
Bitcoin price held above $85,000, but weakening spot BTC ETF flows and a disappointing end-of-year performance cast doubt on a December rally to $100,000.


Bitcoin price held above $85,000, but weakening spot BTC ETF flows and a disappointing end-of-year performance cast doubt on a December rally to $100,000.
Rolling out enterprise-grade AI means climbing two steep cliffs at once. First, understanding and implementing the tech itself. And second, creating the cultural conditions where employees can maximize its value. While the technical hurdles are significant, the human element can be even more consequential; fear and ambiguity can stall momentum of even the most promising initiatives.

Psychological safety—feeling free to express opinions and take calculated risks without worrying about career repercussions1—is essential for successful AI adoption. In psychologically safe workspaces, employees are empowered to challenge assumptions and raise concerns about new tools without fear of reprisal. This is nothing short of a necessity when introducing a nascent and profoundly powerful technology that still lacks established best practices.
“Psychological safety is mandatory in this new era of AI,” says Rafee Tarafdar, executive vice president and chief technology officer at Infosys. “The tech itself is evolving so fast—companies have to experiment, and some things will fail. There needs to be a safety net.”
To gauge how psychological safety influences success with enterprise-level AI, MIT Technology Review Insights conducted a survey of 500 business leaders. The findings reveal high self-reported levels of psychological safety, but also suggest that fear still has a foothold. Anecdotally, industry experts highlight a reason for the disconnect between rhetoric and reality: while organizations may promote a safe to experiment message publicly, deeper cultural undercurrents can counteract that intent.
Building psychological safety requires a coordinated, systems-level approach, and human resources (HR) alone cannot deliver such transformation. Instead, enterprises must deeply embed psychological safety into their collaboration processes.

Key findings for this report include:
This content was produced by Insights, the custom content arm of MIT Technology Review. It was not written by MIT Technology Review’s editorial staff. It was researched, designed, and written by human writers, editors, analysts, and illustrators. This includes the writing of surveys and collection of data for surveys. AI tools that may have been used were limited to secondary production processes that passed thorough human review.
This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology.
The great AI hype correction of 2025
Some disillusionment was inevitable. When OpenAI released a free web app called ChatGPT in late 2022, it changed the course of an entire industry—and several world economies. Millions of people started talking to their computers, and their computers started talking back. We were enchanted, and we expected more.
Well, 2025 has been a year of reckoning. For a start, the heads of the top AI companies made promises they couldn’t keep. At the same time, updates to the core technology are no longer the step changes they once were.
To be clear, the last few years have been filled with genuine “Wow” moments. But this remarkable technology is only a few years old, and in many ways it is still experimental. Its successes come with big caveats. Read the full story to learn more about why we may need to readjust our expectations.
—Will Douglas Heaven
This story is part of our new Hype Correction package, a collection of stories designed to help you reset your expectations about what AI makes possible—and what it doesn’t. Check out the rest of the package here, and you can read more about why it’s time to reset our expectations for AI in the latest edition of the Algorithm, our weekly AI newsletter. Sign up here to make sure you receive future editions straight to your inbox.
Quantum navigation could solve the military’s GPS jamming problem
Since the 2022 invasion of Ukraine, thousands of flights have been affected by a far-reaching Russian campaign of using radio transmissions that jammed its GPS system.
The growing inconvenience to air traffic and risk of a real disaster have highlighted the vulnerability of GPS and focused attention on more secure ways for planes to navigate the gauntlet of jamming and spoofing, the term for tricking a GPS receiver into thinking it’s somewhere else.
One approach that’s emerging from labs is quantum navigation: exploiting the quantum nature of light and atoms to build ultra-sensitive sensors that can allow vehicles to navigate independently, without depending on satellites. Read the full story.
—Amos Zeeberg
The must-reads
I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology.
1 The Trump administration has launched its US Tech Force program
In a bid to lure engineers away from Big Tech roles and straight into modernizing the government. (The Verge)
+ So, essentially replacing the IT workers that DOGE got rid of, then. (The Register)
2 Lawmakers are investigating how AI data centers affect electricity costs
They want to get to the bottom of whether it’s being passed onto consumers. (NYT $)
+ Calculating AI’s water usage is far from straightforward, too. (Wired $)
+ AI is changing the grid. Could it help more than it harms? (MIT Technology Review)
3 Ford isn’t making a large all-electric truck after all
After the US government’s support for EVs plummeted. (Wired $)
+ Instead, the F-150 Lightning pickup will be reborn as a plug-in hybrid. (The Information $)
+ Why Americans may be finally ready to embrace smaller cars. (Fast Company $)
+ The US could really use an affordable electric truck. (MIT Technology Review)
4 PayPal wants to become a bank in the US
The Trump administration is very friendly to non-traditional financial companies, after all. (FT $)
+ It’s been a good year for the crypto industry when it comes to banking. (Economist $)
5 A tech trade deal between the US and UK has been put on ice
America isn’t happy with the lack of progress Britain has made, apparently. (NYT $)
+ It’s a major setback in relations between the pair. (The Guardian)
