The Cancer Research Center of Marseille (CRCM) is the basic science and translational research unit of the IPC (http://www.institutpaolicalmettes.fr/en/research/). Also affiliated to INSERM, CNRS and Aix-Marseille University, the 400 researchers working at the CRCM form a strongly multi-disciplinary research environment characterized by frequent and close collaborations with IPC clinicians. IPC is a member of the UNICANCER network (http://www.unicancer.fr/en/unicancer). This project will investigate the application of Artificial Intelligence, and especially its Machine Learning (ML) component, to Precision Oncology (PO). PO is a form of medicine that uses personal information to prevent, diagnose and treat cancers.

AI and quantum computing are terms that most people are familiar with. But, did you ever hear of quantum machine learning? Quantum Machine Learning will be the next big thing in the domain of data science and technology in today's age, as quantum data science is becoming more mainstream. Quantum Machine Learning is essentially a hybrid of quantum computing and machine learning. Quantum computing is a field of research that focuses on developing computer technology based on quantum mechanics concepts, which describes the origin and behavior of matter and energy at the quantum (atomic and subatomic) levels.

In a recent survey, "2021 Thriving in an AI World," KPMG found that across every industry--manufacturing to technology to retail--the adoption of artificial intelligence (AI) is increasing year over year. Part of the reason is digital transformation is moving faster, which helps companies start to move exponentially faster. But, as Cliff Justice, US leader for enterprise innovation at KPMG posits, "Covid-19 has accelerated the pace of digital in many ways, across many types of technologies." Justice continues, "This is where we are starting to experience such a rapid pace of exponential change that it's very difficult for most people to understand the progress." But understand it they must because "artificial intelligence is evolving at a very rapid pace." Justice challenges us to think about AI in a different way, "more like a relationship with technology, as opposed to a tool that we program," because he says, "AI is something that evolves and learns and develops the more it gets exposed to humans." If your business is a laggard in AI adoption, Justice has some cautious encouragement, "[the] AI-centric world is going to accelerate everything digital has to offer." Business Lab is hosted by Laurel Ruma, editorial director of Insights, the custom publishing division of MIT Technology Review.

DHAKA (THE DAILY STAR/ASIA NEWS NETWORK) - Nobel Prize-winning author Kazuo Ishiguro's latest novel Klara and the Sun, his first since receiving the award in literature in 2017, has some relevance for policymakers and ordinary citizens across the globe. The main protagonist in this dystopian science fiction story is Klara, an artificial friend (AF) - a human-like teenager who behaves and thinks almost like her cohort of the same age and is a fast learner, as any device or robot using artificial intelligence (AI) can be expected to be. However, what we also learn is that if robots, even if they are super-intelligent, are allowed to make decisions that affect the lives of humans, it might lead to unintended consequences unless there are strict guidelines protecting privacy and other individual rights. Many discerning readers might already be aware that AI is whipping up quite a storm, particularly as it makes inroads into facial recognition software, law enforcement, and hiring decisions in the corporate world. Policymakers in many countries are alarmed, realising the pros as well as the cons of this revolutionary technology.

Nobel Prize-winning author Kazuo Ishiguro's latest novel Klara and the Sun, his first since receiving the award in literature in 2017, has some relevance for policymakers and ordinary citizens across the globe. The main protagonist in this dystopian science fiction story is Klara, an artificial friend (AF)--a human-like teenager who behaves and thinks almost like her cohort of the same age and is a fast learner, as any device or robot using artificial intelligence (AI) can be expected to be. However, what we also learn is that if robots, even if they are super-intelligent, are allowed to make decisions that affect the lives of humans, it might lead to unintended consequences unless there are strict guidelines protecting privacy and other individual rights. Many discerning readers might already be aware that AI is whipping up quite a storm, particularly as it makes inroads into facial recognition software, law enforcement, and hiring decisions in the corporate world. Policymakers in many countries are alarmed, realising the pros as well as the cons of this revolutionary technology.

It's common knowledge, at this point, that artificial intelligence will soon be capable of outworking humans -- if not entirely outmoding them -- in plenty of areas. How much we'll be outworked and outmoded, and on what scale, is still up for debate. But in a new interview published by The Guardian over the weekend, Nobel Prize winner Daniel Kahneman had a fairly hot take on the matter: In the battle between AI and humans, he said, it's going to be an absolute blowout -- and humans are going to get creamed. "Clearly AI is going to win [against human intelligence]. It's not even close," Kahneman told the paper.

