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High-capacity benchtop video measurement system

Optical Gaging Products has introduced the SmartScope^® E18, a compact, benchtop video measurement system. Featuring a 12" x 12" stage, IntelliCentric™-E fixed-lens optics, and VIRTUAL ZOOM™ technology, it offers fully automatic 3-axis performance without taking up floor space. Standard LED lighting, a rigid fixed-bridge design, optional touch probes, and advanced metrology software ensure accurate, repeatable inspection.
Learn more.

Tech Tip: Fan selection - Why airflow is not just CFM

For many engineers, fan selection starts and ends with a single number: CFM (cubic feet per minute). Higher CFM feels like a clear win. More air moved must mean better cooling. However, in practice, this assumption is one of the most common causes of thermal problems, excess noise, and late-stage redesigns. Find out why.
Read this Orion Fans technical article.

Useful! Snap-together LED enclosure lighting

Seifert StripLite SL 4000 Series LED enclosure lighting provides bright illumination to 700 lumens. On/off switch and motion sensor models are available. Easily daisy chain up to 16 light strips. Magnetic or clip mounting. See video/info on website or contact Bristol Instruments for more information.
Learn about snap-together lighting.

The hidden hardware helping AI's heat problem: PCHEs

Across AI infrastructure, thermal constraints now connect semiconductor design with power and cooling systems. More compact, lighter, and efficient than conventional shell-and-tube models, printed circuit heat exchangers save floor space, reduce energy costs, and improve overall efficiency in dense, hyperscale environments.
Read the full article.

Nearly 1,000 parts: Industrial enclosure range expanded

Altech Corp. has expanded its industrial enclosure lineup to 10 unique series with nearly 1,000 parts! Designed for control, junction, and terminal applications, these plastic and aluminum housings offer up to IP69 protection. They mount directly to walls or panels, resisting chemicals, corrosion, flames, impacts, and severe outdoor conditions without sacrificing aesthetics.
Find your perfect enclosure today.

Cool Tools: MetraSCAN BLACK2 -- Next-gen shop-floor 3D inspection

You'll gain some superhero powers when you brandish FARO CREAFORM's new MetraSCAN BLACK2, a next-gen portable metrology-grade optical 3D scanner engineered to deliver total inspection flexibility on the shop floor. This unit boasts a 3-in-1 architecture that combines C-Track scanning, stand-alone scanning, and probing in a single metrology-grade system.
Read the full article.

Compact, touchless position sensors: Wear-free operation in tight spaces

Novotechnik's TFD-4000 Series of touchless linear position sensors delivers wear-free measurement in tight spaces. Featuring ranges up to 50 mm, IP67 protection, 12-bit resolution, and analog outputs, these reliable sensors operate from -40 C to 125 C across diverse industrial, mobile, and medical applications such as short-stroke linear valve positioning, solenoid valves, off-highway brake actuation, and more.
Learn more.

World's first 10-m safety laser scanner: See farther, protect more

Datasensing, Datalogic's Sensor & Safety and Machine Vision business unit, has launched the SLS10 Safety Laser Scanner, the world's first 10-meter safety laser scanner. Delivering a 275-degree scanning angle, 240-m² of coverage, and an 84-msec response time, the SLS10 protects larger workspaces with fewer devices. It features best-in-class angular resolution for precise AGV navigation, SIL-2/PLd compliance, dust immunity, and the new ONEGUI platform for simplified configuration.
Learn more and see it in action.

Accelerate AI-driven machine vision systems

BitFlow has announced full production of its Claxon CXP-12 frame grabbers, designed for NVIDIA GPU-accelerated machine vision. Across five models, the CoaXPress 2.0 lineup delivers up to 50 Gbps -- five times 10 GigE Vision -- eliminating data bottlenecks. The full CXP-12 specification ensures deterministic, high-bandwidth streaming to unleash modern AI inference models.
Learn more.

Millimeter-wave imaging inspection in real time

With its new quality and inspection R&S IMAGER millimeter-wave scanner, Rohde & Schwarz aims to simplify the industrial inspection of packaged products. The system sees through common packaging materials at production speed without using X-rays, protecting both products and operators. The high-contrast 3D images are used as digital twins and can be automatically integrated into AI-powered fault-detection systems. Sees through plastics, cardboard, and composites. Applications include food and beverage, pharmaceuticals, logistics.
Learn more.

What are single-loop process controllers?

PLCs are powerful, but complex control isn't always necessary. For standalone processes requiring single-variable monitoring -- like temperature, pressure, or flow -- a single-loop controller is ideal. See how single-loop controllers can streamline your next project.
Read the AutomationDirect tech tip.

Great Resources: Flexible circuit design guide

Tech-Etch uses advanced techniques to manufacture flex and rigid-flex circuits to exacting customer specs. Special processes include selective plating a single circuit with two different finishes, contoured circuits with variable metal thickness, semi-additive and subtractive techniques, open window or cantilevered contact leads, plus SMT for component assembly. Tech-Etch specializes in flexible circuits for medical, telecommunications, aerospace, semiconductor, and other high-reliability electronic applications.
Learn about flex circuits and get the guide (no registration required).

EMI Investigations: New immunity development system

Saelig Company announces the Langer E1 Immunity Development System for EMI investigations. This compact, affordable kit simulates burst and ESD interference to pinpoint layout weak spots down to IC pins. By eliminating "black box" guesswork early in development, engineers can efficiently identify coupling mechanisms, test measures, and resolve immunity issues before compliance failure.
Learn more and see it in action.

