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Aspen is known for its world-class skiing, sky-high real-estate prices and breath-taking mountain views. The town has been known to conjure artistic inspiration, as well; its the town where Stevie Nicks reportedly wrote the hit Landslide, and a place John Denver called home for many years.

According to Swift Luxe, there are approximately 1.5 million visitors to Aspen each year who come to take in the beauty of the area.

While its practically impossible to capture Aspen and the surrounding areas beauty in an image, an AI program tried. The images below were created using a program calledDream Studio beta, a more rapid and accessible version ofStable Diffusion, a text-to-image modelthat was released to the public last month.

When this artificial intelligence text-to-image application thinks of Aspen, it thinks of vast mountain ranges.

Aspen, ColoradoStable Diffusion

Aspen, ColoradoStable Diffusion

Aspen, ColoradoStable Diffusion

Aspen, ColoradoStable Diffusion

Aspen, ColoradoStable Diffusion

Aspen, ColoradoStable Diffusion

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This is pretty close if you ask us.

Maroon BellsStable Diffusion

Maroon BellsStable Diffusion

Maroon BellsStable Diffusion

Maroon BellsStable Diffusion

Maroon BellsStable Diffusion

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Aspen Real EstateStable Diffusion

Aspen Real EstateStable Diffusion

Aspen Real EstateStable Diffusion

Aspen Real EstateStable Diffusion

Aspen Real EstateStable Diffusion

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Snowmass VillageStable Diffusion

Snowmass VillageStable Diffusion

Snowmass VillageStable Diffusion

Snowmass VillageStable Diffusion

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Close, very close.

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Artificial intelligence thinks the Aspen area looks like this - The Aspen Times

A new tool that uses artificial intelligence (AI) to analyze healthcare records may aid in the early diagnosis of fragile X syndrome, a new study reports.

By incorporating a combination of co-occurring conditions, an AI-assisted pre-screening tool was developed and validated to identify potential cases at least 5 years earlier than the time of clinical diagnosis, the researchers wrote.

The scientists said their AI tool was used successfully to analyze a healthcare database in the U.S. state of Wisconsin. Moving forward, this artificial intelligence-based program could be used across other healthcare databases to better and potentially much sooner identify individuals who may be affected by fragile X.

Our AI-assisted pre-screening approach can facilitate and accelerate the clinical diagnosis of [fragile X syndrome] and decrease the duration of the diagnostic odyssey and degree of stress experienced by patients and their families, the team wrote.

One concern in the move forward is that the AI tool thus far was only used in healthcare systems that were predominately comprised of white patients. More testing and validation is needed in other racial and ethnic patient populations, the researchers said.

The study, Advancing artificial intelligence-assisted pre-screening for fragile X syndrome, was published inBMC Medical Informatics and Decision Making.

Fragile X syndrome can manifest very differently from person to person, which makes diagnosing the genetic disorder a challenge. Studies have shown a marked gap between the estimated prevalence of fragile X and the actual number of people diagnosed suggesting that as many as 70% of people affected by fragile X syndrome have not been properly diagnosed.

To bridge that gap, a team led by scientists at the University of Wisconsin-Madison created an artificial intelligence tool aimed at better diagnosing fragile X syndrome. This tool is applied to data that is routinely collected in electronic healthcare records (EHRs).

Their aim was to identify data in such EHRs that could predict the diagnosis of fragile X, even before the disorder itself is formally diagnosed.

The pre-screening model is not intended to be a replacement for genetic testing, but it can serve as a tool to automatically alert physicians about the presence of multiple [fragile X syndrome]-related phenotypes in the patients medical records, the scientists wrote.

By prompting the physician to further evaluate such individuals and refer them for genetic testing and counseling, our approach could accelerate the diagnostic process and be instrumental in identifying un-diagnosed individuals in the population and addressing their health conditions, the team wrote.

To create the tool, the team used EHR data collected from 1979 to 2018 served by the Marshfield Clinic Health System in Wisconsin.

From the data, the team identified 55 people who had been diagnosed with fragile X syndrome at an age of 10 or older. The scientists also used data from 5,500 people without a fragile X diagnosis, who were similar to the patients in terms of age and sex.

For all of these patients, the researchers extracted data from five years before the formal diagnosis of fragile X syndrome, or the equivalent ages for controls.

