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Humber researcher shares four takeaways from global AI conference

Node read time
2 minutes
A massive auditorium filled with people waiting to watch a presentation on Immersive AI Art.

This year’s GPU Technology Conference (GTC) hosted 900 sessions, 300 exhibitors and tens of thousands of attendees. One of these attendees was Parisa Pouladzadeh, a Humber College researcher and the Program Coordinator of the Faculty of Applied Sciences & Technology's Artificial Intelligence with Machine Learning program.

Parisa attended GTC as part of her research project 'Utilize data analytics to identify common communication challenges for autistic children and develop customized visual and textual content to address these specific issues’.

The project, funded by an NSERC-Applied Research and Technology Partnership (ARTP) grant, centers around the utilization of data analytics to pinpoint prevalent communication challenges experienced by autistic children.

Held in San Jose, California, GTC showcased the latest advancements in GPU (Graphics Processing Unit) technology and its applications across various industries such as artificial intelligence, data science, healthcare and autonomous vehicles.

“Participating in various sessions at GTC covering emerging technologies such as machine learning, deep learning, computer vision, and related fields, as well as attending keynote presentations, provided me with the opportunity to acquire knowledge about cutting-edge research methodologies, algorithms, and applications,” said Parisa.

“Exploring the exhibition area proved beneficial, as it allowed me to discover teaching materials, textbooks, software packages, development kits, and online resources that can be incorporated into our curriculum to enrich the learning experiences of our students.”

Parisa outlined her four key takeaways from the conference, noting that these new announcements in the AI world will impact the ARTP project.

  1. Announcement of new AI super chip
    NVIDIA introduced their new Blackwell chip – the latest, more powerful GPU successor to the company’s Hopper chip.
  2. Introducing NIM
    NVIDIA Inference Microservices (NIM) could transform the future of software development, enabling the assembly of AIs to effectively generate and write code.
  3. Robotics revolution
    Project GR00T, a general-purpose foundation model for humanoid robots, will empower a diverse range of robots to observe and imitate human movements and speech using a robust sensory robotics processing chip.
  4. Advancements in generative AI
    Beyond the Blackwell chip, NVIDIA announced several advancements in their tools for generative AI, which have the potential to revolutionize various industries.

“Engaging with fellow educators, industry professionals, and AI enthusiasts facilitated the establishment of valuable connections, enabling the exchange of ideas and the exploration of potential research collaborations,” Parisa said.