Category Archives: Artificial Intelligence

When it comes to artificial intelligence (AI), America is still on top. A major reason for that? America is quite good at recruiting AI students from around the world and retaining them after they graduate from school. But if certain plans proposed by the White House come to fruition, then that could all change very quickly.

Americas increasingly convoluted and unwelcoming immigration system has put the countrys front-runner status in jeopardy, according to a landmark report from Georgetown Universitys Center for Security and Technology (CSET). And, if the Trump administration moves forward with its plan to rescind the Optional Practical Training (OPT) program, then Americas. leadership position in AI will become even more vulnerable.

Rescinding OPT, which allows thousands of international students to work in the United States after graduation, notably undermines President Donald Trumps own plan to protect Americas AI advantage. More than two hundred thousand people are brought into the American workforce each year through the OPT program. Roughly two-thirds of them hold the sorely-needed advanced graduate and Ph.D. degrees that AI relies on.

If theyre gone, then Americas workforce has a problem. After all, domestic interest in these fields remains woefully insufficient to meet the spike in employer demand for AI workers.

These kinds of labor shortages cant be taken lightly, given the beneficial impact AI has on American lives. AI is improving a vast and diverse range of industries including healthcare, entertainment, auto manufacturing, social media, finance, and many, many more, Matthew Feeney, the Cato Institutes Director of Emerging Technologies, told me. In fact, the OPT program helps ameliorate talent gaps that may otherwise see that crucial progress grind to a halt.

Right now, OPT offers graduates in science, technology, engineering, and mathematics (STEM) the chance to work in the United States for up to three years after graduation. Theres no limit to the number of people who can participate in the program, and, while working, many of these folks hope to nab an H-1B visa, which can give them an additional six years of U.S. employment. Firms can also sponsor their H-1B workers for green cards, making it one of the few viable ways that foreign students can gain permanent residency.

But the H-1B visa is subject to strict numerical limits. In fact, for every year since 2015, the number of H-1B applications the U.S. government received was more than double that of the eighty-five thousand visas available. The executive branch has dealt with this excess in applications by awarding visas through a lottery system. Since an applicant may not get an H-1B visa on their first try, the OPT program allows them to re-apply for a second and third year while they maintain their authorization to work in the United States.

As such, the OPT program is treated as a waiting room of sorts for immigrant hopefuls. An applicant may not get an H-1B visa on their first try, but OPT allows STEM graduates, including those in AI-related fields, to keep working in the United States as they reapply the next year and, if theyre still unlucky, the year after.

By the end of August, that could all come to a crashing halt. The Trump administration is slated to curtail the programeven possibly dismantling it altogether.

Even if Trump chooses not to do so, the program still faces challenges in court. In Washington Alliance of Technology Workers v. U.S. Department of Homeland Security, et. al, a union of U.S. tech workers have argued that OPT harms Americans by forcing them to compete with foreigners for the same employment opportunities.

Extensive research on the program, however, shows that this simply isnt the case. According to a study by Jeremy Neufeld of the Niskanen Center, for every ten OPT workers in a given locality, American wages increase by an average of at least $2and five patents get added to that area. OPT recipients are highly educated and motivated by the desire to prove themselves, says Neufeld. They even make the people around them and the teams theyre on more productive, increasing innovation and raising the earnings of similarly educated natives.

The OPT program is under fire from both the executive and legislative branches, so its up to Congress to make certain that America continues to be an attractive place for AI graduates to build their futures. For starters, lawmakers could consider codifying OPT into law, so that the programs fate no longer rests on executive discretion. Congress should also examine solutions such as extending the H-1B cap exemptions that many nonprofit and governmental organizations already enjoyand ending green card restrictions that would keep some applicants waiting in line for over one hundred years.

The OPT program has been one of the many Band-Aids holding together an immigration system that hasnt been updated since the early 1990s before the internet became the world economys major driver. The Trump administration is moving to eliminate this crucial but imperfect fix. But Congress can use this opportunity to make lasting changesreforms that recognize Americas desperate need to increase and keep the AI talent Trump said he wanted.

Sam Peak is a Tech and Innovation Fellow for Young Voices and a policy associate at Americans for Prosperity. The views expressed in this column dont necessarily reflect those of the organizations with which the author is affiliated.