All data used in this study are directly collected in a medical setting and are in fact real world data from actual patients, providing further proof of [the AI tools] potential utility in real world clinical applications, the team noted.

With these data in hand, the researchers then trained their artificial intelligence algorithm using a mathematical strategy called random forest. Conceptually, the AI tool uses a set of mathematical rules to look for patterns in the diagnostic codes that could differentiate between people with or without fragile X syndrome.

To test the utility of the trained algorithm, the scientists tested it on data collected from UW Health, a separate healthcare system in Wisconsin.

Our next step, reported here for the first time, was to evaluate the performance of this model in a new unseen dataset, i.e., an external validation study, they wrote.

In this dataset, the team identified data for 52 fragile X cases and 5,200 people without the disorder, matched for sex and age.

To test the tools accuracy, the researchers calculated a statistical measurement called the area under the receiver operating characteristic curve, or AUROC. This is basically a measurement of how well a test can tell the difference between two groups i.e., fragile X or not. AUROC values can range from 0.5 to 1, with higher values suggesting better ability to discriminate.

In the original Marshfield dataset, the AUROC for the AI tool was 0.798. In the UW Health analysis, it was 0.795.

The AUROCs of the predictive models created and evaluated using the Marshfield cases and the UW Health cases were almost identical (0.798 vs. 0.795), representing the high level of reproducibility of results in different health care systems, the scientists wrote.

Our AI-assisted pre-screening tool could significantly improve the diagnostic process and could provide substantial benefits for patients, families and the health care system, they concluded.

A noted limitation of this analysis was that nearly 90% of patients in both healthcare systems were white. The researchers highlighted a need to further validate this model in other populations, especially those of non-European ancestry.

Additional studies on larger populations will provide more precise information on the performance of the model, they wrote.

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Artificial Intelligence Tool May Help in Early Diagnosis of... - Fragile X News Today

Airlines aiming for total revenue optimization need intelligent solutions. While artificial intelligence and deep learning algorithms promise better forecasting capabilities, those systems can only truly shine when coupled with the flexibility and human touch of a data analyst.

FLYR

Commercial airlines and other travel and transportation leaders are facing significant challenges in managing pricing, demand, and logistics in todays volatile environment. This summers travel disruptions have laid bare the potential for intermittent hiccups in post-pandemic operations to have drastic effects on customer satisfaction and revenue opportunities.

With travelers patience wearing thin, airlines need to reinforce their people, processes, and technologies. By building artificial intelligence (AI) solutions into processes across their organizations, airlines can leverage their data, analysts, and revenue management opportunities to take advantage of new business fundamentals in this changing environment.

Artificial intelligence isnt replacing the airline data analysts job, said Alex Mans, founder and CEO of FLYR Labs, a technology company driving commercial optimization for airlines. But it is changing their role and hopefully unlocking their potential to drive revenue and improve operational efficiencies.

Airline data can be difficult to parse, but artificial intelligence makes it easier. Its impossible for humans to manually process all the information airlines are collecting from digital sources, but deep learning neural networks can provide effective forecasts that give analysts the confidence to make better decisions.

Historically, the leading forecasting type has been linear, regression-based models, where analysts look at very concentrated year-over-year patterns, Mans said. The problem is that theres just not enough data on any single flight for a given point in time to drive accurate forecasts in a volatile environment. Legacy systems are really bad at determining whether booking one seat on a given flight has a meaningful impact on the outcome.

To power deep learning algorithms, airlines feed neural networks vast amounts of historical data such as bookings, searches, events, promotions, and competitive prices resulting in forecasts that keep analysts better informed on revenue and load-factor performance into the future.

They can compare how the actual performance builds against the forecast data as the departure date approaches, Mans said. The real value comes when, with a platform such as ours, analysts come to trust the forecast and can start using it to inform strategic decisions instead of viewing it as a loose guideline.

According to Mans, artificial intelligence should be thought of as an airline data analysts smart sidekick its not replacing the analysts job, but rather enhancing the analysts ability to make coordinated operational decisions in areas where automation alone is insufficient.

In the past, analysts have not had accurate forecasts, so most of their decisions were based on instinct, Mans said. On top of that, they havent had good user interfaces for consuming that data. We generate much better forecasts, enable smarter workflows, and provide a dedicated user interface where analysts can easily access and filter the data and then use the resulting information. With better load and revenue forecasts at any level of granularity across the network, they can do amazing things.

