Philip Inghelbrecht, Belgian co-founder of Shazam, gives a keynote at SuperNova Conference 2018 recounting the company's history from its founding in December 1999, years before smartphones existed. He describes how universities laughed off the music-recognition problem until Stanford's Julius Smith pointed him to Avery Wang, who invented the core algorithm; the team then built its own GPU infrastructure, ripped 120,000 CDs to create the largest digital music database, and launched via the dial-code 2580 on feature phones. He distills two lessons: focus on hard problems and solve them with simple, elegant solutions (illustrating with the slim but worthwhile odds of blockchain fixing music rights), and 'think big or think bigger' — something he says Belgians are bad at and Americans excel at. He closes by envisioning adaptive and AI-composed music as the problems worth working on today.
Philip Inghelbrecht's public thinking centers on a single operating principle he returns to again and again: pursue the hardest possible problem, then solve it as simply as possible. At SuperNova 2018 he distilled his Shazam experience into an explicit instruction to "focus on the difficult, on the hard problems, and try to solve them with simple solutions" 1. This isn't presented as a slogan but as a description of how Shazam actually got built, against the judgment of the era's best research institutions. He recounts that Xerox PARC, MIT Media Lab and Carnegie Mellon all "laughed the music-recognition problem away as unsolvable," and that it took stubborn persistence plus one optimistic Stanford professor to crack it 1. The lesson he draws is not that the team was smarter than those institutions, but that breakthrough solutions only look inevitable after the fact: people who read the Shazam patent today tell him they "would have done the same thing," even though nobody could solve it the year before 1.
Alongside the hard-problems dictum sits a second, closely linked theme: think bigger than feels comfortable. He frames this partly through a self-deprecating cultural lens, saying "we Belgians suck at" thinking big, that it's "something I fail at every day," and contrasting it with what "Americans are incredibly good at" 1. But the point isn't cultural commentary for its own sake, it's a practical claim about how ambition changes execution: "if you can dream ridiculously big and you start acting like it, then all of a sudden building towards it becomes so much easier" 1. He ties the moon-landing metaphor directly to Shazam's method, arguing that shooting for the stars with simple solutions is what makes an outsized payoff possible: "if you want to land on the moon you got to shoot for the stars, and if you do, and you do so with simple solutions, the payoff can be rewarding" 1.
A recurring analytical device in his talk is probability multiplication as a way of retroactively explaining improbable success. He walks through Shazam's early 2000s circumstances, the absence of cloud computing, the absence of a smartphone platform, the technical impossibility of the core recognition problem, and concludes that "the probability of Shazam succeeding in the year 2000 was virtually none... if you look at each component in isolation and you multiply it through, we should not have been here" 1. This isn't false modesty; it's offered as a genuine framework he then reuses to evaluate other hard problems, applying the same multiplication logic to blockchain for music rights (standards adoption around 10%, rights-holder buy-in around 5%, legacy catalog integration, coin-flip execution odds) and concluding the combined odds are "incredibly slim," while still predicting that "one company will eventually do it and it will look obvious in retrospect" 1. The throughline is that low compound probability is not a reason to avoid a problem, it's simply the natural state of any genuinely hard problem worth solving.
His account of Shazam's history also emphasizes that success was largely unplanned and platform-dependent rather than the product of foresight. He notes the company's chart "flatlined for its first six to seven years" because the iPhone didn't arrive until 2007 and the App Store a year after that, meaning the product existed before the platform that would make it succeed, and "none of it was planned" 1. This detail complicates the think-big narrative in an honest way: big thinking and hard problem-solving got Shazam to a working product, but timing and external platform shifts, not strategy, are what let that product finally reach scale. Similarly, he describes the technical constraints of the era shaping engineering choices that persisted for years afterward: because cloud computing didn't exist in 2000-2001, Shazam built its infrastructure from scratch and, he says, "even today runs on GPUs with custom-written software rather than cloud services or CPUs" 1.
He also uses small, concrete design decisions to illustrate the same simple-solution-to-hard-problem philosophy at a granular level. The choice of the dial code 2580, he explains, wasn't arbitrary: people can't remember phone numbers but do remember patterns, and 2580 is "the only vertical thumb-stroke of digits in the middle of any handset keypad worldwide" 1. It's a small example doing a lot of work in his narrative, showing that the hard-problem/simple-solution principle applied not just to the core recognition algorithm but to every layer of the product, down to how users would dial in.
Finally, his forward-looking remarks extend the same big-thinking instinct to where he sees the industry heading next. He describes Shazam becoming "a leading indicator for the music industry," where songs peak on the app before they peak in sales or radio, and points to artists like The Weeknd and Demi Lovato using Shazam geography data to plan tours 1 as evidence that solving one hard problem generates unanticipated downstream value. He then poses the next hard problems in the same register: not incremental playlist recommendation, but "adaptive music" that reshapes playlists fluidly based on place, time and company, and AI-composed music generating an effectively infinite catalog on the fly 1. Taken together, the concrete takeaway from his public statements is a repeatable test he applies to any new venture or technology: "are you solving the hard problems and are you thinking big enough?" 1.
Shazam co-founder Philip Inghelbrecht's SuperNova 2018 keynote on how Shazam solved an 'impossible' problem with simple solutions, and his two lessons: tackle hard problems and think bigger.