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Predicting Atlantic Hurricanes Using Machine Learning

#artificialintelligence

Every year, tropical hurricanes affect North and Central American wildlife and people. The ability to forecast hurricanes is essential in order to minimize the risks and vulnerabilities in North and Central America. Machine learning is a newly tool that has been applied to make predictions about different phenomena. We present an original framework utilizing Machine Learning with the purpose of developing models that give insights into the complex relationship between the land–atmosphere–ocean system and tropical hurricanes. We study the activity variations in each Atlantic hurricane category as tabulated and classified by NOAA from 1950 to 2021. By applying wavelet analysis, we find that category 2–4 hurricanes formed during the positive phase of the quasi-quinquennial oscillation. In addition, our wavelet analyses show that super Atlantic hurricanes of category 5 strength were formed only during the positive phase of the decadal oscillation. The patterns obtained for each Atlantic hurricane category, clustered historical hurricane records in high and null tropical hurricane activity seasons. Using the observational patterns obtained by wavelet analysis, we created a long-term probabilistic Bayesian Machine Learning forecast for each of the Atlantic hurricane categories. Our results imply that if all such natural activity patterns and the tendencies for Atlantic hurricanes continue and persist, the next groups of hurricanes over the Atlantic basin will begin between 2023 ± 1 and 2025 ± 1, 2023 ± 1 and 2025 ± 1, 2025 ± 1 and 2028 ± 1, 2026 ± 2 and 2031 ± 3, for hurricane strength categories 2 to 5, respectively. Our results further point out that in the case of the super hurricanes of the Atlantic of category 5, they develop in five geographic areas with hot deep waters that are rather very well defined: (I) the east coast of the United States, (II) the Northeast of Mexico, (III) the Caribbean Sea, (IV) the Central American coast, and (V) the north of the Greater Antilles.


AI/ML, Data Science Jobs #hiring

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Google sued for using the NHS data of 1.6 million Britons 'without their knowledge or consent'

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Google is being sued over its use of confidential medical records belonging to 1.6 million individuals in the UK. The company's artificial intelligence arm, DeepMind, received the data in 2015 from the Royal Free NHS Trust in London for the purpose of testing a smartphone app called Streams. The claim is being brought by Andrew Prismall in a representative action in the High Court. It alleges that Google and DeepMind "obtained and used a substantial number of confidential medical records without patients' knowledge or consent". Why did Google get access to patient records?


Need Help -- An AI / ML Enthusiast Professional with 18+ years of experience in SAP (ERP)…

#artificialintelligence

Reaching out to you with a request for Career related advice / input. I am a professional with about 18 years of experience in advisory services and implementation of SAP solutions across industries and geographies, presently working with a consulting firm in the U.S. I am a Chartered Accountant from India by education. From 2018, I started focusing on ML/AI as my parallel interest / career in addition to SAP. For the last four years, I started putting efforts to learn fundamentals of the ML/AI domain. I read multiple blogs, books, completed courses as well as completed PoC for a few Embedded Machine Learning solutions of SAP.


Artificial intelligence predicts patients' race from their medical images

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The miseducation of algorithms is a critical problem; when artificial intelligence mirrors unconscious thoughts, racism, and biases of the humans who generated these algorithms, it can lead to serious harm. Computer programs, for example, have wrongly flagged Black defendants as twice as likely to reoffend as someone who's white. When an AI used cost as a proxy for health needs, it falsely named Black patients as healthier than equally sick white ones, as less money was spent on them. Even AI used to write a play relied on using harmful stereotypes for casting. Removing sensitive features from the data seems like a viable tweak.


Python and Machine-Learning for Asset Management with Alternative Data Sets

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Founded in 1906, EDHEC is now one of Europe's top 15 business schools . Based in Lille, Nice, Paris, London and Singapore, and counting over 90 nationalities on its campuses, EDHEC is a fully international school directly connected to the business world. With over 40,000 graduates in 120 countries, it trains committed managers capable of dealing with the challenges of a fast-evolving world. Harnessing its core values of excellence, innovation and entrepreneurial spirit, EDHEC has developed a strategic model founded on research of true practical use to society, businesses and students, and which is particularly evident in the work of EDHEC-Risk Institute and Scientific Beta. The School functions as a genuine laboratory of ideas and plays a pioneering role in the field of digital education via EDHEC Online, the first fully online degree-level training platform.


