Always glad to get more people involved. People didn't think SETI@home would take off like it did, but it spread really well by mostly word of mouth, given how bad the Internet was then. I'm currently running about 20 devices, but have another two coming in today. I just ask people to have their old Androids and Chromebooks, because those are fairly energy efficient and people are constantly upgrading. But I will admit I bought ten Androids from eBay once just to add to my donation.
Joseph Robert Turcotte PRO
Fishtiks
AI & ML interests
Roleplaying, lorabration, abliteration, smol models, extensive filtering, unusual datasets, home usage, HPCs for AI, distributed training/federated learning, and sentience.
AI should find and label AI hallucinations with GANs so we can give them context and use.
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31 minutes ago
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 Stick, 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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to
danielhanchen's
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about 18 hours ago
NVIDIA releases Nemotron 3 Nano, a new 30B hybrid reasoning model! 🔥
Has 1M context window & best in class performance for SWE-Bench, reasoning & chat. Run the MoE model locally with 24GB RAM.
GGUF: https://huggingface.co/unsloth/Nemotron-3-Nano-30B-A3B-GGUF
💚 Step-by-step Guide: https://docs.unsloth.ai/models/nemotron-3
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reacted to
mindchain's
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about 2 hours ago
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762
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
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
reacted to
danielhanchen's
post with 🔥
about 18 hours ago
Post
5378
NVIDIA releases Nemotron 3 Nano, a new 30B hybrid reasoning model! 🔥
Has 1M context window & best in class performance for SWE-Bench, reasoning & chat. Run the MoE model locally with 24GB RAM.
GGUF: unsloth/Nemotron-3-Nano-30B-A3B-GGUF
💚 Step-by-step Guide: https://docs.unsloth.ai/models/nemotron-3
Has 1M context window & best in class performance for SWE-Bench, reasoning & chat. Run the MoE model locally with 24GB RAM.
GGUF: unsloth/Nemotron-3-Nano-30B-A3B-GGUF
💚 Step-by-step Guide: https://docs.unsloth.ai/models/nemotron-3
- 1 reply
posted
an
update
about 18 hours ago
Post
109
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 Stick, 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.
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 Stick, 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.
-
- 3 replies
reacted to
CRAFTFramework's
post with 👀
about 19 hours ago
Post
133
Getting Started with CRAFT
No coding required. CRAFT uses programming metaphors, not programming skills.
Your first recipe: Pick a repeated task. Define what, context, and output. Build once, reuse forever.
Beta: February 2026 → craftframework.ai
No coding required. CRAFT uses programming metaphors, not programming skills.
Your first recipe: Pick a repeated task. Define what, context, and output. Build once, reuse forever.
Beta: February 2026 → craftframework.ai
reacted to
CRAFTFramework's
post with 🚀
about 19 hours ago
Post
1282
🔧 Behind the Scenes
CRAFT development: Sun-Mon only (full-time job Wed-Sat). 48 projects completed solo.
The time constraint is the proof—if the methodology works under pressure, it works.
Beta: February 2026 → craftframework.ai
CRAFT development: Sun-Mon only (full-time job Wed-Sat). 48 projects completed solo.
The time constraint is the proof—if the methodology works under pressure, it works.
Beta: February 2026 → craftframework.ai
liked
a
model
about 24 hours ago
posted
an
update
2 days ago
Post
263
When you have good goals, along the lines of what will inevitably be implemented, the initial response is an uproar of "Why?!," followed by lazy attempts, and then, someone actually doing it right. Now, say you're the only driving force behind getting it right, and the rest want some other resource, like money. They will get the money, but not the influence, and the one with the influence, if pure in their goals, doesn't need the money, so ends up poor. I'm a ghostwriter. This is the ghostwriter's dilemma. I get things right often, but I can't touch the things. Shouldn't being right more often than the people that touch this stuff, alone, afford me access? Well, we're working on it.
upvoted
an
article
3 days ago
Article
Tiny Agents: an MCP-powered agent in 50 lines of code
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305
reacted to
julien-c's
post with 🔥
3 days ago
Post
8683
BOOOOM: Today I'm dropping TINY AGENTS
the 50 lines of code Agent in Javascript 🔥
I spent the last few weeks working on this, so I hope you will like it.
I've been diving into MCP (Model Context Protocol) to understand what the hype was all about.
It is fairly simple, but still quite powerful: MCP is a standard API to expose sets of Tools that can be hooked to LLMs.
