AudioVerse Lab is a Music Tech Innovation Club at Berklee College of Music that explores and promotes the intersection of artificial intelligence, new music tech, and music. We foster creativity, collaboration, and innovation among students. Our club provides a supportive environment for students to learn about AI technologies, VR, AR, blockchain, and apply them to music composition, performance, production, and analysis.
Boston, MA 02118, US
AudioVerse Lab reposted this
FINALLY!! OpenAI just rolled out their new Advanced Voice model, and it's very...very impressive. It’s packed with exciting updates like custom instructions, memory, five new voices, improved accents, and more. Check out the live demo: #openai #voicemodel #ai
AudioVerse Lab reposted this
What is the key element to thriving with GenAI platforms? If you guessed prompts, you’re absolutely right! Streamly attended three sessions where prompt experts shared their top tips and tricks for getting the best results when using GenAI as a creative tool. First up, let's hear from @Amal Irgashev, Generative AI Engineer & Founder of AudioVerse Lab, who specialises in music production http://spr.ly/6042W8DMG #GenAI #AIInnovation #PromptEngineering #CreativeTech #MusicTech
AudioVerse Lab reposted this
A Beginner’s Roadmap to AI Engineering 🚀📚 When I first started in the generative AI space, I began with no-code tools like Zapier ,Make , Bubble, and Retool which allowed me to automate tasks and build simple AI apps and workflows. As my confidence grew, I transitioned into more advanced frameworks, diving deep into AI engineering. It wasn't an easy journey, but the results were worth it! If you're interested in a structured path, the "Roadmap to Becoming an AI Engineer" (by Harshit Tyagi) is a fantastic guide. It outlines the journey from a beginner to an advanced AI engineer, covering key tools and skills at each stage: Beginner (1 month): Learn the basics of APIs, prompt engineering, and chains of operations with tools like OpenAI APIs, LangChain, and HuggingFace. Intermediate (2 months): Dive into context-aware applications and start working with vector databases, building and deploying basic RAG (Retrieval-Augmented Generation) apps. Advanced (3 months): Excel at building advanced applications and fine-tuning models for specific use cases, incorporating LLMOps, multi-modal applications, and AI security. Here are some additional resources that helped me transition from beginner to more advanced AI projects: 📚 AI Agents in LangGraph - DeepLearning.AI 📚 AI Python for Beginners - DeepLearning.AI 📚 Intro to AI Engineering - Scrimba 📚 Dave Ebbelaar - Youtube 📚 Data-Centric - Youtube Channel 📚 VRSEN - YouTube Channel Start small, stay curious, and progressively build your expertise by following this roadmap. It's a challenging but rewarding path that can lead to exciting opportunities in AI.
AudioVerse Lab reposted this
The inaugural AES International Symposium on AI and the Musician will highlight exciting capabilities and dissect ethical challenges AI technology poses.
If you missed our panel discussion on the legal implications of AI in music with experts Kevin Casini and Ash Kernen, Esq. you have another chance to catch up! Check out our article for key insights and strategies discussed during the panel:
📣Legal Aspects of AI panel this Friday! #audioverselab #musiclaw #ai #copyright
Join us for an insightful panel ‘Legal Aspects of AI’ focusing on protecting your intellectual property and mastering ethical AI use. Featuring dynamic speakers: IP & Entertainment Lawyer Ash Kernen, Esq. and a Music Lawyer, Law Professor Kevin Casini. ⚡️Don’t miss out this Friday at 4:30 pm at the Immersive Technology Lab! #audioverselab #aicopyright #musiclaw
AudioVerse Lab reposted this
It's time for artists and rights holders to get in the game! I commend artists taking action by going the legal rout to protect their rights against the onslaught of generative AI companies training on their data. The issue at hand is a metadata issue. Since the dawn of the Napster age, digital music has had no digital provenance. No digital ID. Attribution is an afterthought on platforms. As its not their core business to care if the data is properly tagged. Industry rights-holders and distributor/aggregators have largely contributed to this paradigm by 1. Not publishing an open database containing all metadata about music IP (splits, contact payment info, terms of usage, etc.) and 2. Not prioritizing the importance that metadata information is publicly required for any music IP to exist on the internet. Machines can read this information. This would then make it possible for anyone training AI models on music to have to abide by those rules or else they would be clearly choosing to commit a criminally liable act. So to my original point if you're an artist or rights holder, get in the game and make sure all of your metadata is up to date and open sourced. That's what we did with Grimes and then we built a way for an AI model to be built on top of her metadata and remunerate her when people use her music IP in their creations. The next way to get in the game is to cold-call/email/DM any of these generative AI companies and let them know you want to collaborate. Writing letters leaves it in the hands of lawyers vs. creators. https://lnkd.in/g3N7aMQC
Join us for an electrifying session delving into Tools for a New Music Industry, where Daouda Leonard, the dynamic co-founder & CEO of CreateSafe, unveils how AI is supporting music creation, distribution, and management. Get ready to be captivated on Friday, April 5th, from 5:00 pm to 6:00 pm at the Immersive Technology Lab! #CJ2024 , #Createsafe , #AudioVerseLab
Comment “change” to receive a link to the article⬇️ #ai #audioverse #berkleecollegeofmusic #series