Neil Lee @phycause

『法務省はＡＩによる声や肖像の無断生成に対する民事上の責任について考える有識者検討会の次回会合（２８日）で、サービス提供の違法性について議論する。』 「雇うより安価」と著名人の声をＡＩで無断生成、「フリー素材のように使うのは問題」と声優憤り yomiuri.co.jp/national/20260…

【生成AIで津田健次郎さん模倣 提訴】 news.yahoo.co.jp/pickup/6581302

This is huge and welcome news in the world of AI music. Two of the biggest music distributors are banning music from Suno and other AI music companies they call "pirate studios". They will allow AI music that comes from products that license training data, but not from products that don't. (These distributors are what you use to get your music on Spotify etc.) Believe's CEO said he doesn't understand why other distributors aren't doing the same. "Anyone distributing copyright-infringing content is liable for copyright infringement [action]." Some will want them to ban all AI music, and I understand that. But their ban of what they call "pirate studios" sends a clear & important message: AI companies must license the training data they use. musicbusinessworldwide.com/believe-and-tu…

歌手などの顔や声をＡＩで無断生成、権利の侵害を明確化…法務省が議論始める : 読売新聞 yomiuri.co.jp/national/20260… #NOMORE無断生成AI

ＡＩ法で事業者に罰則検討を…著作権侵害やディープフェイク被害相次ぎ、自民が提言案(読売新聞オンライン) #Yahooニュース news.yahoo.co.jp/articles/d1d0b… ”ディープフェイクの被害や著作権侵害が顕在化している」（略）「罰則を含めたより実効性ある適切な方策を検討」するように求めた” よっしゃあ!!!!!

Turn any audio sample into a time-stretched intersecting instrument instantly

Library for object detection and segmentation github.com/facebookresear…

The godmother of AI just delivered the reality check Silicon Valley refuses to hear. She has the standing to say it. Li: “Silicon Valley as a whole tends to mistake clear vision with short distance.” Seeing the destination clearly has nothing to do with how hard it is to reach. Self-driving cars were first demonstrated in 2006. Twenty years later Waymo is barely on the road. The vision was never the problem. The distance was. Clarity of destination gets mistaken for proximity to arrival. That’s the mistake the industry keeps making. And keeps making. Li: “I consider myself a scientist in my heart and I actually really don’t like hyping.” In an industry running at maximum temperature, Fei-Fei Li is one of the few people at the top willing to say that publicly. Not because the technology isn’t real. Because the gap between what’s visible and what’s required is being systematically underestimated. Large Language Models dominate the conversation. Text to text. Comparatively contained. The harder problem is spatial intelligence. AI that reasons about and acts within the physical three-dimensional world. Hardware. Physics. Data that doesn’t exist yet. Real-time adaptation to chaos. A robot that can clean a bathroom requires understanding every surface, every object, every force, every exception. That’s not a software update. That’s a civilizational research problem. Li: “I don’t call it hype. I call it a misleading sentiment. We don’t want to replace human creators.” The second place the industry gets it wrong is creativity. The narrative has hardened around replacement. AI takes the jobs. AI tells the stories. AI makes the art. Li considers that not just wrong but destructive. Wrong because AI doesn’t replicate creativity. Destructive because believing it can devalues the humans creating culture. Human creativity isn’t a process to be automated. It’s fundamental to what we are as a species. The goal is augmentation. Tools that make human creators faster and more capable. Not systems that generate output in the style of human work and call it creation. That distinction matters more than most people in the industry are willing to sit with. Precision of imagination is not proximity to reality. Li has spent her career in the gap between those two things. The map isn’t the territory. The journey is long. The hurdles are deep. And the scientist who built the foundation this era stands on is telling you the timeline everyone is selling is wrong. We’ve been almost there with self-driving for twenty years. The pattern doesn’t change just because the destination looks different.

