Dipti Sharma

This is what a full fashion shoot looks like in 2026. No studio No models No reshoots Just 1 product image. @TheDreemAI

Finally, privacy done right not just promised, but built in Smart, thoughtful, and practical exactly what AI needs right now This is a big step forward

OpenArt is beautifully bridging imagination and reality with seamless creative control.

This is what a full fashion shoot looks like in 2026. No studio No models No reshoots Just 1 product image. @TheDreemAI

From lab to open-source: A new milestone for AI-driven education. 🎓 🤗 We’ve been closely following the MAIC project at Tsinghua University, and we’re thrilled to see it now open-sourced as #OpenMAIC. ✨ This isn't just another chatbot; it takes Multi-Agent orchestration to the next level by building a fully interactive classroom where AI instructors and peers collaborate in real-time. What makes it technically impressive: 🛠️ Complex Orchestration: Leveraging #LangGraph to manage spontaneous interactions—like #AI students "raising hands" during a live lecture. 🧠 Structured Planning: A dedicated "Plan Agent" that transforms raw PDFs into coherent, logically sequenced pedagogical flows. 💻 Beyond Text: A masterclass in GenUI implementation, featuring synchronized TTS, laser pointers, and real-time whiteboard demonstrations. 🥳 If you’re building complex, multi-modal #Agent workflows, this repo is a treasure trove of engineering insights. 🖥️Explore the project: github.com/THU-MAIC/OpenM… 📰 Read the research: jcst.ict.ac.cn/article/doi/10…

(1/2) Glad to announce our OpenMAIC! 🎉 Open-sourcing MAIC (Multi-Agent Interactive Classroom) from Tsinghua University — LLM-driven multi-agent classroom for scalable & adaptive online education. 🏗️ Core Architecture: ✅ MAIC-Craft: Read (multimodal extraction) → Plan (course components + agent generation) ✅ Adaptive Engine: Cognitive student modeling + Token-level personalization (RAG + Bloom's/ZPD/UDL) ✅ Multi-Agent Classroom: 1 Student + N Agents (Teacher, Assistant, 4 Peer Archetypes) ✅ Manager Agent: Class state receptor for turn-taking orchestration 🔗 Give it a try 👉🏻 GitHub: github.com/THU-MAIC/OpenM… #AI #EdTech #MultiAgent #LLM #Research #OpenSource #Tsinghua

(1/2)🦞 Using @openclaw but worried about sending sensitive data to the cloud? 🤔 Meet #EdgeClaw — a dedicated Local Routing Layer for #OpenClaw that handles data sensitivity and task complexity on the edge. 💻 It’s a drop-in enhancement that reactivates your local hardware to act as a Privacy Guard & Cost Judge. 3-Tier Security (Regex + Local LLM Engine) 🟢 S1 (Safe): Transparent passthrough to cloud. 🟡 S2 (Sensitive): On-device PII redaction before forwarding. 🔴 S3 (Private): 100% Local inference. Cloud only sees a 🔒 placeholder. 🧠 #LLM-as-Judge Routing Classifies requests locally and routes to the ideal model tier (e.g., #MiniCPM ➡️ #GPT-4o/#Claude), optimizing resource allocation and reducing unnecessary cloud dependency. 📉 Learn more🔗 github.com/openbmb/edgecl… #EdgeAI #LLM #Privacy #EdgeClaw #OpenClaw

Curious what an always-on personal AI actually looks like in action? We made some use cases to show what MuleRun can do for you:

Introducing MuleRun 2.0. Your personal AI, act before you ask. It learns your habits, anticipates your needs, and works while you sleep — running 24/7 on your Personal Computer assigned to you alone. No complex setup. Just talk to it.

@OpenBMB @openclaw Love this approach! keeping sensitive data local while still using cloud power is a perfect balance.

@thetripathi58 This looks next-level.

MIND-BLOWING: The most underrated AI tool of 2026 just dropped. You can now literally type a sentence and generate an entire 3D world you can walk through. No 3D knowledge required. Here's how OpenArt Worlds creates these worlds in seconds:

@openart_ai Love this idea. Makes creating feel much more natural and less frustrating

Today, we’re launching a new way to create with AI. With OpenArt Worlds, you can generate a fully navigable 3D environment from a single prompt or image, step inside it, and capture shots exactly the way you envision them. No more starting over. No more inconsistent scenes. You build the world once - and create inside it. • Move through your scene freely • Find your angles • Add characters and elements • Capture production-ready shots

This approach works because: → You don’t anchor yourself to a low number → You force them to reveal their budget first → You signal you’ve done your research (which raises your perceived value) → You leave room to negotiate the full package, not just base salary

(The Solution): Use the Deflect and Research script instead: I want to make sure I’m aligned with the market and the value this role brings. Could you share the approved salary range for this position?” If they push: Based on my research and experience, I’m targeting [range 10-15% above your minimum]. But I’m open to discussing the full compensation package.

I MESSED UP MY SALARY NEGOTIATION IN ONE SENTENCE. “I’m quite flexible.” The hiring manager smiled. That should’ve been my warning.

From 1 product image → full content pipeline. Photos Models Product shots Video That’s Dreem. If you’re running fashion or ecommerce, this changes how fast you can ship creatives. dreem.ai

Image → Video Then it gets interesting. Took that same model and converted it into a short video. → 5-sec motion → Product in action → Ready for ads / reels From image to video… instantly.