But while doing that, came my second realization:
Once you have a MCP Client, an Agent is literally just a while loop on top of it. 🤯
➡️ read it exclusively on the official HF blog: https://huggingface.co/blog/tiny-agents
the 50 lines of code Agent in Javascript 🔥
I spent the last few weeks working on this, so I hope you will like it.
I've been diving into MCP (Model Context Protocol) to understand what the hype was all about.
It is fairly simple, but still quite powerful: MCP is a standard API to expose sets of Tools that can be hooked to LLMs.
But while doing that, came my second realization:
Once you have a MCP Client, an Agent is literally just a while loop on top of it. 🤯
➡️ read it exclusively on the official HF blog: https://huggingface.co/blog/tiny-agents
- 1 reply
liked
a
model
3 days ago
upvoted
a
collection
3 days ago
liked
2
Spaces
3 days ago
upvoted
a
paper
3 days ago
reacted to
AdinaY's
post with 👍
4 days ago
Post
3560
2025.1 - DeepSeek entered the scene, backed by High Flyer Quant
2026.1 - IQuest enters the game, backed by Uniquant Quant 📈 and launching IQuest-Coder on huggingface
https://huggingface.co/collections/IQuestLab/iquest-coder
✨ 40B models: Instruct / Thinking / Loop
✨ Loop = MoE-level performance with only ~5% extra training cost
✨ Native 128K context
2026.1 - IQuest enters the game, backed by Uniquant Quant 📈 and launching IQuest-Coder on huggingface
https://huggingface.co/collections/IQuestLab/iquest-coder
✨ 40B models: Instruct / Thinking / Loop
✨ Loop = MoE-level performance with only ~5% extra training cost
✨ Native 128K context
- 1 reply
upvoted
a
paper
5 days ago
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cedricbonhomme's
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5 days ago
Post
2635
With VLAgentIc, you can now use your local Qwen installation via Ollama and leverage the models
CIRCL/vulnerability-severity-classification-roberta-base and
CIRCL/cwe-parent-vulnerability-classification-roberta-base.
The project is available here:
https://github.com/vulnerability-lookup/VLAgentIc
The VLAI Severity and CWE classifiers are available on Hugging Face:
- CIRCL/vulnerability-severity-classification-roberta-base
- CIRCL/cwe-parent-vulnerability-classification-roberta-base
The concept of AI agents—combining models, tools, and orchestration—has become fairly standardized during the last year, but VLAgentIc brings something unique:
- Agents communicate over XMPP, enabling concurrent tasks and asynchronous messaging thanks to the SPADE framework.
- Built-in presence and discovery streamline interactions between components.
- Flexible behaviours make orchestrating AI-assisted security workflows seamless for future connections
- Last but not least, the VLAI Severity and VLAI CWE classifiers are now wrapped as LLM Tools and run entirely locally.
New, more comprehensive agent tools will soon be available, leveraging the Vulnerability-Lookup API and supporting the GCVE project.
The Human-in-the-Loop agent tool will be designed to notify you and request authorization whenever a query to an external service is about to be made—ensuring that, by default, all reasoning and processing stay local on your computer.
VLAI: A RoBERTa-Based Model for Automated Vulnerability Severity Classification (2507.03607)
The project is available here:
https://github.com/vulnerability-lookup/VLAgentIc
The VLAI Severity and CWE classifiers are available on Hugging Face:
- CIRCL/vulnerability-severity-classification-roberta-base
- CIRCL/cwe-parent-vulnerability-classification-roberta-base
The concept of AI agents—combining models, tools, and orchestration—has become fairly standardized during the last year, but VLAgentIc brings something unique:
- Agents communicate over XMPP, enabling concurrent tasks and asynchronous messaging thanks to the SPADE framework.
- Built-in presence and discovery streamline interactions between components.
- Flexible behaviours make orchestrating AI-assisted security workflows seamless for future connections
- Last but not least, the VLAI Severity and VLAI CWE classifiers are now wrapped as LLM Tools and run entirely locally.
New, more comprehensive agent tools will soon be available, leveraging the Vulnerability-Lookup API and supporting the GCVE project.
The Human-in-the-Loop agent tool will be designed to notify you and request authorization whenever a query to an external service is about to be made—ensuring that, by default, all reasoning and processing stay local on your computer.
VLAI: A RoBERTa-Based Model for Automated Vulnerability Severity Classification (2507.03607)
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Spaces
27 days ago