Endometriosis often takes years to diagnose. This ultrasound simulation innovation could help change that
Updated
March 17, 2026 1:01 AM
A group of women facing backwards. PHOTO: UNSPLASH
Endometriosis affects roughly one in ten women worldwide, yet diagnosing the condition often takes years. In many cases, patients experience symptoms for nearly a decade before receiving a confirmed diagnosis. One reason is that detecting endometriosis through ultrasound requires specialized training and clinicians do not always encounter enough real cases to build that expertise.
To address this gap, medical simulation company Surgical Science has introduced a new ultrasound training module designed specifically for identifying endometriosis. The system allows clinicians to practice scanning techniques in a virtual environment, helping them recognize signs of the disease without relying solely on real-patient cases.
A key feature of the simulator is training on the “sliding sign,” an ultrasound indicator used to detect deep endometriosis. Because the condition can appear differently from patient to patient, mastering this assessment in real clinical settings can be difficult. The simulator allows clinicians to repeat the process across multiple scenarios, improving their ability to identify the condition during routine examinations.
The module also incorporates the International Deep Endometriosis Analysis (IDEA) protocol, which provides a structured method for performing a complete pelvic ultrasound assessment. Additional training cases, region-based scenarios and certification options are included to support standardized learning.
Early training results suggest strong improvements in clinician confidence, including higher skill levels in transvaginal ultrasound and better recognition of deep endometriosis. By expanding access to structured ultrasound training, simulation tools like this could help reduce diagnostic delays and improve care for millions of women living with the condition.
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Inside the funding round driving the shift to intelligent construction fleets
Updated
March 17, 2026 1:02 AM
Aerial shot of an excavator. PHOTO: UNSPLASH
Bedrock Robotics has raised US$270 million in Series B funding as it works to integrate greater automation into the construction industry. The round, co-led by CapitalG and the Valor Atreides AI Fund, values the San Francisco-based company at US$1.75 billion, bringing its total funding to more than US$350 million.
The size of the investment reflects growing interest in technologies that can change how large infrastructure and industrial projects are built. Bedrock is not trying to reinvent construction from scratch. Instead, it is focused on upgrading the machines contractors already use—so they can work more efficiently, safely and consistently.
Founded in 2024 by former Waymo engineers, Bedrock develops systems that allow heavy equipment to operate with increasing levels of autonomy. Its software and hardware can be retrofitted onto machines such as excavators, bulldozers and loaders. Rather than relying on one-off robotic tools, the company is building a connected platform that lets fleets of machines understand their surroundings and coordinate with one another on job sites.
This is what Bedrock calls “system-level autonomy”. Its technology combines cameras, lidar and AI models to help machines perceive terrain, detect obstacles, track work progress and carry out tasks like digging and grading with precision. Human supervisors remain in control, monitoring operations and stepping in when needed. Over time, Bedrock aims to reduce the amount of direct intervention those machines require.
The funding comes as contractors face rising pressure to deliver projects faster and with fewer available workers. In the press release, Bedrock notes that the industry needs nearly 800,000 additional workers over the next two years and that project backlogs have grown to more than eight months. These constraints are pushing firms to explore new ways to keep sites productive without compromising safety or quality.
Bedrock states that autonomy can help address those challenges. Not by removing people from the equation—but by allowing crews to supervise more equipment at once and reduce idle time. If machines can operate longer, with better awareness of their environment, sites can run more smoothly and with fewer disruptions.
The company has already started deploying its system in large-scale excavation work, including manufacturing and infrastructure projects. Contractors are using Bedrock’s platform to test how autonomous equipment can support real-world operations at scale, particularly in earthmoving tasks that demand precision and consistency.
From a business standpoint, the Series B funding will allow Bedrock to expand both its technology and its customer deployments. The company has also strengthened its leadership team with senior hires from Meta and Waymo, deepening its focus on AI evaluation, safety and operational growth. Bedrock says it is targeting its first fully operator-less excavator deployments with customers in 2026—a milestone for autonomy in complex construction equipment.
In that context, this round is not just about capital. It is about giving Bedrock the runway to prove that autonomous systems can move from controlled pilots into everyday use on job sites. The company bets that the future of construction will be shaped less by individual machines—and more by coordinated, intelligent systems that work alongside human crews.