Valeo says next-gen lidar can enable Level 4

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A recent Valeo test vehicle in Tokyo demonstrated how Scala lidars and a front camera, combined with vehicle-to-infrastructure communication, could autonomously steer through crowded boulevards, thread between lumbering trucks and zipping passenger vehicles, while navigating pedestrians. The system is Level 4-capable but operates in Level 2 mode during public testing, with a Valeo engineer always at the ready to take control. The self-driving system had its faltering moments, usually while negotiating scenarios that require bending traffic rules -- such as leaving a lane to go around idling trucks or bicyclists. And the steering and braking aren't always as smooth as would be done with a human touch. Valeo engineers say that coming versions will better address such borderline scenarios.


Steve Blank Artificial Intelligence and Machine Learning– Explained

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Hundreds of billions in public and private capital is being invested in Artificial Intelligence (AI) and Machine Learning companies. The number of patents filed in 2021 is more than 30 times higher than in 2015 as companies and countries across the world have realized that AI and Machine Learning will be a major disruptor and potentially change the balance of military power. Until recently, the hype exceeded reality. Today, however, advances in AI in several important areas (here, here, here, here and here) equal and even surpass human capabilities. If you haven't paid attention, now's the time. Artificial Intelligence and the Department of Defense (DoD) The Department of Defense has thought that Artificial Intelligence is such a foundational set of technologies that they started a dedicated organization- the JAIC – to enable and implement artificial intelligence across the Department. They provide the infrastructure, tools, and technical expertise for DoD users to successfully build and deploy their AI-accelerated projects. Some specific defense related AI applications are listed later in this document. We're in the Middle of a Revolution Imagine it's 1950, and you're a visitor who traveled back in time from today. Your job is to explain the impact computers will have on business, defense and society to people who are using manual calculators and slide rules. You succeed in convincing one company and a government to adopt computers and learn to code much faster than their competitors /adversaries. And they figure out how they could digitally enable their business – supply chain, customer interactions, etc. Think about the competitive edge they'd have by today in business or as a nation. That's where we are today with Artificial Intelligence and Machine Learning. These technologies will transform businesses and government agencies.


This AI tool predicts whether COVID patients will live or die

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A tool has been developed to help healthcare professionals identify hospitalised patients most at risk of dying from COVID-19 using artificial intelligence (AI). The algorithm could help doctors to direct critical care resources to those in most immediate need, which the developers of the AI tool say could be especially valuable to resource-limited countries. And with no end in sight for the coronavirus pandemic, with new variants leading to fresh waves of sickness and hospitalisation, the scientists behind the tool say there is a need for generalised tools like this which can be easily rolled out. To develop the tool, scientists used biochemical data from routine blood samples taken from nearly 30,000 patients hospitalised in over 150 hospitals in Spain, the US, Honduras, Bolivia and Argentina between March 2020 and February 2022. Taking blood from so many patients meant the team were able to capture data from people with different immune statuses – vaccinated, unvaccinated and those with natural immunity – and from people infected with every variant of COVID-19.


How Automation Hero uses accurate AI to process documents

#artificialintelligence

We are excited to bring Transform 2022 back in-person July 19 and virtually July 20 - 28. Join AI and data leaders for insightful talks and exciting networking opportunities. Before Dr. Alan Turing designed the first computer, people merely dreamed of intelligent machines that could read paperwork and do most of their grunge work for them. Science-fiction movies depict advanced software processing large amounts of documents to find hidden insights that save the day. Today this is available in real life from progressive-thinking software providers. One of them, San Francisco-based Automation Hero, today launched v6.0 of its Hero Platform, a SaaS service the company claims takes a quantum leap in OCR (optical character recognition) document-processing accuracy.