NVIDIA CUDA Virtual Connect With Experts Event Information

We are starting a monthly virtual event where CUDA enthusiasts can connect directly with a panel of real-life CUDA developers at NVIDIA. This is a chance to meet some of the people designing and implementing your favorite CUDA drivers, kernels, libraries and tools; and ask questions related to your project or work.

Event Information:

When?

Friday, September 27, 2024 at 10-11:30am PT

What?

This month, we will be discussing the CUDA Python ecosystem. You will have the opportunity to ask questions via chat about topics like CuPy, Numba, and other Python libraries to our LIVE panel of CUDA Python experts.

Who can Attend?

CUDA and Python developers of all levels and backgrounds.

Where?

Join us on NVIDIA’s Microsoft Teams Instance here

Less known features of C
https://jorenar.com/blog/less-known-c

How AI is Changing Coding and Education
FREE STANFORD WEBINAR

October 9, 2024 | 11:00-11:45 am PT

Registration

Installing Lama locally
Video
https://ollama.com/library/llama3.2

bash
sudo ufw allow 1143/tcp 
curl -fsSL https://ollama.com/install.sh | sh     

# v3.1, 8billions parameters
ollama pull llama3.1:8b
ollama run llama3.1
# v3.2, 3 billions parameters
ollama pull llama3.2
ollama run llama3.2
# https://127.0.0.1:11434/ to check ollama is working

Haiping Huang - Statistical Mechanics of Neural Networks

#book

NotebookLM from Google has new feature to make a podcast from provided resources, it's pretty cool to try.

Video for more information.

Daily dose of data science archive 2024

How to use open wbui and run LLM models locally:
The cleanest method is to use docker, So if you have installed docker on your local machine and also have installed olama just need to download the image from docker with the following command:

docker run -d -p 3000:8080 --add-host=host.docker.internal:host-gateway -v open-webui:/app/backend/data --name open-webui --restart always ghcr.io/open-webui/open-webui:main

find more options from here.

I uploaded a 360 page book and asked some questions, seems work fine.
Every thing runs locally without need to connect internet after getting the models.

Demo credit: Tarfandoon

Equivalently or even easier :

https://lmstudio.ai/

I am still trying this one, Got some issue reading articles in PDF. Only read Citation part :| .

Copilot now has a free version. unfortunately need vpn from Iran, we are banned 🤷‍♂.

Link

https://centuri-livingsystems.org/recruitment/

PhD and postdoc Applications Now Open
The deadline for submission is January 27.
CENTURI, Marseille, France

#j2p: A simple Python package to convert Jupyter notebooks to Python scripts.

If you find yourself needing to convert a notebook to a Python script, you likely turn to nbconvert. However, this often results in a script with annoying cell separators. Consequently, you may try manually removing these extra lines to focus solely on the code itself.
This tiny package provide a cleaner solution

## Installation

pip install ju2py

## Usage

j2p example.ipynb [output.py]

output name is optional.

P.S:
There is already a package (not by me) for the reverse action

pip install p2j
p2j example.py

GitHub: https://github.com/Ziaeemehr/j2p

Our new research article from PNAS investigates how localized brain manipulations, such as lesions or silencing, impact the entire brain's functional connectivity in mice. Combining fMRI data with computational modeling, the study reveals that these targeted interventions lead to widespread network reconfigurations, sometimes decreasing and other times increasing connectivity. We used personalized brain simulations to explore the underlying mechanisms of this phenomenon, known as diaschisis, finding that alterations in local neuronal excitability drive these global changes. The findings offer insights into understanding the broad effects of focal brain disruptions and could inform the development of more precise therapeutic strategies targeting brain dynamics. The data and analysis tools are publicly available.

https://www.pnas.org/doi/10.1073/pnas.2405706122

ام‌اس (Multiple Sclerosis) یک بیماری خودایمنی است که سیستم عصبی مرکزی را درگیر می‌کند و منجر به ضایعاتی در غلاف میلین می‌شود. این آسیب به میلین باعث کند شدن سرعت هدایت سیگنال‌های عصبی می‌شود که به آن تاخیر هدایتی می‌گویند.
هدف اصلی این کار، برآورد ارتباط بین شدت ضایعات میلین در هر بیمار و افزایش ناشی از آن در تاخیرهای هدایتی در سراسر راه‌های عصبی آسیب‌دیده بود. چگونگی ترجمه دقیق شدت ضایعات ساختاری میلین به کند شدن تاخیرهای هدایت عصبی تاکنون ناشناخته بود.
در این مطالعه از داده‌های ۳۸ نفر (۲۰ فرد سالم و ۱۸ بیمار مبتلا به ام‌اس) استفاده کردیم که شامل ثبت فعالیت مغزی با مگنتوانسفالوگرافی (MEG) و تصویربرداری رزونانس مغناطیسی (MRI) برای تحلیل ساختار مغز و ضایعات ماده سفید بود.
همچنین از مدل‌های محاسباتی بزرگ‌مقیاس مغز و تکنیکی به نام استنتاج مبتنی بر شبیه‌سازی (Simulation-Based Inference - SBI) استفاده شده است.
ادامه …
LinkedIn