For example, if an analyst sees a cluster of flights months into the future with a 99-percent forecasted load factor, they can alert colleagues in charge of scheduling and suggest adding capacity. At most airlines, where functions across the organizations are typically siloed, this kind of cross-functional collaboration between commercial teams isnt common.

All it takes to start breaking down those silos is for other teams to have access to the same information that the revenue management team has access to, Mans said. At the end of the day, different departments are trying to achieve the same results: maximize revenue and contain costs.

In addition to playing gatekeeper of that information, the analysts role will evolve to support a variety of critical functions across the organization.

For one thing, they can look around corners that the data itself cant see, Mans said. The analyst might know that a schedule change is coming, but unless that information is passed to our system, we have no awareness. Artificial intelligence doesnt know everything. Another thing to note is that optimizing for maximum revenue isnt always the goal. An airline entering a new market may want to follow a non-revenue-optimal strategy focused on market control or market share, so the analyst is needed to fine-tune that strategy. Or consider promotions every airline runs tons of promotions throughout the year, whether tied to their credit card program, certain destinations, or other variables that require the analyst to actively work with our platform and their marketing team to achieve the best results.

For airlines to weather the storm of todays unprecedented industry disruptions, dynamic pricing powered by deep learning algorithms is essential. FLYR was built to provide a singular platform that helps airlines manage data, break past data silos with consistently accurate forecasts that can be accessed by anybody in the organization, and achieve total revenue management across all of their products.

Our job is to help airlines effectively price everything they want to sell, including ancillaries like seat selection, extra baggage, priority boarding, and other upsells, Mans said. FLYRs operating system provides a vertically integrated SaaS platform across data management, forecasting, pricing, automation, business intelligence, and reporting which includes simulation and scenario evaluation while also removing constraints within e-commerce and fulfillment thanks to acquisitions such as Newshore so airlines can get stuff done faster and more efficiently. Thats what were building as a company, and thats the future of work within this industry.

Join us on October 19th at 11:00 a.m. ET for a webinar featuring FLYR founder and CEO Alex Mans, How Artificial Intelligence Is Reshaping the Travel Business. Register today

For more information on how FLYR is helping airlines achieve total revenue optimization, check out their latest whitepaper with IATA.

This content was created collaboratively by FLYR and Skifts branded content studio, SkiftX.

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How Artificial Intelligence Is Influencing the Future of Work in the Airline Industry - Skift Travel News

PALM BEACH, Fla., Sept. 15, 2022 /PRNewswire/ -- FinancialNewsMedia.com News Commentary - Artificial Intelligence (AI) is crossing over to new markets and brings additional revenues along with it. Increasing demand for Intelligent Tutoring Systems (ITSs) is fueling the AI in education industry growth. ITSs have a common aim of enabling learning effectively. The growing integration of ITS into the learning process has assisted in improving students learning styles, offering personalized tutoring and high-quality education to the students, thereby accelerating industry statistics. Cloud computing technology is increasingly being used by educators, faculties, facilitators, and students at schools & higher education institutes to improve productivity and the overall learning experience. Cloud computing allows schools and universities to upgrade their prevailing infrastructure with advanced technologies without any substantial increase in their capital costs. A reportfrom Global Market Insights projected that AI in Education Marketsize is set to surpass USD 80 billion by 2030. The report said: "There is a growing demand for outsourcing the management of AI in educational platforms. AI in education managed service segment is estimated to grow at a CAGR of over 55% through 2030 impelled by the increasing usage of intelligent algorithms among managed service providers. The cost-effectiveness of AI solutions is a major factor promoting the acceptance of AI among MSPs." Active Tech Companies in the markets today include: Amesite Inc. (NASDAQ: AMST), Microsoft Corporation (NASDAQ: MSFT), 2U, Inc. (NASDAQ: TWOU), Blackbaud(NASDAQ: BLKB),Instructure Holdings, Inc. (NYSE: INST).

The report added: "Natural Language Processing (NLP) held a market share of nearly 60% in 2021 owing to the growing adoption of NLP technology across educational institutes. NLP is a branch of AI, which assists computers in understanding, interpreting, and operating human language, filling human communication & computer interpretation gaps. Learning platforms and virtual facilitators accounted for about 50% of the artificial intelligence in education market share in 2021 led by the growing usage of various technologies by educational institutions to improve the quality of education for students. On-premise deployment held a market share of around 80% in 2021 credited to the security offered by on-premise deployment models. The on-premise storage of this data helps in providing instant access to the data as and when required with complete control over the system. These solutions also enable privacy and security of the student's data, accelerating their demand in the market."

