Digital Biology: The Convergence Creating Agriculture's Future
Dr. Allan Gray examines how the convergence of artificial intelligence and biological science is transforming agriculture from inputs to consumer products. Dr. Gray uses Waymo autonomous vehicles as a powerful analogy: over 200 cars in Phoenix and San Francisco all share the same AI driver, which has already accumulated more driving miles than any human alive and continuously improves with every experience. This same principle applies to agricultural AI systems.
By Dr. Allan Gray
There's a question that comes up in nearly every conversation about AI in agriculture: "But ChatGPT makes so many mistakes. How can we trust AI to make farming decisions?"
It's a fair question. And it's the wrong question.
Let me tell you about riding in a Waymo.
The Waymo Lesson
If you've ridden in one of the Waymo autonomous vehicles operating in Phoenix or San Francisco, they're cool. Maybe a little scary at first, but cool. They drive smart, and they're going nationwide before too long.
The first time I got brave enough to get in one, I thought it might be like my grandmother driving me around in a golf cart. That's absolutely not true. If the speed limit is 40 miles per hour and that car is first at a red light, when it turns green, it will be going 40. It won't rip your head off, but you know it's going to 40. And when it gets to 40, it's going to drive 40, not above it or below it.
But here's what I want you to think about. Every single one of those cars is the exact driver. The same system is driving that car. Every one of those cars that has an experience, all of those experiences from all of those cars, is feeding the exact driver.
That driver has driven 100 times more miles than any human being alive. Already. And that driver will only get better from now on. It will not get worse. It's only going to get better.
That's where we're headed with respect to data and AI in agriculture.
Be Careful About Dismissing What's Coming
Just because ChatGPT can make obvious mistakes, be careful about saying this stuff is never going to happen. I'm going to tell you right now: you're full of it if you think AI's not here to stay. You're just wrong. I promise you, it's here to stay.
AI is going to expose parts of biology we haven’t even scratched the surface of. And if you ask my biologist friends, they’ll tell you we still have a long way to go in understanding biology.
This convergence of data and AI is going to make us so much smarter about how to put biology where we need it to solve problems.
The Marriage of Data and Biology
We're making digital biology a bigger and bigger part of what we do in agriculture. It's going to drive a lot of the innovation coming into this industry.
As we get more personalized nutrition data showing what different groups of people actually need, we'll be able to bring that into plant genetics and connect more of those puzzle pieces.
That's almost impossible right now. But that won’t be the case much longer. We're going to have the information and capabilities to influence biology in ways we simply can't yet.
The Feedback Loop
Here's where this gets really powerful. Increasingly, data will be a feedback loop.
Suppose you're a company developing genetics or biological products. In that case, you're going to have to figure out what the next thing is to address, and it's going to come directly from farm-level data, where you can see it happening in real time.
You're going to be able to see data from your CPG partners showing the kinds of things they need in their food products. You'll also see what's happening on the farm that can create that. And you'll have the data that tells you, in your R&D, what you can do with your genetics and biologicals.
This is a huge driver of innovation because we have increasing capabilities to combine data with our biological capabilities.
What This Means for Startups
At DIAL Ventures, we're watching this convergence because it creates multiple layers of opportunity:
Data Infrastructure: The feedback loops I'm describing don't exist at scale. Farm-level data doesn't flow smoothly to CPG companies. CPG requirements don't translate clearly into R&D priorities. Someone needs to build the pipes that enable this information flow.
Analytical Capabilities: The companies that can translate data patterns into actionable biological insights will be extraordinarily valuable.
Biological Solutions: As data reveals biological opportunities we didn't know existed, there will be enormous demand for companies that can rapidly develop and deploy biological solutions.
The Partnership Imperative
This convergence doesn't happen in isolation. You can't build meaningful digital biology solutions without deep partnerships across the value chain.
That's why at DIAL Ventures we don't just bring in entrepreneurs and tell them to build something incredible. We facilitate conversations between our Fellows and corporate partners across the agri-food system. We need input from seed companies, CPG brands, farmers, and food manufacturers.
The startups that will win in this space understand biology, understand data, and understand how to create value for multiple stakeholders simultaneously.
The Innovator's Dilemma
Large companies in agriculture are investing heavily in data science teams, AI capabilities, and digital biology platforms. But they face the classic innovator's dilemma. Their business models and organizational structures are built for a different era.
That's where startups have an advantage. You can build from scratch with this convergence at your core. You don't have to retrofit a legacy system.
A Word of Caution
This is not about technology for technology's sake. Digital biology is only interesting if it solves a problem someone will pay to solve.
At DIAL Ventures, we're technology agnostic. We want to solve a problem. If AI is the right solution for the problem we're trying to solve, we're all about it. But a fair amount of the challenges we've got in food and agriculture could be solved with the tech stacks that already exist today. You don't have to get all that fancy to start solving problems.
The Opportunity Is Now
The convergence of digital and biological capabilities is not ten years away. It's happening now. The companies being built in this space today will define the next generation of agricultural innovation.
