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What would it take to make AI 'greener'?

#artificialintelligence

The carbon footprint of a model can be complicated to determine and compare across modelling approaches and data centre infrastructures. A reasonable place to start may be by assessing the number of floating-point operations – that is, a discrete count of how many simple mathematical operations (for example, multiplication, division, addition, subtraction, and variable assignment) – that need to be performed to train a model. This factor and others can impact energy consumption along with the architecture of the model and the training resources, such as hardware like GPU or CPUs. Additionally, the physical considerations of the storage and cooling of the servers comes into play. As a final complication, it also matters where the energy is sourced from.


Nanox to Host Live Streaming AI Vision Event

#artificialintelligence

Ran Poliakine, Chairman and CEO and Erez Meltzer, Director, will host industry experts and Nanox team members to share the Company's AI vision of the integration of the AI technologies with the Nanox.ARC and Nanox.SOURCE NEVE ILAN, Israel, Sept. 24, 2021 (GLOBE NEWSWIRE) -- NANO-X IMAGING LTD ("Nanox" or the "Company," Nasdaq: NNOX), an innovative medical imaging technology company, today announced that Ran Poliakine, Chairman and Chief Executive Officer, and Erez Meltzer, Director (appointed CEO effective January 1, 2022), will host a Nanox AI Vision event. About Nanox: Nanox, founded by the serial entrepreneur Ran Poliakine, is an Israeli corporation developing a commercial-grade digital X-ray source designed to be used in real-world medical imaging applications. Nanox believes that its novel technology could significantly reduce the costs of medical imaging systems and plans to seek collaborations with world-leading healthcare organizations and companies to provide affordable, early detection imaging services for all. For more information, please visit www.nanox.vision. Forward-Looking Statements This press release may contain forward-looking statements that are subject to risks and uncertainties.


The Top Ten Mistakes That Traders Make.

#artificialintelligence

we have dealt with thousands and thousands of traders every year. We have come to understand exceptionally well the pitfalls and stumbling blocks that traders face every day in the financial markets. Here is a short list of the most frequent and damaging errors that most traders and investors make.


What Green AI Needs

#artificialintelligence

LONDON – Long before the real-world effects of climate change became so abundantly obvious, the data painted a bleak picture – in painful detail – of the scale of the problem. For decades, carefully collected data on weather patterns and sea temperatures were fed into models that analyzed, predicted, and explained the effects of human activities on our climate. And now that we know the alarming answer, one of the biggest questions we face in the next few decades is how data-driven approaches can be used to overcome the climate crisis. Data and technologies like artificial intelligence (AI) are expected to play a very large role. But that will happen only if we make major changes in data management.


How Apple TV's 'Foundation' is different from the books

Mashable

To say Apple TV's Foundation diverges from its source material would be a bit of an understatement. An adaptation of Isaac Asimov's classic science fiction novels, Foundation is less interested in following its source material to the letter than it is in creating a story within Asimov's universe that would make good TV. The basic plot remains the same: mathematician Hari Seldon (Jared Harris) foretells the fall of the Galactic Empire thanks to his theory of psychohistory. Knowing the fall is inevitable, he establishes the Foundation in order to preserve knowledge and, hopefully, civilization in the years to come. Foundation takes this story and tweaks it in some pretty big ways, which makes sense when considering the scale of Asimov's work.


GPT-3 Finally Correctly Nailed

#artificialintelligence

GPT-2 was a great success. OpenAI didn't want to publish the most enormous and mightiest version, with 1.5B parameters. At least, claiming that they were afraid of misusing it for less ethical purposes. Lately, they claimed that they didn't found shreds of evidence of such. All of this is legit, considering the volume of the false "news" generated using it. And the truth is that it can be very successful in developing false news/stories.


Rank and File

#artificialintelligence

Try the Evanston RoundTable's free daily and weekend email newsletters – sign up now! By subscribing, you agree to share your email address with us and Mailchimp to receive marketing, updates, and other emails from us. Use the unsubscribe link in those emails to opt out at any time. Championship tournaments for computer chess engines moved from onsite competition to online well before many human tournaments made the move last year in response to the COVID-19 pandemic. In recent years the Top Engine Chess Competition, which has been played virtually since 2010, has become the unofficial world computer chess championship.


NLP Natural Language Processing Fundamentals in Python

#artificialintelligence

Welcome to your first step into the Natural Language Processing and Text Mining world! This is your risk-free approach (30-day refund policy) to delve deep into the fundamentals which Google, Amazon and Microsoft base themselves on when working with text data. Natural Language Processing is one of the most exciting fields in Data Science and Analytics nowadays. The ability to make a computer understand words and phrases is a technological innovation that brought a huge transformation to tasks such as Information Retrieval, Translation or Text Classification. In this course we are going to learn the fundamentals of working with Text data in Python and discuss the most important techniques that you should know to start your journey in Natural Language Processing.


Sinergies between automation and robotics

Robohub

In this IEEE ICRA 2021 Plenary Panel aimed at the younger generation of roboticists and automation experts, panelists Seth Hutchinson, Maria Pia Fanti, Peter B. Luh, Pieter Abbeel, Kaneko Harada, Michael Y. Wang, Kevin Lynch, Chinwe Ekenna, Animesh Garg and Frank Park, under the moderation of Ken Goldberg, discussed about how to close the gap between both disciplines, which have many topics in common. The panel was organised by the Ad Hoc Committee to Explore Synergies in Automation and Robotics (CESAR). As the IEEE Robotics and Automation Society (IEEE RAS) explain, "robotics and automation have always been siblings. They are similar in many ways and have substantial overlap in topics and research communities, but there are also differences–many RAS members view them as disjoint and consider themselves purely in robotics or purely in automation. This committee's goal is to reconsider these perceptions and think about ways we can bring these communities closer."


Gradient Descent: Taking a Different View

#artificialintelligence

I had my first encounter with the Gradient Descent algorithm when I was learning about Linear Regression for the very first time. I devoured information about Gradient Descent as much as I could. Scouring through the internet looking for an explanation that would satisfy me. The most common explanation I found was analogous to the "going downhill on a cliff" experience. While this was really intuitive and easily comprehensible.