7 lessons from the Tech Pulse event on Quantum+AI

Representing academia, industry, and the public sector, panelists Fred Chong of the University of Chicago; Sierra Clouse of deep-tech venture firm Barclo; Kristi Dula of the State of Illinois Office of Entrepreneurship, and Innovation, and Technology; and David Kremer, AI for Quantum lead at IBM, “are the people not just thinking about the future; they're actually building it,” said moderator Maria Odiamar Racho, operating partner at Qubits Ventures. Both Chong and Kremer have experience in both academia and industry. 

Host Xiaochen Zhang of AI 2030 added, “Bring the right people to the room, and the magic will happen.”  

Here are the main takeaways from the evening: 

Lesson 1: What Quantum+ AI actually means for business is still unknown 

The science behind both AI and quantum computing has been around for a while. But we’re only beginning to explore the possibilities of using the two together.  Most companies looking at quantum technology tend to be “quantum-curious,” Chong said, with an advanced development group that works with a quantum group.  Business is still in a “sort of research-y time,” he said, but the goal is to be ready when the technology is mature.  

“Think of AI five years ago,” Kremer said. “No one expected it to happen, but a lot of companies gained a lot by just trying.” But right now, there is no clear-cut demonstration of an industry best-practice application. 

Lesson 2: The business side has to talk to the science side. 

Panelists agreed that if you don’t have a basic understanding of the tech, you won’t know what it can — and can’t — do for you.   

“You don’t have an advantage if you don’t have utility,” Clouse said. “You need to be able to tell the difference between a science fair project and a product.” She clarified, however, that the understanding only needs to go so deep: “you don't need to know how a transmission works to put gas in your car.”  

Lesson 3: A real-world use case 

The applications of AI and quantum have been talked about in general terms: finance, energy and healthcare. Chong got into more specifics: researchers are studying multimodal biomarkers to potentially predict treatment outcomes for certain types of cancer. They could use quantum computing to select biomarkers and AI to predict outcomes. AI can also facilitate the discovery of quantum algorithms. But the possibilities are endless, really. 

“We have no idea” what could be possible with AI + Quantum, Kremer said. “And that's exciting.”

Lesson 4: The biggest roadblocks to quantum computing right now are hardware and workforce.

Chong and Kremer agreed that hardware — a reliable quantum computer that can run on the fewest number of quantum bits— is where we have the furthest to go. That said, “If someone came with 1000 qubits today, we wouldn’t know what to do with them,” Kremer said. It takes a trained workforce to know what to do with those qubits, but Clouse said there’s a need for, “people more than talent” — to look at people in totality, with a variety of different skills and interests, and also basic morality and ethics. 

“These AI scam farms are killing it,” she said. “I need those people with us.” Odiamar Racho pointed out the scam farms further underscore the need for responsible AI practices.  

Lesson 5: Don’t forget algorithms. 

AI quantum algorithm discovery, including work that is being done by the National Quantum Algorithm Center, is another important part of preparing for the quantum revolution. Quantum algorithms are different from classical algorithms, and some can be both.  “There’s a lot of cross-discipline work that needs to be done,” Chong said. 

Lesson 6: Cybersecurity will be crucial. 
In response to an audience question, panelists said cybersecurity is another crucial need — and potentially a hazard.  With net, new, and novel types of data, “there's this nebulous concept of ‘workforce,’” Clouse said, but there are no coding bootcamps training people in cybersecurity. Quantum encryption is more secure, but it doesn’t exist yet, and quantum hacking will emerge as well. Thinking that companies will just provide what customers need in terms of securing their data is a mistake, Clouse said. 

“People aren’t willing to pay for it,” Chong said. “Until there’s, like, 10 disasters in a row.”  

Lesson 7: Parting words and instructions 

Odiamar Racho asked each panelist to provide one word summarizing the tech future, and one action they wanted attendees to take. 

Chong’s word was “exponential.” With that in mind, he advised the audience to think about difficult problems for quantum computing to solve: “hard enough that you wouldn't know how to solve them.”

Clouse’s word was “discovery.” She advised people to play: “Get your hands dirty with this stuff.” Earlier in the evening, she recommended trying hack-a-thons and resources like GitHub and IQMP partner qBraid.  

Dula’s word was “utility, not hype.” She suggested that anyone interested in being part of Illinois’ quantum future should come talk to her.
 
Kremer had two words: “really exciting.”  

“This is not something that happens every decade, or even every century,” he said. Like Clouse, he advised anyone interested in these topics to “go learn and play.” 
 
Before the main event, Clouse held a special introductory session discussing her work with Barclo and demystifying a lot of the thinking around Quantum + AI. She likened them to earlier emerging technologies: railroads and cars. Some business owners didn’t understand how trains or cars worked, but they knew that trains needed rails, and that cars needed roads and service stations. “You do not have to be an expert to put your thinking cap on and ask, what is it going to take to deliver on this really cool thing?” she said. 

Along those lines, she said businesses don’t need a crystal ball, “just some good, pragmatic common sense.”

At the end of the evening, people left inspired.  

And that was the goal: to lay the groundwork for successful partnerships in support of a Quantum + AI future.