A Look at What's Next in AI, Deep Learning and Beyond

While deep learning (DL) is a complex and continually evolving area, developers can learn and connect with industry experts through a plethora of online resources. NVIDIA is sharing expertise through their extensive catalog of resources; on-demand sessions, demos, and more, and at their GTC conferences. 

Staying ahead of a sharp curve

Over the last few decades, AI has rapidly evolved from a science fiction dream to an everyday notion used in applications as broad as home security and space exploration. Improved methods of data analysis and GPU-accelerated computing are now solving problems that seemed well beyond our reach only a few years ago. 

Learning the fundamentals of accelerated data analytics, grasping new problem-solving methods, and understanding how deep learning is transforming every industry is important for developers at all career stages. Due to the rapid pace of innovation, engineers must stay ahead of the deep learning curve within their fast-paced industries. 

Fortunately, there is a wealth of free knowledge in the forms of podcasts, webinars, keynotes, and workshops that can assist in demystifying these complex topics.

In this article, we explore key deep learning resources designed for all technical levels from NVIDIA, available from their on-demand site as well as relevant sessions from their global conference for developers, GTC. Note some sessions require registration to view. 

Demystifying deep learning

Advances in hardware have driven explosive interest in deep learning. In 2009, NVIDIA was involved in what was called the “big bang” of deep learning, as deep-learning neural networks were trained with NVIDIA Graphics Processing Units (GPUs) for the first time. That year, Andrew Ng, one of the world's most influential computer scientists, determined that GPUs could increase the speed of deep-learning systems by about 100 times. Suddenly, training a four-layer neural network, which had previously taken several weeks, took less than a day.

Unlike traditional software engineering, humans are not programming the entire instructions to be executed by the machines. AI-driven solutions are about programming instructions for the machine to learn from the input data. This requires a new set of tools and technologies. In the Deep Learning Demystified session held on March 21, as part of GTC 2022, Ozzy Johnson, Director, Solutions Engineering shared insights into the key challenges organizations face in adopting this new approach and how to address them. The talk also discussed the latest tools and technologies, along with training resources, that can help deliver breakthrough results. 

Other relevant sessions for new developers to the space include Introduction to "Learning Deep Learning" by Magnus Ekman, Director, Architecture, NVIDIA. 

Building a career in AI

AI is everywhere. No matter what industry. Contrary to the misconception that AI is all about maths and computing, working with AI requires interpretation and artistic skills to think differently and solve problems programmatically. Thus, careers in Artificial Intelligence often require a combination of mathematics, computer programming, and creativity. Fortunately, each of these aspects can be strengthened via participation in online courses, workshops, and by attending events such as GTC.

The world is already enjoying the benefits of incredible breakthroughs in AI, from better camera software on your phone to predictive cancer diagnosis. However, what has become clear in recent years is that the purpose and core of AI is only as good as the programmers behind it - and that meaningful diversity within the industry is essential for AI to remain accessible and relevant for all. 

According to World Economic Forum data, only 22% of AI professionals globally are women, and fewer than 1% of the applications received by companies for expert-level positions come from women. Actively working to close the gender gap in AI will contribute to the growth of AI and contribute to the lowering of the algorithmic gender bias by having more women training the algorithms. Everyone in the industry should check out the session by Louis Stewart, head of strategic initiatives for NVIDIA Developer Ecosystem, about how to get more women into AI available on-demand from the 2021 November GTC. 

Further, at the most recent GTC there were several sessions dedicated to women in deep learning. The Empowering Women in Data Science session showcased the success stories of several women using NVIDIA products helping them trail-blaze future opportunities for next generation of women in data science. 

Finding your AI niche

The potential of AI can be explored across all aspects of our lives, and for that reason, finding a niche for developers to focus on and become an expert in can be difficult. For any developers looking to explore various aspects or angles of deep learning that they might not have been exposed to before may find value in watching previous GTC sessions available on the NVIDIA on-demand page. Developers can engage with professionals across the AI spectrum, including the growing areas of Conversational AI and Machine Learning Inference. For the upcoming GTC, NVIDIA has curated a selection of sessions, specifically for students and new graduates who are exploring how to build or switch to a career in AI.

Uplevel your skills with hands-on developer training

Listening and reading are proven ways to expand your knowledge, but nothing beats learning by doing. Hands-on, instructor-led training sessions are available at GTC conference's to help you stay up to date with the latest SDKs, hardware, and deep learning trends. All attendees get access to two-hour workshops at no further cost as part of their GTC registration. A full-day workshop is also available in which participants can earn the NVIDIA Deep Learning Institute certificate. Stay tuned to  NVIDIA socials for workshop news. 

GTC

GTC is a global AI conference for developers that brings together developers, engineers, researchers, inventors, and IT professionals. Attendees hear from some of the leading experts across industries about how the power of AI is redefining the world of tomorrow. Find out more here.

This article was significantly contributed to by Sreekiran A R. 

About the sponsor: NVIDIA

NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world.