WHAT’S NEXT?
By Bob Tedeschi
As the world battled a pandemic, geopolitical fires, and climate-related catastrophes, you’d have hoped for a massive push for the scientific and technological breakthroughs we need to address humanity’s toughest challenges. Instead, attention continued to drift to the latest social-media darlings, crypto schemes and other ventures that were perhaps well-intentioned, but stood little chance of solving the climate crisis or helping us gain fuller agency over our biology.
That may be changing. In some cases, recent crises have prompted governments and industry leaders to seek solutions to their most daunting issues, while in others, scientific pathways to important breakthroughs finally started to appear where none previously existed. Taken as a whole, one could argue that so-called “deep-tech,” where emerging scientific advances can change the underlying structure of entire industries, now has a market-opportunity big enough to match its moral imperative – and a greater share of the investment attention it deserves.
A problem of a different sort, however, remains. Namely, investors aren’t always armed with the domain expertise needed to help grow practical technologies from the seeds of theoretical science, or grow brilliant scientists into great business leaders.
In the case of Playground Global, at least, the task is made somewhat less fraught, thanks to an unusually deep bench of science-minded entrepreneurs (or business-minded scientists; take your pick). The result is an ability to quickly toggle between the weeds of theoretical physics, say, and 10,000-foot macroeconomic views of the aerospace or software industries.
In that spirit, Playground Global’s What’s Next? offers a snapshot of deep-tech’s current state across the firm’s four target investment areas, alongside 1-year, 5-year, and 10-year forecasts and pointers to trends and technologies that will likely shape the future of the planet and how we inhabit it. Unlike with most prediction-minded content, the intent isn’t so much to provoke reaction as it is to prompt deeper conversation. As with any distillation, there’s potency in these pages, and just as with any distilled spirit, the contents here will evolve over time. The hope, ultimately, is that future readers will contribute even as they consume, and help steer the community’s collective wisdom as the future becomes the now.
NEXTGEN COMPUTE
The problem
“To move beyond carbon-based economies, beyond being trapped indoors because of a tiny virus, in order to have agency over our biology, our environment, industrial processes, and agricultural processes, we need better kinds of computation that can answer impossible questions,” as Peter Barrett puts it. “Today we’re fumbling in the dark, guessing at stuff and butterfly collecting rather than designing and engineering things.”
Headwinds and Tailwinds
In 1950 the world’s population stood at roughly 2.5 billion. Now it’s 8 billion, and will reach 10 billion by 2058. The strain on Earth’s natural resources is already evident, of course, with soaring global food shortages, persistent drug shortages, and acute climate change events growing in frequency and magnitude – and in lockstep with carbon-based approaches to supporting humanity. Researchers and policymakers need significantly more powerful computational methods to solve these problems, but first computer scientists must simultaneously find new ways to squeeze better performance out of traditional silicon-based frameworks (now that Moore’s Law is a thing of the past), while also speeding the advent of quantum computing. All the while, this research must also account for the growing environmental impact of humanity’s appetite for data and computing, given the vast amounts of energy required to deliver it. The good news: quantum computing is close to becoming a reality, while strong incentives continue to drive innovation in silicon-based frameworks.
Deep-tech watchlist items
Quantum computing, advances in artificial intelligence and machine learning, and photon-based advances in traditional computing architecture.
Where we’ll be at the end of 2023
Quantum moves toward the starting line; older technologies get incremental boosts.
“On quantum, we won’t have a million qubit machine running, but you will have an algorithm that’ll allow us to understand, say, the method of action of our most important drugs,” Barrett said. We’ll know the impossible questions across a bunch of different domains we’ll be able to answer, and how transformative those quantum machines will be. We have some examples of that, but I think we’ll see very concrete examples in therapeutics, battery chemistries, how we design superconductors – specific examples of what you pay for and what you do with it. See how Mercedes plans to work with PsiQuantum to develop the next generation of EV batteries. So you’ll see an increasing focus in the Fortune 50 or Global 2000 on doing the preparatory work for when the quantum machine shows up in a handful of years. One of the biggest surprises over the last couple of years is that companies like Goldman Sachs now has 30 of the smartest quantum engineers on the planet. A lot of these companies now have serious people who are domain experts looking to find a quantum advantage.”
“That relentless and expensive march, like ‘Let’s go to 5 nanometers to 3 nanometers,’ will continue,” Matt Hershenson said. “But we’ll also see innovation that’s orthogonal and complementary to that, and silicon photonics and chiplets are two examples.” While “chiplets” allow computers to more efficiently allocate and execute subsets of computational tasks, optical interconnectivity moves data more quickly and demands less energy than traditional, copper-based data transport. Both exemplify the coming seismic shift from electron-based to photon-based computing, sometimes collected under the “silicon photonics” label.
