From digital red packets to memecoins, Bitcoin continues its love affair with Lunar New Year in 2025.
SushiSwap’s total value locked has declined sharply since 2021 highs, according to DefiLlama.
SoftBank is negotiating a $500 million investment in Skild AI, a software company building a foundational model for robotics at a $4 billion valuation, Bloomberg and Financial Times reported. The two-year-old company raised its previous funding round of $300 million at a $1.5 billion valuation last July from investors including Jeff Bezos, Lightspeed Venture Partners, […]
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The jury is still out on whether the Chinese AI upstart DeepSeek is a game changer or possibly part of an elaborate plan by its hedge fund parent company to short Nvidia and other tech stocks. Whichever it might be (maybe both?), DeepSeek and its large language model has made some major waves. Now, it’s […]
© 2024 TechCrunch. All rights reserved. For personal use only.
DeepSeek has gone viral. Chinese AI lab DeepSeek broke into the mainstream consciousness this week after its chatbot app rose to the top of the Apple App Store charts. DeepSeek’s AI models, which were trained using compute-efficient techniques, have led Wall Street analysts — and technologists — to question whether the U.S. can maintain its lead in the AI race […]
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David Sacks, Trump’s AI and crypto “czar,” said in an interview on Fox on Tuesday that there’s “substantial evidence” that Chinese AI company DeepSeek “distilled” knowledge from OpenAI’s AI models, a process that Sacks compared to theft. Sacks, who didn’t cite the source of this “evidence,” suggested that DeepSeek used responses from OpenAI models to […]
© 2024 TechCrunch. All rights reserved. For personal use only.
Hype around DeepSeek sent the stock price of several Chinese companies soaring, but proof of their ties to DeepSeek is non-existent.
© 2024 TechCrunch. All rights reserved. For personal use only.
Mice with two fathers have been born—and have survived to adulthood—following a complex set of experiments by a team in China.
Zhi-Kun Li at the Chinese Academy of Sciences in Beijing and his colleagues used CRISPR to create the mice, using a novel approach to target genes that normally need to be inherited from both male and female parents. They hope to use the same approach to create primates with two dads.
Humans are off limits for now, but the work does help us better understand a strange biological phenomenon known as imprinting, which causes certain genes to be expressed differently depending on which parent they came from. For these genes, animals inherit part of a “dose” from each parent, and the two must work in harmony to create a healthy embryo. Without both doses, gene expression can go awry, and the resulting embryos can end up with abnormalities.
This is what researchers have found in previous attempts to create mice with two dads. In the 1980s, scientists in the UK tried injecting the DNA-containing nucleus of a sperm cell into a fertilized egg cell. The resulting embryos had DNA from two males (as well as a small amount of DNA from a female, in the cytoplasm of the egg).
But when these embryos were transferred to the uteruses of surrogate mouse mothers, none of them resulted in a healthy birth, seemingly because imprinted genes from both paternal and maternal genomes are needed for development.
Li and his colleagues took a different approach. The team used gene editing to knock out imprinted genes altogether.
Around 200 of a mouse’s genes are imprinted, but Li’s team focused on 20 that are known to be important for the development of the embryo.
In an attempt to create healthy mice with DNA from two male “dads,” the team undertook a complicated set of experiments. To start, the team cultured cells with sperm DNA to collect stem cells in the lab. Then they used CRISPR to disrupt the 20 imprinted genes they were targeting.
These gene-edited cells were then injected, along with other sperm cells, into egg cells that had had their own nuclei removed. The result was embryonic cells with DNA from two male mice. These cells were then injected into a type of “embryo shell” used in research, which provides the cells required to make a placenta. The resulting embryos were transferred to the uteruses of female mice.
It worked—to some degree. Some of the embryos developed into live pups, and they even survived to adulthood. The findings were published in the journal Cell Stem Cell.
“It’s exciting,” says Kotaro Sasaki, a developmental biologist at the University of Pennsylvania, who was not involved in the work. Not only have Li and his team been able to avoid a set of imprinting defects, but their approach is the second way scientists have found to create mice using DNA from two males.
The finding builds on research by Katsuhiko Hayashi, now at Osaka University in Japan, and his colleagues. A couple of years ago, that team presented evidence that they had found a way to take cells from the tails of adult male mice and turn them into immature egg cells. These could be fertilized with sperm to create bi-paternal embryos. The mice born from those embryos can reach adulthood and have their own offspring, Hayashi has said.
