Lessons From Our First AI Dev Conference How our learners began building their way to AI in everything at AI Dev 25 Tags

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Top left: attendees watch a presentation. Top right: crowd at a developer booth. Bottom left: fortune cookie says ‘Build baby build!’ Bottom right: staff check in attendees.
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Dear friends,

Last Friday on Pi Day, we held AI Dev 25, a new conference for AI Developers. Tickets had (unfortunately) sold out days after we announced their availability, but I came away energized by the day of coding and technical discussions with fellow AI Builders! Let me share here my observations from the event.

I'd decided to start AI Dev because while there're great academic AI conferences that disseminate research work (such as NeurIPS, ICML and ICLR) and also great meetings held by individual companies, often focused on each company's product offerings, there were few vendor-neutral conferences for AI developers. With the wide range of AI tools now available, there is a rich set of opportunities for developers to build new things (and to share ideas on how to build things!), but also a need for a neutral forum that helps developers do so.

Based on an informal poll, about half the attendees had traveled to San Francisco from outside the Bay Area for this meeting, including many who had come from overseas. I was thrilled by the enthusiasm to be part of this AI Builder community. To everyone who came, thank you!

Other aspects of the event that struck me:

  • First, agentic AI continues to be a strong theme. The topic attendees most wanted to hear about (based on free text responses to our in-person survey at the start of the event) was agents!
  • Google's Paige Bailey talked about embedding AI in everything and using a wide range of models to do so. I also particularly enjoyed her demos of Astra and Deep Research agents.
  • Meta's Amit Sangani talked compellingly as usual about open models. Specifically, he described developers fine-tuning smaller models on specific data, resulting in superior performance than with large general purpose models. While there're still many companies using fine-tuning that should really just be prompting, I'm also seeing continued growth of fine-tuning in applications that are reaching scale and that are becoming valuable.
  • Many speakers also spoke about the importance of being pragmatic about what problems we are solving, as opposed to buying into the AGI hype. For example, Nebius' Roman Chernin put it simply: Focusing on solving real problems is important! 
  • Lastly, I was excited to hear continued enthusiasm for the Voice Stack. Justin Uberti gave a talk about OpenAI’s realtime audio API to a packed room, with many people pulling out laptops to try things out themselves in code! 

DeepLearning.AI has a strong “Learner First” mentality; our foremost goal is always to help learners. I was thrilled that a few attendees told me they enjoyed how technical the sessions were, and said they learned many things that they're sure they will use. (In fact, I, too, came away with a few ideas from the sessions!) I was also struck that, both during the talks and at the technical demo booths, the rooms were packed with attendees who were highly engaged throughout the whole day. I'm glad that we were able to have a meeting filled with technical and engineering discussions.

I'm delighted that AI Dev 25 went off so well, and am grateful to all the attendees, volunteers, speakers, sponsors, partners, and team members that made the event possible. I regretted only that the physical size of the event space prevented us from admitting more attendees this time. There is something magical about bringing people together physically to share ideas, make friends, and to learn from and help each other. I hope we'll be able to bring even more people together in the future.

Keep building!

Andrew

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