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Trump Policy Tactics that Target Foreigners Put America's Artificial Intelligence at Risk - The National Interest Online

Alterovitz is also looking for other uses to help VA staff members make better use of their time and help patients in areas where resources are limited.

"Being able to cut the (clinician) workload down is one way to do that," he said. "Other ways are working on processes, so reducing patient wait times, analyzing paperwork, etc."

Barriers to AI

But Alterovitz notes there are challenges to implementing AI, including privacy concerns and trying to understand how and why AI systems make decisions.

Last year, DeepMind Technologies, an AI firm owned by Google, used VA data to test a system to predict deadly kidney disease. But for every correct prediction, there were two false positives.

Those false results may cause doctors to recommend inappropriate treatments, run unnecessary tests, or do other things that could harm patients, waste time, and reduce confidence in the technology.

"It's important for AI systems to be tested in real-world environments with real-world patients and clinicians, because there can be unintended consequences," said Mildred Cho, the Associate Director of the Stanford Center for Biomedical Ethics.

Cho also said it's important to test AI systems with a variety of demographics, because what may work for one population may not for another. The DeepMind study acknowledged that more than 90 percent of the patients in the dataset it used to test the system were male veterans, and that performance was lower for females.

Alterovitz said the VA is taking those concerns into account as the agency experiments with AI and tries to improve upon the technology to ensure it is reliable and effective.

This story was produced by the American Homefront Project, a public media collaboration that reports on American military life and veterans. Funding comes from the Corporation for Public Broadcasting.

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The VA Has Embraced Artificial Intelligence To Improve Veterans' Health Care - WUNC

Is there room in theworld for two Travis Scotts?

Digital agency Space150 recently created a completely AI-generated song with lyrics and melodies designed with Scotts music in mind, purely for his unique style, Adweek reports. After fueling a text generator model with lyrics for two weeks, the company ended up with a track titled Jack Park Canny Dope Man." It also came with a strange videorapped by a deepfake of Scott named Travisbott, which you can view above.

The song even includesScotts trademark ad-libs, and has extremely Auto-Tuned vocals and absurd rhymes, such as:

I aint got the surfers 'cause I know Im not that hardBut I got all my old bitches mad by the barsThinkin at the Grammys, in the family, I got starsTry to put in the plane, but the blame be on the cars

Space150s executive creative director, Ned Lampert told Adweekthe project wasnt created for any specific client. We were sort of fascinated with like, What if we tried to make a songlike an actual good songby using AI and basically creative directing AI? he said. And so we chose Travis Scott just because he is just such a unique artist and he has a unique sound and everything sort of has an aesthetic to it, both audibly and visually.

Lampert explained that the bot kept producing lyrics about eating, while still figuring out how to imitate Scotts musical style. There was one line like, I dont want to fuck your party food, he said.

It came up with things that we would never come up with, Lampert continued. I love the beautiful mistakes that we make all the time that get turned into work or [situations] where someone says something ridiculous and then we end up doing it. And there were some of those types of behaviors within this process.

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This Travis Scott-Type Song Was Created by Artificial Intelligence - Complex

Even though the full optimization of AI and the IoT is relatively far away, the two technologies are now being combined across industries in scenarios where problem-solving and information can improve outcomes for all stakeholders.

Last such great convergence occurred in the late 1990s as mobile phones and the internet collided to change the course of human history. The convergence of AI and the IoT will bring in a similar revolution on an even grander scale.

AIoT Helps Companies Garner the Real Value of IoT Data

The ability to capture data through IoT is a large scale evolution that has exploded on the scene over the past five years. These new advancements have been accompanied by new concerns and threats associated with privacy and security. Large volumes of confidential company information and user data are tempting targets for dark web hackers as well as the global government entities. The high level of risk has also brought in newer and more responsibilities that accompany the increased capability.

Sensors are now applied to almost everything. This indicates that infinitely more data can be collected from every transaction or process in real-time. IoT devices are the front line of the data collection process in manufacturing environments and also in the customer service departments. Any device with a chipset can potentially be connected to a network and begin streaming data 24/7.

Complex algorithms allow performing predictive analytics from all conceivable angles. Machine learning (ML), a subset of AI, continues to upgrade workflows and simplify problem-solving. Companies now capture all the meaningful data surrounding their processes and problems to develop specific solutions for real challenges within the organization, improving efficiency, reliability, and sustainability.

