As countless case studies published on Computer Weekly have shown through the years, every minute and every penny that a Formula 1 team is spending on research, development and testing is precious and only grudgingly wasted.
In a cost-capped sport that is as much an engineering competition as it is one of driver skill, victory – whether in the drivers’ or constructors’ championships – often comes down to the finest of margins.
This season, the world of F1 is also dealing with a once-in-a-decade overhaul of the sporting regulations that have essentially forced a ground-up redesign of its cars. For some, like Mercedes-AMG Petronas, this has paid off big time. But for Oracle Red Bull Racing, the past few weeks have been rough ones.
The team’s drivers, former world champ Max Verstappen and his new partner Isack Hadjar, may not have much to show for it as they head to Miami for the fourth round of the season, but at HQ in Milton Keynes, its engineers are working flat out and morale is good.
When it comes to testing parts and components in its wind tunnel, a recent engagement with identity and access management specialist 1Password is paying dividends, with the team’s technicians now able to work much more efficiently.
In a world like cyber security, success can be hard to quantify. Sometimes it can even be dangerous to say too much, lest you speak candidly and give a watching threat actor something to go on. But in this instance, Oracle Red Bull Racing can definitively state that after adopting 1Password, it has slashed its wind tunnel recovery time from an hour to two minutes – that’s a cut of 97% – during the test and development process.
But why is that the statistic we’re running with? And how does identity and access management (IAM) technology apply to wind tunnels? It seems an unlikely link on the surface, but Matt Cadieux, team CIO, explains why it matters.
“The guys who are developing and improving the tunnel and its software push boundaries. The models are bigger, the complexity is bigger, and sometimes when you’re running that load for the first time, the infrastructure is not capable enough,” says Cadieux. “Probably once a every few months we have an outage, and it’s largely due to pushing boundaries with our tools and methods.”
A challenging customer
Ian Brunton heads up software development at Oracle Red Bull Racing’s Aerodynamics team. He takes up the story.
“The people I work with are essentially responsible for writing the software used across the teams of engineers that design the car. We plug into commercial CAD [Computer Aided Design] packages and tie them up to the CFD [Computational Fluid Dynamics] estate so that we can iterate quickly in those early stages,” he says.
“We also support the wind tunnel … We’re currently building a new wind tunnel here which is a significantly challenging project, but I think will pay a dividend in helping us build, ultimately, the fastest car on the planet.”
Brunton describes his team as challenging customers when it comes to IT. He sets high standards and expectations, and by his own admission is harsh in their application. “We’re aiming to provide high uptime,” he says, “and the last thing we need is any system, regardless of what it is, not operating as it is expected to.”
The need for uptime becomes even more important because the wind tunnel environment is a highly regulated one in terms of the number of hours the team is allowed to do testing, as well as the number of experiments that it can run.
“We basically have an eight-week period in which we have to audit what we’ve done in that period, and we have a budget to use in that period,” says Brunton. “To some extent, the pressure is on – it’s almost worse in the wind tunnel than it is at the track … Generally, at the track, you have components that are well manufactured, you know they’re going to fit together and you have a limited number of options in which to configure and build the car.
“But when you’re at the tunnel, it’s effectively an experiment in what we think is going to add performance. There might be parts that maybe don’t completely fit; engineers are discovering, as they’re going, how to design that part.
“[With] the pressure that those guys are under to build the car in that timeframe, they can’t afford any downtime – [we don’t want to waste] time, or waste runs in terms of that experiment. Losing that budget is criminal in the sense that it has a direct impact on the performance of the car on the track.”
It’s about trying to optimise the amount of time that the people working at the tunnel can focus on just working at the tunnel Ian Brunton Oracle Red Bull Racing
From Brunton’s perspective, a failure in an inherently complex system – with close to 20 services running across multiple clusters using multiple Kafka topics and different databases, that has caused the tunnel to shut down before completion, wasting time and slows development – is a big problem.
“If something happens and the system needs to be reset, it relies on someone at the tunnel realising there’s a problem and getting on the phone to someone like me – and that can be in the middle of the night because the tunnel runs 24 hours a day – I’ve got to take the call, get onto my machine, figure out the problem and start bringing that system back online,” says Brunton.
