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More Practical AI Strategies: Designing
More Practical AI Strategies: Designing
Educators continue to grapple with the ethical and practical implications of Generative AI, but it has proven valuable in enhancing teaching methods and student engagement. LLMs like ChatGPT can ai…
·leonfurze.com·
More Practical AI Strategies: Designing
The “Deepfake Defense”: An Evidentiary Conundrum
The “Deepfake Defense”: An Evidentiary Conundrum
Judge Dixon discusses the struggle to determine the appropriate considerations when the opposition claims evidence is a deepfake—a video or audio created or manipulated using artificial intelligence.
·americanbar.org·
The “Deepfake Defense”: An Evidentiary Conundrum
AI Risk Repository
AI Risk Repository
A comprehensive living database of over 700 AI risks categorized by their cause and risk domain.
·airisk.mit.edu·
AI Risk Repository
GraphCast: AI model for faster and more accurate global weather forecasting
GraphCast: AI model for faster and more accurate global weather forecasting
Our state-of-the-art model delivers 10-day weather predictions at unprecedented accuracy in under one minute
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.
·deepmind.google·
GraphCast: AI model for faster and more accurate global weather forecasting
The Adoption of ChatGPT | BFI
The Adoption of ChatGPT | BFI
Recent research from UChicago economists has revealed that the AI chatbot ChatGPT can excel at investing tasks including predicting corporate investment policies, processing dense corporate disclosures, and detecting corporate risk. Beyond investing, experts predict that ChatGPT will disrupt many high-skilled occupations, including journalism, IT support, human resources, and marketing. In this paper, the authors study Read more...
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.
·bfi.uchicago.edu·
The Adoption of ChatGPT | BFI
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…
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…
— Suno (@suno_ai_)
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
·x.com·
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…
How to spot deepfakes created by AI image generators
How to spot deepfakes created by AI image generators
The 2024 election brings opportunities for dangerous misinformation fueled by a new wave of AI-powered image generators. Train yourself on how to spot these images and be more aware of common misinformation techniques.
·axios.com·
How to spot deepfakes created by AI image generators
Generative AI vs. Traditional AI: Understand Key Differences
Generative AI vs. Traditional AI: Understand Key Differences
Artificial Intelligence (AI) has transformed various sectors, reshaping how people interact with technology. It has undergone a significant…
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.
·medium.com·
Generative AI vs. Traditional AI: Understand Key Differences
Fully-automatic robot dentist performs world's first human procedure
Fully-automatic robot dentist performs world's first human procedure
Nightmare fuel? Maybe – but in a historic moment for the dental profession, an AI-controlled autonomous robot has performed an entire procedure on a human patient for the first time, about eight times faster than a human dentist could do it.
·newatlas.com·
Fully-automatic robot dentist performs world's first human procedure