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- AI-generated song mimicking Drake and the Weeknd gets submitted for Grammys
AI-generated song mimicking Drake and the Weeknd gets submitted for Grammys
Plus: Open Interpreter, the open source Code Interpreter

Welcome to The Dispatch! We are the newsletter that keeps you informed about AI. Each weekday, we scour the web to aggregate the many stories related to artificial intelligence; we pass along the news, useful resources, tools or services, technical analysis and exciting developments in open source. Even if you aren’t an engineer, we’ll keep you in touch with what’s going on under the hood in AI.
Good morning. Today in AI:
TIME covers Elon Musk’s quest for an AI that seeks truth and meaning
Could an AI-generated song ever win a Grammy?
Popular gaming platforms Steam and Epic are clashing over the role of AI in game development
Work collaboration platform Slack gets an infusion of AI upgrades
An open source alternative to ChatGPT’s powerful Code Interpreter
A Reddit user creates a massive remote jobs database with ChatGPT & more
From Variety: An AI-generated track titled "Heart on My Sleeve," featuring vocal facsimiles of Drake and the Weeknd, has been submitted for Grammy consideration. Mixed using AI by the shadowy creator ‘Ghostwriter’, the song went viral in April and has now received an endorsement (of sorts) from Recording Academy CEO Harvey Mason Jr., who stated that the track is "absolutely eligible" for a Grammy since it was written by a human. However, neither Drake nor the Weeknd had any involvement in the creation of the song.
More details:
Ghostwriter submitted "Heart on My Sleeve" for "best rap song" and "song of the year" - categories that traditionally honor the writers rather than the performers. Ghostwriter wrote the lyrics, while the vocals were AI-generated.
The Recording Academy has established rules against awarding AI-generated compositions but allows for "assistive AI," as in the case where Paul McCartney used the technology to enhance an old John Lennon vocal track. The emphasis remains on human authorship for eligibility.
Despite its creative ingenuity, the song has had a turbulent journey in terms of distribution. Initially appearing on YouTube and streaming platforms, it was taken down due to apparent copyright issues from Universal Music but has since resurfaced thanks to third parties.
Recording Academy CEO Harvey Mason Jr. elaborated that any work involving AI can be submitted for a Grammy, but only the "human portion" of the composition would be considered for an award. He mentioned the Recording Academy's position on distinguishing between human-driven and AI-generated creativity - a fine line.
Takeaways: If you haven’t heard it yet, here is the song in question. Perhaps not coincidentally, Ghostwriter released a second such creation yesterday on TikTok featuring two other popular artists - and it garnered well over 5 million views before it was removed/deleted from the platform. Here’s how we see it:
Using an artist’s voice to create content without consent is clearly illegal. Ghostwriter has said if the original artists endorse his creations, he will pay them royalties. Is that enough? For some artists, it seems like the answer is yes. For most, we would expect not.
Platforms like YouTube are put in an impossible situation: to issue a copyright takedown to YouTube, there needs to be an obvious copyright. Since “Heart on my Sleeve” is an original song, UMG doesn’t own it. This is why, after initially being taken down, the song is still on the platform.
Something that can get lost amid the high stakes: AI-generated music can be awesome, and fun. The historically important intertwining of technology and music is at the dawn of a new era, and it’s something we should be celebrating - even as we navigate complex and sensitive realities with the deepest care for our artist’s identities.
![]() | Despite being relatively quiet in the AI space compared to its tech peers, Apple is reportedly spending millions of dollars per day on AI-related developments. Among other things, the company wants to supercharge Siri with the power of large language models. With the enhancements, iPhone users would be able to perform multi-step tasks with Siri - e.g. creating and sending gifs from their camera roll with a simple voice request. |
Microsoft and Google’s most recent earnings calls mentioned AI 73 and 90 times, respectively, while Apple’s only mentioned it six. Given the secrecy around their new language model ‘Ajax’, it’s clear that Apple is taking a more ‘top secret’ approach to AI development than their tech peers.
