🗣️ Post 1: Show HN: OpenAI/reflect – Physical AI Assistant that illuminates your life

As posted by: Sean-Der  |  🔥 Points: 72

https://github.com/openai/openai-reflect

💬 Summary

I have been working on making WebRTC + Embedded Devices easier for a few years. This is a hackathon project that pulled some of that together. I hope others build on it/it inspires them to play with hardware. I worked on it with two other people and I had a lot of fun with some of the ideas that came out of it.

* Extendable/hackable - I tried to keep the code as simple as possible so others can fork/modify easily.

* Communicate with light. With function calling it changes the light bulb, so it can match your mood or feelings.

* Populate info from clients you control. I wanted to experiment with having it guide you through yesterday/today.

* Phone as control. Setting up new devices can be frustrating. I liked that this didn't require any WiFi setup, it just routed everything through your phone. Also cool then that they device doesn't actually have any sensitive data on it.

🗣️ Post 2: OpenAI Employee Stock Sale Would Value ChatGPT Maker at $500B

As posted by: xnx  |  🔥 Points: 14

https://www.nytimes.com/2025/08/19/technology/openai-chatgpt-stock-sale-valuation.html

💬 Summary

“Everybody thinks it’s a big market opportunity,” Mr. Ghodsi said. “It wouldn’t be smart for me to say let’s wait another two years before we do that investment.” He said Databricks has “no immediate plans” to go public. Before this latest financing, the start-up, which was founded in 2013, had raised $19 billion from investors including Thrive Capital and Andreessen Horowitz. The company did not disclose the funding amount it raised on Tuesday because the round has not closed. OpenAI has been raising money as it competes fiercely with rivals like Google. In its March fund-raising for $40 billion, SoftBank is providing 75 percent of the funding, with other investors chipping in the rest. While the other investors have delivered...

🗣️ Post 3: Show HN: Lemonade: Run LLMs Locally with GPU and NPU Acceleration

As posted by: ramkrishna2910  |  🔥 Points: 12

https://github.com/lemonade-sdk/lemonade

💬 Summary

Lemonade is an open-source SDK and local LLM server focused on making it easy to run and experiment with large language models (LLMs) on your own PC, with special acceleration paths for NPUs (Ryzen™ AI) and GPUs (Strix Halo and Radeon™).

Why?

There are three qualities needed in a local LLM serving stack, and none of the market leaders (Ollama, LM Studio, or using llama.cpp by itself) deliver all three:

1. Use the best backend for the user’s hardware, even if it means integrating multiple inference engines (llama.cpp, ONNXRuntime, etc.) or custom builds (e.g., llama.cpp with ROCm betas).
2. Zero friction for both users and developers from onboarding to apps integration to high performance.
3. Commitment to open source principles and collaborating in the community.

Lemonade Overview:

Simple LLM serving: Lemonade is a drop-in local server that presents an OpenAI-compatible API, so any app or tool that talks to OpenAI’s endpoints will “just work” with Lemonade’s local models.

Performance focus: Powered by llama.cpp (Vulkan and ROCm for GPUs) and ONNXRuntime (Ryzen AI for NPUs and iGPUs), Lemonade squeezes the best out of your PC, no extra code or hacks needed.

Cross-platform: One-click installer for Windows (with GUI), pip/source install for Linux.

Bring your own models: Supports GGUFs and ONNX. Use Gemma, Llama, Qwen, Phi and others out-of-the-box. Easily manage, pull, and swap models.

Complete SDK: Python API for LLM generation, and CLI for benchmarking/testing.

Open source: Apache 2.0 (core server and SDK), no feature gating, no enterprise “gotchas.” All server/API logic and performance code is fully open; some software the NPU depends on is proprietary, but we strive for as much openness as possible (see our GitHub for details). Active collabs with GGML, Hugging Face, and ROCm/TheRock.

Get started:

Windows? Download the latest GUI installer from https://lemonade-server.ai/

Linux? Install with pip or from source (https://lemonade-server.ai/)

Docs: https://lemonade-server.ai/docs/

Discord for banter/support/feedback: https://discord.gg/5xXzkMu8Zk

How do you use it?

Click on lemonade-server from the start menu

Open http://localhost:8000 in your browser for a web ui with chat, settings, and model management.

Point any OpenAI-compatible app (chatbots, coding assistants, GUIs, etc.) at http://localhost:8000/api/v1

Use the CLI to run/load/manage models, monitor usage, and tweak settings such as temperature, top-p and top-k.

Integrate via the Python API for direct access in your own apps or research.

Who is it for?

Developers: Integrate LLMs into your apps with standardized APIs and zero device-specific code, using popular tools and frameworks.

LLM Enthusiasts, plug-and-play with:

Morphik AI (contextual RAG/PDF Q&A)

Open WebUI (modern local chat interfaces)

Continue.dev (VS Code AI coding copilot)

…and many more integrations in progress!

Privacy-focused users: No cloud calls, run everything locally, including advanced multi-modal models if your hardware supports it.

Why does this matter?

Every month, new on-device models (e.g., Qwen3 MOEs and Gemma 3) are getting closer to the capabilities of cloud LLMs. We predict a lot of LLM use will move local for cost reasons alone.

Keeping your data and AI workflows on your own hardware is finally practical, fast, and private, no vendor lock-in, no ongoing API fees, and no sending your sensitive info to remote servers.

Lemonade lowers friction for running these next-gen models, whether you want to experiment, build, or deploy at the edge.

Would love your feedback!

Are you running LLMs on AMD hardware? What’s missing, what’s broken, what would you like to see next? Any pain points from Ollama, LM Studio, or others you wish we solved?

Share your stories, questions, or rant at us.

Links:

Download & Docs: https://lemonade-server.ai/

GitHub: https://github.com/lemonade-sdk/lemonade

Discord: https://discord.gg/5xXzkMu8Zk

Thanks HN!

🗣️ Post 4: DeepSeek v3.1 just dropped – and it might be the most powerful open AI yet

As posted by: ed  |  🔥 Points: 11

https://venturebeat.com/ai/deepseek-v3-1-just-dropped-and-it-might-be-the-most-powerful-open-ai-yet/

💬 Summary

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🗣️ Post 5: Show HN: Tambo Add A Cursor style assistant for React apps (OSS, self-hosted)

As posted by: grouchy  |  🔥 Points: 11

https://github.com/tambo-ai/tambo

💬 Summary

Hi HN--

Tambo is a React SDK that lets your app render and control UI components based on natural language input.

We are hooked on Cursor and want all our apps (Stripe, Vercel, GitHub) to have the same experience. I should be able to type `update env key` and get a UI to add it.

Tambo lets an AI assistant render or update the state of registered React components.

It can fetch context via MCP (Model Context Protocol) or client-side fetches (similar to OpenAI tool calls).

The SDK handles streaming messages and prop updates, maintains thread history, and passes context across turns. It’s BYOM (Bring Your Own Model) and works with Next.js, Remix, Vite, and React Native.

If you’re building a “Cursor for X” (spreadsheets, video, design, etc.), check it out.

Yesterday, we went 100% open source.

Docs: https://docs.tambo.co

GitHub: https://tambo.co/gh

— Michael x2, Alec, Akhilesh

🎯 Final Takeaways

These discussions reveal how developers think about emerging AI trends, tool usage, and practical innovation. Take inspiration from these community insights to level up your own development or prompt workflows.