🥁AI Music Controversy Explodes

Major labels sue AI song generators Suno and Udio for copyright infringement

Key Points 

• Major record labels have sued Suno and Udio, accusing them of copyright infringement for using artists' works without permission. 

• The lawsuits, led by RIAA seek damages up to $150,000 per infringed work, alongside other expenses.

• RIAA's complaints cite specific instances where Suno and Udio produced songs resembling copyrighted tracks like Chuck Berry's "Johnny B. Goode" and ABBA's "Dancing Queen." 

♨️News - Major record labels, including Universal Music Group (UMG), Sony Music Entertainment, and Warner Records, have filed lawsuits against Suno and Udio — two leading companies in generative AI music creation. The labels claim that these companies have violated copyright laws by using artists' work from various genres and eras without consent.

The lawsuits, initiated by the Recording Industry Association of America (RIAA) and a consortium of labels, seek damages of up to $150,000 per infringed work, in addition to other costs.

In its complaints, the RIAA provided examples of songs generated by Suno and Udio that resemble those owned by the labels. One example is Suno's "Deep down in Louisiana close to New Orle" [sic], which mimics the lyrics and style of Chuck Berry's "Johnny B. Goode." Another example is "Prancing Queen," created with a "70s pop" prompt, which includes lyrics from ABBA's "Dancing Queen" and sounds very similar to the original.

🪇What's more? The plaintiffs allege that when they accused Suno of using copyrighted works, the company deflected by claiming its training data was "confidential business information." Udio made similar assertions. According to Mitch Glazier, RIAA's chairman and CEO, while the music industry collaborates with responsible AI developers, unlicensed services like Suno and Udio undermine the potential of genuinely innovative AI by copying artists' work without consent or payment.

After the news of the lawsuits broke, Suno AI's CEO, Mikey Shulman, countered that their technology is designed to generate new outputs and doesn't allow users to reference specific artists. Udio has not yet commented on the issue.

Tech giants back new telecom network set to slash AI's energy use

Key Points 

• Leading tech giants such as Microsoft, Google, Intel, and Sony are backing a new telecommunications network aimed at cutting energy consumption in AI applications.

• The initiative involves collaboration among cloud providers, telecom firms, and chipmakers to establish "all-photonic" networks (APN) by 2030.

• These networks use light instead of electrical signals for data transmission, promising significant energy savings globally.

• By decentralizing data centers and enabling AI development in smaller, distributed locations, photonic networks would alleviate pressure on current telecom networks and support sustainable data center operations.

⚡News - Major tech firms including Microsoft, Google, Intel, and Sony are supporting a new telecommunications network aimed at reducing the energy consumption of data-hungry AI applications and accelerating the rollout of 6G mobile internet. 

This initiative, known as the IOWN Global Forum, involves collaboration among cloud providers, telecom companies, and semiconductor manufacturers. Their collective goal is to achieve a fully operational "all-photonic" network (APN) by 2030.

🔖For context - 

• Photonic networks rely on light rather than electrical signals to transmit data, resulting in significantly lower energy consumption for global data transmission.

• The IOWN Global Forum is a global group focused on establishing technical standards for all-photonics networks.

🔅How exactly will it help reduce AI energy consumption? The goal is to ease pressure on current telecom networks, expected to intensify with increasing adoption and demand for AI, especially generative AI. Masahisa Kawashima, IOWN technology director at NTT Corporation, explained how photonic networks can help achieve that.

Kawashima pointed out that traditional data centers, especially large hyperscale ones, pose challenges for society's carbon reduction goals due to their concentrated energy demands in small areas. He noted that implementing IOWN APNs allows data centers to be distributed over larger areas.

He emphasized that each data center within this network, even medium-sized ones, can operate effectively like a hyperscale data center. This setup enables AI developers to utilize shared GPU infrastructure in smaller, distributed locations for developing AI models. Thus, photonic networks would not only support efficient data transmission but also facilitate a more sustainable approach to data center operations.