Comprehending the enormity of climate change is about as mind-bending as understanding the ultimate effect novel coronavirus SARS-CoV-2 (the virus that causes Covid-19) will have on America and the world. But a free, interactive tool made by artificial intelligence start-up HyperGiant helps put both global crises and their relationship to each other in perspective. The "ACES: A post Covid Emissions Simulator" allows you to adjust pandemic-induced behaviors like the percentage of Americans who are working from home and the reduced amount of air travel to calculate how much carbon dioxide would be eliminated from the atmosphere if those changes were to be made permanent. For instance, if 30% of the workforce is working from home, air traffic is reduced by 50% and people eat 15% less meat, according to the tool that eliminates 18 billion tons of carbon dioxide, which is 38% of the way towards the changes dictated by the Paris climate accord. In 2019, the U.S. officially withdrew from the commission.)

In this module, we introduce the core idea of teaching a computer to learn concepts using data--without being explicitly programmed. The Course Wiki is under construction. Please visit the resources tab for the most complete and up-to-date information.

Whether employers are currently operating as normal, teleworking, or planning for the future, the Covid-19 experience may lead them to turn to the proliferation of workplace artificial intelligence (AI) tools to help streamline recruiting and hiring so they can continue maintaining social distancing best practices. Employers should be aware, however, that using such AI tools brings with it various regulatory challenges regardless of its utility in these trying times. AI has been exerting an ever-growing influence on companies' employment decisionmaking for some time. AI tools that have long been used to market services and products to customers (e.g., algorithms for personalized pop-up ads) are making increasing inroads into the employment arena, including those that mine data from an applicant's social media and internet presence to determine personal attributes and those that evaluate an applicant's responses during a video interview in making employment decisions. Employers considering using AI recruitment and selection tools during the Covid-19 crisis, which some experts expect to last for months after the curve has "flattened," should be mindful of the potential for misuse and of discriminatory impact raised by these technologies.

This event is hosted by Bahcesehir University, Istanbul Bar Association and deeplearning.ai's We continue to work as we targeted by trying to minimize the impact of the challenging process since the beginning of 2020 on our motivation. In this regard, we will realize the activity we planned on May 8, 2020, in a virtual environment. The program, which is planned to be broadcast on the YouTube Channel in one panel, is organized in cooperation with the Istanbul Bar Association, Bahçeşehir University, and the deeplearning.ai About the event: Participants will be discussed on AI and Social Effects, Risks, and Advantages, A Roadmap for Developing Countries.

Artificial intelligence (AI) has evolved into a new era, and its rapid development will profoundly affect the everyday life of citizens worldwide. Countries around the world are establishing governmental strategies and initiatives to guide the development of AI. The Chinese government is using the development of AI as a major strategy to enhance national competitiveness and protect national security. In January 2016, the Chinese State Council released the 13th Five-year Plan on National Science and Technology Innovation, explicitly putting forward the guidance, general requirements, strategic mission and reform measures for Chinese science and technology innovation. Over the next five years, smart manufacturing will be one of the major missions of the "Science and Technology Innovation 2030 Project" and there will be a focus on the development of AI technology.

Laila is currently an A-Level student studying Maths, Further Maths, Chemistry, and Latin and she has also written an EPQ dissertation on the ethics of AI. Laila has always had an interest in Computer Science and is enthusiastic to see more girls in the field in the future. Laila took part in her first Acorn Accelerator in August 2018, where she worked on a collaborative project, developing an application which helps teens get the most productive experience while online. She enjoyed the Accelerator so much that she returned to take part in the Gen Z Hackathon in January 2019, where her team won with "UVO", an app which enables teenagers to become more involved in politics. Laila has become involved in the Acorn Aspirations family and has had the opportunity to attend lectures at Cambridge University and take part in workshops at Imperial College.

Laila is currently an A-Level student studying Maths, Further Maths, Chemistry, and Latin and she has also written an EPQ dissertation on the ethics of AI. Laila has always had an interest in Computer Science and is enthusiastic to see more girls in the field in the future. Laila took part in her first Acorn Accelerator in August 2018, where she worked on a collaborative project, developing an application which helps teens get the most productive experience while online. She enjoyed the Accelerator so much that she returned to take part in the Gen Z Hackathon in January 2019, where her team won with "UVO", an app which enables teenagers to become more involved in politics. Laila has become involved in the Acorn Aspirations family and has had the opportunity to attend lectures at Cambridge University and take part in workshops at Imperial College.

Artificial Intelligence may seem transient, yet it always managed to have a controversial presence. Recently it raised concerns about its sustainability. In June 2019, the University of Massachusetts at Amherst study discovered that a single large (213 million parameters) Transformer-based neural network built using NAS (commonly used in machine translation) has produced around 626,000 pounds of carbon dioxide. This amount is equivalent to five times more than an average car produces in its lifespan. These massive consumption numbers are because of the energy needed to run specialized hardware like GPUs and TPUs for AI training and development.

Plants are intelligent beings with profound wisdom to impart--if only we know how to listen. And Monica Gagliano knows how to listen. The evolutionary ecologist has done groundbreaking experiments suggesting plants have the capacity to learn, remember, and make choices. Gagliano, a senior research fellow at the University of Sydney in Australia, talks to plants. Plants summon her with instructions on how to live and work. Some of Gagliano's conversations happened in prophetic dreams, which led her to study with a shaman in Peru while tripping on psychoactive plants. Along with forest scientists like Suzanne Simard and Peter Wohlleben, Gagliano raises profound scientific and philosophical questions about the nature of intelligence and the possibility of "vegetal consciousness." But what's unusual about Gagliano is her willingness to talk about her experiences with shamans and traditional healers, along with her use of psychedelics. For someone who'd already received fierce pushback from other scientists, it was hardly a safe career move to reveal her personal experiences in otherworldly realms. Gagliano considers her explorations in non-Western ways of seeing the world to be part of her scientific work.

While social distancing has forced healthcare conferences to go virtual, it hasn't stopped startups from raising money to fund their early development efforts. Here is a list of companies that have raised money this week. A company developing machine learning algorithms in diagnostics, Dascena said Thursday that it raised $50 million in a Series B round led by Frazier Healthcare Partners, with participation from Longitude Capital, existing investor Euclidean Capital and an undisclosed investor. The company plans to use the money to advance its suite of algorithms to inform patient care strategies and improve outcomes. In addition, Dascena announced Thursday the publication of a prospective study to evaluate the effect of its machine learning algorithm in predicting severe sepsis, in the journal BMJ Health & Care Informatics.