6 Why does no one want to make the cure for dengue?
A new antiviral pill appears to prevent infection—but its development has been abandoned. (Vox)
7 The majority of the world’s glaciers are forecast to disappear by 2100
At a rate of around 3,000 per year. (New Scientist $)
+ Inside a new quest to save the “doomsday glacier”. (MIT Technology Review)
8 Hollywood is split over AI
While some filmmakers love it, actors are horrified by its inexorable rise. (Bloomberg $)
9 Corporate America is obsessed with hiring storytellers
It’s essentially a rehashed media relations manager role overhauled for the AI age. (WSJ $)
10 The concept of hacking existed before the internet
Just ask this bunch of teenage geeks. (IEEE Spectrum)
Quote of the day
“So the federal government deleted 18F, which was doing great work modernizing the government, and then replaced it with a clone? What is the point of all this?”
—Eugene Vinitsky, an assistant professor at New York University, takes aim at the US government’s decision to launch a new team to overhaul its approach to technology in a post on Bluesky.
One more thing

How DeepSeek became a fortune teller for China’s youth
As DeepSeek has emerged as a homegrown challenger to OpenAI, young people across the country have started using AI to revive fortune-telling practices that have deep roots in Chinese culture.
Across Chinese social media, users are sharing AI-generated readings, experimenting with fortune-telling prompt engineering, and revisiting ancient spiritual texts—all with the help of DeepSeek.
The surge in AI fortune-telling comes during a time of pervasive anxiety and pessimism in Chinese society. And as spiritual practices remain hidden underground thanks to the country’s regime, computers and phone screens are helping younger people to gain a sense of control over their lives. Read the full story.
—Caiwen Chen
We can still have nice things
A place for comfort, fun and distraction to brighten up your day. (Got any ideas? Drop me a line or skeet ’em at me.)
+ Chess has been online as far back as the 1800s (no, really!) 
+ Jane Austen was born 250 years ago today. How well do you know her writing? ($)
+ Rob Reiner, your work will live on forever.
+ I enjoyed this comprehensive guide to absolutely everything you could ever want to know about New England’s extensive seafood offerings.
Can I ask you a question: How do you feel about AI right now? Are you still excited? When you hear that OpenAI or Google just dropped a new model, do you still get that buzz? Or has the shine come off it, maybe just a teeny bit? Come on, you can be honest with me.
Truly, I feel kind of stupid even asking the question, like a spoiled brat who has too many toys at Christmas. AI is mind-blowing. It’s one of the most important technologies to have emerged in decades (despite all its many many drawbacks and flaws and, well, issues).
At the same time I can’t help feeling a little bit: Is that it?
If you feel the same way, there’s good reason for it: The hype we have been sold for the past few years has been overwhelming. We were told that AI would solve climate change. That it would reach human-level intelligence. That it would mean we no longer had to work!
Instead we got AI slop, chatbot psychosis, and tools that urgently prompt you to write better email newsletters. Maybe we got what we deserved. Or maybe we need to reevaluate what AI is for.
That’s the reality at the heart of a new series of stories, published today, called Hype Correction. We accept that AI is still the hottest ticket in town, but it’s time to re-set our expectations.
As my colleague Will Douglas Heaven puts it in the package’s intro essay, “You can’t help but wonder: When the wow factor is gone, what’s left? How will we view this technology a year or five from now? Will we think it was worth the colossal costs, both financial and environmental?”
Elsewhere in the package, James O’Donnell looks at Sam Altman, the ultimate AI hype man, through the medium of his own words. And Alex Heath explains the AI bubble, laying out for us what it all means and what we should look out for.
Michelle Kim analyzes one of the biggest claims in the AI hype cycle: that AI would completely eliminate the need for certain classes of jobs. If ChatGPT can pass the bar, surely that means it will replace lawyers? Well, not yet, and maybe not ever.
Similarly, Edd Gent tackles the big question around AI coding. Is it as good as it sounds? Turns out the jury is still out. And elsewhere David Rotman looks at the real-world work that needs to be done before AI materials discovery has its breakthrough ChatGPT moment.
Meanwhile, Garrison Lovely spends time with some of the biggest names in the AI safety world and asks: Are the doomers still okay? I mean, now that people are feeling a bit less scared about their impending demise at the hands of superintelligent AI? And Margaret Mitchell reminds us that hype around generative AI can blind us to the AI breakthroughs we should really celebrate.
