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mlabonne 
posted an update 2 days ago
tsungyi 
posted an update about 21 hours ago
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1224
🎉 Exciting News — NVIDIA Cosmos is celebrating its 1st birthday and has hit 5 MILLION downloads! 🎉

In just one year, the Cosmos ecosystem has grown rapidly:
🧠 Cosmos Reason and Cosmos Predict have surpassed 2 MILLION downloads each on @HuggingFace , topping physical AI leaderboards
🔄 Cosmos Transfer is enabling adaptation across domains and tasks
🔮 Cosmos Cookbook is the go-to hub for recipes from developers and partners like Uber and IntBot.

Thank you to our amazing developer community for making this possible. Here's to pushing the boundaries of world foundation models together!

🧑🏻‍🍳Read the Cosmos Cookbook: https://nvda.ws/4qevli8
📚 Explore Models & Datasets: https://huggingface.co/collections/nvidia/nvidia-cosmos-2
Reality123b 
posted an update about 22 hours ago
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427
Happy birthday to me!!!
dhruv3006 
posted an update about 17 hours ago
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1165

Assertions are sanity checks for your API.
In Voiden, assertions are reusable blocks .

How it works :
1. Type /assertion-block
2. Run the request Ctrl + Enter )
3. Check the Response Panel to see if it passed or broke

Quick confidence. Zero guesswork.

Download Voiden here : https://voiden.md/
Nymbo 
posted an update about 24 hours ago
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457
Genuine recommendation: You should really use this AutoHotKey macro. Save the file as macros.ahk and run it. Before sending a prompt to your coding agent, press Ctrl + Alt + 1 and paste your prompt to any regular chatbot. Then send the output to the agent. This is the actual, boring, real way to "10x your prompting". Use the other number keys to avoid repeating yourself over and over again. I use this macro prolly 100-200 times per day. AutoHotKey isn't as new or hype as a lot of other workflows, but there's a reason it's still widely used after 17 years. Don't overcomplicate it.

; Requires AutoHotkey v1.1+

; All macros are `Ctrl + Alt + <variable>`

^!1::
    Send, Please help me more clearly articulate what I mean with this message (write the message in a code block):
return

^!2::
    Send, Please make the following changes:
return

^!3::
    Send, It seems you got cut off by the maximum response limit. Please continue by picking up where you left off.
return


In my experience the past few months, Ctrl + Alt + 1 works best with Instruct models (non-thinking). Reasoning causes some models to ramble and miss the point. I've just been using GPT-5.x for this.
mindchain 
posted an update 1 day ago
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1037
Scaling Physical AI: SAM 3D, NVIDIA Cosmos, and Unreal Engine!

The "Sim-to-Real" gap is officially history. In early 2026, we are no longer just rendering data; we are simulating reality. By bridging Meta’s SAM 3D, Unreal Engine, and the NVIDIA Cosmos suite, we’ve built an autonomous pipeline for Physical AI that evolves itself.

The 2026 Tech Stack:
SAM 3D: Generates high-fidelity digital twins from 2D photos in seconds.

Unreal Engine + MCP: The AI "Director" orchestrates environments via the Model Context Protocol, providing perfect Ground Truth.

NeMo Data Designer: The orchestration hub on GitHub. Following NVIDIA’s acquisition of Gretel in early 2025, its leading generative privacy and tabular tech are now fully integrated here.

NVIDIA Cosmos Transfer: Neural rendering that adds hyper-realism to Unreal Engine outputs.

NVIDIA Cosmos Predict: Predicts physically accurate motion (falling, sliding) without manual animation.

NVIDIA Cosmos Reason: The automated supervisor checking every frame for logical and physical consistency.

The Workflow:
Asset Capture: SAM 3D turns real-world photos into Nanite meshes for Unreal Engine.

Orchestration: NeMo Data Designer (with Gretel-powered integrity) defines the data schema, while AI builds the world in Unreal Engine.

Completion: NVIDIA Cosmos (Transfer & Predict) adds photorealism and physics, while NVIDIA Cosmos Reason guarantees quality.

By combining Gretel’s data heritage with the visual power of Unreal Engine, we generate 100,000 perfect frames per hour. Weights and tools are on Hugging Face. Stop labeling. Start simulating.

#PhysicalAI #SAM3D #NVIDIACosmos #UnrealEngine #NeMo #Gretel #SyntheticData #HuggingFace #Robotics #AI #ComputerVision
MaziyarPanahi 
posted an update 3 days ago
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2243
🎉 OpenMed 2025 Year in Review: 6 Months of Open Medical AI

I'm thrilled to share what the OpenMed community has accomplished since our July 2025 launch!

