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.

Material Cultures looks to the past to build the future

Despite decades of green certifications, better material sourcing, and the use of more sustainable materials, the built environment is still responsible for a third of global emissions worldwide. According to a 2024 UN report, the building sector has fallen “significantly behind on progress” toward becoming more sustainable. Changing the way we erect and operate buildings remains key to tackling climate change.

London-based design and research nonprofit Material Cultures is exploring how tradition can be harnessed in new ways to repair the contemporary building system. As many other practitioners look to artificial intelligence and other high-tech approaches, Material Cultures is focusing on sustainability, and finding creative ways to turn local materials into new buildings. Read the full story.

—Patrick Sisson

This story is from our new print edition, which is all about the future of security. Subscribe here to catch future copies when they land.

MIT Technology Review Narrated: How a top Chinese AI model overcame US sanctions

Earlier this year, the AI community was abuzz over DeepSeek R1, a new open-source reasoning model. The model was developed by the Chinese AI startup DeepSeek, which claims that R1 matches or even surpasses OpenAI’s ChatGPT o1 on multiple key benchmarks but operates at a fraction of the cost.

DeepSeek’s success is even more remarkable given the constraints facing Chinese AI companies in the form of increasing US export controls on cutting-edge chips. Read the full story.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.

The must-reads

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

1 Google won’t be forced to sell Chrome after all
A federal judge has instead ruled it has to share search data with its rivals. (Politico)
+ He also barred Google from making deals to make Chrome the default search engine on people’s phones. (The Register)
+ The company’s critics feel the ruling doesn’t go far enough. (The Verge)

2 OpenAI is adding emotional guardrails to ChatGPT
The new rules are designed to better protect teens and vulnerable people. (Axios)
+ Families of dead teenagers say AI companies aren’t doing enough. (FT $)
+ An AI chatbot told a user how to kill himself—but the company doesn’t want to “censor” it. (MIT Technology Review)

3 China’s military has showed off its robotic wolves
Alongside underwater torpedoes and hypersonic cruise missiles. (BBC)
+ Xi Jinping has pushed to modernize the world’s largest standing army. (CNN)
+ Phase two of military AI has arrived. (MIT Technology Review)

4 ICE has resumed working with a previously banned spyware vendor
Paragon Solutions’ software was found on the devices of journalists earlier this year. (WP $)
+ The tool can manipulate a phone’s recorder to become a covert listening device. (The Guardian)

5 An identical twin has been convicted of a crime based on DNA analysis 
It’s the first time the technology has been successfully used in the US, and solves a 38-year old cold case. (The Guardian)

6 People who understand AI the least are the most likely to use it 
Those with a better grasp of how AI works know more about its limitations. (WSJ $)
+ What is AI? (MIT Technology Review)

7 BMW is preparing to unveil a super-smart EV
Its new iX3 sport utility vehicle will have 20 times more computing power. (FT $)

8 Sick and lonely people are turning to AI “doctors”
Physicians are too busy to spend much time with patients. Chatbots are filling the void. (Rest of World)
+ AI companies have stopped warning you that their chatbots aren’t doctors. (MIT Technology Review)

9 Around 90% of life on Earth is still unknown
But shedding light on these mysterious organisms is essential to our future survival. (Vox)

10 Wax worms could help tackle our plastic pollution problem 🪱
The plastic-hungry pests can eat a polythene bag in a matter of hours. (Wired $)
+ Think that your plastic is being recycled? Think again. (MIT Technology Review)

Quote of the day

“It’s a nothingburger.”

—Gabriel Weinberg, chief executive of search engine DuckDuckGo, reacts to the judge’s decision in the Google Chrome monopoly case, the New York Times reports.

 One more thing

Why we can no longer afford to ignore the case for climate adaptation

Back in the 1990s, anyone suggesting that we’d need to adapt to climate change while also cutting emissions was met with suspicion. Most climate change researchers felt adaptation studies would distract from the vital work of keeping pollution out of the atmosphere to begin with.

Despite this hostile environment, a handful of experts were already sowing the seeds for a new field of research called “climate change adaptation”: study and policy on how the world could prepare for and adapt to the new disasters and dangers brought forth on a warming planet. Today, their research is more important than ever. Read the full story

—Madeline Ostrander

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 have a happier life, even when you’re living through bleak times (maybe skip the raisins on ice cream, though.)
+ If you’re loving Alien: Earth right now, why not dive back into the tremendously terrifying Alien: Isolation game?
+ The first freaky images of the second part of zombie flick 28 Years Later have landed.
+ Anthony Gormley, you will always be cool.

