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"More than just a poetic metaphor, the butterfly effect says that there are some things that even the most advanced science can never predict. Well, that list of things just got a lot shorter. Scientists from the University of Maryland have used machine learning to predict chaos."

"The researchers found that "increasing machine and AI readership … motivates firms to prepare filings that are more friendly to machine parsing and processing". So far, so predictable. But there's more: "firms with high expected machine downloads manage textual sentiment and audio emotion in ways catered to machine and AI readers""

"It is in the nature of AI that makers do not, and often cannot, predict what their creations do. We know how to make machines learn. But programmers do not understand completely the knowledge that intelligent computing acquires. If we did, we wouldn't need computers to learn to learn."

"That can include statistical or machine learning algorithms that rely on police records detailing the time, location, and nature of past crimes in a bid to predict if, when, where, and who may commit future infractions. In theory, this should help authorities use resources more wisely and spend more time policing certain neighborhoods that they think will yield higher crime rates."

"Over the years critics have pointed out their many shortcomings as well. Perhaps the biggest flaw of all is that the laws are vague. If machines become so human that we find it difficult to tell them and us apart, how will a machine tell the difference? Where does humanity end and artificial intelligence begin? And even if an AI can distinguish itself from a human being, we also cannot know what loopholes and reprogramming a robot is capable of. Surely an AI more clever than us could plan a way to access its core and bypass any of its existing limitations."

"Researchers at Columbia University sought to shed light on the problem by tasking 400 AI engineers with creating algorithms that made over 8.2 million predictions about 20,000 people. In a study accepted by the NeurIPS 2020 machine learning conference, the researchers conclude that biased predictions are mostly caused by imbalanced data but that the demographics of engineers also play a role."

"Consider abstract art. We've noted that machine learning, in aiming to make an accurate prediction, constructs a high-dimensional feature space that contorts and reconfigures the data representing features of the natural world. Likewise, artists "mash and rip" features of visual reality to create a system of forms, texture, and color that richly represent features of visual experience in an alien way. The subject of representation is abstracted but represented none-the-less. "

"If you've been job hunting recently, chances are you've interacted with a resume robot, a nickname for an Applicant Tracking System, or ATS. In its most basic form, an ATS acts like an online assistant, helping hiring managers write job descriptions, scan resumes and schedule interviews. As artificial intelligence advances, employers are increasingly relying on a combination of predictive analytics, machine learning and complex algorithms to sort through candidates, evaluate their skills and estimate their performance. Today, it's not uncommon for applicants to be rejected by a robot before they're connected with an actual human in human resources. The job market is ripe for the explosion of AI recruitment tools. Hiring managers are coping with deflated HR budgets while confronting growing pools of applicants, a result of both the economic downturn and the post-pandemic expansion of remote work. As automated software makes pivotal decisions about our employment, usually without any oversight, it's posing fundamental questions about privacy, accountability and transparency."

"In Neural Photo Editing With Introspective Adversarial Networks, a group of University of Edinburgh engineers and a private research colleague describe a method for using "introspective adversarial networks" to edit images in realtime, which they demonstrate in an open project called "Neural Photo Editor" that "enhances" photos by predicting what should be under your brush."

"More controversially, however, Genomic Prediction is also offering IVF patients the option of screening embryos for projected cognitive ability."

"Robots will begin replacing teachers in the classroom within the next 10 years as part of a revolution in one-to-one learning, a leading educationist has predicted. Sir Anthony Seldon, vice-chancellor of the University of Buckingham, said intelligent machines that adapt to suit the learning styles of individual children would soon render traditional academic teaching all but redundant."

"Raji says her investigation into the data has made her gravely concerned about deep-learning-based facial recognition. "It's so much more dangerous," she says. "The data requirement forces you to collect incredibly sensitive information about, at minimum, tens of thousands of people. It forces you to violate their privacy. That in itself is a basis of harm. And then we're hoarding all this information that you can't control to build something that likely will function in ways you can't even predict. That's really the nature of where we're at.""

"The BBC spoke to several students and parents who vouched for the quality of Byju's learning content - in a country where rote learning is often the norm, Byju's has been credited for deftly using technology to create immersive, engaging lessons. It also claims to have the industry's highest net promoter score (NPS), which measures customer experience and predicts business growth. "

"In the future, the team predict the software could also learn the appropriate emotion to express at a given time. "It could be mostly empathic," said Huang, adding that a challenge would be to avoid the chatbot reinforcing negative feelings such as rage."

"In 2015, a research group fed an AI system called Deep Patient health and medical data from some 700,000 people, and tested whether it could predict diseases. It could, but Deep Patient provides no explanation for the basis of a diagnosis, and the researchers have no idea how it comes to its conclusions. A doctor either can either trust or ignore the computer, but that trust will remain blind."

"The arcane nature of "protein folding", a mind-boggling form of molecular origami, is rarely discussed outside scientific circles, but it is a problem of profound importance. The machinery of biology is built from proteins and it a protein's shape defines its function. Understand how proteins fold up and researchers could usher in a new era of scientific and medical progress."

"The system uses AI to predict situations before they occur - thus informing on how resources could be better allocated - and to provide insights for better decision-making."

"The models work by dividing maps into what Google calls "supersegments" "

"Admission algorithms can make or break your academic plans. A Washington Post investigation found 44 schools use prediction software to give applicants a score out of 100 for its admissions process. The score considers different aspects of a student's application from test scores, home address, transcripts, and even what websites they've visited. That's all calculated to rate how strong of a match a student is for a school."

"Recent advances in AI are likely to spell the end of the traditional school classroom, one of the world's leading experts on AI has predicted. Prof Stuart Russell, a British computer scientist based at the University of California, Berkeley, said that personalised ChatGPT-style tutors have the potential to hugely enrich education and widen global access by delivering personalised tuition to every household with a smartphone. The technology could feasibly deliver "most material through to the end of high school", he said."