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Meta Launches Tool To Create Music Using AI

Also: People are becoming more robotic — and AI could make it worse

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In AI news, Meta has launched AudioCraft, an AI-driven tool facilitating music creation using text inputs, available to all Facebook users. Meanwhile, as AI's transformative value gains recognition, the focus shifts towards applications like generative AI, which are predicted to drive significant economic benefits and rapid technology adoption. Concurrently, the escalating demand for AI is fueling fast growth in AI-ready data centers, optimally designed for compute-intensive AI workloads. However, the proliferation of AI and automation has sparked concerns about the blurring line between humans and machines, with AI potentially exacerbating this trend. In product news, Tinder is testing an AI photo selection feature to assist users in building profiles, pointing to future applications of generative AI. Finally, in investment news, AI chip startup Tenstorrent has raised $100 million in strategic financing, underscoring investor interest in AI and its underpinning infrastructure.

Sliced:

  • 🎹 Meta Launches Tool To Create Music Using AI

  • 🦾 AI Has Finally Become Transformative

  • 🏢 AI-Ready Data Centers Are Poised for Fast Growth

  • 🤖 People are becoming more robotic — and AI could make it worse

Meta has unveiled AudioCraft, an AI-powered tool designed to simplify the creation of music and sounds from text-based inputs. The new tool is a blend of three AI models: MusicGen, for creating music from text, AudioGen, for generating sounds like footsteps or barking dogs, and an improved version of EnCodec for enhancing the perceived quality of the sounds and music generated. The goal of AudioCraft, which is open-source and available to all Facebook users, is to democratize generative AI for audio. However, the use of AI in music has sparked debate about potential copyright infringement, with artists having divergent views on the issue.

AI despite generating considerable value in multiple applications over the last decade, has largely benefited tech giants like Google and Facebook rather than creating a new class of market-transforming companies, akin to the internet or mobile revolution. The value extracted from AI diminishes over time, requiring substantial continuous investment, which has made it challenging for startups to sustain growth. Previous AI startups often spiraled into mediocrity by relying too much on human input due to early AI limitations. However, a shift is anticipated with the advent of generative AI applications like ChatGPT and foundation models like GPT-4. These applications can significantly improve time, cost, and performance, leading to rapid technology and product adoption. Generative AI is also enabling previously impossible uses, from companionship to therapeutic art communities.

The surge in demand for AI applications is stimulating a burgeoning market for data centers specifically designed to handle AI's compute-intensive workloads. Some emerging companies, like CoreWeave, are seizing the opportunity to build new facilities from scratch that are optimized with advanced chips for AI tasks. These purpose-built AI data centers not only run multiple computations simultaneously but also provide efficient storage to support AI models at scale. CoreWeave, which already operates seven AI data centers, recently secured a $2.3 billion debt facility to expedite the construction of more AI-ready data centers. Industry analysts predict a global AI infrastructure market worth $422.55 billion by 2029, driven largely by data centers and related hardware. However, AI data centers require significantly more power and advanced cooling systems than conventional ones, indicating increased infrastructure needs and potential challenges.

As AI and automation technology continue to advance, humans are becoming more machine-like, adapting to the needs of AI and automated systems in workplaces, often under heightened surveillance and monitoring. Optimists argue that AI can free humans from menial tasks, allowing them to be more human, however, current trends suggest the opposite, with humans becoming a cog in the machine. From AI chatbots populating social media platforms, to people behaving like bots for entertainment on TikTok, the line between human and machine is blurring. Modern Turing test discussions have shifted from making machines indistinguishable from humans, to proving humans aren't machines, evident in widespread use of captchas and ventures like Worldcoin. Generative AI holds the promise of making machines more human-serving, but this requires imaginative design and is contingent on cost. Hence, the "uncanny valley", the unsettling space between traditional life and digital replication, is increasingly becoming the norm.

🛠️ AI tools updates

Tinder is testing an AI feature to assist users in selecting the best photos for their profiles, an announcement made by Match Group during its recent earnings call. This AI-powered tool aims to eliminate the stress of photo selection, creating a profile that accurately portrays users. Tinder plans to further leverage AI to improve the relevance of content surfaced for users. Furthermore, there are hints at the use of generative AI to help write bios, with a recent study showing a third of Tinder members expressing interest in this application. The company, however, emphasises the importance of ensuring authenticity and addressing ethical and privacy concerns. Other AI features and product improvements, like prompts, quizzes, and conversation starters, are also in the pipeline.

💵 Venture Capital updates

AI chip startup Tenstorrent, led by renowned chip designer Jim Keller, has secured $100 million in an up-round strategic financing from notable investors, including Hyundai Motor Group and Samsung Catalyst Fund. This latest investment will be deployed for the company's product development, focusing on AI chiplets and its machine learning software roadmap. Established in 2016, Tenstorrent has achieved unicorn status and raised nearly $335 million to date. The company's success not only highlights the general investors' appetite for AI but also two specific trends in the AI ecosystem: a massive investment from strategic players and the growing interest in the infrastructure layer that underpins large generative AI platforms.

🫡 Meme of the day

⭐️ Generative AI image of the day