“Some of these things will be in limited use next year, and much more broadly available the year or so after,” Hershenson said. “That’s important because the scale of computing is often limited by those two things – power consumption and how fast data can move around. So data centers will start to become more efficient and higher performing.”
Where we’ll be in five years
- Quantum breakthroughs start arriving.
- Photons more forcibly nudge electrons out of the computing spotlight.
“In five years we’ll have a working quantum machine,” Barrett said. “At that point you’ll see the most immediate changes happen in areas that won’t require a lot of infrastructure change: there’ll be discoveries in financial services like in portfolio management, for instance, or the way we schedule flights. Now quantum will certainly bring huge changes in pharmaceuticals, and help us discover materials for decarbonization. We’ll be able to plan on solar cells being twice as efficient, or having 50-megawatt windmills. It’ll just take longer to build the infrastructure to help make those kinds of discoveries possible.”
Hershenson: “Early movers will increasingly enjoy the benefits of silicon photonics, with mainstream enterprises watching closely from the sidelines and preparing to enter the fray as the technologies mature and industries shift their operations and infrastructure to suit the new technologies, and the possibilities offered. The overall impact of these advances will be significant, however. With major cloud-computing giants like Amazon, Google and others shifting to these technologies, they’ll be better positioned to serve the world’s ever-growing appetite for computing power more efficiently (read: with a lower carbon footprint) and more quickly. “When data movement and execution improve by tenfold, that will certainly have benefits in a lot of applications,” Hershenson said. “It’s just hard to be specific right now about what problems will be solvable based on that.”
Where we’ll be in ten years
Following decades of promise, Quantum makes a profound impact across industries and populations.
Quantum machines will be yielding significant advances in computational theory and methodology, which will themselves produce advances across a range of disciplines and industries. “Ten years from now we will have superconducting materials. We will have ways of making photo fuels,” he said, referring to fuels created by harnessing the power of photosynthesis. “We will understand the mechanisms by which our important drugs work, and we’ll have designed drugs that can treat maladies that we currently don’t have good answers for. We will have far superior battery technology. We will have the ability to make renewables with very large scale and reliable storage, so that wind and solar can completely replace gas. We will have ways of using natural gas in a way that doesn’t emit carbon. We will have real scalable mechanisms for carbon sequestration. In other words, we’ll have the mechanisms and the materials we need for energy transformation.”
Market forces will of course direct some of the innovation, Barrett said. “If Elon wants to make 20 million cars a year, it’s $120 billion of metal, and we don’t know where most it is coming from. So we need to be able to mine more efficiently, and make steel without carbon. All of those processes demand quantum design of catalysts and materials. And we may have entirely new classes of materials which obviate the need for much of that metal. We’ll have things like potassium batteries instead of lithium batteries, and potassium is 1000 times more ubiquitous.”
“We’re bad at imagining things that don’t exist. But we are on thresholds of materials and chemistries and capabilities that we just can’t get our heads around.”
Please pitch
Innovations in exotic materials that allow for computation in using so-called “majority logic” and using ferroelectricity, allowing computation that sidesteps the manufacturing and voltage limitations of silicon. “Majority logic relies on computational gates that work differently from those made out of transistors,” Barrett said. “Transistor-based computation relies on traditional computing logic, where an operation requires a certain number of gates. With majority logic, you have different kinds of gates: gates that turn on if three of five inputs are true, for instance, or if one of seven inputs are true. The physical representation of those gates is much smaller, so you need as little as one-tenth as much geometry on the device in order to synthesize the same amount of logic, and if you fabricate those gates with various exotic materials, you can use 100-times less power for that computation. We’re looking at companies in that space to invest in, and haven’t yet found one.”
Not computation-related but please pitch anyway
“Methane pyrolysis is the single best approach to decarbonization, and it’s being almost completely overlooked,” Barrett said. “While existing decarbonization efforts for coal, natural gas and oil seek to capture carbon after burning it, methane pyrolysis captures carbon from natural gas before burning. Energy suppliers can fairly easily retrofit existing equipment to enable this process, making it both efficient and scalable, and given that the world’s economy will rely on natural gas for the foreseeable future, methane pyrolysis is a powerful way to give gas companies a path to decarbonization.”
AI & AUTOMATION
The problems
Policymakers and industry leaders are looking to escape offshore manufacturing, given the inherent vulnerabilities to geopolitical unrest, the potential for workers’ rights abuses, and the climate-related impact of transporting goods across the globe. Meanwhile, warehouses and retail floors often can’t manage because so many American front-line workers are fleeing tasks that could be better (and more safely) executed by machines. At the management level, decision makers haven’t yet embraced artificial-intelligence and machine-learning tools that could greatly inform strategy, begging the question: “Is AI only for the biggest companies with armies of software engineers?” said Laurie Yoler. The true AI revolution, she added, will finally arrive “when we’ve built much more intuitive interfaces, so warehouse workers or other folks who might not have computer science degrees can rely on this for everyday applications.”