Amesite Inc.(NASDAQ: AMST) BREAKING NEWS: Amesite and NAFEO Announce Addition of New Member Universities to Alliance - Amesite Inc., a leading artificial intelligence software company offering a cloud-based learning platform for business and education markets, announces that five new member universities have joined their collaborative alliance with the National Association for Equal Opportunity in Higher Education (NAFEO). New members include:

which have agreed to join NAFEO's Center for Opportunity and Equity (COE), a vehicle that NAFEO intends to support with a $30M fundraising effort to bring online learning resources to a first group of NAFEO's constituents, including Historically Black Colleges and Universities (HBCUs) and Predominantly Black Institutions (PBIs). Members of NAFEO's COE will have the opportunity to utilize NAFEO's planned Learning Community Environment, powered by Amesite, to deliver eLearning to build professional skills. The NAFEO members collectively enroll more than 700,000 students, and have over 7 million living alumni, all of whom are anticipated to benefit from the COE.

Lezli Baskerville, Esq., CEO of NAFEO, stated,"We are growing this alliance to deliver critical online learning infrastructure to our members through NAFEO's Center for Opportunity and Equity because it is the most efficient way to build enrollments and impact. Each university building its own infrastructure would take a great deal of time and be an inefficient use of resources. By working together and leveraging the strong history of trust and collaboration within NAFEO to engage and uplift our members, we ultimately intend to deliver millions of effective and affordable elearning opportunities. These will advance our constituencies economically, while enabling our universities to retain their storied brands and build greater impact." CONTINUED Read this full release for Amesite at: https://ir.amesite.com/

Other recent developments in the tech industry include:

Instructure Holdings, Inc. (NYSE: INST) recently announced it has earned a renewed Ed-Fi Managed Operational Data Store and API Platform Badge for Elevate K-12 Analytics and the Ed-Fi API Provider Badge for Elevate Standards Alignment (formerly Academic Benchmarks), both for another two years. The distinction validates Instructure as an ongoing, trusted Ed-Fi Operational Data Store, Analytics provider and API partner.

Instructure's renewed badges reaffirm the ongoing contributions the SaaS platform is making as part of the collaborative Ed-Fi Community, which advocates for the effective use of data at scale in education agencies of all sizes through a data standard. Because Instructure's Elevate products leverage the Ed-Fi standard and technology suite, any state or local education agency can more effectively leverage their own data to support administrators, educators, students and parents. Districts have hundreds of applications in use and typically this data remains siloed and unused. By seamlessly and securely bringing these data sources together through a data standard; administrators, educators and parents can more clearly see important data in real-time to support student success.

Blackbaud(NASDAQ: BLKB),the world's leading cloud softwarecompany powering social good, recently announced that it has acquiredKilter. The acquisition will allow Blackbaud toexpand activity-based peer-to-peer fundraising engagement, to support activity-based health and wellness initiatives for socially responsible companies, and to grow the ways individuals can connect with the causes they care about most through the activities they love.

Kilter is an intuitive, gamified, activity-based engagement app boasting virtually limitless activity type choices. Kilter expands activity-based engagement beyond the familiar options of running, walking and cycling, enabling users to track new, popular and personally relevant activities, from pickleball to meditation to motorcycling and more.

2U, Inc. (NASDAQ: TWOU),the parent company of leading global online learning platformedX, recently announced a significant update to its partnership model as part of its transition to a platform company, unveiling new revenue share options that give universities greater flexibility, as well as new tools to assist partners in lowering the tuition of their online degree programs at their discretion.

"As we embrace our future as a platform company under the edX brand, we're taking bold and important steps to support our university partners in transforming their institutions, expanding access, and helping bring down the cost of higher education,"said 2U Co-Founder and CEO Christopher "Chip" Paucek. "Higher education is at an inflection point, with learners demanding more flexibility and better ROI. 2U and edX strongly believe that greater affordability is better for students, better for universities, better for the company, and critical to the future of higher education."

