Ente Launches Ensu: A Privacy-Focused Local LLM App for Offline AI
By
matthiaswh
An everything bagel for the brain. Substantive, layered, well-seasoned.
Summary
Ente introduces Ensu, a new offline LLM app that runs locally on user devices, positioning it as a privacy-focused alternative to big tech's cloud-based models. The article argues that local models are rapidly improving and will soon reach a capability threshold where they become viable for most purposes while offering full privacy and control. The post announces the first release of Ensu and explains the company's vision for personal, private AI that grows with users over time.
Key quotes
· 4 pulledLLMs are too important to be left to big tech.
There is a gap between frontier models and models that can run on your device, but local models improve each day, and once they cross a certain capability threshold, they will be good enough for most purposes; and will come with full privacy and control.
Introducing Ensu, our first step toward a private, personal LLM app that runs on your device and grows with you over time.
Based on these assumptions, we've been working on Ensu, Ente's offline LLM app. Today is our first release.
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