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Almost 10 years ago, physician and data scientist Dr. Ruben Amarasingham founded Pieces Technologies in Dallas with a clear goal: use artificial intelligence to make clinical work lighter, not heavier. At a time when much of healthcare AI focused on prediction and automation, Pieces concentrated on something harder to quantify but more consequentialhow clinicians actually think, document, and make decisions inside busy hospital workflows. That focus helped Pieces gain traction with health systems looking for AI that could assist with documentation, coordination, and decision-making without disrupting care. But as hospitals began relying more heavily on AI for diagnosis, triage, and daily operations, the expectations placed on these tools changed. It was no longer enough for AI to sound impressive or move fast. It had to be trustworthy under real clinical pressure. Pieces did not set out to become a case study in healthcare AI accountability. But over the past two years, that is effectively what it became. In 2024, a regulatory investigation by the Texas Attorney Generals office into the accuracy and safety of its systems forced the company to examine how its models behaved in real-world settings, how clearly their reasoning could be explained, and how quickly problems could be identified and corrected. Rather than retreat, the company reexamined its models, documentation practices, and safeguards. Those efforts later became central to its acquisition by Smarter Technologies, a private equity-backed healthcare automation platform formed earlier this year through the combination of SmarterDx, Thoughtful.ai, and Access Healthcare, in September 2025. The purchase price was not disclosed. Pieces journey captures a defining truth about healthcare AI today: the technology is no longer judged by ambition alone, but also by whether it can withstand scrutiny, explain itself under pressure, earn clinician trust, and operate safely in environments where the cost of error is measured in human outcomes. FROM PROMISE TO PROOF AI arrived in healthcare with big promises. It would ease physician workloads, speed decisions in emergencies, and cut through the complexity of modern care. Some of those promises materialized early. But as adoption spread, hospitals began to see the limits of systems that were impressive in theory but fragile in practice. In early 2025, the U.S. Food and Drug Administration published updated guidance on AI and machine learning-enabled medical devices, calling for stronger post-market monitoring, clearer audit trails, and safeguards against model drift in high-stakes settings. The Federal Trade Commission reinforced that message through enforcement actions targeting exaggerated AI claims and misuse of sensitive health data. Those signals changed the conversation, forcing many hospitals to ask vendors harder questions: How does your system reach its conclusions? Can clinicians understand and override its recommendations? And does the model behave consistently as conditions change? For many AI companies, the excitement of the last decade no longer buys time. Proof does. A REAL-LIFE TEST Pieces encountered those expectations earlier than most. The regulatory scrutiny forced the company to confront how its models reasoned through patient data and how clearly that reasoning could be explained to clinicians and regulators alike. But Amarasingham says the companys mission never shifted. Our team is focused on building the tools to make life easier for physicians, nurses, and case managers who are carrying the weight of the health system every day, he tells Fast Company. That focus meant publishing method papers, sharing documentation with health systems, and creating processes that exposed when models struggled, drifted, or required recalibration. Those practices became foundational to the companys next chapter. Shekhar Natarajan, founder and CEO of Orchestro.ai and a longtime observer of healthcare regulation, sees this as part of a larger reckoning. Many AI companies, he says, relied on what he calls emergent safety, assuming ethical outcomes would arise naturally from good intentions and culture. That approach no longer holds, Natarajan explains. Regulators now expect safety and accountability to be engineered into systems themselves, with reproducible reasoning, documented controls, and safeguards that hold up even when teams are stretched thin. BUILDING TRUST Trust in healthcare does not come from branding or inspiration. It comes from repeated proof that technology understands clinical work and behaves consistently under changing conditions. Clinicians want AI that respects the pace of the workday, adapts to the unpredictable rhythm of patient care, and reduces cognitive burden rather than adds to it. Above all, they want systems that behave predictably. Pieces shaped its approach around these realities, focusing on building tools to work alongside clinicians rather than ahead of them and creating ways for teams to question the systems conclusions. It also designed its internal processes to document when the model was correct, struggled, drifted, or needed recalibration. For Amarasingham, that kind of thinking was essential for the progress of the company. Innovation, to us, had to serve the care team first. The goal was to reduce cognitive load rather than