Henrik Werdelin has spent the last 15 years helping entrepreneurs build big brands like Barkbox through his startup studio Prehype. Now, with his new, New York-based venture Audos, he’s betting that AI can help him scale that process from “tens” of startups a year to “hundreds of thousands” of aspiring business owners. The timing certainly […]

This study demonstrates that extrachromosomal DNA (ecDNA) replication induces DNA double-strand breaks and activates the DNA damage response (DDR). The DDR pathways, such as alt-NHEJ, are critical for ecDNA maintenance in tumor cells. Mechanistic insights into ecDNA replication and maintenance unveil a therapeutic approach for treating tumors harboring ecDNA.

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.

Google’s new AI will help researchers understand how our genes work

When scientists first sequenced the human genome in 2003, they revealed the full set of DNA instructions that make a person. But we still didn’t know what all those 3 billion genetic letters actually do.

Now Google’s DeepMind division says it’s made a leap in trying to understand the code with AlphaGenome, an AI model that predicts what effects small changes in DNA will have on an array of molecular processes, such as whether a gene’s activity will go up or down.

It’s just the sort of question biologists regularly assess in lab experiments, and is an attempt to further smooth biologists’ work by answering basic questions about how changing DNA letters alters gene activity and, eventually, how genetic mutations affect our health. Read the full story.

—Antonio Regalado

It’s officially summer, and the grid is stressed

It’s crunch time for the grid this week. Large swaths of the US have reached or exceeded record-breaking temperatures. Spain recently went through a dramatic heat wave too, as did the UK, which is bracing for another one soon.

We rely on electricity to keep ourselves comfortable, and more to the point, safe. These are the moments we design the grid for: when need is at its very highest. The key to keeping everything running smoothly during these times might be just a little bit of flexibility. But demand for electricity from major grids is already peaking, and that’s a good reason to be a little nervous. Read the full story.

—Casey Crownhart

This article is from The Spark, MIT Technology Review’s weekly climate newsletter. To receive it in your inbox every Wednesday, sign up here.

MIT Technology Review Narrated: How did China come to dominate the world of electric cars?

From generous government subsidies to support for lithium batteries, here are the keys to understanding how China managed to build a world-leading industry in electric vehicles.

This is our latest story to be turned into a MIT Technology Review Narrated podcast, which we’re publishing each week on Spotify and Apple Podcasts. Just navigate to MIT Technology Review Narrated on either platform, and follow us to get all our new content as it’s released.

Inside OpenAI’s empire with Karen Hao

Journalist Karen Hao’s newly released book, Empire of AI: Dreams and Nightmares in Sam Altman’s OpenAI, tells the story of OpenAI’s rise to power and its far-reaching impact all over the world.

Hao, a former MIT Technology Review senior editor, will join our executive editor Niall Firth in an intimate subscriber-exclusive Roundtable conversation exploring the AI arms race, what it means for all of us, and where it’s headed. Register here to join us at 9am ET on Monday June 30th June.

Special giveaway: Attendees will have the chance to receive a free copy of Hao’s book. See registration form for details.

The must-reads

I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology.

1 Meta has won an AI copyright case against authors
The judge said the authors hadn’t presented enough evidence to back up their case. (TechCrunch)
+ It’s not an entirely decisive victory for Meta, though. (Wired $)
+ It’s the second lawsuit in favor of AI giants this week. (Insider $)

2 The US will stop contributing towards a global vaccine alliance
RFK Jr made unsubstantiated claims about Gavi’s safety record. (WP $)
+ Kennedy’s newly-assembled vaccine panel is reviewing its guidelines for children. (Vox)
+ Experts are worried the once-influential panel will cause irreparable harm. (Ars Technica)
+ How measuring vaccine hesitancy could help health professionals tackle it. (MIT Technology Review)