We're looking for entrepreneurs who understand both sides of this equation. Who can speak the language of data science and the language of plant biology? Who can see the systems-level opportunities that emerge when these capabilities combine?
If that's you, we want to talk.
By Dr. Allan Gray
There's a question that comes up in nearly every conversation about AI in agriculture: "But ChatGPT makes so many mistakes. How can we trust AI to make farming decisions?"
It's a fair question. And it's the wrong question.
Let me tell you about riding in a Waymo.
The Waymo Lesson
If you've ridden in one of the Waymo autonomous vehicles operating in Phoenix or San Francisco, they're cool. Maybe a little scary at first, but cool. They drive smart, and they're going nationwide before too long.
The first time I got brave enough to get in one, I thought it might be like my grandmother driving me around in a golf cart. That's absolutely not true. If the speed limit is 40 miles per hour and that car is first at a red light, when it turns green, it will be going 40. It won't rip your head off, but you know it's going to 40. And when it gets to 40, it's going to drive 40, not above it or below it.
But here's what I want you to think about. Every single one of those cars is the exact driver. The same system is driving that car. Every one of those cars that has an experience, all of those experiences from all of those cars, is feeding the exact driver.
That driver has driven 100 times more miles than any human being alive. Already. And that driver will only get better from now on. It will not get worse. It's only going to get better.
That's where we're headed with respect to data and AI in agriculture.
Be Careful About Dismissing What's Coming
Just because ChatGPT can make obvious mistakes, be careful about saying this stuff is never going to happen. I'm going to tell you right now: you're full of it if you think AI's not here to stay. You're just wrong. I promise you, it's here to stay.
AI is going to expose parts of biology we haven’t even scratched the surface of. And if you ask my biologist friends, they’ll tell you we still have a long way to go in understanding biology.
This convergence of data and AI is going to make us so much smarter about how to put biology where we need it to solve problems.
The Marriage of Data and Biology
We're making digital biology a bigger and bigger part of what we do in agriculture. It's going to drive a lot of the innovation coming into this industry.
As we get more personalized nutrition data showing what different groups of people actually need, we'll be able to bring that into plant genetics and connect more of those puzzle pieces.
That's almost impossible right now. But that won’t be the case much longer. We're going to have the information and capabilities to influence biology in ways we simply can't yet.
The Feedback Loop
Here's where this gets really powerful. Increasingly, data will be a feedback loop.
Suppose you're a company developing genetics or biological products. In that case, you're going to have to figure out what the next thing is to address, and it's going to come directly from farm-level data, where you can see it happening in real time.
You're going to be able to see data from your CPG partners showing the kinds of things they need in their food products. You'll also see what's happening on the farm that can create that. And you'll have the data that tells you, in your R&D, what you can do with your genetics and biologicals.
This is a huge driver of innovation because we have increasing capabilities to combine data with our biological capabilities.
What This Means for Startups
At DIAL Ventures, we're watching this convergence because it creates multiple layers of opportunity:
Data Infrastructure: The feedback loops I'm describing don't exist at scale. Farm-level data doesn't flow smoothly to CPG companies. CPG requirements don't translate clearly into R&D priorities. Someone needs to build the pipes that enable this information flow.
Analytical Capabilities: The companies that can translate data patterns into actionable biological insights will be extraordinarily valuable.
Biological Solutions: As data reveals biological opportunities we didn't know existed, there will be enormous demand for companies that can rapidly develop and deploy biological solutions.
The Partnership Imperative
This convergence doesn't happen in isolation. You can't build meaningful digital biology solutions without deep partnerships across the value chain.
That's why at DIAL Ventures we don't just bring in entrepreneurs and tell them to build something incredible. We facilitate conversations between our Fellows and corporate partners across the agri-food system. We need input from seed companies, CPG brands, farmers, and food manufacturers.
The startups that will win in this space understand biology, understand data, and understand how to create value for multiple stakeholders simultaneously.
The Innovator's Dilemma
Large companies in agriculture are investing heavily in data science teams, AI capabilities, and digital biology platforms. But they face the classic innovator's dilemma. Their business models and organizational structures are built for a different era.
That's where startups have an advantage. You can build from scratch with this convergence at your core. You don't have to retrofit a legacy system.
A Word of Caution
This is not about technology for technology's sake. Digital biology is only interesting if it solves a problem someone will pay to solve.
At DIAL Ventures, we're technology agnostic. We want to solve a problem. If AI is the right solution for the problem we're trying to solve, we're all about it. But a fair amount of the challenges we've got in food and agriculture could be solved with the tech stacks that already exist today. You don't have to get all that fancy to start solving problems.
The Opportunity Is Now
The convergence of digital and biological capabilities is not ten years away. It's happening now. The companies being built in this space today will define the next generation of agricultural innovation.
We're looking for entrepreneurs who understand both sides of this equation. Who can speak the language of data science and the language of plant biology? Who can see the systems-level opportunities that emerge when these capabilities combine?
If that's you, we want to talk.