to add to it, he says, a view that aligns with a growing consensus in healthcare AI research. That emphasis aligns with what independent clinicians say is holding healthcare AI back. Dr. Ruth Kagwima, an internist at Catalyst Physician Group in Texas, says AI adoption stalls when tools disrupt already overloaded clinical workflows or fail to earn trust through clarity and validation. AI systems that succeed in hospitals are easy to understand, fit naturally into daily work, and show clear proof of safety and accuracy, she says. They have to protect patient data, respect clinical judgment, and improve care without adding friction. Another independent healthcare analyst, Dr. Patience Onuoha, who is an internist affiliated with multiple hospitals in Indiana, points to the practical constraints that still slow adoption at the bedside. Data is often messy and siloed, and new tools can disrupt already busy clinical workflows, she says. There are also real concerns around safety, bias, legal risk, and trusting algorithms that are not easy to understand. Natarajan believes this will be the defining standard of the next decade. In his view, companies survive regulatory pressure when they transform their internal principles into systems that can be inspected. They build clear chains of accountability, create evidence trails that reveal where bias may appear, and show clinicians not only how a model works but also why it does. IMPACT ON THE FUTURE Healthcare AI is moving toward a world where oversight is a design requirement rather than an afterthought, especially with regulators demanding documentation that spans the full lifecycle of a system. They want performance data segmented across race, age, and medical conditions, assurances that the system cannot infer sensitive traits that patients never disclosed, and they want companies to demonstrate how quickly they can detect and correct model drift. Some of this momentum comes from damage that has surfaced over time. For example, recent research reported by the Financial Times found some AI medical tools tended to understate the symptoms of women and ethnic minority patients, potentially worsening disparities in care because models werent trained or evaluated for fairness and transparency. Companies that adapt to this new reality will shape the next generation of clinical AI. Pieces now operates within this landscape. As part of Smarter Technologies, it is working to bring its governance practices to a wider network of hospitals. That means integrating safety frameworks across larger datasets, more diverse populations, and broader distribution environments. It is difficult work, but also the kind of work that defines leadership in a field where the cost of failure is measured in human outcomes. A NEW CHAPTER Healthcare AI is entering a consequential phase of growth, where the safety of AI systems is far more important than headline-grabbing breakthroughs. As hospitals sharpen their expectations for AI, Amarasingham believes the industry will need to adopt a different mindset. In healthcare and AI, youre not playing to win once and for all; youre playing to keep playing, keep learning, and keep improving outcomes for patients, he says. The work, he adds, will never be finished, because the rules shift and the needs evolve. What matters is whether companies choose to design for that reality. In other words, AI in healthcare will advance only as fast as it earns trust. And that means healthcare AI vendors and buyers must now, more than ever, be committed to steady, transparent work that stands up under pressure.
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E-Commerce
The humble tripod is an unheralded but essential part of any film or photo shoot. It’s the key to making shots level and pans smooth, and as a piece of equipment it’s seemingly about as simple as can be, with three legs and a mount at the top. But as any photographer or filmmaker knows, setting up a tripod properly can involve dozens of moving parts, clamps, pivots, and adjustments. A new tripod system from Italian camera equipment maker Manfrotto turns this setup into a single fluid motion. [Photo: Manfrotto/Layer Design] The Manfrotto Ones unique design allows for all three of its legs to be deployed simultaneously, extending out to the desired length in concert, each locking in place with a single lever. Thanks to a ball-based hub at the top of the tripod, the camera can be leveled in another single motion. And a custom-designed mount makes it possible to swap out cameras within seconds. [Photo: Manfrotto/Layer Design] The idea was to adapt this essential piece of gear to the way content creators are blending their media types. It’s increasingly common for content producersfrom social media amateurs to film and photography prosto quickly move from still cameras to mobile phones, toggle between photo and film, and alternate between horizontal and vertical frames. Designed by the London industrial design studio Layer, the Manfrotto One tripod was reconsidered from every angle to be easier to use and more adaptable to dynamic conditions. “Much of the brief was around quickness,” says industrial designer Benjamin Hubert, founder of Layer. “You’re quickly moving or panning a camera, then you’re able to snap it off and do some handheld shots, and then [you can put the camera] back on and quickly reset the height