Li’s team’s more complicated approach was less successful. Only a small fraction of the mice survived, for a start. The team transferred 164 gene-edited embryos, but only seven live pups were born. And those that were born weren’t entirely normal, either. They grew to be bigger than untreated mice, and their organs appeared enlarged. They didn’t live as long as normal mice, and they were infertile.
It would be unethical to do such risky research with human cells and embryos. “Editing 20 imprinted genes in humans would not be acceptable, and producing individuals who could not be healthy or viable is simply not an option,” says Li.
“There are numerous issues,” says Sasaki. For a start, a lot of the technical lab procedures the team used have not been established for human cells. But even if we had those, this approach would be dangerous—knocking out human genes could have untold health consequences.
“There’s lots and lots of hurdles,” he says. “Human applications [are] still quite far.”
Despite that, the work might shed a little more light on the mysterious phenomenon of imprinting. Previous research has shown that mice with two moms appear smaller, and live longer than expected, while the current study shows that mice with two dads are overgrown and die more quickly. Perhaps paternal imprinted genes support growth and maternal ones limit it, and animals need both to reach a healthy size, says Sasaki.
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.
AI’s energy obsession just got a reality check
Just a week in, the AI sector has already seen its first battle of wits under the new Trump administration. The clash stems from two key pieces of news: the announcement of the Stargate project, which would spend $500 billion—more than the Apollo space program—on new AI data centers, and the release of a powerful new open-source model from China.
Together, they raise important questions the industry needs to answer about the extent to which the race for more data centers—with their heavy environmental toll—is really necessary.
If, in dissecting DeepSeek R1, AI companies discover some lessons about how to make models use existing resources more effectively, perhaps constructing more and more data centers won’t be the only winning formula for better AI. Read the full story.
—James O’Donnell
This story originally appeared in The Algorithm, our weekly newsletter on AI. To get stories like this in your inbox first, sign up here.
Robotaxis: 10 Breakthrough Technologies 2025
If you live in certain cities in America or China, you’ve probably spotted driverless cars dropping off passengers. Perhaps you’ve even ridden in one yourself. That’s a radical change from even three years ago, when these services were still learning the rules of the road. And robotaxis could soon be operating in many more cities.
After years of beta testing, driverless taxis are now finally becoming available to the public. In more than a dozen cities worldwide, riders can summon one whenever they want. Now, the biggest players are ramping up for intense competition as they expand into new cities under regulators’ watchful eyes. Read the full story.
—Rhiannon Williams
Robotaxis is one of our 10 Breakthrough Technologies for 2025, MIT Technology Review’s annual list of tech to watch. Check out the rest of the list, and cast your vote for the honorary 11th breakthrough.
The must-reads
I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology.
1 DeepSeek’s AI model is sending US data to China
Which could open it up to a lot of scrutiny in the US. (Wired $)
+ The model’s popularity has made it a cyber attack target. (The Guardian)
+ The company was forced to limit the number of new users registering. (The Verge)
+ How a top Chinese AI model overcame US sanctions. (MIT Technology Review)
2 DeepSeek’s success is emboldening other Chinese startups
Moonshot and Zhipu are among the firms racing to capitalize on the world’s attention. (FT $)
+ DeepSeek mania has gripped the world and shaken the markets. (404 Media)
+ The country is cheering on its homegrown success story. (Bloomberg $)
+ …And many Americans are impressed by it, too. (The Atlantic $)
3 Microsoft has entered the fray to buy TikTok
According to Donald Trump, at least. (WP $)
+ Microsoft had originally floated buying the app back in 2020. (Reuters)
4 Google Maps is changing the Gulf of Mexico to Gulf of America
But users in Mexico will continue to see its original name. (CNBC)
+ Other countries across the world will be presented with both names. (Forbes $)
5 Scammers are using AI to create blackmail videos
The clips feature AI-generated news anchors reporting on sextortion cases. (Wired $)
+ An AI startup made a hyperrealistic deepfake of me that’s so good it’s scary. (MIT Technology Review)
6 Amazon is seeking permission to fly drones in the North of England
The retail giant is lagging behind other drone projects in the UK.(The Guardian)
7 This new fertility treatment could be a viable IVF alternative
As well as a much less painful, invasive procedure. (The Atlantic $)
+ This biotech CEO decided to take her own (fertility) medicine. (MIT Technology Review)
8 Yahoo is determined to become cool again
By capitalizing on our obsession with nostalgia. (Insider $)
9 The Pebble smartwatch is back
Almost a decade after Fitbit bought the company, it’s relaunching. (The Verge)
+ But it’s going to need a new name. (TechCrunch)
10 How to measure the shape of the universe
Subtle signals could help us to map it out. (Quanta Magazine)
+ Why is the universe so complex and beautiful? (MIT Technology Review)
Quote of the day
“It’s legit invigorating to have a new competitor!”
