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There is an uncanniness in listening to a musical instrument you have never heard being played for the first time. As your brain makes sense of a new sound, it tries to frame it within the realm of familiarity, producing a tussle between the known and unknown.

The second album from Mexican-American producer Delia Beatriz, AKA Debit, embraces this dissonance. Taking the flutes of the ancient Mayan courts as her raw material and inspiration, Beatriz used archival recordings from the Mayan Studies Institute at the Universidad Nacional Autnoma de Mxico to create a digital library of their sounds. She then processed these ancient samples through a machine-learning program to create woozy, ambient soundscapes.

Since no written music has survived from the Mayan civilisation, Beatriz crafts a new language for these ancient wind instruments, straddling the electronic world of her 2017 debut Animus and the dilatory experimentalism of ambient music. The resulting 10 tracks make for a deliciously strange listening experience.

Opener 1st Day establishes the undulating tones that unify the record. They flutter like contemplative humming and veer from acoustic warmth to metallic note-bending. Each track is given a numbered day and time, as if documenting the passage of a ritual, and echoes resonate down the record: whistles appear like sirens during the moans of 1st Night and 3rd Night; snatches of birdsong are tucked between the reverb of 2nd Day and 5th Day.

The Long Count of the records title seems to express the linear passage of time itself, one replicated in the eternal, fluid flute tones. We hear in them the warmth of the human breath that first produced their sound, as well as Beatrizs electronic filtering that extends their notes until they imperceptibly bleed into one another and fuzz like keys on a synth. It is a startlingly original and enveloping sound that leaves us with that ineffable feeling: the past unearthed and made new once more.

Korean composer Park Jiha releases her third album, The Gleam (tak:til), a solo work featuring uniquely sparse compositions of saenghwang mouth organ, piri oboe and yanggeum dulcimer. British-Ghanaian rapper KOG brings his debut LP, Zone 6, Agege (Heavenly Sweetness), a deeply propulsive mix of English, Pidgin and Ga lyrics set to Afrobeat fanfares. Cellist and composer Ana Carla Maza releases her latest album, Baha (Persona Editorial), an affecting combination of Cuban son, bossa and chanson in homage to the music of her birthplace of Havana.

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Debit: The Long Count review Mayans, machine learning and music - The Guardian

While AI-enabled decision-making seems to take out the subjective human areas of bias and prejudice, many observers worry that machine analytics have the same or different biases embedded in the systems.

As with many advances in technology, the legal issues can be unsettled until a body of case law has been established. This is likely to be the case with artificial intelligence or AI. While legal scholars have already begun discussing the ramifications of this advance, the number of court cases, though growing, has been relatively meager up to this point.

Rapid Advances in AI

New and more powerful chips have the potential to accelerate many applications that rely on AI. This solves some of the impediments that have made advances in AI slower than some observers have anticipated. This speeds up the time it takes to train new machines and new models from months to just a few hours or even minutes. With better and faster chips for machine learning, the AI revolution can begin to reach its potential.

This potent advance will bring an array of important legal questions. This capability will usher in new ideas and techniques that will impact product development, analytics and more.

Important Impacts on Intellectual Property

While AI will impact many areas of the law, a fair share of its influence will be on areas of intellectual property. Certainly, areas of negligence, unfairness, bias, cyber security and other matters will be important, but some might wonder who owns the fruits of innovations that come from AI. In general, the patentability of computer-generated works has not been established, and the default is that the owner of the AI design is the owner of the new material. Since a computer cannot own personal property, at present, the right to intellectual property also does not exist.

More study and discussion will no doubt go into this area of law. This will become more pressing as technological advances will make it more difficult to identify the creator of certain products or innovations.

Increasing Applications in Medical Fields

The healthcare industry is also very much involved in harnessing the power associated with AI. Many of these applications involve routine tasks that are not likely to present overly complex legal concerns, although they could result in the displacement of workers. While the processing of paperwork and billing is already underway, the use of AI for imaging, diagnosis and data analysis is likely to increase in the coming years.

This could have legal implications when regarding cases that deal with medical malpractice. For example, could the creator of a system that is relied upon for an accurate diagnosis be sued if something goes wrong. While the potential is enormous, the possibility of error raises complicated questions when AI systems play a primary role.

Crucial Issues With Algorithmic Decision-Making

While AI-enabled decision-making seems to take out the subjective human areas of bias and prejudice, many observers worry that machine analytics have the same or different biases embedded in the systems. In many ways, these systems could discriminate against certain segments of society when it comes to housing or employment opportunities. These entail ethical questions that at some point will be challenged in a court of law.

The ultimate question is whether or not smart machines can outthink humans, or if they just contain the blind spots of the programmers. In a worst-case scenario, these embedded prejudices would be hard to combat, as they would come with the imprint of scientific progress. In other words, the biases would claim objectivity.

Some observers, though, believe that business practices have always been the arena for discrimination against certain workers. With AI, thoughtfully engaged and carefully calibrated, these practices could be minimized. It could offer more opportunities for a wider pool of individuals while minimizing the influence of favoritism.

The Legal Future of AI

As with other areas of the courts, AI issues will have to be slowly adjudicated in the court system. Certain decisions will establish court precedents that will gain a level of authority. Technological advances will continue to shape society and the international legal system.

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Legal Issues That Might Arise with Machine Learning and AI - Legal Reader

Job Description

Vessel Collision Avoidance System is a real-time framework to predict and prevent vessel collisions based on historical movement of vessels in heavy traffic regions such as Singapore strait. We are looking for talented developers to join our development team to help us develop machine learning and agent-based simulation models to quantify vessel collision risk at Singapore strait and port. If you are data curious, excited about deriving insights from data, and motivated by solving a real-world problem, we want to hear from you.