Andrew Ng knows a thing or two about artificial intelligence. The former head of Google Brain and prior chief scientist at Baidu, Ng also co-founded Coursera and regularly teaches popular courses on the technology online and at Stanford. And he runs Landing AI, which provides manufacturers (and soon, other industries) with an AI platform to help developers more easily build and deploy computer vision models. That experience has given Ng a deep understanding of the benefits that AI can produce -- and the limitations of the tech. As Ng expands his work outside of consumer internet companies, he's seeing a pattern: Organizations are setting their AI ambitions too high.

The 3rd edition of the Montreal AI Ethics Institute's The State of AI Ethics captures the most relevant developments in AI Ethics since October 2020. It aims to help anyone, from machine learning experts to human rights activists and policymakers, quickly digest and understand the field's ever-changing developments. Through research and article summaries, as well as expert commentary, this report distills the research and reporting surrounding various domains related to the ethics of AI, including: algorithmic injustice, discrimination, ethical AI, labor impacts, misinformation, privacy, risk and security, social media, and more. In addition, The State of AI Ethics includes exclusive content written by world-class AI Ethics experts from universities, research institutes, consulting firms, and governments. Unique to this report is "The Abuse and Misogynoir Playbook," written by Dr. Katlyn Tuner (Research Scientist, Space Enabled Research Group, MIT), Dr. Danielle Wood (Assistant Professor, Program in Media Arts and Sciences; Assistant Professor, Aeronautics and Astronautics; Lead, Space Enabled Research Group, MIT) and Dr. Catherine D'Ignazio (Assistant Professor, Urban Science and Planning; Director, Data + Feminism Lab, MIT). The piece (and accompanying infographic), is a deep-dive into the historical and systematic silencing, erasure, and revision of Black women's contributions to knowledge and scholarship in the United Stations, and globally. Exposing and countering this Playbook has become increasingly important following the firing of AI Ethics expert Dr. Timnit Gebru (and several of her supporters) at Google. This report should be used not only as a point of reference and insight on the latest thinking in the field of AI Ethics, but should also be used as a tool for introspection as we aim to foster a more nuanced conversation regarding the impacts of AI on the world.

The 4th edition of the Montreal AI Ethics Institute's The State of AI Ethics captures the most relevant developments in the field of AI Ethics since January 2021. This report aims to help anyone, from machine learning experts to human rights activists and policymakers, quickly digest and understand the ever-changing developments in the field. Through research and article summaries, as well as expert commentary, this report distills the research and reporting surrounding various domains related to the ethics of AI, with a particular focus on four key themes: Ethical AI, Fairness & Justice, Humans & Tech, and Privacy. In addition, The State of AI Ethics includes exclusive content written by world-class AI Ethics experts from universities, research institutes, consulting firms, and governments. Opening the report is a long-form piece by Edward Higgs (Professor of History, University of Essex) titled "AI and the Face: A Historian's View." In it, Higgs examines the unscientific history of facial analysis and how AI might be repeating some of those mistakes at scale. The report also features chapter introductions by Alexa Hagerty (Anthropologist, University of Cambridge), Marianna Ganapini (Faculty Director, Montreal AI Ethics Institute), Deborah G. Johnson (Emeritus Professor, Engineering and Society, University of Virginia), and Soraj Hongladarom (Professor of Philosophy and Director, Center for Science, Technology and Society, Chulalongkorn University in Bangkok). This report should be used not only as a point of reference and insight on the latest thinking in the field of AI Ethics, but should also be used as a tool for introspection as we aim to foster a more nuanced conversation regarding the impacts of AI on the world.

The use case for Artificial Intelligence (AI) in the workplace is there. Deloitte's Tech Trends 2021 found AI and machine learning technologies are helping financial services firm Morgan Stanley use decades of data to supplement human insight with accurate models for fraud detection and prevention, sales and marketing automation, and personalized wealth management, among others. For marketing and customer experience, in particular, organizations are using AI and machine learning to improve internal business processes and workflow, automating repetitive tasks and to improve customer journeys and touchpoints, among other use cases. The CMO Survey by Duke University reports a steady increase as far as the extent to which companies are reporting implementing AI or ML into their marketing toolkits. However, the majority of marketers know AI is very important or critical to their success this year, according to Paul Roetzer, founder and CEO of the Marketing AI Institute and PR 20/20.