Ezra Sandzer-Bell’s Post

Ai audio search is definitely one of the more interesting use cases for musicians. Nice to see sample libraries like WAVS and Splice improving the experience for customers.

MiniMax Music is redefining music creation with an AI model that generates complete, studio-quality songs—including vocals and instrumentals—from text prompts or reference tracks. Unlike tools that produce only background music, MiniMax creates full compositions in seconds, enabling creators, brands, and developers to scale audio production without hiring composers or booking studios. 🔑 Key Advantages • Vocals + Instrumentals: Generate entire songs, not just loops. • Reference Track Learning: Upload a song to define style, mood, and genre—AI creates original music in that vein. • Lyrics Integration: Input custom lyrics—they become sung vocals in the final track. • Multi-Genre Support: Pop, rock, electronic, classical, lo-fi, and more. • API Integration: Developers can embed MiniMax into games, apps, CMS, or content pipelines. • Batch Processing: Generate dozens of variations for A/B testing or global campaigns. 🚀 Use Cases Marketing: Create branded jingles in hours, not weeks—cutting costs and speeding time-to-market. Film & TV: Prototype scene scores rapidly, aligning music with narrative beats. Game Development: Build adaptive soundtracks that respond to player actions. Podcasts: Generate custom intros/outros for every episode—no composer fees. Education: Teach music theory through hands-on AI experimentation. 📊 Industry Impact One agency reduced jingle production from 3 weeks to under 2 hours. A film composer scored 20 scenes in one day using AI prototypes. A podcast network eliminated $50K/year in music licensing. Game studios deploy real-time dynamic audio for immersive experiences. ✅ Best Practices ✔ Use clear, descriptive prompts: “upbeat synthwave with male vocals, retro vibe” ✔ For voice cloning: Use 5+ seconds of clean audio ✔ Test multiple reference tracks for emotional accuracy ✔ Combine with AI lyric generators for rapid songwriting ✔ Review outputs for brand and quality alignment 🛠️ Implementation Strategy Pilot on a Project: Test on a jingle, podcast intro, or ad. Train Teams: On prompt writing, reference selection, and refinement. Integrate API: Connect to CMS, DAM, or game engines. Standardize Workflows: Define prompt templates and quality checks. Monitor Trends: Stay updated on AI music ethics and regulations. MiniMax Music is more than a tool—it’s a creative multiplier. It empowers organizations to: Own their sonic brand Scale content without scaling costs Deliver personalized, emotionally resonant audio For CMOs, CTOs, and innovation leaders, this is how you win in the attention economy. How is your team using AI for audio creation? Share below. 👇 #MiniMaxMusic #AIMusic #AIComposition #TextToMusic Read the full article here: https://lnkd.in/dY3y9Rk3

AI music roundup: SoundPatrol, Suno Studio, SGAE study, UK concerns… We brought you news of Spotify’s new measure to tackle AI spam and impersonation yesterday. But it was a bumper day for other news relating to AI, music, the impact on creators and regulation of this fast-evolving space. Here’s a breakdown of the most interesting announcements. First, Universal Music Group and Sony Music Entertainment have come together to work with a research lab spawned from Stanford University. It’s called SoundPatrol, and has developed a “forensic AI model for audio-video fingerprinting” that it says will be able to “identify the influence of original human-created music in fully or partly AI-generated music content”. There’s a media-industry heavyweight involved in this too: SoundPatrol was co-founded by Michael Ovitz, co-founder of talent agency Creative Artists Agency and former president of The Walt Disney Company. “This is the first of-its-kind technology implemented to protect all copyright holders and creators of any type of intellectual property,” he said in a statement. UMG and Sony Music are collaborating with SoundPatrol, but another company they’re not so happy with – Suno – had some big news yesterday. It has launched its ‘generative audio workstation’ Suno Studio: a tool for musicians to generate stems (vocals, drums etc) to work with as audio and MIDI files. The launch comes three months after Suno acquired a startup called WavTool that had built a browser-based digital audio workstation (DAW). Suno Studio is also launching in the same week as the latest version of Suno’s model, v5, with both restricted to premium subscribers. 🔗 Read the full story via the link in the comment section...

