Async (formerly Podcastle) vs MusicLM

Async lets you record, edit, and republish audio and video by chatting with AI instead of dragging clips on a timeline. You can capture remote podcasts, generate footage from prompts, clean up audio, add subtitles, dub content, and turn long recordings into social clips inside one browser workflow.

Where most editors split recording, transcription, and clip creation across separate apps, Async bundles them behind a chat interface called Bumblebee. You upload footage or start from a template, tell Async what to cut or generate, and it handles pacing, captions, and export. The platform also lists 100+ generative models for video, image, music, and voice, including Kling, Veo, Sora, and GPT Image 2.

The free plan includes 10 lifetime AI credits and 1 hour of media uploads, enough to test the chat editor before upgrading. Paid tiers add monthly credit pools (450 on Essentials, 1,200 on Pro, 3,000 on Teams) that meter video generation, dubbing, and other AI actions. Annual billing saves up to 40%.

Podcasters, video creators, marketing teams, and social media managers who want recording, editing, and repurposing in one place without learning traditional NLE software are the target audience. An iOS app is available, and remote recording supports up to 10 participants per session.

MusicLM is a Google Research audio generation model that creates music from text captions at 24 kHz. The public examples page hosts sample clips for prompts like arcade soundtracks, reggaeton-EDM fusions, and relaxing jazz, plus longer story-mode generations that shift styles across timed segments. Google released the MusicCaps dataset of 5,500 music-text pairs alongside the paper.

Unlike consumer apps that ship one prompt box, MusicLM was published as a research demo with pre-generated samples rather than a login product. Its headline trick is joint text-and-melody conditioning: you can hum or whistle a tune and have the model re-render it in a new genre described in text. Story mode chains multiple captions so the music evolves across sections.

MusicLM matters as the research foundation behind Google's later Lyria music models, but this page is for listening to published examples, not creating new tracks interactively. Researchers and musicians study it for long-form consistency, painting-to-music conditioning, and melody transfer results documented in the 2023 paper.