In essence, what 1Password enables him to do is to automate returning the systems to a known steady state, so that someone who is technical in terms of car design and engineering but may not know what Kubernetes is or what a SQL database does can effectively hit a big red button and get things moving again.
With 1Password, service restoration is fully automated with Ansible and RunDeck, and a complete redeploy can be triggered in around two minutes with the playbook authenticating via a dedicated, rotatable token to retrieve the secrets it needs at runtime.
“It’s about trying to optimise the amount of time that the people working at the tunnel can focus on just working at the tunnel,” says Brunton.
ID control plane
But the engagement doesn’t begin and end with wind tunnel uptime; the efficiencies go much deeper.
In moving its secrets into 1Password, Oracle Red Bull Racing has created a single, trusted control plane for credentials spanning Kubernetes clusters, environments, namespaces, factory, wind tunnel and simulation workloads.
Developers now access shared vaults with clear ownership and repeatable patterns to make sure that they can retain predictable access during redeployments or workflow changes, while human and automation access are segregated into dedicated vaults with limited user access for critical Kubernetes workloads – this includes Aero clusters and Kubernetes deployments.
The team is now using 1Password’s Kubernetes Operator, authenticated via 1Password Connect Server, to pull values from 1Password items and create Kubernetes secrets for workloads. If items change, the operator can update the secret and trigger a roll-out to allow workloads to pick up the new values.
In Brunton’s Aerodynamics unit alone, for example, five vaults hold almost 100 entries for cluster credentials, SQL passwords, client secrets, access tokens and Windows Virtual Machine (VM) logins. Meanwhile, his colleagues in Vehicle Performance and Powertrains maintain more than 150 entries. Now that new deployments default to 1Password, the two teams can reduce the time they spend coordinating access, limit potentially dangerous ad hoc sharing, and understand what credentials are current when developers are in the process of modifying (or restoring) workloads.
For simulation workflows, Oracle Red Bull Racing is using the 1Password command line interface (CLI) to retrieve SQL connection strings and Microsoft Entra ID credentials to access their needed services. Now that these secrets are centralised, they can replace plaintext credentials with secret references from a shared and governed source instead of having to embed secrets in code or configuration files – another risk.
Since their applications now rely on secret references, this means users can safely change out their credentials and support both safer automation and earlier application programming interface (API) adoption. The results are improved fidelity and capability much earlier in the simulation process, when changes are much easier to manage – and more affordable – than doing it outside of simulation.
Going trackside
“We’re always trying to raise the bar with our cyber posture and credential management,” says Cadieux. “Everyone here is part of a team and tries to do the right thing – and if you tap someone on the shoulder, it usually corrects the behaviour quite quickly – so having early visibility and being able to nip problems in the bud with a simple tap is helpful.”
Having standardised secrets and access across engineering, Oracle Red Bull Racing is now looking to take 1Password trackside. On a given race weekend, it runs multiple advanced Monte Carlo (the mathematical model, not the Grand Prix) simulations to evaluate different scenarios and support on-the-fly strategy decisions.
It is now exploring the application of these same patterns to its Oracle Cloud Infrastructure (OCI)-based trackside systems – including credential and certificate management – through which it can achieve consistent automation at race-day pressure.
Upgrading your home office can feel like going down a rabbit hole. A simple search for a basic new desk can quickly turn into hours down the drain and endless tabs open on your computer, with every option starting to blur together. Uplift has a loyal following for its super customizable desks, smart (and creative—under-desk hammock, anyone?) accessories, and a solid build quality that makes long workdays more manageable.
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Two days before the Musk v. Altman trial began, Elon Musk asked OpenAI cofounder and president Greg Brockman about reaching a settlement. When Brockman suggested both sides drop their claims, Musk responded, “By the end of this week, you and Sam [Altman] will be the most hated men in America. If you insist, so be it.”
