In a letter to streamers including Spotify and Apple Music, the record label Universal Music Group expressed fears that AI labs would scrape millions of tracks to use as training data for their models and copycat versions of pop stars. UMG instructed the platforms to block those downloads, saying it would "not hesitate to take steps to protect our rights and those of our artists". The letter, first reported by the Financial Times, comes after a similar move from the Recording Industry Association of America, the industry's trade body, last October. Writing to the US trade representative, the RIAA said that AI-based technology was able "to be very similar to or almost as good as reference tracks by selected, well known sound recording artists". The group added: "To the extent these services, or their partners, are training their AI models using our members' music, that use is unauthorised and infringes our members' rights by making unauthorised copies of our members works."

AI has been making steady progress over the last decade owing to advances in computing and better access to quality data sets. More recently, however, OpenAI's ChatGPT chatbot model has captured the public's attention with its ability to answer, augment and automate across a wide range of knowledge-based functions. While far from foolproof, the model has been known to pass qualifying exams in several fields and could be a clarion call for how education, and society more broadly, must prepare for a new wave of disruptive innovation. Knowledge workers are not the only ones who have taken notice. DALL-E, the artistic form of OpenAI, has also made waves with its creative expression in poetry and imagery.

Generative AI has picked up incredible momentum in the last few months. Hype is now becoming reality, with companies of all sizes, in all industries, embracing GPT and other large language models (LLMs) to enhance business operations and customer offerings. We are seeing first-hand how this technology can truly transform organisations, and the relationship between human and machine. At the same time, we are in the defining'decade of data' – a period marked by the fundamental shifts in power created by the intersection of technology and data and the impact this has in every facet of our lives. In today's landscape, a company's data can be two or three times more valuable than the company itself.

Students at the University of Texas at Austin tell Fox News whether they know or have heard of fellow students using ChatGPT to complete class assignments. AUSTIN, Texas – A majority of college students who spoke with Fox News said they knew or had heard of fellow pupils using ChatGPT for class assignments. "Unfortunately, yes," Riley, an economics major, told Fox News. "I definitely have heard of a couple of people using it for certain things," Piper, a STEM major, said. Recent advances in artificial intelligence technologies, including ChatGPT and Google's Bard, have ignited plagiarism concerns across American schools.

If educators actively engage with students about the technology's capabilities and limitations--and work with them to define new academic standards--ChatGPT, and generative AI more broadly, could both democratize and revitalize K–12 education on an unprecedented scale. A bold claim, I know. Few things are as mentally draining as applying to college these days, and as I slaved away at my supplemental essays, the promise of using ChatGPT as a real-time editor was attractive--partly as a potential productivity boost, but mostly as a distraction. I had ChatGPT carefully review my cloying use of semicolons, grade my writing on a 0–10 scale (the results were erratic and maddening)2, and even role-play as an admissions counselor. Its advice was fundamentally incompatible with the creative demands of the modern college essay, and I mostly ignored it.

OpenAIが、Consistency Models の実装をリリースしました。Consistency ModelsとはConsistency Modelsの論文の概要では次のように説明されています。「拡散モデルは画像、音声、動画生成におい

Is it worth training your own large language model (LLM) on domain-specific data from scratch? Researchers at Bloomberg did just that and shared a detailed technical report describing the dataset, model configuration, and training procedure. The core question is, is it worth training the LLM from scratch? In my experience, it makes total sense if we want to apply LLMs to novel data sources (e.g., protein amino acid sequences as ProtBERT demonstrated). BloombergGPT is a 50-billion parameter language model for finance, trained on 363 billion tokens from finance data and 345 billion tokens from a general dataset.

There are already over 50 different 1B+ parametersLLMs accessible via open-source checkpoints or proprietary APIs. That’s not counting any private models or models with academic papers but no available API or model weights. There’s even more if you count fine-tuned models like Alpaca or InstructGPT. A list of the ones I know about (this is an evolving document). GPT-J (6B) (EleutherAI) GPT-Neo (1.3B, 2.7B, 20B) (EleutherAI) Pythia (1B, 1.4B, 2.8B, 6.9B, 12B) Polyglot (1.3B, 3.8B, 5.8B) J1 (

いろいろと便利に使えると話題のChatGPTですが、基本OpenAIのウェブサイトから使う仕様なのに機能が少なくて使いやすいとは言えなかったりします。この記事ではそんなChatGPTの弱点を改善するChrome拡張を紹介します。Glarity-Summary for Google/YouTube (ChatGPT)Glarity-Summary for Google/YouTube (ChatG

Welcome to the world of ChatGPT, If you're new to ChatGPT, prompts are your trusty sidekicks, enabling you to communicate with this AI language model. They play a crucial role in getting meaningful responses and unlocking the true potential of ChatGPT. So what are ChatGPT prompts exactly? ChatGPT prompts are a way to interact with the AI model by giving it specific instructions or questions. They come in different classes, including question, statement, and opinion prompts. They are useful for various purposes, such as content creation, customer service, and education. Let's break it down, shall we? Think of prompts as conversation starters or cues.