Headwinds and Tailwinds
The pandemic forced industry leaders to adopt new approaches to the creation, processing and delivery of goods and services to customers. That trend, in turn, helped boost investment and innovation in automation, robotics, 3-D printing-based manufacturing, and more user-friendly AI algorithms. Amid those promising tailwinds, though, comes a potentially-stiff headwind, in the form of a stubborn global economic downturn. And with the pandemic easing, so too has the urgency to innovate. With many industry-leading companies retrenching financially and re-orienting to pre-pandemic business practices, will their forays into new technology follow suit?
Deep-tech watchlist items
Artificial intelligence powered by advanced natural-language processing; robotics, 3-D printing.
Where we’ll be at the end of 2023
A.I. gets more attention from decision makers.
“A growing number of companies, especially in financial services and telecommunications, followed by advertising media and retail, will have begun building A.I. models so they can actually start doing predictive analysis and better understand what’s happening in the business,” Yoler said.
Leak agreed, adding: “We’ll see A.I. start having real impact in automating things like customer service, and it’ll not only save companies time and money, but it’ll actually be a better experience for customers getting their problems solved over text.”
Where we’ll be in five years
A.I. becomes less of a “thing” as it’s more deeply baked into daily computational methods.
“Once we have the data and some early AI wins within companies, we won’t be talking about AI anymore,” Yoler said. “It will be ‘Hey, I have this great tool that allows me to do better sales forecasting, or my supply chain workflow,’ rather than it being AI.”
Where we’ll be in ten years
Robots commiserate, and get better as a result.
Please pitch
“A breakthrough we don’t have that we need is for Robots to be able to manipulate objects,” Leak said. “Robots today are great at gross movement, and have challenges with fine movements. I can carry a box from here to there, but opening that door is a pain, and picking up a t-shirt is really complicated because its model of the world has real trouble with flexible or floppy things. So dextrous manipulation unlocks a whole new class of things that can be done – whether it’s picking a raspberry or organizing things in a package, or putting on a screw and tightening it.”
INFRASTRUCTURE
The problem
The world’s population has long been overly reliant on a handful of nations for goods and raw materials, but the pandemic laid bare the perils of that strategy. Manufacturers, transportation companies and retailers all failed to effectively manage their supply chain, despite the promise of software ostensibly designed for such tasks. Meanwhile, policymakers and manufacturers alike are wary of geopolitical instability in the Far East (especially in the Taiwan Strait and the Korean Peninsula), and the ongoing threat posed to everything from network security to the supply of food and consumer goods to semiconductors. In the U.S., workers are increasingly turning away from manual-labor tasks that could be better (and more safely) executed by machines, leaving warehouses and retail floors woefully understaffed. Finally, the climate crisis is forcing nations and enterprises to confront vast inefficiencies in mining, production, shipping, and base-load energy generation and storage – all of which are hastening global warming.
Headwinds and Tailwinds
Quantum is coming – along with massive exposure to hacking.
Deep-tech watchlist items
- Hydrogen fuel cells for existing transportation assets
- high-temperature superconductivity.
- AI and machine-learning technologies dedicated to supply-chain inefficiencies.
- quantum and post-quantum cryptography; precision-mining technologies.
Where we’ll be at the end of 2023
- Cybersecurity becomes too big a problem to ignore.
- early gains come for grid-scale energy storage.
“Companies will by necessity be paying more attention to cybersecurity. Whereas just 26% of companies have instituted multi-factor authentication, that’ll pass 50%. It’s still not ideal, but there’ll be huge efforts on the cybersecurity front, because they have no choice. In the same way, we’ll see more companies paying attention to sustainable transportation, robotics and things like AI to make their supply chain more predictable – again, because they have to,” said Laurie Yoler.
“Grid-scale energy storage is an interesting problem we’ll see movement on by the end of next year,” Bruce Leak said. “With grid-scale, you don’t care about weight or size, and the best and most common approach is pumped hydro, where you pump water uphill when you have electricity and have it run downhill and run your generator when you have no electricity, and it’s super-efficient. You lose like 10 percent as your cost of storage. The problem is, if you’re in a flat desert there’s nowhere to pump it uphill, and you need a lot of areas to fill with water. But it’s a fantastic solution. We need something like that that you can put in a shipping container and drop next to a solar field and have it just work. And people are working on it. You’ll see demonstrations of promising technologies for solving this in the next year. Nothing will be solved at scale, but we’ll start to see the paths to pursue.”
Where we’ll be in five years
- Automation, green transportation and hydrogen fuels make market inroads.
