000s trace the utilization of artificial intelligence in digitally programmed industrial robots. The global scenario has widely changed since then. Skillful integration of machine learning and robotics has been developed to advance the alleged ambit of robotic intelligence, enabling it to attain a sound human vision to detect potent stimuli. Huge algorithms and datasets go into this process of evolving the robotics potential into a human-like vision.

The current generation of blending machine learning and robotics allegedly seems to be the most powerful combination in the history of technological innovations. A completely new era of automation is set to disrupt every possible institution of human civilization. AI-driven robots are considered more efficient than the ones without this technology. For instance, the industrial sector stands as the biggest consumer of functions like robotics and further automation, saving time and human effort and ensuring validity, accuracy, and minor errors. In such an occupied workspace, one cannot risk the security of the place with basic traditional robots.

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Information Technology for Open Science: Innovation for Research | #Sciencefather #researcher #professors

What does innovation mean for higher education? I've asked many college/university and association presidents this question. The typical response points to successful startups, economic development programs, and entrepreneurship training. Yes, these are important ways that we serve society through innovation. But how do higher education institutions themselves innovate?

Colleges and universities are much more facile at outside innovation than inside innovation. By that, I mean that they have created cultures and rewards for moving ideas and inventions outside of the institution through technology transfer or student education but are not as adept at achieving change within.

For fifteen years, while serving as vice president of research at the University of Southern California (USC), I witnessed—and encouraged—a transformation in research practices. Under the umbrella of the "Creativity and Collaboration in the Academy" initiative, USC explored and experimented with how higher education institutions might evolve to a research culture that, aligned with information technology, could achieve innovation inside the institution so as to be more impactful on the outside.

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Artificial Intelligence in Science | #Sciencefather #reserachawards #AI

The rapid advances of artificial intelligence (AI) in recent years have led to numerous creative applications in science. Accelerating the productivity of science could be the most economically and socially valuable of all the uses of AI. Utilising AI to accelerate scientific productivity will support the ability of OECD countries to grow, innovate and meet global challenges, from climate change to new contagions.

                                         


Accelerating the productivity of research could be the most economically and socially valuable of all the uses of artificial intelligence (AI). While AI is penetrating all domains and stages of science, its full potential is far from realised. Policy makers and actors across research systems can do much to accelerate and deepen the uptake of AI in science, magnifying its positive contributions to research. This will support the ability of OECD countries to grow, innovate and address global challenges, from climate change to new contagions.


A distinctive contribution is the book’s examination of policies for AI in science. Policy makers and actors across research systems can do much to deepen AI’s use in science, magnifying its positive effects, while adapting to the fast-changing implications of AI for research governance.


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Research Scientist

Research scientists delve deep into the study of machine learning and computational intelligence systems. Candidates typically hold a PhD or master’s degree in mathematics or computer science. Companies seek individuals with a solid background in AI for these positions, which offer high salaries. Demand for research scientists is expected to remain strong over the next decade.

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