I’ve been thinking about graphics processing units (GPUs) a lot lately… but I’m not the only one. The great GPU shortage is panicking everyone from industry leaders like NVIDIA and AMD to everyday gamers and crypto-enthusiasts.

That’s because GPUs are driving innovation from mining cryptocurrency and minting NFTs to powering AR, VR, machine learning, and AI. They’re not just powering new technology, products, and brand experiences — they’re creating and transforming entire economies.

But that’s not the only reason I’ve got GPUs on my mind. I believe their defining characteristic — real-time rendering — is what humans need more of, too.

In other words, solving problems and presenting a tangible, viable solution in the moment.

This entails having an ample capacity for concurrency, which is doing multiple, high-quality computations seamlessly at the same time. Whereas a computer’s central processing unit (CPU) is designed for speed, it’s limited by its ability to execute multiple tasks concurrently.

GPUs do it all — and fast.

The lesson today’s business leaders can derive from GPUs is clear: the better you are at grokking real-time information and rendering solutions, the clearer your vision becomes for business growth and success.

The trick is to identify and eliminate limiting factors for inspiration acceleration.

Process problems faster

Like most technological advances, the modern GPU revolution was started in a world fueled by simulated reality: video games. (What, you thought I was talking about pornography? That too.)

Back in the late 1990s, when I was busy fighting terrorists and other bad guys from my bedroom playing Counter-Strike and my favorite, GoldenEye 007, NVIDIA took hold of the graphics market and the PC gaming market.

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To power the growing hunger for more realistic video games, NVIDIA revolutionized parallel computing. The ability to crack computational problems simultaneously is the crux of their paradigm-shifting innovation. And that’s also why they’re a market leader nearly three decades later; their GPU deep learning is a driving force behind today’s AI.

Other GPU-driven software solutions, like OTOY’s token-based render network, are helping creatives like me do mind-boggling work at a fraction of the time and cost. Photorealistic images can be created in about the same time it would take to snap a picture. We’re all Player One nowadays; it’s just a question of being ready to use our imagination to respond to challenges and create new worlds of possibility.

And so, just as we’ve trained machines to learn from us, we can learn from machines. You don’t have to be in the video game industry to get traction from GPUs: it’s all about being able to perceive and understand simultaneously. This allows you to quickly explore more than one gateway to solve a problem. When you deploy different approaches to address challenges, you ultimately end up with novel solutions.

This is an eloquent expression of a growth mindset, which is essential for beating the competition and winning market share in today’s uber-competitive, lightning-fast world.

How I like to employ this practice is through something we call a Vision Sprint. It’s a unique set of specially curated exercises that enable a group of people to imagine and shape new ways forward for their business or products and services. By taking a swift but deep dive into user trends and behaviors, it helps uncover possibilities to shape, improve, and reimagine the user experience.

The goal? Narrow the gap between the initial execution and iterating new opportunities. While creation is important, fast learning and continual improvement is what drives growth.

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Render decisions in real-time

Real-time is today’s sexy buzzword. We hear it a lot lately from the analytics and business intelligence world in particular, with “agile research” startups, like Hubilo and Feedback Loop, making news as they raise multi-millions to automate the process of providing brands with real-time consumer analytics. Or real-time AI insights platforms like Dataminr, which just raised $465M on a $4.1B valuation.

The question is, what are managers doing with this unprecedented on-demand access to customer preferences, habits, demands, and desires?

The answer must have everything to do with responding in kind — in real-time, as quickly as possible — and nothing to do with business as usual. If your company tends to have meetings about when the next meeting is, you’re in trouble.

As Peter Drucker sagely pointed out more than two decades ago, “Culture eats strategy for breakfast.”

That means you’re only as facile and opportunistic as your team is.

It’s incumbent on leadership to move out their people of analysis paralysis and into action. I recommend taking a page out of another iconic business leader’s book: Andrew Grove, the legendary Intel CEO.

Maybe it’s because he was an engineer first, at the forefront of the CPU revolution, but Grove instinctively understood the urgency for being as unencumbered and stealthy as possible at a managerial level. His 1983 book, High Output Management, is as relevant today as ever. It’s all about what managers can do to take positive, high-leverage actions, like being decisive and motivating to their teams. Any real-time delays like meddling, abdication, or unnecessary interruptions, must be avoided.

He even recommends that managers make counterintuitive actions, like delegating what they’re good at because it’s easier to monitor others’ progress with subject-matter expertise. Naturally, that expands leadership’s bandwidth and ability to manage more concurrently.

Just like a GPU.

By understanding your limiting factors and eliminating them, you’re able to close the gap between strategy, tactics, and execution. And you also can iterate more rapidly, which gives your business a competitive advantage.

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The Need for Speed

I have mixed feelings about our instant gratification culture. In the mad scramble to cater to people’s micro-attention spans, it can be easy to fall into the trap of solving for symptoms, not systems.

More inspiration from the computer processing race, then. The fight for chip dominance is another helpful analogy because it’s all about waging the battle of the best user experience to win the marketplace war. Intel and AMD are continually duking it out, and Apple is flipping both of them the bird with their M1s.

Apple’s promise? “An entire system. On a single chip.”

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The selling point is clear: up-level the system to make experiences seamless, richer, more life-like, and as close to instantaneous as possible.

Society no longer has patience, so it’s all about accelerating implementation, time to market, and advancement. That means that the new cost model should be measured in time and attention, not dollars. (Although, as the adage goes, they are the same.)

The faster you understand your customers and innovate to make what they need accessible, the more powerful your market position.

This is where the GPU allusion is literal. Using AI and machine learning to solve customer pain points and challenges instantaneously is a must today, not a future wish.

By offloading mundane tasks, you make space to do the vital work of designing today for the outcome you want tomorrow. That’s something I learned many years ago from Counter-Strike: map out the other side of the divide before you charge ahead.

To envision your future, start by identifying the fastest incremental steps forward and act immediately. Showing improvements to your users, both internal and external, makes it simple for them to buy into your progress.

Ultimately, that’s the moral of the GPU story. The word “render” means both to cause something to become and to provide a service. By rendering your vision in real-time, you unlock possibilities for your customers.

And that’s the best way to make your brand’s value proposition compute.