GTC is the developer conference for the Era of AI and is all about four days of discovering the latest innovations for startups in over 70 NVIDIA Inception sessions. There are technical training workshops, expert panels, and presentations from leading startups who are disrupting key markets with GPU-accelerated applications. GTC starts with a full day of learning for all technical levels and interests-from general sessions on getting started with GPU computing to product and SDK deep-dive developer talks to hands-on workshops covering AI. It is also an opportunity to kick off your GTC experience with sessions to build our skills with hands-on, and instructor-led training.

I was invited to be one of the speakers at the GTC conference. My session on March 22 covered the topic “NVIDIA Emerging chapter Developer Meetup South east Asia [SE2140]”.

During this online session, we’ll have lightning talks from industry and academia experts and also Interact with Nvidia experts as below.

For more information about the conference itself, you can visit GTC official website #1 AI Developer Conference | GTC March 2022 | NVIDIA

UTM and Cuatro Services Sdn Bhd (Cuatro) has entered into an MOA to execute a pilot project for purpose of defect classification to X-FAB Sarawak Sdn Bhd (X-FAB). Cuatro Services Sdn Bhd has been awarded the contract for the same project from X-FAB. The pilot project only covers a maximum of 25 types of defects on metal layers only. The success of this pilot project will give strong justification for X-FAB to award Cuatro a global contract for improved and complete defect detection to be integrated into the existing production system.

The developed SaaS will expedite the adoption of Artificial Intelligence (AI) technology in the semiconductor Industry. In general, the semiconductor industry does not invest upfront capital in employing AI services. The experience between UTM and Cuatro Services Sdn. Bhd. in solving the X-FAB problem will facilitate the development. Currently, the X-FAB as subject matter expert has provided design requirements and the defect inspection will be used in the local area network within the factory. The cooperation of all involved parties has successfully met X-FAB expectations in terms of defect inspection accuracy. Hence, all the obtained experience and knowledge are ready to support the SaaS for defect inspection to be run in the cloud at UTM.

The same system can also be used by other wafer foundries all over the world such as Silterra, TSMC, SMIC, and Global Foundries through the proposed Software as a Service (SaaS) on Defect Inspection.

On 1st November 2021, we made a site visit to Silterra Malaysia to discuss more the project.

As one of the biggest advancements in technology in recent years, Artificial Intelligence (AI) is set to increasingly disrupt the way industries work now and in the future. In Malaysia, industries as well as research agencies and universities, have been actively involved in applying and carrying out research for advancement in AI Revolution.

Recently, I was invited as a speaker for the program webinar series “Advancement in AI Revolutionizes Industry and Accelerates Research” and the program collaborated with Tenaga Nasional Berhad Research (TNBR). The program as a below:

OUTLINE OF THE TOPIC

1. Introduction
2. Overview Of AI
3. Deep Learning For Computer Vision
4. Smart Cities
5. Medical Imaging
6. AI Platform For Self-Driving Vehicles
7. Big Data In GPU
8. Nvidia EGX – Edge Computing
9. Intelligent Video Analytic
10. AI and Deep Learning Selected Usecase
11. From Our Lab – Case Study

The example of a Case Study from our lab:

Livestock monitoring – to count and cows, cattle, and bull in 5000 acres area. The counting is done using the captured video from the drone and AI- Deep learning is automatically counting. The proposed solution is also should be able to predict livestock behavior. The framework is used to auto-generate asset management report

Automatic Inspection – Drone will capture real-time telco tower asset

With the rise of the Industrial Revolution 4.0 (IR 4.0), the need for computer vision in many applications has become indispensable. In Malaysia, industries as well as research agencies and universities, have been actively involved in applying and carrying out research in this field. A key component in successful computer vision applications is the ability of computer algorithms in making accurate decisions.

Traditionally, machine learning approaches have achieved good performance. Nevertheless, with the advent of deep learning in the past decade, researchers have increasingly focused on taking advantage of the benefits it provides. Thus, due to its higher performance as well as its adaptability, deep learning has become very popular in computer vision applications. In this Summer School, we are proposing topics that cover both the traditional machine learning (ML) and deep learning (DL) approaches, so that researchers will benefit from the strengths of both, whilst also gaining a historical understanding for the need and importance of the transition from ML to DL in modern computer vision. These important topics and their applications in computer vision will be delivered by prominent national and international speakers. Due to the Covid-19 situation, this Summer School will be conducted in a hybrid fashion, catering for both those who prefer face-to-face participation as well as those attending virtually. All lectures and hands-on practicals will be conducted via live online sessions, while poster sessions will be held in the conference room.

Over the 5 days, we propose 6 lecture/tutorial sessions covering various topics of Machine Learning (ML) and Deep Learning (DL) applications in computer vision, 4 hands-on sessions, and 4 other sessions of forums and discussions with relevant industries. 

The list of topics to be covered during the School is as summarized below:

Technical Topics

1. Introduction to Machine Learning – Classical methods
2. Object Recognition/Classification using Classical Methods
3. Fundamental Concepts in Deep Learning
4. Variations and Advantages of Deep Learning Frameworks
5. Object Recognition/Classification using Deep Learning
6. Transfer Learning and Reinforcement Learning
7. Deep Learning for Video Processing
8. Deep Learning Future and the Way Forward (Forum)

The 5-day hybrid program will cover all aspects of ML and DL, and their applications in computer vision. To gain better understanding as well as make the school more exciting and interactive, hands-on sessions will be conducted during the afternoon time slots. For ML, the school will start with an introduction before covering more advanced topics such object recognition and classification. Similarly, for DL, the school will initially cover the fundamental aspect of DL before proceeding with more advanced topics such as deep convolutional neural network, transfer and deep reinforcement learning, and deep learning architectures. Besides the regular lecture sessions, there will also be online live discussions or forums between the participants and speakers to discuss particular topics of interest in computer vision. There will also be poster sessions for participants to showcase their current work. At the end of the school, participants will be exposed to the fundamental and advanced knowledge of DL and big data, and their applications in computer vision. The expected outcome of this Summer School would be that participants would be able to create better solutions and explore greater perspectives in their domains of interest within this growing field of research.

Coordinator for Japan-Asia Youth Exchange Program in Science (SAKURA Exchange Program in Science) at Tokyo City University Japan (30th July -8th Aug 2017). The program is a platform for student exchanges between Asia and Japan of youths. They will play a crucial role in the future field of science and technology through the close collaboration of industry-academia-government by facilitating short-term visits of competent Asian youths to Japan. This program aims at raising the interest of Asian youths toward the leading Japanese science and technologies at Japanese universities, research institutions, and private companies. The program aims to invite a student to experience the research in a Japanese-style laboratory, a family-like organization composed of professors, graduate students, and undergraduate students. Invited students will experience a aseries of research activities from problem discovery to problem resolution by problem-based learning (PBL).