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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 Aufrufe • vor 3 Monaten •via X (Twitter)

Anya Rossi• Live Now

Private livecam show

13 Kommentare

Profilbild von Aaliya

Aaliyavor 3 Monaten

Running privacy tools locally is a smart idea

Profilbild von Daniel Lougen

Daniel Lougenvor 3 Monaten

@luksamuk Done

Profilbild von Broooooklyn

Broooooklynvor 3 Monaten

@ewind_dev this is what you want for @spoollabs

Profilbild von Mariusz Kurman

Mariusz Kurmanvor 3 Monaten

Nice👀

Profilbild von Krish Dasgupta

Krish Dasguptavor 3 Monaten

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

Profilbild von Spaghetti Stories

Spaghetti Storiesvor 3 Monaten

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.

Profilbild von Omar Gashi

Omar Gashivor 3 Monaten

How can I invest in @liquidai

Profilbild von luis

luisvor 3 Monaten

@Presidentlin

Profilbild von Michel aka Agent B

Michel aka Agent Bvor 3 Monaten

Cool one. Bravo to the team ! 👏👏

Profilbild von AI Mastery Guide

AI Mastery Guidevor 3 Monaten

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

Profilbild von toji

tojivor 3 Monaten

Fascinating

Profilbild von Zohaib Ai

Zohaib Aivor 3 Monaten

Privacy features are becoming more important than ever.

Profilbild von Sani Ai Tech

Sani Ai Techvor 3 Monaten

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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There’s a brand new AI model. It’s FREE. It runs on your laptop. No cloud. No subscription. No GPU. And it has 24 BILLION parameters. Here’s the crazy part: It only activates ~2.3B at a time. That means it stays fast, lean, and runs on normal hardware. You can: • Read massive docs • Build full content plans • Answer complex questions • Run unlimited prompts All privately. No one sees your data. No per-token fees. No usage caps. It’s called LFM2 24B A2B from Liquid AI. This is one of the biggest shifts in local AI we’ve seen.

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starmex

981,107 Aufrufe • vor 3 Monaten

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1,237,742 Aufrufe • vor 3 Monaten

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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kepo

15,451 Aufrufe • vor 3 Monaten

AMD JUST KILLED THE $200 - A - MONTH AI SUBSCRIPTION - A 65-WATT BOX WITH 128GB OF UNIFIED MEMORY THAT RUNS 70B MODELS LOCALLY. that clip is amd's ryzen ai max+ 395 mini box, held up on stage. the whole pitch is one spec: 128gb of high-speed unified memory. why it matters: cpu, gpu and npu share the same 128gb pool, so a model that used to need a rack of vram just fits. what it actually runs: llama 70b in full precision on the built-in gpu open models up to ~100b parameters, locally, no cloud all of it in a mini pc pulling around 65 watts that's the part that ends the subscription: your prompts, your data, your model, on a box on your desk, not metered by the token. honest line: this runs open models, not gpt-5 or claude opus. for chat, coding help and agents on your own data it's more than enough. for the absolute frontier, the cloud still wins. and it isn't free: the box runs ~$1,500 and up. but that's a few months of a $200 sub, then it's yours forever. no monthly ai bill, no tokens metered, no prompt leaving the room. the uncomfortable part isn't that amd made a fast box. it's that "you need the cloud for ai" was a pricing choice, and unified memory just made it optional. follow RetroChainer for the hardware that turns rent into ownership, and bookmark this before your next ai renewal.

AMD JUST KILLED THE $200 - A - MONTH AI SUBSCRIPTION - A 65-WATT BOX WITH 128GB OF UNIFIED MEMORY THAT RUNS 70B MODELS LOCALLY. that clip is amd's ryzen ai max+ 395 mini box, held up on stage. the whole pitch is one spec: 128gb of high-speed unified memory. why it matters: cpu, gpu and npu share the same 128gb pool, so a model that used to need a rack of vram just fits. what it actually runs: llama 70b in full precision on the built-in gpu open models up to ~100b parameters, locally, no cloud all of it in a mini pc pulling around 65 watts that's the part that ends the subscription: your prompts, your data, your model, on a box on your desk, not metered by the token. honest line: this runs open models, not gpt-5 or claude opus. for chat, coding help and agents on your own data it's more than enough. for the absolute frontier, the cloud still wins. and it isn't free: the box runs ~$1,500 and up. but that's a few months of a $200 sub, then it's yours forever. no monthly ai bill, no tokens metered, no prompt leaving the room. the uncomfortable part isn't that amd made a fast box. it's that "you need the cloud for ai" was a pricing choice, and unified memory just made it optional. follow RetroChainer for the hardware that turns rent into ownership, and bookmark this before your next ai renewal.

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dunik

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Perplexity CEO Aravind Srinivas on the biggest threat to the data center industry: It's not competition. It's not regulation. It's decentralisation. "The biggest threat to a data center is if the intelligence can be packed locally on a chip that's running on the device and then there's no need to inference all of it on like one centralized data center." He outlines how this could work in practice. Personalisation doesn't necessarily require on-device model training. Retrieval augmented generation, tool calls, and local data can already tailor AI to individual users. But the real unlock? Test time training. Aravind Srinivas describes a future where AI lives on your device, watches how you work and gradually automates your repetitive tasks. "Imagine we crack test time training where the AI watches tasks you repeatedly do on your local system, adapts to you over time and starts automating a lot of the things you do." The key insight: in this model, the intelligence belongs to you. It's your data, your device, your personalised AI brain. And if that future arrives, the economics of centralised infrastructure start to collapse. "That really disrupts the whole data center industry. It doesn't make sense to spend all this money, 500 billion, 5 trillion, whatever on building all the centralized data centers across the world that do a lot of the intelligence workloads for people." The companies spending trillions on centralised infrastructure may want to rethink where intelligence actually needs to live.

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Big Brain AI

90,276 Aufrufe • vor 7 Monaten

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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

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28,504 Aufrufe • vor 2 Monaten