Microsoft Corporation (NASDAQ: MSFT) recently Barclays Bank PLC (Barclays) and Microsoft Corp. announced that Barclays has deployed Microsoft Teams as its preferred collaboration platform, powering collaboration for more than 120,000 colleagues and service partners in key locations around the globe. Under the agreement, Barclays is streamlining its existing communications and collaboration solutions, with Teams replacing several point solutions previously in use across the company.

As part of its efforts to better connect employees across its business units and functions, Barclays and Microsoft jointly executed a deployment plan for the use of Teams across the company.This plan included enhancing the data retention, search and retrieval capabilities available within Microsoft Purview to meet Barclays' needs.

DISCLAIMER: FN Media Group LLC (FNM), which owns and operates FinancialNewsMedia.com and MarketNewsUpdates.com, is a third party publisher and news dissemination service provider, which disseminates electronic information through multiple online media channels. FNM is NOT affiliated in any manner with any company mentioned herein. FNM and its affiliated companies are a news dissemination solutions provider and are NOT a registered broker/dealer/analyst/adviser, holds no investment licenses and may NOT sell, offer to sell or offer to buy any security. FNM's market updates, news alerts and corporate profiles are NOT a solicitation or recommendation to buy, sell or hold securities. The material in this release is intended to be strictly informational and is NEVER to be construed or interpreted as research material. All readers are strongly urged to perform research and due diligence on their own and consult =a licensed financial professional before considering any level of investing in stocks. All material included herein is republished content and details which were previously disseminated by the companies mentioned in this release. FNM is not liable for any investment decisions by its readers or subscribers. Investors are cautioned that they may lose all or a portion of their investment when investing in stocks. For current services performed FNM has been compensated twenty six hundred dollars for news coverage of the current press releases issued by Amesite Inc. by a non-affiliated third party. FNM HOLDS NO SHARES OF ANY COMPANY NAMED IN THIS RELEASE.

This release contains "forward-looking statements" within the meaning of Section 27A of the Securities Act of 1933, as amended, and Section 21E the Securities Exchange Act of 1934, as amended and such forward-looking statements are made pursuant to the safe harbor provisions of the Private Securities Litigation Reform Act of 1995. "Forward-looking statements" describe future expectations, plans, results, or strategies and are generally preceded by words such as "may", "future", "plan" or "planned", "will" or "should", "expected," "anticipates", "draft", "eventually" or "projected". You are cautioned that such statements are subject to a multitude of risks and uncertainties that could cause future circumstances, events, or results to differ materially from those projected in the forward-looking statements, including the risks that actual results may differ materially from those projected in the forward-looking statements as a result of various factors, and other risks identified in a company's annual report on Form 10-K or 10-KSB and other filings made by such company with the Securities and Exchange Commission. You should consider these factors in evaluating the forward-looking statements included herein, and not place undue reliance on such statements. The forward-looking statements in this release are made as of the date hereof and FNM undertakes no obligation to update such statements.

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Artificial Intelligence (AI) In Education Market Size Is Expected to Hit $80 Billion By 2030 - PR Newswire

When I was a kid, my favorite poem was Shel Silversteins The Homework Machine, which summed up my childhood fantasy: a machine that could do my homework at the press of a button. Decades later that technology, the innocuously titled GPT-3, has arrived. It threatens many aspects of university education above all, college writing.

The web-based GPT-3 software program, which was developed by an Elon Musk-backed nonprofit called OpenAI, is a kind of omniscient Siri or Alexa that can turn any prompt into prose. You type in a query say, a list of ingredients (what can I make with eggs, garlic, mushrooms, butter, and feta cheese?) or a genre and prompt (write an inspiring TED Talk on the ways in which authentic leaders can change the world) and GPT-3 spits out a written response. These outputs can be astonishingly specific and tailored. When asked to write a song protesting inhumane treatment of animals in the style of Bob Dylan, the program clearly draws on themes from Dylans Blowin in the Wind:

How many more creatures must suffer?How many more must die?Before we open up our eyesAnd see the harm were causing?

When asked to treat the same issue in the style of Shakespeare, it produces stanzas of iambic tetrameter in appropriately archaic English:

By all the gods that guide this EarthBy all the stars that fill the skyI swear to end this wretched dearthThis blight of blood and butchery.

GPT-3 can write essays, op-eds, Tweets, jokes (admittedly just dad jokes for now), dialogue, advertisements, text messages, and restaurant reviews, to give just a few examples. Each time you click the submit button, the machine learning algorithm pulls from the wisdom of the entire internet and generates a unique output, so that no two end products are the same.

