javadtaghia (Javad Taghia

reacted to their post with 🚀 2 months ago

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221

We have published a complete paper about AetnaMem
Check it out here.
Please refer to the technical paper below.
https://github.com/aetna000/aetnamem/blob/e24d5aa74e62dbebeeb28a2e49b5c4d2006bbb4d/paper/aetnamem-control-plane.pdf

Check the benchmark

https://huggingface.co/spaces/Aetna000/MemoryStackBench

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replied to their post 6 months ago

https://en.wikipedia.org/wiki/Wikipedia:Signs_of_AI_writing

posted an update 8 months ago

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221

We have published a complete paper about AetnaMem
Check it out here.
Please refer to the technical paper below.
https://github.com/aetna000/aetnamem/blob/e24d5aa74e62dbebeeb28a2e49b5c4d2006bbb4d/paper/aetnamem-control-plane.pdf

Check the benchmark

https://huggingface.co/spaces/Aetna000/MemoryStackBench

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replied to ZennyKenny's post 8 months ago

I have created https://huggingface.co/spaces/telcom/ResumeQA if someone wants to use or at least get some inspiration

reacted to ZennyKenny's post with 👍 8 months ago

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😎 My new personal website is live! Check out https://kennethhamilton.me to chat with an LLM about my professional skills and personal projects.

🙈 Think of it like a really, really vain version of ChatGPT.

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replied to ZennyKenny's post 8 months ago

love the idea. I heard about this approach in https://www.youtube.com/watch?v=0teZqotpqT8

Stop Competing With 400 Applicants. Build This in One Weekend (Yes, there's a no code option too!)

reacted to AdinaY's post with 👍 8 months ago

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After a VLM, StepFun dropped a new audio model: Step-Audio-R1.1, enabling thinking while speaking 🔥

stepfun-ai/Step-Audio-R1.1

✨ Apache 2.0
✨ Combines dual-brain architecture and acoustic-grounded reasoning to enable real-time dialogue with SOTA-level reasoning

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posted an update 8 months ago

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MAD-GRPO: https://huggingface.co/blog/telcom/mad-grpo
In R1-Zero-Like Training *, Dr.GRPO treats GRPO’s by dropping std, but that often comes with a hidden side effect: length-weighted updates that can nudge model toward verbosity.
MAD-GRPO provides robust scale (MAD + epsilon) per-token normalization stability without verbosity bias.

*https://huggingface.co/papers/2503.20783

reacted to their post with 👀 8 months ago

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215

CAQBI Index
is like a credit score for how an AI understands a concept.
Please check
https://huggingface.co/blog/telcom/caqbi

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reacted to AdinaY's post with 👍 8 months ago

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Wechat AI is shipping!

WeDLM 🔥 A new language model that generates tokens in parallel, making it faster than standard LLMs , with the same Transformer setup!
https://huggingface.co/collections/tencent/wedlm

✨ 7B/8B - Base & Instruct
✨ Apache 2.0

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reacted to kanaria007's post with 👍 8 months ago

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2009

✅ New Article: *PoC Architecture for Education & Developmental Support*

Title:
🎓 Building an SI-Core Wrapped Learning Companion - PoC architecture for education and developmental support
🔗 https://huggingface.co/blog/kanaria007/poc-architecture-for-education-development-support

---

Summary:
Most “AI tutors” are built as *LLM-first* systems. This article flips the default:

* The LLM is treated as an *untrusted proposal engine*
* *SI-Core owns* observation, consent, ethics, memory, and rollback
* Teachers and guardians get *real oversight*, not just chat transcripts

Scoped intentionally to *one subject × a small cohort (10–30 learners)*, this is a PoC you can actually ship—and audit.

> Don’t ask: “Can an AI replace teachers?”
> Prove: “Can we make an AI companion *safe, explainable, and governable* for real learners?”

---

Why It Matters (for AI on real stacks):
• *Consent & accommodations* are first-class (especially for minors / neurodivergent learners)
• *Ethics decisions are logged* (ALLOW / DENY / ESCALATE) with traceable reasoning
• “*Why this?*” explanations are built in for learners—and deeper inspection for adults

---

What’s Inside:
• A minimal reference architecture (frontend → SI-Gate → ethics/memory/logging → LLM APIs)
• Non-negotiables for the pilot (SI-wrapped LLM, Effect Ledger, ethics overlay, dashboards)
• Failure modes + safe-mode behavior
• Implementation checklist + rough effort/cost ballparks (kept explicitly non-normative)

---

📖 Structured Intelligence Engineering Series
A deployable pattern for taking today’s LLM tutor ideas and making them *auditable, overrideable, and rollback-safe*.

replied to their post 8 months ago

https://huggingface.co/blog/telcom/caqbi

reacted to paulpham157's post with 😎👍 8 months ago

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1294

This isn't really related, but... do people generally prefer dark themes or light themes?

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reacted to Fishtiks's post with 👍 8 months ago

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2472

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 monetizes 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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reacted to Nymbo's post with 👍 8 months ago

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3720

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.

reacted to Reality123b's post with 😎 8 months ago

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Happy birthday to me!!!

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reacted to tsungyi's post with 👍 8 months ago

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🎉 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

reacted to dhruv3006's post with 👍 8 months ago

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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/

reacted to sergiopaniego's post with 👍 8 months ago

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2355

New GRPO + TRL free Colab notebook out! 🔥

Fine-tune 7B+ models on T4 GPUs thanks to a ton of memory optimizations for GRPO

7B model uses only 9.2 GB VRAM (~7× reduction) 🤯

Try the notebook here 👉 https://colab.research.google.com/github/huggingface/trl/blob/main/examples/notebooks/grpo_trl_lora_qlora.ipynb

Javad Taghia | PhD

AI & ML interests

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Javad Taghia | PhD

AI & ML interests

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