Mango AI vs A Generalist Agent

Mango AI catalogs more than 13,000 AI tools in one searchable directory. You browse cards with pricing badges, filter by Free, Freemium, or Paid, and jump straight to each tool's website. A free newsletter goes out to 40,000+ readers highlighting new additions and AI news.

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The homepage rotates featured tools across categories like image generation, chatbots, finance, and real estate. Listings label pricing type on the card itself, so you can scan for free options without opening every site. Contact is available at [email protected] for questions or submissions.

AI enthusiasts hunting new products, developers comparing options, and newsletter readers who want a curated weekly digest are the core audience. The directory itself costs nothing to browse, and the newsletter subscription is also free.

Gato is the generalist agent DeepMind introduced in its May 2022 research post "A Generalist Agent." One transformer policy with shared weights handles chat, image captioning, Atari games, and real robot arm block stacking from the same model. The post describes it as a multi-modal, multi-task, multi-embodiment policy that picks whether to emit text, joint torques, button presses, or other tokens based on context.

Most tools in this space train a separate model per task domain. Gato instead serializes every modality and environment into a flat token sequence and runs it through a transformer shaped like a large language model. That means one pretrained checkpoint moves between dialogue, vision, and control without swapping architectures.

During training, data from simulated and real environments mixes with natural language and image datasets, with loss masked so Gato predicts only action and text targets. At deployment, a prompt tokenizes first, each new observation appends to the sequence, and the model samples an action vector one token at a time inside a 1024-token context window. The blog includes domain-grouped charts of tasks where the pretrained model clears expert score thresholds.

The writeup targets AI and robotics researchers more than everyday software buyers. You read and cite the research on deepmind.google; there is no public signup flow, API tier, or download button on the pages reviewed here.