The quality of GPT-3s writing is often striking. I asked the AI to discuss how free speech threatens a dictatorship, by drawing on free speech battles in China and Russia and how these relate to the First Amendment of the U.S. Constitution. The resulting text begins, Free speech is vital to the success of any democracy, but it can also be a thorn in the side of autocrats who seek to control the flow of information and quash dissent. Impressive.

From an essay written by the GPT-3 software program

The current iteration of GPT-3 has its quirks and limitations, to be sure. Most notably, it will write absolutely anything. It will generate a full essay on how George Washington invented the internet or an eerily informed response to 10 steps a serial killer can take to get away with murder. In addition, it stumbles over complex writing tasks. It cannot craft a novel or even a decent short story. Its attempts at scholarly writing I asked it to generate an article on social-role theory and negotiation outcomes are laughable. But how long before the capability is there? Six months ago, GPT-3 struggled with rudimentary queries, and today it can write a reasonable blog post discussing ways an employee can get a promotion from a reluctant boss.

Since the output of every inquiry is original, GPT-3s products cannot be detected by anti-plagiarism software. Anyone can create an account for GPT-3. Each inquiry comes at a cost, but its usually less than a penny and the turnaround is instantaneous. Hiring someone to write a college-level essay, in contrast, currently costs $15 to $35 per page. The near-free price point of GPT-3 is likely to entice many students who would otherwise be priced out of essay-writing services.

It wont be long before GPT-3, and the inevitable copycats, infiltrate the university. The technology is just too good and too cheap not to make its way into the hands of students who would prefer not to spend an evening perfecting the essay I routinely assign on the leadership style of Elon Musk. Ironic that he has bankrolled the technology that makes this evasion possible.

To help me think through what the collision of AI and higher ed might entail, I naturally asked GPT-3 to write an op-ed exploring the ramifications of GPT-3 threatening the integrity of college essays. GPT-3 noted, with mechanical unself-consciousness, that it threatened to undermine the value of a college education. If anyone can produce a high-quality essay using an AI system, it continued, then whats the point of spending four years (and often a lot of money) getting a degree? College degrees would become little more than pieces of paper if they can be easily replicated by machines.

The effects on college students themselves, the algorithm wrote, would be mixed: On the positive side, students would be able to focus on other aspects of their studies and would not have to spend time worrying about writing essays. On the negative side, however, they will not be able to communicate effectively and will have trouble in their future careers. Here GPT-3 may actually be understating the threat to writing: Given the rapid development of AI, what percent of college freshmen today will have jobs that require writing at all by the time they graduate? Some who would once have pursued writing-focused careers will find themselves instead managing the inputs and outputs of AI. And once AI can automate that, even those employees may become redundant. In this new world, the argument for writing as a practical necessity looks decidedly weaker. Even business schools may soon take a liberal-arts approach, framing writing not as career prep but as the foundation of a rich and meaningful life.

So what is a college professor to do? I put the question to GPT-3, which acknowledged that there is no easy answer to this question. Still, I think we can take some sensible measures to reduce the use of GPT-3 or at least push back the clock on its adoption by students. Professors can require students to draw on in-class material in their essays, and to revise their work in response to instructor feedback. We can insist that students cite their sources fully and accurately (something that GPT-3 currently cant do well). We can ask students to produce work in forms that AI cannot (yet) effectively create, such as podcasts, PowerPoints, and verbal presentations. And we can design writing prompts that GPT-3 wont be able to effectively address, such as those that focus on local or university-specific challenges that are not widely discussed online. If necessary, we could even require students to write assignments in an offline, proctored computer lab.

Eventually, we might enter the if you cant beat em, join em phase, in which professors ask students to use AI as a tool and assess their ability to analyze and improve the output. (I am currently experimenting with a minor assignment along these lines.) A recent project on Beethovens 10th symphony suggests how such projects might work. When he died, Beethoven had composed only 5 percent of his 10th symphony. A handful of Beethoven scholars fed the short, completed section into an AI that generated thousands of potential versions of the rest of the symphony. The scholars then sifted through the AI-generated material, identified the best parts, and pieced them together to create a complete symphony. To my somewhat limited ear, it sounds just like Beethoven.

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Will Artificial Intelligence Kill College Writing? - The Chronicle of Higher Education