3 Jeff Bezos is cozying up to Donald Trump
If the Trump administration happens to need a new space company, he’s ready and willing to supply it. (WSJ $)
+ Meanwhile, a private astronaut mission is on its way to the ISS. (CNN)

4 Taiwan is working on suicide drones to defend itself from China
The country is taking a leaf out of Ukraine’s defense book. (FT $)
+ This giant microwave may change the future of war. (MIT Technology Review)

5 Biohackers are feeling emboldened by the Trump administration
They welcome lower barriers to entry for their unorthodox treatments. (Wired $)
+ The first US hub for experimental medical treatments is coming. (MIT Technology Review)

6 A UK cyberattack on a health firm contributed to a patient’s death
The ransomware attack disrupted blood services at London hospitals. (BBC)
+ A Russian hacking gang is to blame for the incident. (Bloomberg $)

7 Take a look inside Amazon’s colossal new data center
Four construction teams are working around the clock to finish it. (NYT $)
+ Generating video is the most energy-intensive AI prompt. (WSJ $)
+ We did the math on AI’s energy footprint. Here’s the story you haven’t heard. (MIT Technology Review)

8 The debate around dark energy is intensifying
New research suggests it evolves over time. But not everyone agrees. (Undark)

9 Trump Mobile is no longer claiming to be ‘made in the USA’
It’s now “designed with American values in mind” instead. (Ars Technica)

10 It’s official: The Social Network is getting a sequel
Zuck goes MAGA? (Deadline $)

Quote of the day

“By training generative AI models with copyrighted works, companies are creating something that often will dramatically undermine the market for those works, and thus dramatically undermine the incentive for human beings to create things the old-fashioned way.”

—US district judge Vince Chhabria, who presided over a copyright lawsuit brought against Meta by a group of authors, warns of the implications of the company’s actions, the Guardian reports.

One more thing

Beyond gene-edited babies: the possible paths for tinkering with human evolution

Editing human embryos is restricted in much of the world—and making an edited baby is fully illegal in most countries surveyed by legal scholars. But advancing technology could render the embryo issue moot.

New ways of adding CRISPR, the revolutionary gene editing tool, to the bodies of people already born could let them easily receive changes as well. It’s possible that in 125 years, many people will be the beneficiaries of multiple rare, but useful, gene mutations currently found in only small segments of the population. 

These could protect us against common diseases and infections, but eventually they could also yield improvements in other traits, such as height, metabolism, or even cognition. But humanity won’t necessarily do things the right way. Read the full story.

—Antonio Regalado

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.)

+ Amazing things are happening in New York’s Central Park.
+ A newly-discovered species of dinosaur has gone on display in London, and it’s small but perfectly formed.
+ Cool—Bob Dylan is releasing a new art book, this time of his drawings.
+ Iron Maiden bassist Steve Harris has a secret second career—as a footballer

When scientists first sequenced the human genome in 2003, they revealed the full set of DNA instructions that make a person. But we still didn’t know what all those 3 billion genetic letters actually do. 

Now Google’s DeepMind division says it’s made a leap in trying to understand the code with AlphaGenome, an AI model that predicts what effects small changes in DNA will have on an array of molecular processes, such as whether a gene’s activity will go up or down. It’s just the sort of question biologists regularly assess in lab experiments.

“We have, for the first time, created a single model that unifies many different challenges that come with understanding the genome,” says Pushmeet Kohli, a vice president for research at DeepMind.

Five years ago, the Google AI division released AlphaFold, a technology for predicting the 3D shape of proteins. That work was honored with a Nobel Prize last year and spawned a drug-discovery spinout, Isomorphic Labs, and a boom of companies that hope AI will be able to propose new drugs.

AlphaGenome is an attempt to further smooth biologists’ work by answering basic questions about how changing DNA letters alters gene activity and, eventually, how genetic mutations affect our health. 

