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Today, Turnitin, a leading provider of technology solutions in academic integrity, announced it will expand its offerings to advance classroom digitization through AI-powered grading, enhanced AI writing detection and customizable individual feedback for students. The launch includes a Paper to Digital add-on, helping educators provide faster online grading for paper assignments, ensuring prompt feedback to students, and an enhanced Similarity Report to help educators identify when content generated by AI writing tools may have been submitted. Education-related AI is predicted to be a $6 billion market by next year. Yet, according to Tyton Partners, students continue to lead in regular GenAI adoption rates at 59 percent compared to approximately 40 percent of instructors and administrators. The 2024-2025 school year is anticipated to be the year of AI, and educators need resources that help them adopt the technology in the classroom. “This school year, AI will likely be in every classroom,” said Annie Chechitelli, chief product officer, Turnitin. “Yet, there’s still a disconnect between students and educators about what constitutes acceptable generative AI use andaccess to technology to support learning. Turnitin is helping to address these challenges by providing teachers and administrators with new offerings to adapt to AI’s ever-evolving role in education, and supporting ethical AI usage for students.” googletag.cmd.push(function() { googletag.display('div-gpt-ad-1683043210496-0'); }); New Paper to Digital add-on improves grading accuracy and consistency AI in education goes far beyond plagiarism detection. If used correctly, this technology can simplify the challenges of grading paper-based assessments, and eliminate unintended bias while streamlining customized feedback for students and improving the learning process overall. A recent preprint paper by University of Michigan researchers revealed a significant correlation across 30 million grading records: students with surnames lower in the alphabet tend to receive lower grades. This bias stems from sequential grading practices compounded by the default alphabetical ordering of student submissions in learning management systems. The new Paper to Digital add-on for Turnitin Feedback Studio uses handwriting recognition, AI-assisted grouping and horizontal (question by question) grading of paper quizzes, tests and assignments. By streamlining grading and strengthening the consistency of instructor feedback, institutions can foster a fairer and more effective assessment environment. The new innovative tool also offers faster feedback, enhanced security and integration directly into learning management systems (LMS). Enhanced Similarity Report helps identify AI-Generated content In April 2023, Turnitin launched its AI writing detection feature to help educators identify AI-generated content in student work while safeguarding students’ interests. Since the launch, Turnitin has sourced pedagogical feedback from educators and administrators to inform product improvement and additional tech support features. As a result, Turnitin’s enhanced Similarity Report provides a new foundation for Turnitin’s AI writing detection feature. The tool helps educators identify unoriginal or improperly cited student writing, facilitating productive conversations on proper citation practices and accidental plagiarism. The new report has been thoughtfully redesigned with an intuitive interface and new categorization of match types, making it easier to interpret and use as a formative learning tool to strengthen academic writing skills. This update comes shortly after the launch of Turnitin’s AI paraphrasing detection feature, which is integrated within Turnitin’s AI writing capabilities – as an Originality add-on – enabling educators and publishers to identify when AI paraphrasing tools may have been used to modify AI-generated text to avoid detection.

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GraphCast is now the most accurate 10-day global weather forecasting system in the world, and can predict extreme weather events further into the future than was previously possible.

A staggering gender gap has opened in the adoption of ChatGPT: Women are 20 percentage points less likely to use ChatGPT compared to men in the same occupation.

Suno's mission is to make it possible for everyone to make music. We imagine a future where music is a bigger, more valuable, and more meaningful part of people's lives than it even is today. Technology enables a future where the whole world can explore, create, and be active participants in an art form most have only ever consumed. From professional musicians seeking inspiration to friends and family writing songs for each other, we are exploring new ways to create, listen to, and experience music. So far, more than 12 million people are engaging with music in new ways that wouldn't be possible without Suno. We see this as early but promising progress. Major record labels see this vision as a threat to their business. Each and every time there's been innovation in music — from the earliest forms of recorded music, to sampling, to drum machines, to remixing, MP3s, and streaming music — the record labels have attempted to limit progress. They have spent decades attempting to control the terms of how we create and enjoy music, and this time is no different. So, it is perhaps not a surprise that on June 24th, members of the Recording Industry Association of America, which represents the major record labels, filed a lawsuit against Suno, alleging that the data used in training our music generation technologies infringed on the copyrights of the major record labels that they represent. This lawsuit is fundamentally flawed on both the facts and the law, and is nothing more than yet another instance where they chose litigation over innovation. For starters, the major record labels clearly hold misconceptions about how our technology works. Suno helps people create music through a similar process to one humans have used forever: by learning styles, patterns, and forms (in essence, the "grammar" or music), and then inventing new music around them. The major record labels are trying to argue that neural networks are mere parrots — copying and repeating — when in reality model training looks a lot more like a kid learning to write new rock songs by listening religiously to rock music. Like that kid, Suno gets better the more our AI learns. We train our models on medium- and high-quality music we can find on the open internet — just as Google's Gemini, Microsoft's Copilot, Anthropic's Claude, OpenAI's ChatGPT, and even Apple's new Apple Intelligence train their models on the open internet. Much of the open internet indeed contains copyrighted materials, and some of it is owned by major record labels. But, just like the kid writing their own rock songs after listening to the genre — or a teacher or a journalist reviewing existing materials to draw new insights — learning is not infringing. It never has been, and it is not now. The timing of this lawsuit was somewhat surprising. When this lawsuit landed, Suno was, in fact, having productive discussions with a number of the RIAA's major record label members to find ways of expanding the pie for music together. We did so not because we had to, but because we believe that the music industry could help us lead this expansion of opportunity for everyone, rather than resisting it. Whether this lawsuit is the result of over-eager lawyers throwing their weight around, or a conscious strategy to gain leverage in our commercial discussions, we believe that this lawsuit is an unnecessary impediment to a larger and more valuable future for music. This is particularly the case because Suno is a new kind of musical instrument, one that enables a new kind of creative process for everyone and opens new business opportunities for the industry. Suno is designed for original music, and we prize originality, both in how we build our product and in how people use it. People who use Suno are using the product to create their own, original music. They are not trying to recreate an existing song that can be heard somewhere else on the internet for free. But, even if they were trying to copy existing music, we have myriad controls in place to encourage originality and prevent duplicative use cases. We do so more aggressively than any other company in the industry, including other startups. Some of our originality-guarding features include checking for and preventing copyrighted content in audio uploads, and disallowing artist-based descriptions in requests to generate music. Why do we work to encourage originality? We do this because it makes for a more fun and engaging experience to create entirely original compositions on Suno. We do it because we think it makes Suno incredibly valuable to be a place where new musical talent can shine. AI allows anyone to realize the songs in their head, regardless of the money, equipment, or connections that they have. The future is an explosion of new artists that are creating music in new ways, building fan bases, finding new reasons to smile, and getting famous. We hope that the major record labels realize that we can build a stronger foundation

Comparing Traditional AI vs. Generative AI models shows that both are trained on large datasets. However, TA relies on rules and patterns, whereas Gen AI captures the essence of human-created content.