sensors | Bit.Fan

Omen AI buys Aquatic Labs for $16 million to combine data center coolant monitoring tools

Omen AI, an AI infrastructure company focused on real-time coolant monitoring for data centers, said it is acquiring rival Aquatic Labs in a $16 million deal made up of cash and stock. The transaction is aimed at combining the two companies’ sensor technologies into a broader fluid monitoring platform for data center operations. Omen AI’s existing sensors detect elements in water, while Aquatic Labs’ products measure alkalinity. The companies said the combined system is intended to deliver a more complete view of fluid conditions, with both teams now working to merge the two capabilities into a single sensor. That product is expected to reach the market early next year. Following the acquisition, Aquatic Labs CEO Allan Adams will become chief science officer at Omen AI. Founder Zach Laberge said Omen’s sensors are expected to monitor chips consuming 250 MW to 300 MW of power by the end of this year, representing roughly $5 billion to $7 billion in value. He also said the company wants to expand coverage to the equivalent of 1 GW of chips by the end of 2027. According to the report, Laberge said monitoring demand for already-built data center projects remains firm even if expectations for AI infrastructure investment shift, while Adams said the technology could eventually extend beyond data centers into broader water management use cases.

Qianli Technology

6 days agoNews Editor

Qianli Technology unveils AI-powered 4D millimeter-wave radar with 10 TOPS NPU

Qianli Technology has launched an AI-integrated 4D millimeter-wave radar equipped with a 10 TOPS NPU, adding local perception capabilities to the sensor itself. The company said the product supports three operating modes: a local edge mode that processes data on the radar and outputs structured perception results, a satellite architecture mode that sends raw data at high speed to a central domain controller for multi-source early fusion, and a compatibility mode that runs both paths at the same time. According to the release, the radar uses an end-to-end model across the full chain from antenna design to point-cloud output. Qianli Technology said this delivers a 10x increase in point-cloud density, a 40% improvement in detection range, and a 95% ghost-target elimination rate. The design is aimed at vehicle systems spanning L2 to L4 functional levels, as well as the transition period toward centralized EE architectures. The company is led by Yin Qi, while its affiliated company StepStar provides AI model support. Quantum Bit described the launch as an extension of the "AI + physical terminal" concept into autonomous-driving sensors, with model-driven iteration reshaping the underlying sensor architecture.

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Electric Plant

13 days agoNews Editor

Electric Plant raises $11.2 million seed round for Bombadil, an AI model built to read plant electrical signals

Electric Plant has raised $11.2 million in seed funding to expand Bombadil, a large language model designed to interpret subtle electrical signals moving through plant stems. The round was led by Onto Ventures and Climactic, with participation from Ponderosa, Endeavor Catalyst, and others. According to the company, its system combines stainless-steel screw sensors, low-power wireless transmission, and a cloud-based model to translate internal microvolt changes into signals growers can use to understand whether plants need water, nutrients, or light. Electric Plant said only a few sensors are needed per acre, and the setup can help improve crop yields while cutting water use by 20% or more. Bombadil currently reads electrical signals from about 125 plant species, including ferns, redwoods, tomatoes, and dahlias. Founder Justin Mast said the company has built the most diverse model based on bioelectrical signals.

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