Let’s remember: AI was here before ChatGPT and it will be here after. This hype cycle has been wild, and we don’t know what its lasting impact will be. But AI isn’t going anywhere. We shouldn’t be so surprised that those dreams we were sold haven’t come true—yet.
The more likely story is that the real winners, the killer apps, are still to come. And a lot of money is being bet on that prospect. So yes: The hype could never sustain itself over the short term. Where we’re at now is maybe the start of a post-hype phase. In an ideal world, this hype correction will reset expectations.
Let’s all catch our breath, shall we?
This story first appeared in The Algorithm, our weekly free newsletter all about AI. Sign up to read past editions here.
In late September, a Spanish military plane carrying the country’s defense minister to a base in Lithuania was reportedly the subject of a kind of attack—not by a rocket or anti-aircraft rounds, but by radio transmissions that jammed its GPS system.
The flight landed safely, but it was one of thousands that have been affected by a far-reaching Russian campaign of GPS interference since the 2022 invasion of Ukraine. The growing inconvenience to air traffic and risk of a real disaster have highlighted the vulnerability of GPS and focused attention on more secure ways for planes to navigate the gauntlet of jamming and spoofing, the term for tricking a GPS receiver into thinking it’s somewhere else.
US military contractors are rolling out new GPS satellites that use stronger, cleverer signals, and engineers are working on providing better navigation information based on other sources, like cellular transmissions and visual data.
But another approach that’s emerging from labs is quantum navigation: exploiting the quantum nature of light and atoms to build ultra-sensitive sensors that can allow vehicles to navigate independently, without depending on satellites. As GPS interference becomes more of a problem, research on quantum navigation is leaping ahead, with many researchers and companies now rushing to test new devices and techniques. In recent months, the US’s Defense Advanced Research Projects Agency (DARPA) and its Defense Innovation Unit have announced new grants to test the technology on military vehicles and prepare for operational deployment.
Tracking changes
Perhaps the most obvious way to navigate is to know where you started and then track where you go by recording the speed, direction, and duration of travel. But while this approach, known in the field as inertial navigation, is conceptually simple, it’s difficult to do well; tiny uncertainties in any of those measurements compound over time and lead to big errors later on. Douglas Paul, the principal investigator of the UK’s Hub for Quantum Enabled Precision, Navigation & Timing (QEPNT), says that existing specialized inertial-navigation devices might be off by 20 kilometers after 100 hours of travel. Meanwhile, the cheap sensors commonly used in smartphones produce more than twice that level of uncertainty after just one hour.
“If you’re guiding a missile that flies for one minute, that might be good enough,” he says. “If you’re in an airliner, that’s definitely not good enough.”
A more accurate version of inertial navigation instead uses sensors that rely on the quantum behavior of subatomic particles to more accurately measure acceleration, direction, and time.
Several companies, like the US-based Infleqtion, are developing quantum gyroscopes, which track a vehicle’s bearing, and quantum accelerometers, which can reveal how far it’s traveled. Infleqtion’s sensors are based on a technique called atom interferometry: A beam of rubidium atoms is zapped with precise laser pulses, which split the atoms into two separate paths. Later, other laser pulses recombine the atoms, and they’re measured with a detector. If the vehicle has turned or accelerated while the atoms are in motion, the two paths will be slightly out of phase in a way the detector can interpret.
Last year the company trialed these inertial sensors on a customized plane flying at a British military testing site. In October of this year, Infleqtion ran its first real-world test of a new generation of inertial sensors that use a steady stream of atoms instead of pulses, allowing for continuous navigation and avoiding long dead times.

Infleqtion also has an atomic clock, called Tiqker, that can help determine how far a vehicle has traveled. It is a kind of optical clock that uses infrared lasers tuned to a specific frequency to excite electrons in rubidium, which then release photons at a consistent, known rate. The device “will lose one second every 2 million years or so,” says Max Perez, who oversees the project, and it fits in a standard electronics equipment rack. It has passed tests on flights in the UK, on US Army ground vehicles in New Mexico, and, in late October, on a drone submarine.
“Tiqker operated happily through these conditions, which is unheard-of for previous generations of optical clocks,” says Perez. Eventually the company hopes to make the unit smaller and more rugged by switching to lasers generated by microchips.
Magnetic fields
Vehicles deprived of satellite-based navigation are not entirely on their own; they can get useful clues from magnetic and gravitational fields that surround the planet. These fields vary slightly depending on the location, and the variations, or anomalies, are recorded in various maps. By precisely measuring the local magnetic or gravitational field and comparing those values with anomaly maps, quantum navigation systems can track the location of a vehicle.