🎶Rise to the Top of AI Music: Music is a universal language , yet its composition has traditionally been reserved for the technically skilled , those with years of training , and frequently costly equipment 🎹. What if you could generate an entire song 🎤, with vocals and instruments 🎧, simply by describing it? This is not some distant fantasy — it’s the reality Suno, a Cambridge startup that quickly became an AI superpower 🚀. 🎵From Simple Prompt to Full Symphony : Founded in Cambridge, Massachusetts 🇺🇸, Suno is an AI music generation startup that’s radically reshaping the creative landscape . The startup’s platform lets anyone craft original, studio-quality songs 🎶 just by inputting text prompts ✍️. Under the hood, Suno’s technology is a complex stew of deep learning 🤖 and music theory 🎼. This enables it to take a user’s text description — be it a mood 😌, a genre 🎷, or some lyrics 📝 — and produce a piece of music 🎧. Not a simple melody but a full-blown track, often with vocals 🎤, that’s royalty-free ✅ and ready to be used in all sorts of cool ways 💡. 💰Striking a Chord with Investors: Suno’s innovation has also not gone unnoticed 👀. The startup, which has amassed $125 million in a Series B funding round 💸, demonstrates solid backing from investors 💼. Key investors such as Lightspeed Venture Partners, Daniel Gross and Founder Collective 🌟 all saw the company’s potential to shake up a multi-billion dollar industry 💥. This major infusion of capital gives Suno the ability to scale its technology 📈, grow its team , and establish its market leadership 🏆. And it’s a strong vote of confidence from the industry in Suno’s vision: to make music creation accessible to all 🌐. 🎨 Composing the Future Suno’s ascent is not only that of a triumphant startup , but a preview of the future of creative expression ✨. By eliminating the technical production obstacles , Suno is fueling a generation of creators . • Now, Content Creators can create custom-fit, royalty-free background music 🎶 for their videos 🎥 and podcasts 🎙️ in seconds ⏱️. • App Developers and Game Designers 🎮 can craft dynamic soundtracks 🎵 that supercharge the experience ⚡, without tricky licensing 🧾. • Hobbyists / Aspiring Artists 🎤 - bring your musical ideas to life 💡 without having to play 🎹 or know music theory 📚! Suno occupies the space where tech meets art 🖼️🤖, demonstrating that AI can be a tool to enhance human creativity 🧠, not supplant it ❌. The company’s path — from a promising startup 🌱 to a well-funded industry leader 🏆 — demonstrates a crucial turning point 🔄 in the way we conceptualize, produce, and distribute music 🎶. 💬 How do you feel about AI’s increasing presence in creative domains such as music? Give your thoughts below👇! Entrepreneurship Development Cell of Heritage Institute of Technology Kolkata x E-Cell, IIT Bombay #Suno #AIMusic #StartupSuccess #TechInnovation #FutureOfMusic #ecell_iitb #edic #nec2025 #ecellineverycollege

Lyria 2 is redefining music creation with an AI model that generates complete, studio-quality songs—including vocals and instrumentals—from text prompts or reference tracks. Unlike tools that produce only background music, Lyria 2 creates full compositions in seconds, enabling creators, brands, and developers to scale audio production without hiring composers or booking studios. 🔑 Key Advantages • Vocals + Instrumentals: Generate entire songs, not just loops. • Reference Track Learning: Upload a song to define style, mood, and genre—AI creates original music in that vein. • Lyrics Integration: Input custom lyrics—they become sung vocals in the final track. • Multi-Genre Support: Pop, rock, electronic, classical, lo-fi, and more. • API Integration: Developers can embed Lyria into games, apps, CMS, or content pipelines. • Batch Processing: Generate dozens of variations for A/B testing or global campaigns. 🚀 Use Cases Marketing: Create branded jingles in hours, not weeks—cutting costs and speeding time-to-market. Film & TV: Prototype scene scores rapidly, aligning music with narrative beats. Game Development: Build adaptive soundtracks that respond to player actions. Podcasts: Generate custom intros/outros for every episode—no composer fees. Education: Teach music theory through hands-on AI experimentation. 📊 Industry Impact One agency reduced jingle production from 3 weeks to under 2 hours. A film composer scored 20 scenes in one day using AI prototypes. A podcast network eliminated $50K/year in music licensing. Game studios deploy real-time dynamic audio for immersive experiences. ✅ Best Practices ✔ Use clear, descriptive prompts: “upbeat synthwave with male vocals, retro vibe” ✔ For voice cloning: Use 5+ seconds of clean audio ✔ Test multiple reference tracks for emotional accuracy ✔ Combine with AI lyric generators for rapid songwriting ✔ Review outputs for brand and quality alignment 🛠️ Implementation Strategy Pilot on a Project: Test on a jingle, podcast intro, or ad. Train Teams: On prompt writing, reference selection, and refinement. Integrate API: Connect to CMS, DAM, or game engines. Standardize Workflows: Define prompt templates and quality checks. Monitor Trends: Stay updated on AI music ethics and regulations. Lyria 2 is more than a tool—it’s a creative multiplier. It empowers organizations to: Own their sonic brand Scale content without scaling costs Deliver personalized, emotionally resonant audio For CMOs, CTOs, and innovation leaders, this is how you win in the attention economy. How is your team using AI for audio creation? Share below. 👇 #Lyria2 #AIMusic #AIComposition Read the full article here: https://lnkd.in/dR9ifyuZ