Read more

As brands compete for increasingly price conscious consumers, customer experience (CX) has become a decisive differentiator. Yet many struggle to deliver, constrained by outdated systems, fragmented data, and organizational silos that limit both agility and consistency.

The current wave of artificial intelligence, particularly agentic AI that can reason and act across workflows, offers a powerful opportunity to reshape service delivery. Organizations can now provide fast, personalized support at scale while improving workforce productivity and satisfaction. But realizing that potential requires more than isolated tools; it calls for a unified platform that connects people, data, and decisions across the service lifecycle. This report explores how leading organizations are navigating that shift, and what it takes to move from AI potential to CX impact.

Key findings include:

  • AI is transforming customer experience (CX). Customer service has evolved from the era of voicebased support through digital commerce and cloud to today’s AI revolution. Powered by large language models (LLMs) and a growing pool of data, AI can handle more diverse customer queries, produce highly personalized communication at scale, and help staff and senior management with decision support. Customers are also warming to AI-powered platforms as performance and reliability improves. Early adopters report improvements including more satisfied customers, more productive staff, and richer performance insights.
  • Legacy infrastructure and data fragmentation are hindering organizations from maximizing the value of AI. While customer service and IT departments are early adopters of AI, the broader organizations across industries are often riddled with outdated infrastructure. This impinges the ability of autonomous AI tools to move freely across workflows and data repositories to deliver goal-based tasks. Creating a unified platform and orchestration architecture will be key to unlock AI’s potential. The transition can be a catalyst for streamlining and rationalizing the business as a whole.
  • High-performing organizations use AI without losing the human touch. While consumers are warming to AI, rollout should include some discretion. Excessive personalization could make customers uncomfortable about their personal data, while engineered “empathy” from bots may be received as insincere. Organizations should not underestimate the unique value their workforce offers. Sophisticated adopters strike the right balance between human and machine capabilities. Their leaders are proactive in addressing job displacement worries through transparent communication, comprehensive training, and clear delineation between AI and human roles. The most effective organizations treat AI as a collaborative tool that enhances rather than replaces human connection and expertise.

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.

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Artificial intelligence is fundamentally reshaping how the world operates. With its potential to automate repetitive tasks, analyze vast datasets, and augment human capabilities, the use of AI technologies is already driving changes across industries.

In health care and pharmaceuticals, machine learning and AI-powered tools are advancing disease diagnosis, reducing drug discovery timelines by as much as 50%, and heralding a new era of personalized medicine. In supply chain and logistics, AI models can help prevent or mitigate disruptions, allowing businesses to make informed decisions and enhance resilience amid geopolitical uncertainty. Across sectors, AI in research and development cycles may reduce time-to-market by 50% and lower costs in industries like automotive and aerospace by as much as 30%.

“This is one of those inflection points where I don’t think anybody really has a full view of the significance of the change this is going to have on not just companies but society as a whole,” says Patrick Milligan, chief information security officer at Ford, which is making AI an important part of its transformation efforts and expanding its use across company operations.

Given its game-changing potential—and the breakneck speed with which it is evolving—it is perhaps not surprising that companies are feeling the pressure to deploy AI as soon as possible: 98% say they feel an increased sense of urgency in the last year. And 85% believe they have less than 18 months to deploy an AI strategy or they will see negative business effects.

Companies that take a “wait and see” approach will fall behind, says Jeetu Patel, president and chief product officer at Cisco. “If you wait for too long, you risk becoming irrelevant,” he says. “I don’t worry about AI taking my job, but I definitely worry about another person that uses AI better than me or another company that uses AI better taking my job or making my company irrelevant.”

But despite the urgency, just 13% of companies globally say they are ready to leverage AI to its full potential. IT infrastructure is an increasing challenge as workloads grow ever larger. Two-thirds (68%) of organizations say their infrastructure is moderately ready at best to adopt and scale AI technologies.

Essential capabilities include adequate compute power to process complex AI models, optimized network performance across the organization and in data centers, and enhanced cybersecurity capabilities to detect and prevent sophisticated attacks. This must be combined with observability, which ensures the reliable and optimized performance of infrastructure, models, and the overall AI system by providing continuous monitoring and analysis of their behavior. Good quality, well-managed enterprise-wide data is also essential—after all, AI is only as good as the data it draws on. All of this must be supported by AI-focused company culture and talent development.

Download the 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. It 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.

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