Daniel D. Gutierrez, Editor-in-Chief & Resident Data Scientist, insideAI News, is a practicing data scientist who’s been working with data long before the field came in vogue. He is especially excited about closely following the Generative AI revolution that’s taking place. As a technology journalist, he enjoys keeping a pulse on this fast-paced industry.
Always looking forward to a chance to return to my home away from home of Silicon Valley, I jumped at the opportunity to attend my first-ever hardware focused conference, the 2024 AI Hardware and Edge AI put on by Kisaco Research (#AIHardware2024). The event took place Sept. 9-12, 2024 in beautiful San Jose, Calif., the heart of Silicon Valley. I was eager to learn what innovations were taking place on the hardware side of AI. Boy, I wasn’t disappointed! You mostly hear about all the new advances in GenAI model development, but I see now that we’ll be hearing a lot more about the quick-paced evolution of AI accelerated hardware to support these growing models at scale. AI hardware is advancing quickly and I’m not talking about NVIDIA Blackwell!
After picking up my badge, I checked my schedule of selected sessions to attend, and then instinctively headed into the expo hall containing all the companies exhibiting new technologies. I knew kibitzing with the vendor folks on hand would yield the best use of my time at the show. I learned SO much after speaking to most of the companies present.
Maybe the most important thing I learned, and something I kept hearing over and over, is that “hardware is cool again.” This is because GenAI training and inference have hit somewhat of a brick wall. After all, how many GPUs can you buy? The good thing is I spoke to many companies that are thinking outside of the box by developing alternatives to the GPU, each with a significant capability vector and talent density – think Cerebras, Furiosa, SambaNova, Groq, NeuReality, Etched, plus many others. NVIDIA has a current stranglehold over training (90%) and inference (40%), so the industry is ripe for change. Many of the new accelerated AI hardware solutions cater to inferencing – as they say, training is how you make AI and inferencing is how you use AI. The main thing I gathered from attending this conference is that change is in the wind. NVIDIA better start looking over its shoulder because very soon now the company will have serious competition (not to mention the company’s antitrust worries).
Playing my role as member of the Press, I make a point of making observations. One thing I noticed was the number of job interviews taking place during the show. I saw a number of stand-up interviews taking place right outside the meeting rooms. Additionally, I witnessed a number of strategic meetings taking place between company principals, partners, and investors. In dark corners of the hotel lobby bar area, I overheard plans involving new products, integrations, collaborations, and investment rounds. It was quite invigorating to witness all the excitement, with memories of the heady days of the past, and it led me to the view for how vibrant the AI hardware space has become lately.
You can find a number of recorded speaker presentations from the AI Hardware & Edge AI Summit HERE.
Location and Venue
Silicon Valley was the appropriate location for the conference as most of the companies with their new AI hardware solutions were local to the area.
The 1,300+ attendees were housed in a single venue, the Signia by Hilton Hotel on Market Street. The entire 2nd floor of the hotel’s meeting area was devoted to the show. This space seemed well sized for all concerned. Plus, this hotel was particularly high-tech – I never had to interact with any human during my entire stay as my booking was 100% managed by the hotel’s app (I didn’t even need a key for my room, the app unlocked my door when needed!).
The Exhibition Hall
The exhibition hall was the focal point of the conference. It was routinely packed with companies in their booths along with attendees. In addition, there were overflow booths outside the hall in the adjacent hallways. Walking through the conference area it always seemed jammed with people which to me just increased the excitement.
Here is a hand-selected short list of companies from the conference that I previewed earlier.
The endless coffee and snacks in the expo hall were greatly appreciated. One of the few criticisms I had for the event was the total lack of seating to meet with companies, colleagues, new friends, or even to eat lunch. I noticed that many attendees had to sneak downstairs with their lunch plates/drinks to the hotel lobby to find a place to sit down.
Interviews
My main purpose in attending the AI Hardware & Edge AI Summit was to conduct a number of video interviews with representatives from these companies: Intel Labs, Nscale, MinIO, Hitachi Ventures, Ericsson, and Unilever. Each interview will surface here on insideAI News as an upcoming feature article. All of the interviewees were amazing and such good representatives for their respective companies. They all exhibited vast knowledge of their specialized subject matter. I learned a lot by interviewing them (and I hope you will too!).
The Road Home
I had a great time at this conference. I think the timeliness of the hardware focus for AI was the biggest attraction. I fully intend to do a deep dive on many of the companies I met with. I came away with a new and improved perspective for how the field of AI is advancing.
Waiting for my flight home at San Jose Mineta International Airport (SJC), I felt like I’ll miss “The Valley” once again until my next trip up north (I’m based in Los Angeles). I’m never disappointed with what I take with me when visiting the singular place on Earth where much of AI originates.
I would highly recommend this event to anyone in the AI space, or desiring to enter it. Getting a hardware perspective is important now that hardware is cool again! I believe I’ll have to add this event to my list of annual conferences for sure!
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