Battery packs for unmanned aerial vehicles

Re:Build Manufacturing has launched U.S.-assembled, NDAA-compliant lithium-ion battery packs for commercial, public safety, and defense UAV applications. Available in Core, Power, and Performance series, the packs use non-FEOC cells and are produced at Re:Build's advanced facility in New Kensington, PA. Re:Build also offers custom pack and battery management system development.
Learn more.

Easy-to-use precision measurement system

Optical Gaging Products has announced the StarLite S1, a compact, semi-automatic 3-axis video measurement system. It combines fully automatic video measurements with manual stage motion and features an IntelliCentric-S optical system for high-resolution images. Powered by Measure-X software, this system delivers fast, repeatable, high-accuracy results, making it ideal for both shop-floor and quality-control applications.
Learn more.

MIT researchers show how to create 'humble' AI

Artificial intelligence holds promise for helping doctors diagnose patients and personalize treatment options. However, an international group of scientists led by MIT cautions that AI systems, as currently designed, carry the risk of steering doctors in the wrong direction because they may overconfidently make incorrect decisions.

One way to prevent these mistakes is to program AI systems to be more "humble," according to the researchers. Such systems would reveal when they are not confident in their diagnoses or recommendations and would encourage users to gather additional information when the diagnosis is uncertain.

"We're now using AI as an oracle, but we can use AI as a coach. We could use AI as a true co-pilot. That would not only increase our ability to retrieve information but increase our agency to be able to connect the dots," says Leo Anthony Celi, a senior research scientist at MIT's Institute for Medical Engineering and Science, a physician at Beth Israel Deaconess Medical Center, and an associate professor at Harvard Medical School.

Celi and his colleagues have created a framework that they say can guide AI developers in designing systems that display curiosity and humility. This new approach could allow doctors and AI systems to work as partners, the researchers say, and help prevent AI from exerting too much influence over doctors' decisions.

Celi is the senior author of the study, which appeared Mar. 24 in BMJ Health and Care Informatics. The paper's lead author is Sebastian Andres Cajas Ordonez, a researcher at MIT Critical Data, a global consortium led by the Laboratory for Computational Physiology within the MIT Institute for Medical Engineering and Science.

Instilling human values
Overconfident AI systems can lead to errors in medical settings, according to the MIT team. Previous studies have found that ICU physicians defer to AI systems that they perceive as reliable even when their own intuition goes against the AI suggestion. Physicians and patients alike are more likely to accept incorrect AI recommendations when they are perceived as authoritative.

In place of systems that offer overconfident but potentially incorrect advice, healthcare facilities should have access to AI systems that work more collaboratively with clinicians, the researchers say.

"We are trying to include humans in these human-AI systems, so that we are facilitating humans to collectively reflect and reimagine, instead of having isolated AI agents that do everything. We want humans to become more creative through the usage of AI," Cajas Ordonez says.

To create such a system, the consortium designed a framework that includes several computational modules that can be incorporated into existing AI systems. The first of these modules requires an AI model to evaluate its own certainty when making diagnostic predictions. Developed by consortium members Janan Arslan and Kurt Benke of the University of Melbourne, the Epistemic Virtue Score acts as a self-awareness check, ensuring the system's confidence is appropriately tempered by the inherent uncertainty and complexity of each clinical scenario.

With that self-awareness in place, the model can tailor its response to the situation. If the system detects that its confidence exceeds what the available evidence supports, it can pause and flag the mismatch, requesting specific tests or history that would resolve the uncertainty, or recommending specialist consultation. The goal is an AI that not only provides answers but also signals when those answers should be treated with caution.

"It's like having a co-pilot that would tell you that you need to seek a fresh pair of eyes to be able to understand this complex patient better," Celi says.

Celi and his colleagues have previously developed large-scale databases that can be used to train AI systems, including the Medical Information Mart for Intensive Care (MIMIC) database from Beth Israel Deaconess Medical Center. His team is now working on implementing the new framework into AI systems based on MIMIC and introducing it to clinicians in the Beth Israel Lahey Health system.

This approach could also be implemented in AI systems that are used to analyze X-ray images or to determine the best treatment options for patients in the emergency room, among others, the researchers say.

Toward more inclusive AI
This study is part of a larger effort by Celi and his colleagues to create AI systems that are designed by and for the people who are ultimately going to be most impacted by these tools. Many AI models, such as MIMIC, are trained on publicly available data from the United States, which can lead to the introduction of biases toward a certain way of thinking about medical issues, and exclusion of others.

Bringing in more viewpoints is critical to overcoming these potential biases, says Celi, emphasizing that each member of the global consortium brings a distinct perspective to a broader, collective understanding.

Another problem with existing AI systems used for diagnostics is that they are usually trained on electronic health records, which weren't originally intended for that purpose. This means that the data lack much of the context that would be useful in making diagnoses and treatment recommendations. Additionally, many patients never get included in those datasets because of lack of access, such as people who live in rural areas.

At data workshops hosted by MIT Critical Data, groups of data scientists, healthcare professionals, social scientists, patients, and others work together on designing new AI systems. Before beginning, everyone is prompted to think about whether the data they're using captures all the drivers of whatever they aim to predict, ensuring they don't inadvertently encode existing structural inequities into their models.

"We make them question the dataset. Are they confident about their training data and validation data? Do they think that there are patients that were excluded, unintentionally or intentionally, and how will that affect the model itself?" Celi says. "Of course, we cannot stop or even delay the development of AI, not just in healthcare, but in every sector. But, we must be more deliberate and thoughtful in how we do this."

Source: MIT

Published April 2026

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