Allison Kealy, a navigation researcher at Swinburne University in Australia, is working on the hardware needed for this approach. Her team uses a material called nitrogen-vacancy diamond. In NV diamonds, one carbon atom in the lattice is replaced with a nitrogen atom, and one neighboring carbon atom is removed entirely. The quantum state of the electrons at the NV defect is very sensitive to magnetic fields. Carefully stimulating the electrons and watching the light they emit offers a way to precisely measure the strength of the field at the diamond’s location, making it possible to infer where it’s situated on the globe.
Kealy says these quantum magnetometers have a few big advantages over traditional ones, including the fact that they measure the direction of the Earth’s magnetic field in addition to its strength. That additional information could make it easier to determine location.
The technology is far from commercial deployment, but Kealy and several colleagues successfully tested their magnetometer in a set of flights in Australia late last year, and they plan to run more trials this year and next. “This is where it gets exciting, as we transition from theoretical models and controlled experiments to on-the-ground, operational systems,” she says. “This is a major step forward.”
Delicate systems
Other teams, like Q-CTRL, an Australian quantum technology company, are focusing on using software to build robust systems from noisy quantum sensors. Quantum navigation involves taking those delicate sensors, honed in the placid conditions of a laboratory, and putting them in vehicles that make sharp turns, bounce with turbulence, and bob with waves, all of which interferes with the sensors’ functioning. Even the vehicles themselves present problems for magnetometers, especially “the fact that the airplane is made of metal, with all this wiring,” says Michael Biercuk, the CEO of Q-CTRL. “Usually there’s 100 to 1,000 times more noise than signal.”
After Q-CTRL engineers ran trials of their magnetic navigation system in a specially outfitted Cessna last year, they used machine learning to go through the data and try to sift out the signal from all the noise. Eventually they found they could track the plane’s location up to 94 times as accurately as a strategic-grade conventional inertial navigation system could, according to Biercuk. They announced their findings in a non-peer-reviewed paper last spring.
In August Q-CTRL received two contracts from DARPA to develop its “software-ruggedized” mag-nav product, named Ironstone Opal, for defense applications. The company is also testing the technology with commercial partners, including the defense contractors Northrop Grumman and Lockheed Martin and Airbus, an aerospace manufacturer.

“Northrop Grumman is working with Q-CTRL to develop a magnetic navigation system that can withstand the physical demands of the real world,” says Michael S. Larsen, a quantum systems architect at the company. “Technology like magnetic navigation and other quantum sensors will unlock capabilities to provide guidance even in GPS-denied or -degraded environments.”
Now Q-CTRL is working on putting Ironstone Opal into a smaller, more rugged container appropriate for deployment; currently, “it looks like a science experiment because it is a science experiment,” says Biercuk. He anticipates delivering the first commercial units next year.
Sensor fusion
Even as quantum navigation emerges as a legitimate alternative to satellite-based navigation, the satellites themselves are improving. Modern GPS III satellites include new civilian signals called L1C and L5, which should be more accurate and harder to jam and spoof than current signals. Both are scheduled to be fully operational later this decade.
US and allied military users are intended to have access to far hardier GPS tools, including M-code, a new form of GPS signal that is rolling out now, and Regional Military Protection, a focused GPS beam that will be restricted to small geographic areas. The latter will start to become available when the GPS IIIF generation of satellites is in orbit, with the first scheduled to go up in 2027. A Lockheed Martin spokesperson says new GPS satellites with M-code are eight times as powerful as previous ones, while the GPS IIIF model will be 60 times as strong.
Other plans involve using navigation satellites in low Earth orbit—the zone inhabited by SpaceX’s internet-providing Starlink constellation—rather than the medium Earth orbit used by GPS. Since objects in LEO are closer to Earth, their signals are stronger, which makes them harder to jam and spoof. LEO satellites also transit the sky more quickly, which makes them harder still to spoof and helps GPS receivers get a lock on their position faster. “This really helps for signal convergence,” says Lotfi Massarweh, a satellite navigation researcher at Delft University of Technology, in the Netherlands. “They can get a good position in just a few minutes. So that is a huge leap.”
Ultimately, says Massarweh, navigation will depend not only on satellites, quantum sensors, or any other single technology, but on the combination of all of them. “You need to think always in terms of sensor fusion,” he says.
The navigation resources that a vehicle draws on will change according to its environment—whether it’s an airliner, a submarine, or an autonomous car in an urban canyon. But quantum navigation will be one important resource. He says, “If quantum technology really delivers what we see in the literature—if it’s stable over one week rather than tens of minutes—at that point it is a complete game changer.”