The message—which OpenAI’s lawyers made public on Sunday, and which Judge Yvonne Gonzalez Rogers subsequently refused to let the jury hear about—underscores what may be Musk’s larger goal in this trial. He appears to be trying to not only win over the jurors to potentially remove Brockman and CEO Sam Altman from power, but also stir up dirt on the two men and damage OpenAI’s public image.
As Brockman took the stand on Monday, Musk’s attorney Steven Molo quickly started questioning him about his compensation at OpenAI. Brockman revealed that his equity stake at OpenAI is currently worth more than $20 billion, and perhaps up to $30 billion. While Brockman initially promised to donate $100,000 to OpenAI when it was being set up, he said he ultimately never followed through.
Brockman has held a number of instrumental roles at OpenAI since he cofounded the company in 2015. In the startup’s early days, it operated out of his apartment in the Mission District of San Francisco. Today, he’s deeply involved with refocusing OpenAI on a few key products, such as Codex. In the past year, Brockman has also given millions to super PACs promoting AI and President Trump, and has previously said this increased political spending is related to OpenAI’s founding mission to create artificial general intelligence that benefits all of humanity.
In court on Monday, Molo tried to make the case that Brockman and Altman had essentially looted OpenAI’s original nonprofit, which Musk funded and helped create.
In its early days, OpenAI told investors and employees that its nonprofit mission took precedence over generating profit. Brockman testified that his financial interests are still, to this day, second to OpenAI’s nonprofit mission.
When OpenAI created its for-profit arm in 2019, which received assets from the nonprofit, Brockman testified that he was given a significant stake in the new entity. Early in OpenAI’s history, Brockman had referenced wanting to be a billionaire, writing in his personal journal, “Financially what will take me to $1B?”
On Monday, Molo pressed Brockman for several minutes about the vast wealth he had accumulated beyond his initial goal.
“Why not donate that $29 billion to the OpenAI nonprofit? Why didn’t you do that?” Molo asked. Brockman responded that he and others had poured “blood, sweat, and tears” into building OpenAI in the years since Musk left the company.
OpenAI’s foundation holds a stake of over $150 billion in the company, making it one of the richest nonprofits in history, Brockman said. That’s roughly five times Brockman’s ownership interest. Altogether, OpenAI employees hold about 25 percent of shares. The foundation has 27 percent. Brockman testified that OpenAI’s nonprofit had received less than $150 million from donors, implying Musk had been incidental to the company’s success and that the real drivers were those who stuck around to build out OpenAI.
Of course, Brockman’s stake in OpenAI could be worth much more than $30 billion if the company successfully goes public in the next two years. When asked whether OpenAI was exploring a potential IPO, Brockman said he believes so.
In 1985, the Innovative Design Fund placed an ad in Scientific American offering up to $10,000 to support clever prototypes for clothing, home decor, and textiles. William Freeman PhD ’92, then an electrical engineer at Polaroid and now an MIT professor, saw it and submitted a novel idea: a three-sided zipper. Instead of fastening pants, it’d be like a switch that seamlessly flips chairs, tents, and purses between soft and rigid states, making them easier to pack and put together.
Freeman’s blueprint was much like a regular zipper, except triangular. On each side, he nailed a belt to connect narrow wooden “teeth” together. A slider wrapping around the device could be moved up to fasten the three strips into place, straightening them into a triangular tube. His proposal was rejected, but Freeman patented his prototype and stored it in his garage in the hopes it might come in handy one day.
Nearly 40 years later, MIT Computer Science and Artificial Intelligence Laboratory (CSAIL) researchers wanted to revive the project to create items with “tunable stiffness.” Prior attempts to adjust that weren’t easily reversible or required manual assembly, so CSAIL built an automated design tool and adaptable fastener called the “Y-zipper.” The scientists’ software program helps users customize three-sided zippers, which it then builds on its own in a 3D printer using plastics. These devices can be attached or embedded into camping equipment, medical gear, robots, and art installations for more convenient assembly.
“A regular zipper is great for closing up flat objects, like a jacket, but Freeman ideated something more dynamic. Using current fabrication technology, his mechanism can transform more complex items,” says MIT postdoc and CSAIL researcher Jiaji Li, who is a lead author on an open-access paper presenting the project. “We’ve developed a process that builds objects you can rapidly shift from flexible to rigid, and you can be confident they’ll work in the real world.”
