Daniel D. Gutierrez, Editor-in-Chief and Resident Data Scientist at insideAI News, is an experienced data scientist who has been working in the field long before it became widely popular. He is especially excited to closely follow the ongoing generative AI revolution. As a technology journalist, he enjoys keeping up with the rapid developments in this fast-paced industry.
I was eager to return to my hometown in Silicon Valley, so I seized the opportunity to attend my very first hardware-focused event: the AI Hardware and Edge AI 2024 conference (#AIHardware2024) organized by Kisaco Research. The conference took place from September 9-12, 2024, in the tech hub of San Jose, California, right in the heart of Silicon Valley. My goal was to discover the latest innovations in AI hardware, and I certainly wasn’t disappointed! While most discussions often focus on breakthroughs in generative AI model development, it’s clear that the spotlight is shifting toward the rapid advancements in AI acceleration hardware needed to support these expanding models. The progress in AI hardware is astonishing, and it’s not just about NVIDIA’s Blackwell technology!
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After picking up my badge, I checked the schedule for the sessions I planned to attend and instinctively headed to the exhibit hall, where companies showcased cutting-edge technology. I knew that engaging with the vendors would make the most of my time at the event, and after speaking with many of the companies, I gained valuable insights.
One of the key takeaways from these conversations, which I heard repeatedly, is that “hardware is cool again.” This resurgence in hardware interest is due to bottlenecks in GenAI training and inference processes—after all, there’s only so much you can do with GPUs. The exciting news is that many innovative companies are pushing beyond GPUs, developing alternative solutions with impressive capabilities and talent—firms like Cerebras, Furiosa, SambaNova, Groq, NeuReality, Etched, and more. With NVIDIA dominating both AI training (90%) and inference (40%), the industry is hungry for new approaches. Many of these emerging AI hardware solutions are geared towards inference, highlighting the saying, “Training is how you make AI; inference is how you use AI.” The main message I took away from the conference is that change is coming fast. NVIDIA should start preparing for stiff competition, not to mention the possibility of antitrust scrutiny.
As a media attendee, I took time to observe the behind-the-scenes activity. One interesting aspect I noticed was the number of job interviews happening throughout the event, alongside talk show-style interviews just outside the conference room. I also saw numerous strategy meetings between CEOs, partners, and investors. In the dim corners of the hotel lobby bar, I overheard discussions about new products, integrations, partnerships, and funding rounds. Witnessing all of this energy reminded me of the tech boom days and underscored how vibrant the AI hardware space has become recently.
For those interested, you can find many of the recorded talks from the AI Hardware and Edge AI Summits here.
Location and Venue
Silicon Valley was the perfect setting for this event, as most companies pioneering AI hardware solutions are based in this region.
More than 1,300 attendees gathered at the Hilton Signia hotel on Market Street, with the entire second floor of the hotel’s conference space dedicated to the event. The venue catered to everyone’s needs, and the hotel itself was impressively high-tech. During my stay, I didn’t have to interact with anyone; everything was managed through the hotel’s app, even unlocking my room door!
Exhibition Hall
The exhibition hall was the centerpiece of the conference, bustling with activity. The booths were packed with both companies and attendees, and even the corridors outside the hall were crowded with overflow booths. Walking through the area, I could feel the energy—it was constantly full of people, adding to the overall excitement of the event.
I’ve hand-picked a list of standout companies from the conferences I previewed earlier.
The coffee and snacks provided in the exhibit hall were excellent. However, one of my few critiques of the event was the limited seating. It was challenging to find spots to meet with companies, network with colleagues, or simply enjoy lunch. I noticed many attendees had to head downstairs with their trays and drinks to find seating in the hotel lobby.
Interviews
The main reason I attended the AI Hardware and Edge AI Summit was to conduct several video interviews with key representatives from companies like Intel Labs, Nscale, MinIO, Hitachi Ventures, Ericsson, and Unilever. Each interview will be featured in upcoming articles on insideAI News. All of the interviewees were excellent representatives of their companies, sharing deep insights into specialized topics. I learned a great deal from these interviews, and I’m sure you will too once they are published!
The Road Home
I thoroughly enjoyed my time at the AI Hardware and Edge AI Summit. The conference’s focus on AI hardware felt especially timely and relevant, which made it a major highlight for me. I’m now planning to dive deeper into many of the companies I connected with and have gained a much clearer perspective on the current developments in the AI space.
As I waited for my flight home at San Jose Mineta International Airport (SJC), I couldn’t help but feel nostalgic about leaving Silicon Valley once again until my next visit (I’m based in Los Angeles). Every time I visit this epicenter of artificial intelligence innovation, I leave feeling inspired by what I’ve learned.
I highly recommend this event to anyone involved in AI or looking to break into the field. With hardware becoming a key part of the conversation again, understanding the hardware angle is essential. I’m confident this summit will become a staple on my annual conference list!