ソニーG、作曲AIの学習データを特定　創作者への対価算出可能に nikkei.com/article/DGXZQO…

動画生成AIサービスに関して

Excited to announce our ICASSP 2026 paper "Stemphonic: All-at-once Flexible Multi-stem Music Generation" ! w/ @__gzhu__, @j_p_caceres, @huangcza, and @NicholasJBryan 🔊Demo stemphonic-demo.vercel.app 📰Paper arxiv.org/abs/2602.09891 More details in🧵

This is great news. The Supreme Court has for now blocked Trump from firing Shira Perlmutter, the head of the US Copyright Office. Just before she was fired, Perlmutter's office issued a report saying it was unlikely all generative AI training would be considered fair use. newrepublic.com/post/203753/do…

集英社は単独で別途声明を出しています。 生成ＡＩを利用した権利侵害への対応について shueisha.co.jp/wp-content/upl…

ペンギン @penpenguin2023

7 months ago

講談社や小学館など出版社17社と2協会が「生成AI時代の創作と権利のあり方に関する共同声明」を発表。 kodansha.co.jp/notices/672 『権利者がAI事業者へオプトアウトを申請するのではなく、AI事業者が権利者に対してオプトインを申請し使用許諾を得ることの徹底が、いま一度求められます。』

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講談社や小学館など出版社17社と2協会が「生成AI時代の創作と権利のあり方に関する共同声明」を発表。 kodansha.co.jp/notices/672 『権利者がAI事業者へオプトアウトを申請するのではなく、AI事業者が権利者に対してオプトインを申請し使用許諾を得ることの徹底が、いま一度求められます。』

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Very pleased to see this partnership between Universal Music and Stability AI. Stable Audio was trained on licensed datasets from day one. It's great to see that evolve into this news today. Training on licensed datasets is the way. Onwards. stability.ai/news/universal…

@henrythe9ths FUNDRAISE

I got rejected by 144 investors before raising $150M for my $200M+ rev/year startup. After 144 rejections, I started questioning our approach. Were we solving the right problem? What were we doing wrong? Why weren’t investors seeing what we were seeing? Were we the right team to build this? We tried everything: different pitch angles, new deck structures, and reframing the problem. Then came the 145th meeting, where we closed our first growth round. That yes made everything worth it. But getting there took years of mistakes and hard work. We went through a lot of trial and error just to figure out what resonates with investors. We tried dozens of approaches to figure out what made investors engage. Some landed, most didn't. But each iteration taught us something about what builds conviction versus what just sounds good on paper. And once we cracked that code, our Series C closed faster than expected. And today, I see so many founders in the exact same position I was in 10 years ago: grinding through rejections, questioning everything, and trying to figure out what works. So today I want to give you the resource I wish I had back then: Something that shows you exactly how to structure these conversations and navigate the entire process (because the fundraising cycle can be a big distraction and take a toll on you as a founder). So I've partnered with Notion's Startups Team to create the essential fundraising resource that helps you avoid the mistakes that cost me years. Here's what you are getting: • The actual decks I used to raise $150M for Super[.]com (Series B, C) • 50 real examples from funded startups like Eleven Labs and Artisan AI • A searchable database of 10,000+ investors - angels, VCs, and accelerators you can reach out to immediately (this alone would take months to build manually) • An AI-powered fundraising agent built into Notion with step-by-step prompts (no separate ChatGPT needed) Want access? • Like and share this post • Comment "FUNDRAISE" • Follow me so I can DM you the link I'll send it over ASAP. P.S.: If you are serious about fundraising (now or in the future), you should grab it right away.

A big tech lobbying group has asked Trump to issue an Executive Order telling the DOJ to intervene in AI copyright lawsuits in favor of AI companies. Astonishingly brazen request. Though IMO suggests AI companies are v worried they will lose in court. progresschamber.org/resources/whit…

So that's why Perplexity, Canva and a bunch of other services aren't working... AWS US-EAST-1 is down. 😅 #AWS #Canva #Perplexity

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Eminem sampled Aerosmith, 50 Cent sampled Nina Simone, everybody sampled Chic... Many great songs sampled existing ones! Detecting this is the topic of our latest paper with @serrjoa at @SonyAI Barcelona 😎 tl;dr: multi-track dataset + few tricks = +18% boost over SOTA 🚀 1/N