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'JD' Sends Deere Into AI race 09/01 08:09
John Deere Launches 'JD' AI Assistant to Unlock Farm Data Insights
John Deere unveiled "JD," a free AI assistant embedded in Operations Center,
that analyzes a farm's existing field, machine and operational data to deliver
personalized, actionable insights, with farmers retaining full control of their
data.
Joel Reichenberger
Progressive Farmer Senior Editor
AMES, Iowa (DTN) -- JD is John Deere's answer in AI.
The agriculture machinery giant introduced its artificial intelligence
assistant on Monday, describing "JD" as a solution to the data-heavy world in
which today's farmers work.
"Today, we're introducing JD," said Jackson Baca, the group product
marketing manager for digital at Deere. "JD is the John Deere AI assistant
embedded in Operations Center, and this AI assistant is here to help you get
more value for the data that already exists in your operations center account."
The program will be rolled out to some farmers in a staged release starting
Tuesday, Sept. 1, but there's no timeline for it to be more widely available to
farmers or the public. It will be built straight into Operations Center and
won't command any extra cost or subscription fee to use.
From Deere's Operations Center, it will seek to mine collected farm data to
offer insights that could help farmers make decisions. It could evaluate
performance from previous years in a certain field, compare yields between seed
varieties and, with a farmer's permission and ability to stop the flow at any
time, incorporate third-party apps to assist.
Asked on Monday why a certain field was seeing more weeds than usual, JD set
off, in short order, using years of data on that plot and an understanding of
the most recent season's crops and chemical application to offer up a list of
five possible answers.
"Decades of data generated across farmers' machines, fields and operations
are becoming faster and more accessible, with insights they can put to work,"
said Deanna Kovar, president of Deere's Worldwide Agriculture and Turf
division, summing up JD's capabilities.
"JD can turn that hard-earned data into timely, relevant guidance specific
to their farm and their needs," she said.
The technology has already been tested on some farms and that work will
continue in an early access program available exclusively to some U.S.-based ag
operators.
"What we're after there is additional feedback and understanding the value
that we're bringing with JD and how it's helping them in their operation," Baca
said. "As we continue to get that feedback, we'll look at launching to general
availability after that."
JD works on the back of a large language model, such as ChatGPT from OpenAi,
Claude from Anthropic, Gemini from Google or Grok from xAI, though Deere
declined on Monday to specify which model it's using or even which company it's
working with.
It won't pull all the data already accumulated in such LLMs, so ask
elsewhere how to redecorate the office or where best to vacation with
rambunctious children. It will, however, strive to offer deep insight into a
specific farm's operation using data gathered from a variety of sources. It'll
pull in data from planting, considering variety and density, and data from a
combine's yield monitor. It will check a weed heat map generated from a See &
Spray Deere sprayer and even consult old equipment owner's manuals. It'll
calculate fuel efficiency and machinery wear and tear, collecting information
from throughout the Deere ecosystem, and beyond. It can also use data from
different manufacturers, anything that can currently be loaded into Deere's Op
Center interface.
"It's augmenting human intelligence," said Kevin Seidl, who leads the
Operations Center product management team. "Many of the things it can help with
are things an expert level data analyst could spend a lot of time on and pull
out these kinds of observations."
It could take an expert weeks. JD proposes to do it in seconds.
Deere pitched the system as safe, secure and personal, drawing from a
farmer's own data and keeping any answers generated or data produced within
those same confines.
Collected data will be used to improve results for one farm, but it will not
be used to train JD or any other AI system and won't be available to anyone a
farmer doesn't approve.
"As our technology becomes more capable and enhances our customers'
workflows, we know that our responsibility is going to grow with it," said
Jahmy Hindman, senior vice president and Deere's chief technology officer.
"Greater intelligence requires strong foundations in security, transparency and
clear customer control. Farmers need to understand how the technology can
provide the right answer when limitations exist and how that recommendation was
reached. Regardless of how advanced technology becomes, farmers must always be
the final decision makers, and our ambition goes beyond building market-capable
technology. It's to build technology that customers can confidently rely on and
trust."
For now, JD will be limited in its capability, restricted mostly to
analysis. The first iterations rolled out this fall won't have the ability to
make decisions or perform actions in the cab.
But, among the things that came into focus Monday was the fact that when it
comes to Deere's ambitions with JD, more broadly speaking, this is only the
beginning.
"As we continue to evolve it, we'd like it to take certain actions," Seidl
said. "'Hey, help me create this work plan. Help me create a boundary for this
field,' right? Right now, it's analyzing and producing results, but we would
like it to go beyond that."
Joel Reichenberger can be reached at Joel.Reichenberger@dtn.com
Follow him on social platform X @JReichPF
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