Drake shows us what the future of AI and music looks like

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TODAY’S TOP STORIES:

🎤 Drake uses AI to channel Tupac and Snoop Dogg in latest rap beef freestyle

 🤖 Stanford AI Index reveals AI surpassing human performance on majority of benchmarks

+ Other quick AI developments you should know…

🎤 Drake shows us what the future of AI and music looks like

If you are a rap/hip-hop fan, there’s no doubt you listened to this track over the weekend…

Main Story: Drake dropped a new freestyle on Instagram in response to the ongoing beef with Future and Kendrick Lamar. The "Taylor Made Freestyle" features verses that use AI to imitate the voices of Tupac and Snoop Dogg, commenting on the current rap feud before Drake delivers his final verse.

Dive deeper:

• Drake's AI-generated verses showcase the most convincing example of AI-powered music to date, blurring the lines between human and machine-generated content.

• The freestyle offers a glimpse into a future where AI is seamlessly intertwined with music production and artistry.

• Throughout the rap beef, various fake AI tracks have been released on social media, causing confusion among fans as to their authenticity and origin.

• Drake's move to incorporate AI into his official response sets him apart as a pioneering artist, embracing cutting-edge technology to push the boundaries of music creation.

Industry Impact: Drake's "Taylor Made Freestyle" represents a watershed moment for the use of AI in mainstream music. As the first major artist to incorporate such convincing AI-generated content into an official release, Drake has opened the door for a new era of music production and creativity. This move is likely to inspire other artists to experiment with AI technology, potentially revolutionizing the way music is created and consumed. However, the increasing prevalence of AI-generated content also raises questions about authenticity, authorship, and the role of human artistry in the age of artificial intelligence.

🤖 Stanford AI Index reveals AI surpassing human performance on majority of benchmarks

Main Story: Stanford University's 2024 AI Index report, which tracks global AI trends, reveals that AI has surpassed human-level performance on the majority of significant benchmarks, including image classification, reading comprehension, and visual reasoning.

Dive deeper:

• Many benchmarks have become obsolete due to AI's rapid acceleration, prompting researchers to develop new tests to measure AI capabilities.

• Closed-source models still lead the industry, with major players dominating due to increasing training costs.

• Large Language Models (LLMs) are becoming more truthful and less prone to "hallucinations."

• The report does not cover the significant model advances of 2024, such as Claude 3 and Llama 3, suggesting even more rapid progress in the near future.

Industry impact: The Stanford AI Index report underscores the breakneck pace at which AI technology is advancing, with each year likely to bring exponential progress. As AI continues to surpass human performance across a wide range of tasks, industries must grapple with the implications of this rapid advancement and adapt to the changing landscape.

Some other quick developments you should know…

🛩️ US Air Force successfully pits AI-controlled fighter against manned F-16s in simulated dogfights

In collaboration with DARPA, the US Air Force has successfully tested an AI-controlled X-62A VISTA aircraft against manned F-16s in simulated dogfights, marking a breakthrough in the application of AI in aviation.

🤖 Anthropic CEO warns AI models could "replicate and survive in the wild" by next year

Dario Amodei, CEO of Anthropic, suggests that AI models could become self-sustaining and self-replicating within the next few years, potentially enabling state-level actors to enhance their offensive capabilities.

👾 Mistral Large and Mixtral 8x22B LLMs powered by NVIDIA NIM and NVIDIA API

NVIDIA has released two new AI Foundation models, Mistral Large and Mixtral 8x22B, developed by Mistral AI. These cutting-edge text-generation AI models are supported by NVIDIA NIM microservices and are available through the NVIDIA API catalog, enabling developers to reduce deployment times from weeks to minutes.