📊 The Numbers

29,700,000 downloads Thank you! 🙏

- 481 total models (475 medical NER models + 6 fine-tuned LLMs)
- 475 medical NER models in [OpenMed](
OpenMed ) organization
- 6 fine-tuned LLMs in [openmed-community](
openmed-community )
- 551,800 PyPI downloads of the [openmed package](https://pypi.org/project/openmed/)
- 707 followers on HuggingFace (you!)
- 97 GitHub stars on the [toolkit repo](https://github.com/maziyarpanahi/openmed)

🏆 Top Models by Downloads

1. [OpenMed-NER-PharmaDetect-SuperClinical-434M]( OpenMed/OpenMed-NER-PharmaDetect-SuperClinical-434M) — 147,305 downloads
2. [OpenMed-NER-ChemicalDetect-ElectraMed-33M]( OpenMed/OpenMed-NER-ChemicalDetect-ElectraMed-33M) — 126,785 downloads
3. [OpenMed-NER-BloodCancerDetect-TinyMed-65M]( OpenMed/OpenMed-NER-BloodCancerDetect-TinyMed-65M) — 126,465 downloads

🔬 Model Categories

Our 481 models cover comprehensive medical domains:

- Disease Detection (~50 variants)
- Pharmaceutical Detection (~50 variants)
- Oncology Detection (~50 variants)
- Genomics/DNA Detection (~80 variants)
- Chemical Detection (~50 variants)
- Species/Organism Detection (~60 variants)
- Protein Detection (~50 variants)
- Pathology Detection (~50 variants)
- Blood Cancer Detection (~30 variants)
- Anatomy Detection (~40 variants)
- Zero-Shot NER (GLiNER-based)


OpenMed
OpenMed NER: Open-Source, Domain-Adapted State-of-the-Art Transformers for Biomedical NER Across 12 Public Datasets (2508.01630)
https://huggingface.co/collections/OpenMed/medical-and-clinical-ner
https://huggingface.co/collections/OpenMed/zeroshot-medical-and-clinical-ner
OpenMed/Medical-Reasoning-SFT-GPT-OSS-120B
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AdinaY 
posted an update about 9 hours ago
JLouisBiz 
posted an update about 9 hours ago
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346
I’ve built two Firefox extensions for my personal workflow:

1. **Quick Edit in Emacs**
I manage over 3,500 web pages locally. With this extension, I can now click anywhere on a webpage and instantly jump into Emacs to edit the exact page (or annotate any other page I'm working on).

2. **Describe Images (and soon Videos) on the Web**
Using the right-click menu, I can generate descriptions for images I come across online. These descriptions are stored and reused for my own image collections or web pages. I’m planning to add the same functionality for videos soon.

What makes this possible is running LLMs locally on my own machine — I’ve been experimenting with models like **Mistral Vibe** and others. This lets me automate description generation and text processing entirely offline, keeping everything fast, private, and fully under my control.
Fishtiks 
posted an update 1 day ago
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392
Have extra processing power in downtime? Have old devices you haven't used in years? I recommend primarily Folding@home to do protein folding on your GPUs, but also BOINC, particularly on Android and Apple devices, because of the lower power usage. I've been doing this, and get about 14,000 hours a week in, primarily for mapping cancer markers on BOINC on an Aiyara cluster of Androids. I also hold a sign out by the highway encouraging people to join BOINC. It was Dylan Bucci, a young promoter of BOINC on school's computers, who wished before he died to get as many people on as possible to do this, and in his honor, the Dylan Bucci challenge was implemented. No reason to wait for a challenge. If you care about such things, there is an associated cryptocurrency for such processing, but it's worth it to save lives.

I look forward to AI-related endeavors like this, and only know of NATIX Drive&, Acurast, and HYRA AI, all of which use Androids I'd rather devote to BOINC. However, they also allow one to be paid, and to totally devote old devices to the processing. On the same topic, DexPOINT monitizes your Android's Internet connection.

BOINC runs on Android, Apple, PCs of all sorts, Pi devices, Chrome devices, Fire Sticks, TV boxes, Android watches with the full OS, and all sorts of things that have Android or the ability to run Linux, although it will also run on Windows. Folding@home works best on PCs with modern NVIDIA GPUs, and in a cool room. You can also run BOINC on modern computers, but they must be throttled, because they often get too hot.
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