While IoT and AI are impressive superpowers in their own capacity, thanks to the concept of convergence, their power doubles as IoT enhances the value of AI allowing real-time connectivity, data exchange, and signaling. AI enriches the capabilities of the IoT by applying ML to improve decision making.

Artificial Intelligence Trends for the Modern Enterprise

Industries are now referring to this convergence as AIoT. Presently, many AIoT applications are relatively massive, as companies build the expertise and required systems to deploy for supporting these powerful technologies across their organizations. The future will witness this convergence allowing more optimization and networking, creating even more value.

Experts have predicted a full digital integration between computers and humans by the year 2030. Between this and ongoing advances in robotics and automation, up to 40% of the current workforce could be replaced by technology in the next 10-15 years, by 2023. The predictions continue as:

Hardware manufacturers and solutions providers are already in full swing to leverage this tech convergence and position themselves in a position of favor in the evolving industrial landscape. Innovative companies like Amazon are offering training and re-education opportunities for employees in soon-to-be-obsolete job functions with such technology convergence hitting the market.

IoT Technologies Drive Digital Transformation Strategies of Enterprises

Convergence is a concept everyone should become familiar with, as every technology, discoveries, and advances will witness convergence in the future to innovate and disrupt the way the industries function.

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AIoT Convergence of Artificial Intelligence with the Internet of Things - EnterpriseTalk

The growing use of artificial intelligence (AI) by police forces requires new vigilance on the part of courts and the public about finding the right balance between civil liberties and public safety, warns a professor at the University of California-Davis School of Law.

Law enforcement has been using computers for decades to handle large amounts of investigative information, but new technology such as facial recognition, Shot Spotter, financial anomaly detectio, and automated license plate camera readers, has allowed police to increase the scale and speed of processing information, writes Elizabeth E. Joh, a professor of criminal law and procedure, constitutional law, and policing at the U.C. Davis School of Law

Thatwarrants new scrutiny especially since many communities are unaware of the extent of advanced technology used by their law enforcement agencies, Joh wrote in an essay for Viewpoints, a newsletter published by the Association for Computing Machinery.

For example, the Chicago Police Department uses an algorithm that identifies which city residents may be at especially high risk as perpetrators or victims of gun violence.

Police in Fresno, Ca., piloted an alert system that tells an officer whether the driver the police officer just pulled over to the side of the road poses a threat.

Dozens of other police departments use a program called PredPol, a machine learning algorithm that maps granular 500 x 500-foot sections of the city where crime is more likely to occur, Joh reports.

One danger of the growing reliance on technology is that if the tools malfunction or are used incorrectly, serious consequences can result, according to Joh.

Artificial Intelligence removes human checks where police would traditionally enter a situation using their senses and basic skills to interpret what they are seeing.

Joh gives the example of a bystander reporting abuse.

How would the AI detect truth or lies, she asked?

AI also allows the police to hide their presence in communities, vastly expanding the pool of people and activities the police can watch. Even simple license plate readers identify hundreds of plates a minute.

Moreover, some cameras are connected to the internet, opening up a possibility for hacker activity.

Worse, some [cameras] are leaking sensitive data about vehicles and their drivers and many have weak security protections that make them easily accessible, Tech Crunch writes.

Joh noted that legal rulings already have given a green light to wider law enforcement use of the cellphone location technology.

In Carpenter v. United States, the Supreme Court in 2018 ruled the FBI was able to access the defendants location through cell phone records that showed over 12,000 pings around the time of a robbery, without requiring a warrant.

Even though Carpenters case is not explicitly about AI, it hits notes that are relevant to privacy and information gathering.

The Court was concerned about tools that had extended beyond augmenting the sensory faculties bestowed upon [the police] at birth, Joh explained.

Automated, third-party information-gathering by police challenges traditional notions of privacy, she wrote.

The conventional view is that no matter whether the government has taken one of a thousand snapshots of your face, you have given up your privacy rights, wrote Joh.

The author concludes with a quote from the Carpenter ruling: Unlike the nosy neighbor who keeps an eye on comings and goings, the technology used by the police was ever alert, and [its] memory is nearly infallible.

Courts and civil liberties groups will therefore need to confront a worrying new reality, the paper said.

[The] artificial intelligence tools being adopted by police departments.. are cheap, powerful, ubiquitous, automated and invasive of privacy in ways that are novel and alarming, warned Joh.

