Tim Bucher is the co -founder and CEO of AgtonomyA company of software, services and technology based in California allowing autonomy in agriculture.
The opinions expressed in this article are the specific authors and do not necessarily represent those of Agfundernews.
I have a word to say about what’s going on in agriculture: “Finally!” At a time when every penny counts for farmers, we are finally able to democratize AI in this important industry.
After decades of promises, the convergence of advanced technology, evolutionary manufacturing and the urgent need for solutions by farmers propelled AI propelled agriculture to a tilting point. The industry is on the verge of mass adoption, with implications that could reshape agriculture, food systems and global sustainability.
Recent developments in the AGTECH sector highlight the challenges that are always present in which startups face in this space. Despite the creation of impressive technologies, companies fought with the gap between innovation and the adoption of the market, largely due to unwanted commercial models which could not resist market pressure.
The current economic environment has further exacerbated these challenges. However, the underlying value of robotics and AG automation remains important and customer demand is strong.
In January, I joined a panel at the Consumer Electronics Show (these) called “AI or Die”. It was indicative to see how technological leaders no longer talked about consumer gadgets – they see agriculture as the next border to have a lasting impact. As a person who spent decades with one foot in Silicon Valley and the other in a farm, I can tell you: agriculture is no longer “old-school”. It is the ultimate test bench for AI innovation.
Why we need physical AI
“Physical AI”, in the form of autonomous machines doing critical farm tasks, today gives real results in farms. By combining data collection, followed by data analysis, user-friendly applications and real precision robotic equipment, we approach the challenges of the workforce and the climatic impacts that keep farmers at night, while making agriculture more efficient and more profitable. It is not only a progressive improvement, it is transformer.
Agriculture requires a lot of data. Years ago, the cost of data analysis was more expensive than data collection. Now, it is more expensive to collect data, which is why we need a physical AI to allow robots to collect data so that better analyzes can be carried out on the teraoctets collected in each field.
Take apples as an example of how AI helps producers like never before.
Data collection has been carried out for some time in order to detect diseases and other problems. However, AI sensors passing through the orchard can now also allow more precise management of the culture burden.
At the start of the growth season, a farmer can now obtain analyzes of each number of flowers and position on each tree to ensure the optimal harvest load based on the variety of apples and the size of the trees. Producers can then “slim” harvest it on a tree base by tree so that the positions of the remaining fruits mature to their optimal color and flavor. The juice apples do not need to be pretty, but apples to eat and the producer is more paid for the latter.
These cultures’ analyzes help the farmer optimize the harvest charge which can lead to an increase in their revenues of tens of millions of dollars or simply make the difference between the end of the year with a profit or once again in the red.
The ascent of the “agricultural agent”
Despite the recent setbacks in industry, the AG robotics market is ready for growth.
The shortages of workforce in progress, the increase in production costs and the need for greater durability continue to stimulate adoption. The convergence of these factors with the progress of AI and robotics technologies presents significant opportunities for innovation and growth in the sector.
Agricultural ecosystems are like complex video games – fully variables, challenges and opportunities that require strategic thinking and quick decisions to stay alive.
Imagine a farm powered by AI as an interconnected command center managed partly by the “agricultural agent” of the AI. The agricultural agent takes the comments of many sources such as environmental data, cultivation analysis, soil conditions, autonomous equipment available and a myriad of other data sources. He can then provide the farmer not only with recommendations of what should be done at what time; Once the farmer has hit the “easy” button, the agricultural agent can also send the equipment to do the work.
The farmer remains in control, but now has a kind of dashboard which allows them to perform some of the most critical and costly tasks necessary for their farm.
“The most innovative industry on earth”
In my own farm, Trattore farms Located in northern California, we use several types of technology to manage farm equipment and tasks, computer controlled fermentation tanks to autonomous tractors that use computer vision to use the structure of the harvest itself to sail safely and cultivate around this culture with precision.
Finding the work has always been my challenge to Trattore, but now with Starlink, aerial images, autonomous equipment, an AI and many other technologies, I can keep the farm with a much smaller workforce than I have never had in the past. Fewer people work in agriculture every day, but the last time I have checked, we must all eat, which is why this dynamic forces us to perfect automated solutions for agriculture at an exponentially accelerated rate.
In AG, we treat many GS environments and compliant with GPS and on the Internet, and we had to offer solutions that can still work in these environments. Progress in the Lidar, cameras and on -board computers now allow us to superimpose a sophisticated computer vision which offers reliable and precise performance even in the most difficult agricultural conditions (and, yes, which includes dust). All this will soon lead to the agricultural agent to combine thousands of billions of data and convert it into jobs and tasks that the farmer can manage from a command center.
For years, we have imagined what AI and automation could do for the farm. Now I can literally see the light at the end of the tunnel. AI accelerates research, data synthesis and opportunities training faster than ever. If you think that agriculture is stuck in the past, it is time to see it for what it is really: the most innovative industry on the land.
Agtech: the next generation
But let me be clear: so that autonomy brings real value to agriculture today, we must think of tractors and agricultural tools like farmers. We must collaborate with the brands that farmers know and already trust. And here is the exciting part: the next generation of farmers is advantageous and eager to access these new tools. They grew up with computers, smartphones and now a-assistant, and they see the potential for these technologies to revolutionize their farms. By providing them with advanced AI solutions, we do not only improve agricultural operations, we recall young innovative minds for agriculture. Imagine this: all the AG job openings can one day set up a “video game experience” as a job requirement.
The AI revolution in agriculture is not only a question of efficiency, it is a hat tip for the profitability of the farm, global sustainability and more nutritious food for future generations. It involves empowering the next generation of farmers with tools that make agriculture not only profitable, but exciting and avant-garde.
We are not only changing the way we cultivate; We redefine what is possible – and profitable – in agriculture. And believe me, you haven’t seen anything yet!
