农业科技初创 Electric Plant 融资 1120 万美元,训练大模型 Bombadil 解读植物电信号
Plants can speak using electricity, so this startup built an AI model to decipher their language
- 1农业科技初创 Electric Plant 完成 1120 万美元种子轮融资,Onto Ventures 与 Climactic 领投
- 2公司用三年采集的数据训练出大语言模型 Bombadil,可解读约 125 种植物茎干内的电信号
- 3传感器售价数十美元,远低于现有数千美元的探测工具,每英亩只需几枚即可获得准确结果
- 4CEO Justin Mast 称系统可提升产量并减少 20% 以上用水,首批客户未公开,暂无独立验证
大模型方法正被用于解读植物电信号,农业感知环节从数千美元的专业设备转向数十美元传感器加云端建模的组合。
- 影响:若数十美元定价与每英亩几枚的部署方式成立,种植和林业企业的监测成本结构会明显下移;节水 20% 以上与增产均为创始人自述,投入测算不能直接引用该数字;产品仍在融资推进上市阶段,规模化供货时间未定。
- 参考:可考虑先盘点现有土壤探测、手持光谱与卫星影像工具的采购和维护成本,作为对比基准;值得为种植园或林场圈出一小块地,跟踪该方案首批公开实测数据后再决定是否试点。
- 依据:融资 1120 万美元与约 125 种物种覆盖来自公司口径及 TechCrunch 报道;节水与增产数字为 CEO Mast 自述,暂无独立验证。
Justin Mast’s life was changed by a cyborg plant.
A few years ago, Mast was reading through some scientific literature when he stumbled upon research about a houseplant wired to a motorized stand. When the plant wanted more light, electrical signals flowed through the living tissues. A control board sensed the current and wheeled the plant closer to the light source.
“I’m like, what the heck?” Mast told TechCrunch. “That was the entry to the rabbit hole for me.”
Mast wound up partnering with Lee von Kraus, a neuroscientist who has worked with DARPA, to found Electric Plant, which has been spending the past three years collecting data to build a large language model, Bombadil, capable of interpreting the subtle electrical signals coursing through a plant’s stem and relaying details about the plant’s needs to growers.

The founders believe their model could one day lead to a tool that would let people “speak” to plants. “We’re listening more than we’re speaking, but listening’s the first step,” said Mast, co-founder and CEO of Electric Plant.
To bring its sensors and Bombadil to market, Electric Plant recently raised a $11.2 million seed round led by Onto Ventures and Climactic, with participation from Ponderosa, Endeavor Catalyst, Ludlow, Michigan Rise, The Fund, Schox VC, and Dug Song.
Even in the most controlled greenhouses, farmers and growers don’t have full visibility of what their plants require, Mast said. Traditionally, farmers, growers and foresters have relied on coarse tools that react to plants’ demands for water, nutrients or light. And tools like soil probes, handheld spectroscopes, and satellite imagery work well enough, but they leave much to be desired, Mast said.
“That technology is sophisticated, but its ability to get at the inside of the plant isn’t very sophisticated. Most of that stuff still lags quite a bit behind the real-time needs of the plant,” he said.
Electric Plant had to start somewhere, though, so it used those devices to train its Bombadil model, which is capable of interpreting electrical signals in about 125 different species. “We know the model will surpass a lot of that equipment,” Mast said.
The startup’s sensors are also significantly cheaper than existing tools, which generally cost thousands of dollars. “This is tens of dollars,” he said.
The sensors, about the size of a regular iPhone folded lengthwise, are attached to a plant using stainless steel screws. The screws must penetrate the cambium — the layer of living tissue just under the bark — to connect to the microvolt changes occurring within the plant. Data collected from these sensors is sent to a base station via a low-power wireless network.
Electric Plant only needs a couple sensors per acre for accurate results, Mast said. The data gets interpreted by Bombadil in the cloud, and the results are sent back to the customer, who can use it to, for example, adjust their watering or fertilizer schedules. Mast claims such a system can boost yields while reducing water use by 20% or more.
Mast wouldn’t disclose who Electric Plant’s initial customers are, but it’s easy to imagine applications in agriculture and forestry.
Bombadil’s first hundred-plus species runs the gamut of plant forms, from ferns, redwoods and tomatoes to dahlias, Mast said.
“This is the most diverse model ever created on biological electrical signals,” he said. “No one’s ever done anything equivalent to this in the animal world.”
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Tim De Chant is a senior climate reporter at TechCrunch. He has written for a wide range of publications, including Wired magazine, the Chicago Tribune, Ars Technica, The Wire China, and NOVA Next, where he was founding editor.
De Chant is also a lecturer in MIT’s Graduate Program in Science Writing, and he was awarded a Knight Science Journalism Fellowship at MIT in 2018, during which time he studied climate technologies and explored new business models for journalism. He received his PhD in environmental science, policy, and management from the University of California, Berkeley, and his BA degree in environmental studies, English, and biology from St. Olaf College.
You can contact or verify outreach from Tim by emailing [email protected].
来源:TechCrunch · AI · techcrunch.com