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April 30 - May 1, 2025
North Javits Center | New York City

Data Universe 2024: Highlights and Quotes We’re Still Repeating

The first Data Universe event took place in NYC on April 10-11, 2024. DataVengers assembled, datalympics happened, a beautiful, squidgy, blue Narwhal roamed free. And we learned a lot. Here are some of our highlights and the quotes we just can’t get out of our head.

Data Universe was designed to bring people together and start a new kind of discussion about the role of data in business and society. It promised two unforgettable days of expectation-defying content. And oboy did it deliver.

There was, inevitably, too much to cover in one blog. So, while we’ll be exploring the tech side in upcoming articles, podcasts, and webinars, this is what we loved about the sessions that touched on the interplay between technology and people – less gray area, more incredibly vivid (and complex, and developing) spectrum.

How we got here and how we get there

Data Universe conference chair, Alistair Croll, curated a packed day one keynote program about how we got to today – today being, as he put it, “a consciousness upgrade of historic proportions”. While his day two curation spoke to where we might go next and the mindset we’ll need to get there.

“Data, and the AIs that feed on it, represent a massive change in society. The only thing we need is plasticity – the ability to adapt to those changes.”

How you get to that mindset was very much on the, um, mind of bestselling author David McRaney, who had challenging questions for everyone in his hugely engaging session. It turns out we humans are not perfectly flawed and cutely irrational, we’re biased and lazy. “You don’t make the decision that’s best, you make the decision that’s easiest to justify.” The solution? “Encourage people to argue and argue well – shoulder-to-shoulder, not head-to-head… Groups of three to five make better decisions.”

Bringing your people with you

People were central to many of the event’s themes. If you want to bring them along with you on the AI journey, said Microsoft’s Effie Kilmer, “give everyone the ability to see the data. When they can see it and use it and understand its value, they will take care of it.”

Databricks’ Robin Sutara picked up on the theme, suggesting the tech itself might hold the answer: “Make things easier for people. That’s why generative AI and natural language models are so exciting.”

While Nara Logics’ Jana Eggers recommends asking a very important question: “Why are we giving AI all the fun jobs?” She’s right, of course. I can’t remember the last time anyone asked me to make a demotivated country song with epic bass.

The future is here, but it’s not immutable

Former Amazon VP Joseph Sirosh showed us just how quickly everything is moving – his presentation included Devin, the world’s first fully autonomous AI software engineer, which uses AI to build AI – and how much quicker it’s going to get.

“We have LLMs that can now invent quantum algorithms. That is changing and expanding the scope of human innovation.”

Addressing exactly how wide that scope of innovation is, and how wide it could be, was Columbia University’s Alexis Wichowski. She had some challenging questions about the homogenous worldview informing a lot of tech creation. And some solutions to make it better – learn about more lives, be where you’re the different one, invest in startups with life-balanced co-founders. To willfully misquote Apple: Don’t just think different, invest different. 

And a few of our favorite things

The always excellent Dr. Serena Huang got a GenAI to apologize – but it did suggest that perhaps she hadn’t spoken correctly. We had to invent politics before we invented the non-apology. GenAI is skipping whole evolutionary stages.

Peggy Tsai wanted to start a conversation about unstructured data quality metrics… “If anyone knows what might they be?” We can relate.

While Jeremy Edberg had this advice on how to start a conversation about delivering uptime and resiliency in an LLM world: “Reliability is a balance between reliability and money. Infinite money equals infinite reliability. So, who has infinite money? No? Then we have some difficult decisions to make…”

And finally this, from an unscheduled chat on the Emerging Tech, Society & Ethics stage about discrimination in AI, Elena Yusonov: “We must have recourse and we don’t have it now, which is why we don’t have trustworthy AI.” Alistair Croll: “So there should be a legal statement – this thing involved AI, and therefore you should have recourse?” Shingai Manjengwa: “No, people need to assume AI is being used.” 86% of US adults consume news online. This gives us many feelings.