or the angle of the setup. It’s those transitional elements that allow for speed of use and as frictionless interaction as possible.” Seeing the One as a once-in-a-decade flagship product, Manfrotto has made an eight-figure investment in this new platform. It’s partly an effort to meet changing user needs, but also to stay ahead of the competition. “They’re seeing a lot of people enter the space, a lot of inexpensive products, a lot of commodity, a lot of things out of China and other parts of the world,” Hubert says. “They needed to move the needle and create something that was a big step forward.” [Photo: Manfrotto/Layer Design] Designing a new tripod Despite the seemingly simple makeup of a tripod, it’s a highly complex piece of equipment, and redesigning it to function quickly was far from straightforward. Manfrotto reached out about two years ago to Layer, known for its conceptual and product work ranging from airplane seats to wheelchairs to cryptocurrency wallets to dog toys. Hubert and his team broke the tripod down to what ended up being hundreds of individual components and reconsidered what made them work smoothly. “All the adjustment levers, all the attachment points, all the joints, everything is there because it has to be there from a functional point of view,” Hubert says. “Managing all of that noise and that amount of elements became one of the biggest challenges.” [Photo: Manfrotto/Layer Design] After churning through hundreds of prototyped components and narrowing them down to a series of viable options, Layer presented its designs as a kit of parts, with interchangeable elements and a shared logic. Combining the best bits, they dialed in on what became the One. Prioritizing how quickly the tripod could unfurl and how easily users could swap cameras on and off, Layer’s design focused on the size and placement of its key levers, making sure they could be manipulated almost effortlessly. The designers rethought th tripod’s conventional telescoping legs and created a system for the legs to extend both up and down from a central shaft, allowing the length to be controlled by a single lever. And rather than hiding parts or masking the functional elements of the tripod, Layer opted to accentuate the most critical moving parts in its overall form factor. “It’s like a skeleton constantly on display,” Hubert says. With the Manfrotto One tripod system’s retail price starting at $499, this may not be the gear for the average TikTok user. But the Ones clever design and adaptable use may even have amateurs looking at their old tripods with an unexpected level of scorn.
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E-Commerce
The record-breaking Falcons Flight roller coaster starts out slow, but don’t be fooled. Seconds into the ride at the new Six Flags Qiddiya City in Saudi Arabia, passengers are jolted into a high-speed journey that ascends mountainsides, passes through dark tunnels, and then does it all over again. The ride reaches a height of nearly 640 feet, lasts for nearly 3.5 minutes, and travels more than 2.6 miles. It’s the largest, longest, and fastest roller coaster in the world, reaching peak speeds of about 155 mph. To make it, a European design and manufacturing company used the most powerful electro-magnetic propulsion system on the market. Though Saudi Arabia just killed plans for the Line, its futuristic 150-mile-long city, it now holds records at its park, including the world’s tallest inversion on a roller coaster and the world’s tallest pendulum ride. [Photo: Six Flags Qiddiya City] Falcons Flight holds the speed, height, and length records for roller coasters, according to Intamin Amusement Rides, the Liechtenstein-based company that designed it. Founded in 1967, the company’s work spans from monorails in Moscow to an observation tower in Argentina, and includes what it claims was the world’s first giant drop ride in 1995. It says its newest roller coaster is part of “a commitment to pushing boundaries.” Intamin’s linear synchronous motors (LSM) drive system gives Falcons Flight an edge in terms of engineering. LSMs use electro-magnetic propulsion to move the ride forward through permanent magnets on the coaster train and electromagnets on the tracks. That’s different from other methods, like an old-school chain lift pulled by a motor, or a hydraulic launch. With LSMs, a moving magnetic field pulls the train forward. LSMs debuted on two Intamin-designed ridesSuperman: Escape From Krypton at Six Flags Magic Mountain in Valencia, California, and the Tower of Terror II ride at Dreamworld in Australia, both of which opened in 1997. Today, it’s a popular way to build roller coasters because it’s more efficient and cheaper to run. It’s also super fast. Intamin says Falcons Flight was was always intended to break records; the bird-shaped trains were designed to be aerodynamic, with windshields “engineered to pierce through the air,” not to mention save riders’ eyes from all that wind. The Six Flags Qiddiya City opening late last year came after the November closure of Six Flags America just east of Washington, D.C. Six Flags announced later that month that more closures are forthcoming for underperforming parks. The Quiddiya City park is its first outside the United States.
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E-Commerce
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