See also: CA License Plate Reader Doesnt Protect Privacy

The full paper can be accessed here.

This summary was prepared by Andrea Cipriano, a TCR staff writer.

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Police Use of Artificial Intelligence Poses 'Alarming' Threats to Privacy: Paper - Crime Report

These are the jobs that robots are taking over. Robots take retail. Headlines such as these have become so common, theyre practically accepted as fact. While many are quick to blame advancing technology such as artificial intelligence, the real problem is how that technology is deployed in the workplace along with who stands to benefit from it.

Though tech hubs such as San Francisco, Boston and Seattle routinely grab the limelight, Houston too is on the forefront of an innovation that could drastically change the lives of some workers. Starting last year, a robotics company based in Silicon Valley, Nuro, has been using the suburbs of Houston to test its autonomous grocery delivery service.

In this age of driverless cars, were spending less time celebrating the freedom technology brings and more time worried about what it means for those such as the gig economy workers who deliver groceries who will eventually be replaced by autonomous vehicles.

These concerns are legitimate. Just as urgent is the need to grapple with how we can deploy this new technology to benefit workers. In short, the economic benefits of technology should be broadly shared among all of us.

How technological change is implemented, who benefits and who pays a price, will be based on choices that we make as a society. What scholars are learning, unfortunately, is that high economic inequality is confining the benefits of technological progress and accompanying economic growth primarily to the very rich.

Economic inequality the differences between the top 1 percent and the rest of us has been growing in the United States since the 1980s and stands at its highest point in a century. Houston is not immune: In 2015, the Houston metropolitan area ranked seventh among nearly one thousand metropolitan areas in its share of people who reside in the top 1 percent of incomes nationwide, according to a recent study by the Economic Policy Institute.

Technological progress, while making many workers more productive and adding high-skill jobs to the economy, also reinforces economic and other kinds of inequality, such as by race and gender. Technology has contributed to the rise of independent contractors, franchises and the gig economy. These trends have undermined their bargaining power to obtain wage increases and improved conditions.

Though it might be difficult to predict where technology will take jobs and employment in the decades ahead, we can make policy changes today that address inequality and ensure that workers are treated fairly and can earn their share of the productivity benefits technological advancement provides.

A fundamental step to reducing inequality is to ensure that our economy remains competitive and that the first mover advantage to create new platforms doesnt calcify into monopolies that stifle future innovation and entrepreneurship. Our 21st-century policies must be up to the task of ensuring market competition in the face of new technologies.

We also need to ensure that the gains of growth are shared. We have an easy way to do this: put in place a tax code that does not fossilize wealth into the hands of few. Changes in recent years have mostly benefited the wealthy and corporate interests, not the many. We need a tax code that gives us the capacity to make much-needed investments in our communities and our people that will ensure our economy can be competitive for generations to come. A number of proposals for taxing wealth have been offered; though some go farther than others, any step is a step in the right direction.

And, to directly support the workers who must contend with changing technologies, we need to modernize labor laws and other policies affecting workers to account for the changes taking place in the economy and to reverse actions that have weakened labor unions and worker power. The federal labor standards enacted in the 20th century essentially do not exist for millions of gig workers and others. Those standards for safety, for wages, for working conditions should be updated to meet the needs of todays families by including things like paid leave and extended to all.

In addition, workers voices need to be heard in the workplace. Worker input can lead to greater equity and more efficient production processes. See Harvard Universitys Labor and Worklife Program, which recently issued the Clean Slate for Worker Power, an agenda of policy recommendations that would strengthen the ability of organized labor to rebalance the power between workers and employers.

Luckily Houston has already begun to take action. In 2017, the Mayoral Task Force on Equity produced an in-depth report with a series of recommendations for addressing inequality in Houston. The policies included in Rising Together: A Roadmap to Confront Inequality in Houston ranged from a new jobs program and early childhood education reforms to greater investment in low-income neighborhoods and a more progressive tax system.

Too many conversations about technology and the future of work start from the premise that technology controls us, and not the other way around. If we want to ensure that technology serves all of us and that its benefits are broadly shared then we need to address inequality so that workers are better positioned to weather any challenges the robots might bring.