Qualifications

A B.Sc. in a quantitative field (e.g., Computer Science, Statistics, Engineering, Science) Good coding habit in Python and able to solve problems in a fast pace Familiar with popular machine learning models Eager to learn new things and has passion in work Take responsibility, team oriented, and result oriented The ability to communicate results clearly and a focus on driving impact

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Location: Kent Ridge CampusOrganization: EngineeringDepartment : Industrial Systems Engineering And ManagementEmployee Referral Eligible: NoJob requisition ID : 7334

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Research Engineer, Machine Learning job with NATIONAL UNIVERSITY OF SINGAPORE | 279415 - Times Higher Education (THE)

Since 2019, experts at the University of North Carolina at Chapel Hills University Libraries have investigated the use of machine learning to identify racist laws from North Carolinas past. Now a grant of $400,000 from The Andrew W. Mellon Foundation will allow them to extend that work to two more states. The grant will also fund research and teaching fellowships for scholars interested in using the projects outputs and techniques.

On the Books: Jim Crow and Algorithms of Resistance began with a question from a North Carolina social studies teacher: Was there a comprehensive list of all the Jim Crow laws that had ever been passed in the state?

Finding little beyond scholar and activist Pauli Murrays 1951 book States laws on race and color, a team of librarians, technologists and data experts set out to fill the gap. The group created machine-readable versions of all North Carolina statutes from 1866 to 1967. Then, with subject expertise from scholarly partners, they trained an algorithm to identify racist language in the laws.

We identified so many laws, said Amanda Henley, principal investigator for On the Books and head of digital research services at the University Libraries. There are laws that initiated segregation, which led to the creation of additional laws to maintain and administer the segregation. Many of the laws were about school segregation. Other topics included indigenous populations, taxes, health care and elections, Henley said. The model eventually uncovered nearly 2,000 North Carolina laws that could be classified as Jim Crow.

Henley said that On the Books is an example of collections as datadigitized library collections formatted specifically for computational research. In this way, they serve as rich sources of data for innovative research.

The next phase of On the Books will leverage the teams learnings through two activities:

Weve gained a tremendous amount of knowledge through this project everything from how to prepare data sets for this kind of analysis, to training computers to distinguish between Jim Crow and not Jim Crow, to creating educational modules so others can use these findings. Were eager to share what weve learned and help others build upon it, said Henley.

On the Books began in 2019 as part of the national Collections as Data: Part to Whole project, funded by The Andrew W. Mellon Foundation. Subsequent funding from the ARL Venture Fund and from the University Libraries internal IDEA Action grants allowed the work to continue. The newest grant from The Mellon Foundation will conclude at the end of 2023.

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Grant will expand University Libraries' use of machine learning to identify historically racist laws - UNC Chapell Hill

LEEDS, United Kingdom (StudyFinds.org) An artificial intelligence system is capable of spotting whether someone will have a heart attack within the next year through a routine eye scan.

A team from the University of Leeds believes this AI tool opens the door to a cheap and simple screening program for the worlds No. 1 killer. Their tests find the computer can predict patients at risk of a heart attack in the next 12 months with up to 80% accuracy. The breakthrough adds to evidence that our eyes are not just windows to the soul, but windowsto overall healthas well.

Cardiovascular diseases, including heart attacks, are the leading cause of early death worldwide and the second-largest killer in the UK. This causes chronic ill-health and misery worldwide, project supervisor Professor Alex Frangi says in auniversity release.

This technique opens-up the possibility of revolutionizing the screening of cardiac disease. Retinal scans are comparatively cheap and routinely used in many optician practices. As a result of automated screening, patients who are at high risk of becoming ill could be referred for specialist cardiac services, Frangi adds.

The system could also be used to track earlysigns of heart disease.

The retina is a small membrane at the back of the eye containing light sensitive cells. Doctors have found that changes to the tiny blood vessels canhint at vascular disease, including heart problems.

Study authors used an advanced type of AI, known as deep learning, to teach the machine to automatically read more than 5,000 eye scans. The scans come from routine eye tests during visits to opticians or eye clinics. All of the participants are part of the UK Biobank, which tracks the health of half a million adults.

Deep learning is a complex series of algorithms that enable machines to make forecasts based on patterns in data. The technique, described in the journalNature Machine Intelligence, could revolutionize heart therapy, according to the researchers.

The AI system has the potential to identify individuals attending routine eye screening who are at higher future risk of cardiovascular disease, whereby preventative treatments could be started earlier to prevent premature cardiovascular disease, says co-author Professor Chris Gale, a consultant cardiologist at Leeds Teaching Hospitals NHS Trust.

The study identified associations between pathology in the retina andchanges in the patients heart. Once the system learned each image pattern, the AI could estimate the size and pumping efficiency of the left ventricle from retinal scans alone.

This is one of the hearts four chambers. An enlarged ventricle can increase the risk of heart disease. The computer combined the estimated size of the left ventricle and its pumping efficiency with data like age and sex.

Currently, doctors determine this information using an MRI (magnetic resonance imaging) or echocardiography scans of the heart. The diagnostic tests are expensive and are often only available in a hospital. The tests can be inaccessible for many people in countries with lesser health care systems. They also increase health care costs and waiting times in wealthy nations.

The AI system is an excellent tool for unravelling the complex patterns that exist in nature, and that is what we have found the intricate pattern of changes in the retina linked to changes in the heart, adds co-author Sven Plein of the British Heart Foundation.

A recent study discovered a similar link between biologicalaging of the retina and mortality. Those with a retina older than their actual age were up to 67% more likely to die over the next decade.

South West News Service writer Mark Waghorn contributed to this report.

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AI can predict signs of a heart attack within a year from a routine eye test - KTLA Los Angeles