—OpenAI boss Sam Altman says he’s not worried at all by the success of open-source AI model DeepSeek R1 in a post on X.
The big story
Meet the divers trying to figure out how deep humans can go
February 2024
Two hundred thirty meters into one of the deepest underwater caves on Earth, Richard “Harry” Harris knew that not far ahead of him was a 15-meter drop leading to a place no human being had seen before.
Getting there had taken two helicopters, three weeks of test dives, two tons of equipment, and hard work to overcome an unexpected number of technical problems. But in the moment, Harris was hypnotized by what was before him: the vast, black, gaping unknown.
Staring into it, he felt the familiar pull—maybe he could go just a little farther. Instead, he and his diving partner, Craig Challen, decided to turn back. That’s because they weren’t there to set records. Instead, they were there to test what they saw as a possible key to unlocking depths beyond even 310 meters: breathing hydrogen. Read the full story.
—Samantha Schuyler
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.)
+ How to make a tasty mocktail like a pro. 
+ Happy birthday to the one and only Billy Ocean, who recently turned the ripe old age of 75.
+ Fans of video game Deep Rock Galactic are a rarity—a kind, welcoming and friendly gaming community.
+ Hongbao, the little red envelopes given out at Lunar New Year, have a long and fascinating history. 
This story originally appeared in The Algorithm, our weekly newsletter on AI. To get stories like this in your inbox first, sign up here.
Just a week in, the AI sector has already seen its first battle of wits under the new Trump administration. The clash stems from two key pieces of news: the announcement of the Stargate project, which would spend $500 billion—more than the Apollo space program—on new AI data centers, and the release of a powerful new model from China. Together, they raise important questions the industry needs to answer about the extent to which the race for more data centers—with their heavy environmental toll—is really necessary.
A reminder about the first piece: OpenAI, Oracle, SoftBank, and an Abu Dhabi–based investment fund called MGX plan to spend up to $500 billion opening massive data centers around the US to build better AI. Much of the groundwork for this project was laid in 2024, when OpenAI increased its lobbying spending sevenfold (which we were first to report last week) and AI companies started pushing for policies that were less about controlling problems like deepfakes and misinformation, and more about securing more energy.
Still, Trump received credit for it from tech leaders when he announced the effort on his second day in office. “I think this will be the most important project of this era,” OpenAI’s Sam Altman said at the launch event, adding, “We wouldn’t be able to do this without you, Mr. President.”
It’s an incredible sum, just slightly less than the inflation-adjusted cost of building the US highway system over the course of more than 30 years. However, not everyone sees Stargate as having the same public benefit. Environmental groups say it could strain local grids and further drive up the cost of energy for the rest of us, who aren’t guzzling it to train and deploy AI models. Previous research has also shown that data centers tend to be built in areas that use much more carbon-intensive sources of energy, like coal, than the national average. It’s not clear how much, if at all, Stargate will rely on renewable energy.
Even louder critics of Stargate, though, include Elon Musk. None of Musk’s companies are involved in the project, and he has attempted to publicly sow doubt that OpenAI and SoftBank have enough of the money needed for the plan anyway, claims that Altman disputed on X. Musk’s decision to publicly criticize the president’s initiative has irked people in Trump’s orbit, Politico reports, but it’s not clear if those people have expressed that to Musk directly.
On to the second piece. On the day Trump was inaugurated, a Chinese startup released an AI model that started making a whole bunch of important people in Silicon Valley very worried about their competition. (This close timing is almost certainly not an accident.)