“We have these 3 billion letters of DNA that make up a human genome, but every person is slightly different, and we don’t fully understand what those differences do,” says Caleb Lareau, a computational biologist at Memorial Sloan Kettering Cancer Center who has had early access to AlphaGenome. “This is the most powerful tool to date to model that.”

Google says AlphaGenome will be free for noncommercial users and plans to release full details of the model in the future. According to Kohli, the company is exploring ways to “enable use of this model by commercial entities” such as biotech companies. 

Lareau says AlphaGenome will allow certain types of experiments now done in the lab to be carried out virtually, on a computer. For instance, studies of people who’ve donated their DNA for research often turn up thousands of genetic differences, each slightly raising or lowering the chance a person gets a disease such as Alzheimer’s.

Lareau says DeepMind’s software could be used to quickly make predictions about how each of those variants works at a molecular level, something that would otherwise require time-consuming lab experiments. “You’ll get this list of gene variants, but then I want to understand which of those are actually doing something, and where can I intervene,” he says. “This system pushes us closer to a good first guess about what any variant will be doing when we observe it in a human.”

Don’t expect AlphaGenome to predict very much about individual people, however. It offers clues to nitty-gritty molecular details of gene activity, not 23andMe-type revelations of a person’s traits or ancestry. 

“We haven’t designed or validated AlphaGenome for personal genome prediction, a known challenge for AI models,” Google said in a statement.

Underlying the AI system is the so-called transformer architecture invented at Google that also powers large language models like GPT-4. This one was trained on troves of experimental data produced by public scientific projects.

Lareau says the system will not broadly change how his lab works day to day but could permit new types of research. For instance, sometimes doctors encounter patients with ultra-rare cancers, bristling with unfamiliar mutations. AlphaGenome could suggest which of those mutations are really causing the root problem, possibly pointing to a treatment.

“A hallmark of cancer is that specific mutations in DNA make the wrong genes express in the wrong context,” says Julien Gagneur, a professor of computational medicine at the Technical University of Munich. “This type of tool is instrumental in narrowing down which ones mess up proper gene expression.” 

The same approach could apply to patients with rare genetic disease, many of whom never learn the source of their condition, even if their DNA has been decoded. “We can obtain their genomes, but we are clueless as to which genetic alterations cause the disease,” says Gagneur. He thinks AlphaGenome could give medical scientists a new way to diagnose such cases. 

Eventually, some researchers aspire to use AI to design entire genomes from the ground up and create new life forms. Others think the models will be used to create a fully virtual laboratory for drug studies. “My dream would be to simulate a virtual cell,” Demis Hassabis, CEO of Google DeepMind, said this year. 

Kohli calls AlphaGenome a “milestone” on the road to that kind of system. “AlphaGenome may not model the whole cell in its entirety … but it’s starting to sort of shed light on the broader semantics of DNA,” he says.

Nature, Published online: 25 June 2025; doi:10.1038/s41586-025-09202-9

Disruption of dendritic cell (DC) interstitial motility in the tumour microenvironment promotes immune evasion, and enhancement of DC interstitial motility offers a route for DC-centric immunotherapy.

Nature, Published online: 25 June 2025; doi:10.1038/d41586-025-01998-w

Tool aims to solve the mystery of non-coding sequences — but is still in its infancy.

Midjourney has launched its first video generation V1 model, a web-based tool that allows users to animate still images into 5-second video clips.

By Daniel Dominguez

Nature, Published online: 24 June 2025; doi:10.1038/d41586-025-01717-5

A gender gap in mathematical ability arises shortly after children begin school — irrespective of the type of school they attend and their socio-economic background.

Hundred-year storm tides could strike every decade in Bangladesh

Tropical cyclones can generate devastating storm tides—seawater heightened by the tides that causes catastrophic floods in coastal regions. An MIT study finds that as the planet warms, the recurrence of destructive storm tides will increase tenfold for one of the world’s hardest-hit regions.