Auto-Tune broke and reshaped a $30B music industry model. AI dev tools are doing the same to software. Here's how founders can win: As I'm very close to the music/entertainment industry, I couldn't help but compare a similar trend taking place in the startup and VC space. It's what I'll call the "great democratization of software". Let's have a look at history: Back in the day, if you had a beautiful singing voice, you were royalty. That was your moat. From the 60s to early 2000s, the music game rewarded raw vocal talent because distribution was limited, studio access was expensive, and beautiful voices were rare to hear. Having a voice like Celine Dion, Whitney Houston or Marvin Gaye? You were untouchable. But then came Auto-Tune. Cher's "Believe" in 1998 introduced it to the masses. T-Pain didn't just use it, he made it his signature, then mainstream. Suddenly every artist started using it because listener's ears were now used to it! The game changed completely. What separates artists today isn't just their voice anymore. It's their unique brand, fan bases, background stories, virality, numbers. They have taste, brand, community and distribution. Now let's look at software today. For decades, if you could code, you were royalty. That was your moat. But today? Tools like Lovable, Replit, Cursor etc are becoming the Auto-Tune of software: – Want to build an app? → There's a co-pilot – Want to write production code? → There's an AI pair – Want to ship faster? → Just prompt it This is the great democratization of software. The lesson from history? Whenever there's democratization of tools, what separates winners is community, brand, distribution and taste. Look at cars... They're literally pieces of metal shaped differently (taste) that move you from A to Z, but it's the features, distribution, brand story, and design that create value. Same pattern. Every time. From what I’m seeing, here are 3 insights I believe founders can’t afford to ignore right now: 1. Taste is the new moat Having access to the tools isn't enough. Product taste, user experience intuition, and creative vision become your differentiators. 2. Distribution and community matter more than ever It's not just about building something great, it's about having raving fans, building community, and mastering distribution. 3. This is the Age of the Builder When development becomes accessible to everyone, we unlock more innovation and possibility for creators who were previously locked out. By the way, this isn’t the end of developers. It’s evolution. Augmentation. Empowerment. The same way Auto-Tune didn’t kill music. It created new genres, new stars, and new styles! AI dev tools are creating new builders, new creativity, and new leverage. #GenerativeAI #NoCode #FutureOfWork #TechTrends #MusicIndustry #Startups #VentureCapital #DevTools #Autotune