![]() | Epic Games and Steam, the two major online game platforms, have taken opposing stances on whether to allow games containing AI-generated content. Epic's CEO Tim Sweeney welcomes AI-generated content in games, arguing it should be assessed holistically under current law. His views are similar to the concept of “fair use” in copyright law. |
Meanwhile, Steam has shut the door on even ‘fringe’ AI content over intellectual property worries. Developers will face a more bifurcated landscape in deciding how to pursue game development, as Steam is clearly not taking any chances with regard to AI’s involvement. That will put developers who want to integrate the technology into a bind - Steam is the most widely used video game distribution platform in the world, with around 75% of the global market.
Inside Elon Musk’s struggle for the future of AI
UN calls for age limits for AI tools in schools
How Anthropic’s Daniela Amodei is keeping AI from spinning out of control
Introducing Claude Pro (ChatGPT’s top competitor)
Morgan Stanley to launch AI chatbot to woo wealthy
AI a growing cause of 'tech anxiety' among business leaders
New Slack AI capabilities announced to transform productivity
HubSpot unveils strategy to integrate AI across the platform
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The UAE’s Technology Innovation Institute has just announced the release of their new open source LLM, Falcon 180B. Falcon 180B boasts 180 billion parameters, making it the largest openly available LLM to date. This massive model was trained on an unprecedented 3.5 trillion tokens, using thousands of GPUs over millions of hours on Amazon SageMaker. |
In benchmarks, Falcon 180B achieves state-of-the-art results for an open source model, surpassing Meta's LLaMA 2. Falcon 180B typically sits somewhere between GPT-3.5 and GPT-4 depending on the evaluation benchmark - quite impressive for an open source foundation model.
Falcon 180b can be commercially used, but under very restrictive conditions, excluding any "hosting use". Read more about Falcon and get links to the model weights and demo from the blog post here.
IBM just announced a new family of foundation AI models for business that will be available on their AI platform watsonx.ai. ‘Granite’ is a collection of 13 billion parameter models designed specifically for business use-cases like summarization and question answering. Granite models were trained on over 1 trillion tokens from datasets in areas like academia, legal, finance, and code to better suit commercial vs. personal needs. |
In the blog post, IBM highlights their rigorous approach to trust and data governance in developing Granite, including screening for objectionable content and establishing model lineage back to original training data (read more about why this is important here). Watson Studio will enable capabilities like prompt tuning and synthetic data generation to further adapt models. IBM has been continually expanding Watson Studio’s generative AI capabilities - and they say they’re just getting started.
Open Interpreter - an open-source Code Interpreter that runs locally
SMPLitex: a generative model and dataset for 3D human texture estimation from a single image
‘We’re at the start of a revolution’: could lab brains eventually take over AI?

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Did you know?
Meta’s AI team is struggling with internal drama (paywalled article - The Information).
Their research lab, FAIR, has been facing internal struggles over resources and retaining talent. Following breakthroughs by OpenAI and others, Meta rushed to develop LLaMa to compete as an open source alternative. But with limited computing power, teams at FAIR fought over resource allocation, causing rifts - and some researchers left.
Additionally, the US team was originally working on a larger LLM while a Paris team built the smaller LlaMa, believing it could rival bigger models. But the Paris team felt shorted on computing access versus the US team. Disputes escalated and key researchers resigned, including the Paris lab head. Meta ultimately scrapped the US-based LLM project and combined forces on Llama 2, but many have left FAIR nonetheless.
The public has praised Meta's open-sourced models, but unrest persists over shifts from open research towards profitable products. And, like others, Meta grapples with retaining AI experts amid huge demand.
I can’t just sit around and do nothing. With AI coming, I’m sort of wondering whether it’s worth spending that much time thinking about Twitter. Sure, I could probably make it the biggest financial institution in the world. But I have only so many brain cycles and hours in the day. I mean, it’s not like I need to be richer or something.