NASA has been investigating the now-infamous Boeing Starliner incident since the story dominated headlines in late 2024 and early 2025. The Starliner suffered malfunctions that stranded now-retired astronauts Suni Williams and Butch Wilmore for months. The agency has now released a report on what happened, taking responsibility for its role in the mission’s failure. 

«The Boeing Starliner spacecraft has faced challenges throughout its uncrewed and most recent crewed missions,» said NASA Administrator Jared Isaacman in a NASA blog post on Thursday. «While Boeing built Starliner, NASA accepted it and launched two astronauts into space. The technical difficulties encountered during docking with the International Space Station were very apparent.»

NASA has now labelled the mission a «Type A mishap,» which is defined as a «total direct cost of mission failure and property damage greater than $2 million or more,» or where «crewed aircraft hull loss has occurred.» Both of those apply to the Starliner, which has cost the agency $4.2 billion to date. 

Isaacman also released a letter addressed to all NASA employees on X. The letter outlined various issues with the mission, including a «prior OFT thruster risk that was never fully understood,» disagreements among leadership about Williams and Wilmore’s return options, and the agency’s delay in declaring the mission a failure, despite its high-profile nature clearly showing it was. 

These sentiments were echoed in NASA’s press conference on Thursday. 

NASA has committed to working with Boeing to make the Starliner launch-worthy again and has been investigating technical issues and addressing them since the mishap early last year. Isaacman admitted at the press conference that the «true technical root cause» of the malfunctions still hasn’t been identified, but NASA believes it is close to identifying it. 

«We’re not starting from zero here,» Isaacman told a reporter during the press conference. «We’re sharing the results of multiple investigations that will be coming to light in the hours and days ahead. Boeing and NASA have been working to try and understand these technical challenges during that entire time period.»

A malfunction to remember

The crewed Starliner flight was delayed several times before finally launching on June 5, 2024. The crew experienced malfunctions en route to the ISS, including several thruster failures, which made docking particularly stressful. 

The Starliner’s return was delayed by two weeks before finally being sent home without Wilmore and Williams, who were left stranded on the ISS until returning with Crew-9 in March 2025. 

The Starliner’s story is far from over. NASA and Boeing intend to send the Starliner back to the ISS in an uncrewed resupply mission with a launch date currently set for April 2026.

Apple’s new iPhone 17 typically costs $830 for the 256GB configuration, or up to $1,030 for the 512GB configuration. However, T-Mobile isoffering it to customers for free if they meet certain qualifications. If you’ve been looking to trade in your old device or choose an eligible plan, now is a great time to nab this deal.

T-Mobile doesn’t mention a deadline for this deal’s end, but it’s best to act fast if you’ve been wanting the latest iPhone.

To get a free iPhone 17, you’ll need to switch to T-Mobile on an Experience Beyond or Experience More plan and open a new line. You can also choose a Better Value plan, but you must add at least three lines with that plan to get your phone. You can also add a new line on a qualifying plan to score the deal, so long as you also have an eligible device to trade in.

Buyers are still responsible for the $35 activation fee. You’ll get bill credits for 24 months that amount to your phone’s cost. Additionally, you can only get up to four devices with a new line on a qualifying plan.

Note that newer phones will net you more trade-in credits, but an iPhone 6 will net you at least $400 off. The iPhone 17 Pro is also free with a trade-in of an eligible device on an Experience Beyond plan. The iPhone 17 Pro Max is just over $4 per month right now, with the same qualifications.

We’ve also got a list of the best phone deals, if you’d like to shop around.

Why this deal matters

The iPhone 17 series is the latest in Apple’s ecosystem. These smartphones are made to work with Apple Intelligence, include faster chips, offer improved camera performance and show off Apple’s trademark gorgeous design. Starting at $830, they’re not the cheapest phones around, so carrier deals like this one are the best way to save some serious cash.

Team USA’s skiers and snowboarders are going home with some new hardware, including a few gold medals, from the 2026 Olympics. Along with the years of hard work that go into being an Olympic athlete, this year’s crew had an extra edge in their training thanks to a custom AI tool from Google Cloud.

US Ski and Snowboard, the governing body for the US national teams, oversees the training of the best skiers and snowboarders in the country to prepare them for big events, such as national championships and the Olympics. The organization partnered with Google Cloud to build an AI tool to offer more insight into how athletes are training and performing on the slopes.

Video review is a big part of winter sports training. A coach will literally stand on the sidelines recording an athlete’s run, then review the footage with them afterward to spot errors. But this process is somewhat dated, Anouk Patty, chief of sport at US Ski and Snowboard, told me. That’s where Google came in, bringing new AI-powered data insights to the training process.

Google Cloud engineers hit the slopes with the skiers and snowboarders to understand how to build an actually useful AI model for athletic training. They used video footage as the base of the currently unnamed AI tool. Gemini did a frame-by-frame analysis of the video, which was then fed into spatial intelligence models from Google DeepMind. Those models were able to take the 2D rendering of the athlete from the video and transform it into a 3D skeleton of an athlete as they contort and twist on runs. 

Final touches from Gemini help the AI tool analyze the physics in the pixels, according to Ravi Rajamani, global head of Google’s AI Blackbelt team. which worked on the project. Coaches and athletes told the engineers the specific metrics they wanted to track — speed, rotation, trajectory — and the Google engineers coded the model to make it easy to monitor them and compare between different videos. There’s also a chat interface to ask Gemini questions about performance.

«From just a video, we are actually able to recreate it in 3D, so you don’t need expensive equipment, [like] sensors, that get in the way of an athlete performing,» Rajamani said.

Coaches are undeniably the experts on the mountain, but the AI can act as a kind of gut check. The data can help confirm or deny what coaches are seeing and give them extra insight into the specifics of each athlete’s performance. It can catch things that humans would struggle to see with the naked eye or in poor video quality, like where an athlete was looking while doing a trick and the exact speed and angle of a rotation. 

«It’s data that they wouldn’t otherwise have,» Patty said. The 3D skeleton is especially helpful because it makes it easier to see movement obscured by the puffy jackets and pants athletes wear, she said. 

For elite athletes in skiing and snowboarding, making small adjustments can mean the difference between a gold medal and no medal at all. Technological advances in training are meant to help athletes get every available tool for improvement.

«You’re always trying to find that 1% that can make the difference for an athlete to get them on the podium or to win,» Patty said. It can also democratize coaching. «It’s a way for every coach who’s out there in a club working with young athletes to have that level of understanding of what an athlete should do that the national team athletes have.»

For Google, this purpose-built AI tool is «the tip of the iceberg,» Rajamani said. There are a lot of potential future use cases, including expanding the base model to be customized to other sports. It also lays the foundation for work in sports medicine, physical therapy, robotics and ergonomics — disciplines where understanding body positioning is important. But for now, there’s satisfaction in knowing the AI was built to actually help real athletes.

«This was not a case of tech engineers building something in the lab and handing it over,» Rajamani said. «This is a real-world problem that we are solving. For us, the motivation was building a tool that provides a true competitive advantage for our athletes.»