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Fein-Lines: AI, Big Data, and A Lot of Trade Shows

There have been so many events and trade shows in the past few months, and with them, many important announcements and demonstrations and processes. Now, it’s debatable whether there are too many trade shows today, but these shows and events do allow companies to showcase their truly remarkable technologies, processes, and devices.

I’ve dedicated much of my column space to covering some of these shows and the advances we’ve learned about at these shows. One of the most significant is the inclusion of artificial intelligence into almost every facet of our consumer-driven lives. Here I’ll mention just two shows that have really captured my attention.

HPE Discover 2024
Hewlett-Packard and NVIDIA recently announced NVIDIA AI Computing HPE (Hewlett Packard Enterprise). Antonio Neri, HPE president and CEO, said, “Our world is at an unprecedented inflection point.” Jensen Huang, co-founder and CEO of NVIDIA, demonstrated how AI-led transformations increased productivity for enterprises and now enabled the world to accelerate the rate of discovery and innovation. “The future is now, and HPE is leading the way,” he said. “Never before have NVIDIA and HPE integrated our technologies so deeply, combining the entire NVIDIA AI computer stack along with HPE’s private cloud technology to equip enterprise clients and AI professionals with the most advanced computing infrastructure and services to expand the frontier of AI.”

I have attended many of Huang’s presentations and keynotes by Jensen, as well as having the opportunity to discuss these topics with him personally. Getting to speak with him in person gives you a far superior opportunity to learn and understand.

AWE Show
Augmented and virtual reality feel like they have literally traveled light years since the first AWE event. I’d say this is one event where you can get a good idea of what is now possible, but by following its progress online, you get to see the amazing progress of XR capabilities. Even at that, it’s still just a modest understanding of what XR can now accomplish in so many areas.

Here are some YouTube videos that I’ve found to be particularly useful for learning more about these topics:

• PANEL: Racing Beyond Limits: The Next Lap in XR  (XR Racing)
• PANEL: Spatial Data Revolution — Spatial computing with AI and XR
• Creating the Immersive Future
• Magic, Quests, and Visions: Moving Beyond the Fairy Tales, by Tamir Berliner

As I mentioned, being at these shows gives me a front-row view of the technological developments we see in action today. Here are some of my favorite developments:

1. Customized chatbots: In 2024, generative AI will become more accessible to non-tech users. Google and OpenAI are developing user-friendly platforms that allow people to create customized chatbots without coding skills. These chatbots can process not only text but also images and videos, opening up new possibilities for applications¹.
2. Multimodal AI models: The next breakthrough will likely come from multimodal AI models. These models combine multiple senses, such as computer vision and audio, to interpret information. Integrating language models into other AI systems as they sense the world will be a key focus².
3. Planetary-Scale Computing: Next-generation AI will rely on planetary-scale computing systems. Technologies like neuromorphic and quantum computing will unlock unprecedented performance levels beyond what current systems can achieve³.

Multimodal AI is an advanced form of artificial intelligence that can understand and create content across various modalities simultaneously. Imagine a model that processes text, images, and audio together, like a symphony of information. Here’s how it works:

1. Modalities: Modalities refer to different types of data, such as text, images, audio, and video. Multimodal AI integrates and analyzes these diverse modalities to provide a comprehensive view of the world⁴.
2. Neural networks: Multimodal AI relies on neural network architectures. These networks combine information from various sources, allowing the model to generate richer, contextually relevant outputs. For example, it can describe an image using both visual and textual cues4.
3. Challenges and opportunities: While powerful, multimodal AI presents complex challenges. Aligning different modalities and ensuring seamless fusion is no small feat. However, the opportunities for enhancing human-machine interaction are immense⁴.

Just consider what the rapid advances in AI and the abilities of XR /VR devices now being combined with AI and used in a field such as robotics will make possible. Science fiction of the 1980s will be very common in the 2030s.

The Combination of AI and Robotics
Two topics that are moving closer are robotics and AI. Consider a futuristic robot powered by advanced AI in the 2030s. However, AI and robots have some important distinctions. AI is computer science that provides a level of simulated human intelligence in computers and their computer-connected machines. Robots are physical, mechanical devices that will have the ability to do physical tasks, such as cleaning your home, protecting your property, painting a wall, or making and serving your breakfast. In factories, we will see more robots doing activities from assembling cars to shuttling products in a warehouse. Will the next few decades provide the ability to provide sci-fi-like robots? Will they use AI by incorporating an AI database into their “body” or will they be able to connect into an AI cloud that supports Generative AI workloads kind of like a huge global robotic brain.

Generative AI refers to a category of AI algorithms that generate new outputs based on the data they've been trained on. Unlike traditional AI systems that are designed to recognize patterns and make predictions, Generative AI creates new content in the form of images, text, audio, and more.

What does it do best? It excels in processing and generating textual content such as producing creative documents and even writing articles, generating creative documents and even creating code. Generative AI continues to evolve, and its use continues to grow. It will grow even faster as new advanced neural networks become more available.

In any case, this is a complex and growing topic and I’ve barely touched the surface. This is going to be of great interest to many in the coming decade, so stay tuned. If you can attend one of these shows for yourself, I highly recommend it. But there are other ways to stay on top of the latest advances by following the keynotes and presentations online, and reading the coverage in I-Connect007 publications.

References

1. “What’s next for AI in 2024” by Melissa Heikkila and Will Douglas Heaven, MIT Technology Review.
2. “Where will AI go next?” by Melissa Heikkila, MIT Technology Review.
3. “Powering the next generation of AI,” MIT Technology Review, May 9, 2022.
4. “Multimodal: AI’s new frontier,” by MIT Technology Review Insights.

Dan Feinberg is a technical editor for I-Connect007.