Boushey is the president and CEO of the Washington Center for Equitable Growth. She will be speaking about her book "Unbound: How Inequality Constricts Our Economy and What We Can Do About It" at Rice University on Wednesday, Feb. 12, at 6:30 p.m. This event is free and open to the public but registration is recommended. She will also be presenting at a Rice Scientia Conference on Work in the 21st Century: Automation, Workers, and Society Feb 13-14.

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Robots and artificial intelligence can benefit workers instead of hurting them if we address inequality today [Opinion] - Houston Chronicle

WASHINGTON, February 13, 2020 Biased artificial intelligence poses obstacles for marginalized communities when trying to access financial services like applying for a mortgage loan, said panelists speaking before the House Committee on Financial Services.

In a statement before the committee on Wednesday, privacy and AI advisor Br A. Williams wrote, Data sets in financial services are used to determine home ownership and mortgage, savings and student loan rates; the outcomes of credit card and loan applications; credit scores and credit worthiness, and insurance policy terms.

In practice, biased AI could mean that black homeowners were confined to specific areas of a city and that their credit worthiness led to higher interest rates, Williams said.

Rayid Ghani, of the Machine Learning Department at Carnegie Mellon Universitys Heinz College of Information Systems and Public Policy, said that it is not enough to create an equitable AI. Rather, there needs to be equity across the entire decision-making process.

Machine bias is not inevitable, nor is it final, concurred Brookings Institution Fellow Makada Henry-Nickie.

This bias though, is not benign. AI has enormous consequences for racial, gender, and sexual minorities, said Henry-Nickie.

University of Pennsylvania Professor Michael Kearns said biased AI is generally not the result of human malfeasance, such as racist or incompetent software developers.

However, Williams argued that if AI is being fed historical data, its already biased.

In order to create an equal AI system, Ghani included steps to an equitable process in the actual construction of AI. Ghani suggested:

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Biased Artificial Intelligence has Sinister Consequences for Marginalized Communities, Argue Panelists - BroadbandBreakfast.com

This report presents the worldwide Artificial Intelligence Robotics market size (value, production and consumption), splits the breakdown (data status 2018 and forecast to 2025), by manufacturers, region, type and application.

This study also analyzes the market status, market share, growth rate, future trends, market drivers, opportunities and challenges, risks and entry barriers, sales channels, distributors and Porters Five Forces Analysis.

The report presents the market competitive landscape and a corresponding detailed analysis of the major vendor/key players in the market.

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Top Companies in the Global Artificial Intelligence Robotics Market:

In global market, the following companies are covered: NVIDIAIntelIBMMicrosoftXilinxSoftbankHanson Robotics

Market Segment by Product TypeService RobotsIndustrial Robots

Market Segment by ApplicationMilitary & DefenseLaw EnforcementHealthcare AssistanceEducation and EntertainmentPersonal Assistance and CaregivingStock ManagementOthers

Key Regions split in this report: breakdown data for each region.United StatesChinaEuropean UnionRest of World (Japan, Korea, India and Southeast Asia)

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The report provides a valuable source of insightful data for business strategists and competitive analysis of Artificial Intelligence Robotics Market. It provides the Artificial Intelligence Robotics industry overview with growth analysis and futuristic cost, revenue and many other aspects. The research analysts provide an elaborate description of the value chain and its distributor analysis. This Tire Artificial Intelligence Robotics study provides comprehensive data which enhances the understanding, scope and application of this report.

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Artificial Intelligence Robotics market recent innovations and major events.

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The report has 150 tables and figures browse the report description and TOC:

