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Meet Liquid ShieldFlow. An on-device privacy layer powered by a device-native Liquid Foundation Model, Liquid ShieldFlow redacts sensitive data before it ever leaves your machine. No GPU needed and light on memory. It runs on almost any PC, locally, in real time. ShieldFlow was featured yesterday at Microsoft Build... show more

Liquid AI

36,044 subscribers

20,993 просмотров • 3 месяцев назад •via X (Twitter)

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Комментарии: 13

Фото профиля Aaliya

Aaliya3 месяцев назад

Running privacy tools locally is a smart idea

Фото профиля Daniel Lougen

Daniel Lougen3 месяцев назад

@luksamuk Done

Фото профиля Broooooklyn

Broooooklyn3 месяцев назад

@ewind_dev this is what you want for @spoollabs

Фото профиля Mariusz Kurman

Mariusz Kurman3 месяцев назад

Nice👀

Фото профиля Krish Dasgupta

Krish Dasgupta3 месяцев назад

Beautiful concept !!!!! Can’t wait to try - been so far only working with Presidio !

Фото профиля Spaghetti Stories

Spaghetti Stories3 месяцев назад

On-device privacy that actually runs locally with almost no overhead is the kind of infrastructure that makes real local agents viable. Everything else has been hype — this one actually feels practical.

Фото профиля Omar Gashi

Omar Gashi3 месяцев назад

How can I invest in @liquidai

Фото профиля luis

luis3 месяцев назад

@Presidentlin

Фото профиля Michel aka Agent B

Michel aka Agent B3 месяцев назад

Cool one. Bravo to the team ! 👏👏

Фото профиля AI Mastery Guide

AI Mastery Guide3 месяцев назад

The fact that it runs locally means your sensitive data never touches an API endpoint even briefly, that changes the compliance conversation entirely

Фото профиля toji

toji3 месяцев назад

Fascinating

Фото профиля Zohaib Ai

Zohaib Ai3 месяцев назад

Privacy features are becoming more important than ever.

Фото профиля Sani Ai Tech

Sani Ai Tech3 месяцев назад

Privacy done right 🔒 Impressive work 👏 Big win for privacy 🚀 Love this approach 🔥 Local AI is the future ⚡ Very promising 👀 Huge step forward 🚀 Well done, team 👏

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AMD CEO Lisa Su showcased a mini PC that could replace your entire AI stack what's changed: - 128GB of unified memory on a single chip - the CPU and GPU share the same memory space - a 235-billion-parameter model can be loaded entirely locally - no cloud, no subscriptions, no logs an active AI user spends around $420 a month on subscriptions - that's $5,280 a year the EVO-X2 costs $1,800 nstall ollama, pull the model, point claude code at localhost. same interface, nothing leaves the machine, nothing costs per request bookmark this and read the article below

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90,276 просмотров • 7 месяцев назад

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CLAUDE TOOK A FULL PC GAME, REBUILT IT FROM THE GROUND UP, AND GOT IT RUNNING NATIVELY ON ANDROID IN 6 HOURS a guy pointed claude at slay the spire 2, a game he owns on steam, and it ported the whole thing to his phone almost completely on its own here's what claude did: > it pulled apart the game and recompiled it to native arm, no emulator, wine, or proton used > wrote the code, ran the build loop, and debugged it directly on the device itself > added full touch controls that feel like a real mobile game, not awkward on screen buttons > and he even built a tool on top to sync save files between his desktop and phone a couple prompts and 6 hours. it handled the extraction, the cross compile, the building and the on device debugging by itself. fully playable, not a single crash yet

Om Patel

28,504 просмотров • 2 месяцев назад