The model, called DeepSeek R1, is a reasoning model. These types of models are designed to excel at math, logic, pattern-finding, and decision-making. DeepSeek proved it could “reason” through complicated problems as well as one of OpenAI’s reasoning models, o1—and more efficiently. What’s more, DeepSeek isn’t a super-secret project kept behind lock and key like OpenAI’s. It was released for all to see.
DeepSeek was released as the US has made outcompeting China in the AI race a top priority. This goal was a driving force behind the 2022 CHIPS Act to make more chips domestically. It’s influenced the position of tech companies like OpenAI, which has embraced lending its models to national security work and has partnered with the defense-tech company Anduril to help the military take down drones. It’s led to export controls that limit what types of chips Nvidia can sell to China.
The success of DeepSeek signals that these efforts aren’t working as well as AI leaders in the US would like (though it’s worth noting that the impact of export controls for chips isn’t felt for a few years, so the policy wouldn’t be expected to have prevented a model like DeepSeek).
Still, the model poses a threat to the bottom line of certain players in Big Tech. Why pay for an expensive model from OpenAI when you can get access to DeepSeek for free? Even other makers of open-source models, especially Meta, are panicking about the competition, according to The Information. The company has set up a number of “war rooms” to figure out how DeepSeek was made so efficient. (A couple of days after the Stargate announcement, Meta said it would increase its own capital investments by 70% to build more AI infrastructure.)
What does this all mean for the Stargate project? Let’s think about why OpenAI and its partners are willing to spend $500 billion on data centers to begin with. They believe that AI in its various forms—not just chatbots or generative video or even new AI agents, but also developments yet to be unveiled—will be the most lucrative tool humanity has ever built. They also believe that access to powerful chips inside massive data centers is the key to getting there.
DeepSeek poked some holes in that approach. It didn’t train on yet-unreleased chips that are light-years ahead. It didn’t, to our knowledge, require the eye-watering amounts of computing power and energy behind the models from US companies that have made headlines. Its designers made clever decisions in the name of efficiency.
In theory, it could make a project like Stargate seem less urgent and less necessary. If, in dissecting DeepSeek, AI companies discover some lessons about how to make models use existing resources more effectively, perhaps constructing more and more data centers won’t be the only winning formula for better AI. That would be welcome to the many people affected by the problems data centers can bring, like lots of emissions, the loss of fresh, drinkable water used to cool them, and the strain on local power grids.
Thus far, DeepSeek doesn’t seem to have sparked such a change in approach. OpenAI researcher Noam Brown wrote on X, “I have no doubt that with even more compute it would be an even more powerful model.”
If his logic wins out, the players with the most computing power will win, and getting it is apparently worth at least $500 billion to AI’s biggest companies. But let’s remember—announcing it is the easiest part.
Now read the rest of The Algorithm
Deeper Learning
What’s next for robots
Many of the big questions about AI–-how it learns, how well it works, and where it should be deployed—are now applicable to robotics. In the year ahead, we will see humanoid robots being put to the test in warehouses and factories, robots learning in simulated worlds, and a rapid increase in the military’s adoption of autonomous drones, submarines, and more.
Why it matters: Jensen Huang, the highly influential CEO of the chipmaker Nvidia, stated last month that the next advancement in AI will mean giving the technology a “body” of sorts in the physical world. This will come in the form of advanced robotics. Even with the caveat that robotics is full of futuristic promises that usually aren’t fulfilled by their deadlines, the marrying of AI methods with new advancements in robots means the field is changing quickly. Read more here.
Bits and Bytes
Leaked documents expose deep ties between Israeli army and Microsoft
Since the attacks of October 7, the Israeli military has relied heavily on cloud and AI services from Microsoft and its partner OpenAI, and the tech giant’s staff has embedded with different units to support rollout, a joint investigation reveals. (+972 Magazine)
The tech arsenal that could power Trump’s immigration crackdown
The effort by federal agencies to acquire powerful technology to identify and track migrants has been unfolding for years across multiple administrations. These technologies may be called upon more directly under President Trump. (The New York Times)
OpenAI launches Operator—an agent that can use a computer for you
Operator is a web app that can carry out simple online tasks in a browser, such as booking concert tickets or making an online grocery order. (MIT Technology Review)
The second wave of AI coding is here
A string of startups are racing to build models that can produce better and better software. But it’s not only AI’s increasingly powerful ability to write code that’s impressive. They claim it’s the shortest path to superintelligent AI. (MIT Technology Review)