- with quantum’s arrival comes a cybersecurity reckoning.
“More companies will follow Amazon’s lead and adopt automation, though it won’t get to the mass market by then. And transportation will be much greener thanks to solutions coming on that front, with many more electric vehicles – though again, it won’t get to mass-market levels by then. With cybersecurity, there’ll be a quantum machine running, and then either all hell is going to break loose, if all foreign governments have already been hacked, or we’ll have something good,” said Yoler.
“One of our core tenets is that even if something is the right thing to do, it won’t happen at scale unless the economics are right,” Leak added. “So in that vein, we’ll see hydrogen start to take hold as a fuel for airlines over the next few years.”
Where we’ll be in ten years
- EVs everywhere.
- post-quantum cryptography.
- mining gets smart at last.
“We’ll see lots more electric vehicles, starting with buses, then in distribution vans, and in regional trucks, and finally in long-haul trucking. And we’ll see a much better charging network spanning across the country, and much deeper adoption of AI and machine learning to give folks better visibility and predictability on suppliers and the supply chain. With cybersecurity, we’ll be more comfortable about post-quantum cryptography, and we’ll have a new security architecture that’s scaled with that cryptography,” Yoler said.
“We’ll see more mining in North America,” Leak said, “because we need to grow more independent in sourcing the exotic compounds needed for things like next-generation batteries, but it’ll need to be precision mining because current approaches are just a mess. Of course, recycling is going to be better too by then, because it’s a lot easier to mine those old batteries than to mine the planet. There aren’t enough today to be of much use, but there will be by then.”
Please pitch
High-temperature superconductivity technologies. “These would help solve transmission-line issues, and get energy where you need it without wasting it along the way,” Leak said. “Along the same line, more efficient electrolyzers for breaking down water and creating hydrogen. If you can make that process twice as efficient, life is good.”
LIFE SCIENCES
The problem
“Modern modalities like antibodies, antibody format, cell therapies, mRNA, and genetic medicines all have incredible power, but they’ve all had problems that limit their applicability or make them inaccessible,” Bell said. “So while it feels pretty magical now where we are with modern medicines, it’s still an extremely crude and blunt set of tools that are just as likely to make someone sick as they are to make someone healthy. We need to improve things to the point where every individual patient gets the appropriate medicine, using technology that’s broadly applicable, and also affordable so it’s available to everyone.” Another problem, Bell said, is the slow pace of drug development, which results from what he characterized as “the artisanal discovery of novel biology, which we leverage in a bespoke way.”
Headwinds and Tailwinds
The pandemic – and the previously unimaginable speed of vaccine development that it spurred – demonstrated the power and market potential of synthetically-engineered medicines. Add to this a dramatic drop in the cost of whole-genome sequencing, and a rise in machine-learning algorithms adapted to life sciences, and drug development appears on the verge of a possible revolution. “Biology could become true engineering,” Bell said.
Deep-tech watchlist items
- Whole genome sequencing, protein-based testing and drug-discovery processes.
- programmable mRNA therapeutics; proteomics analysis.
Where we’ll be at the end of 2023
Researchers test newly-inexpensive whole-genome sequencing, and like what they see.
With life-sciences, the 12-month outlook mostly includes incremental changes, Bell said, because most of the sector’s innovations must clear multiple hurdles to reach the market. That said, the cost of whole-genome sequencing has dropped to the $100 threshold with lower prices likely to come. Next year, Bell said, researchers and diagnostic specialists will start devising methods to capitalize on the power of the technology: “They’ll get that the game has changed.”
Where we’ll be in five years
Protein-based computational drug design, long beyond the reach of most researchers, is now in their grasp.
“People will be developing tools for the computational design of proteins so scientists can actually build better drugs and better manufacturing tools, and you’ll see a renaissance of companies in this space now that the tools are more effective,” Bell said. “Taken together, we’ll get to the point where there’s a real inflection point for the industry, and it’ll make a big impact on human health and what the biotech landscape looks like in the next few years beyond.”
Where we’ll be in ten years
Better drug development processes start yielding better, and less expensive, therapies.
The term “targeted therapies” will actually fulfill its promise for many more drugs, Matt Hershenson said. Drugs will spare healthy tissue because “the cell-therapy protein will almost literally be in a cage, and it will only open once it’s arrived at a tumor,” he said. “Those advancements are coming.”
Please pitch
“We’d love to see a step-change in the scale and capabilities of de novo proteomics,” Bell said. “We’re in this baby steps stage where you have companies going through all these permutations to be able to use next-generation sequencing for proteomics in ways that next-gen sequencing wasn’t developed for. But when all you have is a hammer, everything’s a nail. But if we had a proteomics hammer, that would open up a lot of things because right now, it’s only the best and brightest of labs that can come up with ways of using existing assays for data.”