New electronic “skin” could lead to lightweight night-vision glasses 

MIT engineers have developed a technique to grow and peel ultrathin “skins” of electronic material that could be used in wearable sensors, flexible transistors and computing elements, and sensitive compact imaging devices.

Technology makes pesticides stick to plant leaves

A new pesticide application system developed by MIT researchers and their spinoff company could significantly cut use of pesticides and fertilizers, saving farmers money and reducing polluting runoff.

New printable metamaterials that are both strong and stretchy could allow fabrication of bendable ceramics, glass, and metals.

These tough yet bendy materials could be made into tear-resistant textiles, flexible semiconductors, electronic chip packaging, and durable yet compliant scaffolds on which to grow cells for tissue repair.

Nature, Published online: 23 June 2025; doi:10.1038/d41586-025-01946-8

The uncontrolled deployment of machine learning in medicine can distort patient information and sacrifice long-term data reliability for short-term benefits.

Around the world, countries are facing the challenges of aging populations, growing rates of chronic disease, and workforce shortages, leading to a growing burden on health care systems. From diagnosis to treatment, AI and other digital solutions can enhance the efficiency and effectiveness of health care, easing the burden on straining systems. According to the World Health Organization (WHO), spending an additional $0.24 per patient per year on digital health interventions could save more than two million lives from non-communicable diseases over the next decade.

To work most effectively, digital solutions need to be scaled and embedded in an ecosystem that ensures a high degree of interoperability, data security, and governance. If not, the proliferation of point solutions— where specialized software or tools focus on just one specific area or function—could lead to silos and digital canyons, complicating rather than easing the workloads of health care professionals, and potentially impacting patient treatment. Importantly, technologies that enhance workforce productivity should keep humans in the loop, aiming to augment their capabilities, rather than replace them. 

Through a survey of 300 health care executives and a program of interviews with industry experts, startup leaders, and academic researchers, this report explores the best practices for success when implementing integrated digital solutions into health care, and how these can support decision-makers in a range of settings, including laboratories and hospitals. 

Key findings include: 

Health care is primed for digital adoption. The global pandemic underscored the benefits of value-based care and accelerated the adoption of digital and AI-powered technologies in health care. Overwhelmingly, 96% of the survey respondents say they are “ready and resourced” to use digital health, while one in four say they are “very ready.” However, 91% of executives agree interoperability is a challenge, with a majority (59%) saying it will be “tough” to solve. Two in five leaders say balancing security with usability is the biggest challenge for digital health. With the adoption of cloud solutions, organizations can enjoy the benefits of modernized IT infrastructure: 36% of the survey respondents believe scalability is the main benefit, followed by improved security (28%). 

Digital health care can help health care institutions transform patient outcomes—if built on the right foundations. Solutions like AI-powered diagnostics, telemedicine, and remote monitoring can offer measurable impact across the patient journey, from improving early disease detection to reducing hospital readmission rates. However, these technologies can only support fully connected health care when scaled up and embedded in ecosystems with robust data governance, interoperability, and security. 

Health care data has immense potential—but fragmentation and poor interoperability hinder impact. Health care systems generate vast quantities of data, yet much of it remains siloed or unusable due to inconsistent formats and incompatible IT systems, limiting scalability. 

Digital tools must augment, not overload, the workforce. With global health care workforce shortages worsening, digital solutions like clinical decision support tools, patient prediction, and remote monitoring can be seen as essential aids rather than threats to the workforce. Successful deployment depends on usability, clinician engagement, and training. 

Regulatory evolution, open data policies, and economic sustainability are key to scaling digital health. Even the best digital tools struggle to scale without reimbursement frameworks, regulatory support, and viable business models. Open data ecosystems are needed to unleash the clinical and economic value of innovation. Regulatory and reimbursement innovation is also critical to transitioning from pilot projects to high-impact, system-wide adoption.

Download the full report.

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.

This content was researched, designed, and written entirely 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.