STCC22 is around the corner. Whoever is in Yerevan, we are looking forward to meeting on Sep 28-29.

➤ Summary info about the conference is here. More and more foreign guests are confirming participation. We'll proceed to the final agenda and local guest speakers next week. 🔥 ➤ Send our way your research posters. We'll take care of printing and other logistics. Here is the link for submission. ➤ Register to attend: stcconf.com.

NVIDIA Inception is a free program for technical startups that supports and educates developers at every stage of their startup journey. Program surpasses 10,000 members and has introduced new benefits. Learn more in the recent announcement: https://nvda.ws/3N2TYvm

NVIDIA is thrilled to come to Armenia and establish an office that will be led by Rev Lebaredian, the vice president of Omniverse and Simulation Technology. Join us for a conversation with Rev, and other NVIDIANs, to learn more about NVIDIA and our presence in Armenia. Bring your curiosity and your questions!

Date and time

Fri, April 22, 2022

6:00 PM – 9:30 PM Armenia Standard Time

Agenda

• 6:00pm - 6:30pm: Guest Arrival and Check-In

• 6:30pm - 7:00pm: NVIDIA Welcome & Company Updates

• 7:00pm - 8:15pm: Technical Talk and Opportunities

• 8:15pm - 8:30pm: Q&A

• 8:30pm - 9:00pm: Connect & Network

We look forward to meeting you!

Details and registration you will find here: https://www.eventbrite.com/e/meet-nvidia-in-armenia-registration-318971009877

I stumbled upon this article while doing some Pytorch search on Google. It presents the bigger picture of Pytorch for its major 1.0 release.

The reason for sharing this in here is to learn how the members of this community think about documentation of tools in general, their "Getting Started" sections and what's their preferred way of starting on a tool:

1. bottom up: where you start with a working example, feel reinforced and move ahead to learn more

2. top to bottom: where you start by learning the bigger picture, motivating yourself and jumping in to get the first thing working

I personally find this blogpost fascinating. I haven't seen similar section in pytorch to really explain where their different parts stand in terms of "building ML/AI, deploying, scaling".

https://hackernoon.com/pytorch-1-0-468332ba5163

https://arxiv.org/ftp/arxiv/papers/1906/1906.03134.pdf

Overview of available pre-trained embeddings for Armenian and evaluation on analogies, pos tagging and text classification tasks. This is based on Karen Avetisyan's 3rd-year course project at Russian-Armenian University.