Why zippers?
Users can customize how the fasteners look when they’re zipped up in CSAIL’s software program; they can select the length of each strip, as well as the direction and angle at which they’ll bend. They can also choose from one of four motion “primitives” to select how the zipper will appear when it’s zipped up: straight, bent (similar to an arch), coiled (resembling a spring), or twisted (looks like screws).
The Y-zipper that results will appear to “shape-shift” in the real world. When unzipped, it can look like a squid with three sprawling tentacles, and when you close it up, it becomes a more compact structure (like a rod, for instance). This flexibility could be useful when you’re traveling — take pitching a tent, for example. The process can take up to six minutes to do alone, but with the Y-zipper’s help, it can be done in one minute and 20 seconds. You simply attach each arm to a side of the tent, supporting the structure from the top so that the zipper seemingly pops the canopy into place.
This seamless transition could also unlock more flexible wearables, often useful in medical scenarios. The team wrapped the Y-zipper around a wrist cast, so that a user could loosen it during the day, and zip it up at night to prevent further injuries. In turn, a seemingly stiff device can be made more comfortable, adjusting to a patient’s needs.
The system can also aid users in crafting technology that moves at the push of a button. One can attach a motor to the Y-zipper after fabrication to automate the zipping process, which helps build things like an adaptive robotic quadruped. The robot could potentially change the size of its legs, tightening up into taller limbs and unzipping when it needs to be lower to the ground. Eventually, such rapid adjustments could help the robot explore the uneven terrain of places like canyons or forests. Actuated Y-zippers can also build dynamic art installations — for example, the team created a long, winding flower that “bloomed” thanks to a static motor zipping up the device.
Mastering the material
While Li and his colleagues saw the creative potential of the Y-zipper, it wasn’t yet clear how durable it would be. Could they sustain daily use?
The team ran a series of stress tests to find out. First, they evaluated the strength and flexibility of polylactic acid (PLA) and thermoplastic polyurethane (TPU), two plastics commonly used in 3D printing. Using a machine that bent the Y-zippers down, they found that PLA could handle heavier loads, while TPU was more pliable.
In another experiment, CSAIL researchers used an actuator to continuously open and close the Y-zipper to see how long it’d take to snap. Some 18,000 cycles of zipping and unzipping later, they finally broke. Y-zipper’s secret to durability, according to 3D simulations: its elastic structure, which helps distribute the stress of heavy loads.
Despite these findings, Li envisions an even more durable three-sided zipper using stronger materials, like metal. They may also make the zippers bigger for larger-scale projects, but that’s not yet possible with their current 3D printing platform.
Jiaji also notes that some applications remain unexplored, like space exploration, wherein Y-zipper’s tentacles could be built into a spacecraft to grab nearby rock samples. Likewise, the zippers could be embedded into structures that can be assembled rapidly, helping relief workers quickly set up shelters or medical tents during natural disasters and rescues.
“Reimagining an everyday zipper to tackle 3D morphological transitions is a brilliant approach to dynamic assembly,” says Zhejiang University assistant professor Guanyun Wang, who wasn’t involved in the paper. “More importantly, it effectively bridges the gap between soft and rigid states, offering a highly scalable and innovative fabrication approach that will greatly benefit the future design of embodied intelligence.”
Li and Freeman wrote the paper with Tianjin University PhD student Xiang Chang and MIT CSAIL colleagues: PhD student Maxine Perroni-Scharf; undergraduate Dingning Cao; recent visiting researchers Mingming Li (Zhejiang University), Jeremy Mrzyglocki (Technical University of Munich), and Takumi Yamamoto (Keio University); and MIT Associate Professor Stefanie Mueller, who is a CSAIL principal investigator and senior author on the work. Their research was supported, in part, by a postdoctoral research fellowship from Zhejiang University and the MIT-GIST Program.
The researchers’ work was presented at the ACM’s Computer-Human Interaction (CHI) conference on Human Factors in Computing Systems in April.
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