The Future of Music: Consumption or Participation?  For more than a century, the music industry has been built on a simple formula: Artist creates → Listener consumes. But let's take a look at what’s happening today: - TikTok sounds are reinterpreted a million different ways. - Fans remixing tracks into new genres overnight. - Gamers customizing soundtracks to match their play. Lasts year Mark Mulligan (Midia Research) published his thoughts around the Bifurcation Theory and like he envisioned, we have been witnessing the shift from (passive) listening to (co-)creation as form of entertainment. Are we ready for this shift, as an industry? Listeners don’t just want to hear music anymore. They want to play with it. Remix it. Make it their own. And yet, our industry is still operating with rules written for the vinyl era. Copyright frameworks assume music is a finished product to be protected — not raw material for a new generation of creators. This tension is potentially one of the most pressing issues we face. Because instead of unlocking creativity, outdated structures risk stifling it. What if we stopped seeing remixes, stems, and fan participation as threats — and started treating them as opportunities? Artists could benefit from new revenue streams if remix culture was licensed, tracked, and monetized properly. Fans could feel a deeper connection by moving from passive listeners to active participants in the creative process. Rights holders could unlock value in every new version of a track, rather than chasing take-down notices. Interactive music — built from stems and adaptable by design — could be the bridge. It allows fans to explore, reinterpret, and personalize songs while still respecting ownership and rewarding the original creators. Of course it’s important to recognise that while participation is on the rise, traditional “lean-back” listening - whether radio, curated playlists, or background streams - still commands huge audiences and revenues. But the generational trendline is super clear: younger listeners are moving from passive consumption toward active co-creation, and that shift will only accelerate as platforms, tools, and cultural expectations evolve. If the industry can build frameworks that protect ownership while empowering interaction, we’ll stop treating music as static content — and start treating it as a living, evolving cultural experience. And here’s the upside: the next wave of growth won’t come from more streams. It will come from streams of new interpretations of existing artworks. Is the future of music not passive consumption — but rather active lean in participation? What do you think?

Let us introduce you to our Technical Partnership for Legally-Compliant Music AI with aurismatic GmbH What are we working on? 1. Cover detection that sees what others miss When someone submits a recording to CORPUS — for example, a guitar cover of Let It Be — it's critical to identify that this is not an original composition, but a reinterpretation of an existing work. Standard detection methods compare new recordings to known reference tracks. If no such reference exists — as is often the case with unpublished or private covers — these systems fail. Aurismatic is developing a new cover detection system for CORPUS, based on their proprietary technology already used to automatically generate setlists for GEMA reporting at live concerts. This allows us to reliably detect covers even when no prior recording is available — a key step toward building a legally clean dataset. 2. Music protection from misuse in AI APIs Many musicians use services like automated mastering or tagging. These typically require uploading full audio files to central platforms — with little insight into how that data is handled. The incentive to repurpose these recordings for AI training is high, for example, by creating synthetic datasets derived from real songs. These synthetic versions may appear legally safer, giving the illusion that the rights of original creators are not being violated — even though they are often built directly from their work. CORPUS takes a different approach: Aurismatic is building an API interface that transfers only abstract audio embeddings, not the original recordings. This effectively eliminates the opportunity for data extraction or misuse. Technology in service of a fair music ecosystem. Together with Aurismatic, we’re laying the groundwork for transparent, legally-sound, and sustainable use of music in AI in the interest of everyone who creates it. If you want to know more about our work, please feel free to reach out!

🌍 Together with CORPUS, we’re building a legally sound future for music & AI: 1️⃣ Smarter cover detection – recognizing even unpublished reinterpretations. 2️⃣ Fair AI APIs – sharing only audio embeddings, never raw files. 🎶 Our mission: a transparent, sustainable, and fair music ecosystem for all creators. 👉 Check the original post for details – we’d love to hear your thoughts!

Suno - one of the leaders in GenAI music creation tools - has recently presented Suno Studio: a DAW-lookalike web-based application that allows dissecting generated audio to separate instrument tracks and transform audio into MIDI. For quite some time in parallel, they're doing an advertisement campaign targeting musicians: look how easy and nice it is to use AI tools in your production (it actually is btw). There are two thoughts I have about that. First: the pace of improvements in quality of text-to-music genAI is slowing down. We're getting better, but not as dramatically, as it was two-three years ago. Quality of the generated content is still not production-ready - though, it is quite usable in "upcycling-based" genres like hip-hop or electronic dance music. It is very entertaining, btw. Second: the pivot in target audience is obvious. Suno switched from "anyone can make music" to targeting musicians - which, I suppose, is somewhat dramatic reduction in potential TA. It seems it turned out that - surprise surprise - making music is only interesting for those who already do it. I might imagine similar things must happen to AI vibecoding. Anyone can make music, or code, or draw. But who are those who actually WILL? And was ease/speed of implementation ever a problem for those already driven by internal will?