Table of Contents

1 Study Coverage

1.1 Artificial Intelligence Robotics Product

1.2 Key Market Segments in This Study

1.3 Key Manufacturers Covered

1.4 Market by Type

1.4.1 Global Artificial Intelligence Robotics Market Size Growth Rate by Type

1.4.2 Hydraulic Dredges

1.4.3 Hopper Dredges

1.4.4 Mechanical Dredges

1.5 Market by Application

1.5.1 Global Artificial Intelligence Robotics Market Size Growth Rate by Application

2 Executive Summary

2.1 Global Artificial Intelligence Robotics Market Size

2.1.1 Global Artificial Intelligence Robotics Revenue 2014-2025

2.1.2 Global Artificial Intelligence Robotics Production 2014-2025

2.2 Artificial Intelligence Robotics Growth Rate (CAGR) 2019-2025

2.3 Analysis of Competitive Landscape

2.3.1 Manufacturers Market Concentration Ratio (CR5 and HHI)

2.3.2 Key Artificial Intelligence Robotics Manufacturers

2.3.2.1 Artificial Intelligence Robotics Manufacturing Base Distribution, Headquarters

2.3.2.2 Manufacturers Artificial Intelligence Robotics Product Offered

2.3.2.3 Date of Manufacturers Enter into Artificial Intelligence Robotics Market

2.4 Key Trends for Artificial Intelligence Robotics Markets & Products

3 Market Size by Manufacturers

3.1 Artificial Intelligence Robotics Production by Manufacturers

3.1.1 Artificial Intelligence Robotics Production by Manufacturers

3.1.2 Artificial Intelligence Robotics Production Market Share by Manufacturers

3.2 Artificial Intelligence Robotics Revenue by Manufacturers

3.2.1 Artificial Intelligence Robotics Revenue by Manufacturers (2019-2025)

3.2.2 Artificial Intelligence Robotics Revenue Share by Manufacturers (2019-2025)

3.3 Artificial Intelligence Robotics Price by Manufacturers

3.4 Mergers & Acquisitions, Expansion Plans

More Information.

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Artificial Intelligence Robotics Market: Drivers, Restraints, Opportunities, and Threats 2019-2029 - Instant Tech News

This has long been a staple of my collection of QTWTAIN Questions To Which The Answer Is No. Originally the question took the form of headlines such as, Will robots replace human journalists? A few years ago, the questions became more insistent as some news organisations experimented with automating sports results or market reporting.

The answer was still always No. Most journalism is a form of conversation. While it is possible to imagine weather reporting or traffic updates being handled by software, writing news stories or comment articles is a form of Turing test that computers are still a long way from passing.

Even so, artificial intelligence is capable of some amazing things. One of the big advances in technology recently has been in voice recognition software. Many journalists, including me, now use a programme called Otter.ai (the ai stands for artificial intelligence), which converts audio recordings into text.

Sharing the full story, not just the headlines

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Editor's Letter: Will artificial intelligence put journalists out of work? - The Independent

Digital agency space150 created a deepfake version of the rapper named Travisbott.

Recent advances in machine learning have allowed musicians like Holly Herndon to use artificial intelligence programs while creating their music. As reported in Adweek, digital agency space150 recently pushed the technology to its limits by creating an entirely AI-generated song with lyrics and melodies modeled after Travis Scotts music.

After two weeks of feeding lyrics into a text generator model, the creative team produced a track titled Jack Park Canny Dope Man by a deepfake version of the rapper named Travisbott. It was released with an unsettling music video:

The track comes complete with Scotts signature its lit and straight up ad-libs and features heavily auto-tuned vocals with nonsensical rhymes:

I aint got the surfers cause I know Im not that hardBut I got all my old bitches mad by the barsThinkin at the Grammys, in the family, I got starsTry to put in the plane, but the blame be on the cars

Ned Lampert, executive creative director at space150, explained to Adweek why the agency created the project, which wasnt designed for any particular client.

We were sort of fascinated with like, What if we tried to make a songlike an actual good songby using AI and basically creative directing AI? he said. And so we chose Travis Scott just because he is just such a unique artist and he has a unique sound and everything sort of has an aesthetic to it, both audibly and visually.

According to Lampert, the bot initially kept generating lyrics about food while it was still learning to mimic the Houston rappers style. There was one line like, I dont want to fuck your party food, he recalled.

Much like Herndon did with her 2019 album, PROTO, the agency used neural network programs to create the melodies and percussion arrangements for the songs instrumental, which falls just short of approximating the feel of Travis' signature sound.

In late 2019, Canadian musician Grimes spoke about AIs growing capacity to create music on the Mindscape podcast. Once theres actual AGI (Artificial General Intelligence), its gonna be so much better at making art than us, she said. Once AI can totally master science and art, which could happen in the next 10 years, probably more like 20 or 30 years.

While Travisbott shows machine learning hasnt surpassed human ability quite yet, AI-generated music continues to improve at a rapid pace.

Check out the full Adweek report here, and read all the lyrics to TravisBotts Jack Park Canny Dope Man on Genius now.

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This Fake Travis Scott Song Created By Artificial Intelligence Sounds Almost Like The Real Thing - Genius