Radically different
The Trump administration is doubling down on its opposition to harm reduction services for people who use illicit drugs.
In an open letter on April 24, the federal agency overseeing addiction and mental health policy warned its grantees against using federal funds to buy harm reduction supplies including sterile syringes and pipes, or to distribute test strips for common drug supply adulterants like fentanyl, xylazine, and medetomidine.
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.
On Friday, Chinese AI firm DeepSeek released a preview of V4, its long-awaited new flagship model. Notably, the model can process much longer prompts than its last generation, thanks to a new design that handles large amounts of text more efficiently.
While the model remains open source, its performance matches leading closed-source rivals from Anthropic, OpenAI, and Google. It is also DeepSeek’s first release optimized Huawei’s Ascend chips—a key test of China’s dependence on Nvidia.
Here are three ways V4 could shake up AI.
—Caiwei Chen
AI systems have already gained impressive mastery over the digital world, but the physical world remains humanity’s domain. As it turns out, building an AI that composes novels or code apps is far easier than developing one to fold laundry or navigate city streets. To bridge this gap, many researchers believe you need something called a world model.
Proponents like Stanford professor Fei-Fei Li and AMI Labs founder Yann LeCun argue these models can overcome the well-known limitations of LLMs—and realize AI’s promise for robotics. Find out why they’ve brought world models to the forefront of the field.
—Grace Huckins
World models are on our list of the 10 Things That Matter in AI Right Now, our essential guide to what’s really worth your attention in the field.
Subscribers can watch an exclusive roundtable unveiling the technologies and trends on the list, with analysis from MIT Technology Review’s AI reporter Grace Huckins and executive editors Amy Nordrum and Niall Firth.
The must-reads
I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology.
1 China has blocked Meta’s $2 billion acquisition of AI startup Manus
Regulators cited national security grounds. (WSJ $)
+ Beijing called the deal a “conspiratorial” attempt to hollow out its tech base. (FT $)
+ The country is tightening its grip on AI firms that try to leave. (TechCrunch)
+ The decision escalates China’s AI rivalry with the US. (Bloomberg $)
+ But there will be no winners in their competition. (MIT Technology Review)
2 Google is investing up to $40 billion in Anthropic
In a deal valuing the AI firm at $350 billion. (CNBC)
+ The funding will support the firm’s growing computing needs. (TechCrunch)
+ Anthropic and OpenAI are fighting for compute capacity. (Axios)
3 President Trump just fired the entire National Science Board
The NSF has played a crucial role in developing technology. (The Verge)
+ The move heightens fears over political interference in US science. (Nature)
4 Conspiracy theories about the Washington shooting are proliferating online
Over 300,000 posts appeared on X using the keyword “staged.” (NYT $)
+ The theories are also swirling on Bluesky and Instagram. (Wired)
5 The AI compute crunch is starting to hit the broader economy.
It’s affecting jobs, gadgets, and electricity prices. (404 Media)
+ The AI compute explosion is the tech story of our time. (MIT Technology Review)
6 Elon Musk says a new banking tool brings X close to a “super app”
He’s pledged to launch the tool this month. (Bloomberg)
7 AI optimism is surging across Asia while US sentiment cools
The divide could shape where adoption happens fastest. (Rest of World)
8 Apple is tying its new CEO’s ascent to its first foldable iPhone
It wants to build the buzz around John Ternus. (Gizmodo)
9 Twelve firms are developing the Golden Dome’s space-based interceptors
They’ve won contracts worth up to $3.2 billion. (Ars Technica)
10 NASA has shared promising results from Artemis II
The spacecraft and rocket fared well. (Engadget)
Quote of the day
—Amanda Crawford, associate professor at the University of Connecticut, tells the NYT why conspiracy theories are gaining traction online.
One More Thing
Kenya’s Great Rift Valley is home to five geothermal power stations, which harness clouds of steam to generate about a quarter of the country’s electricity. But some of the energy escapes into the atmosphere, while even more remains underground for lack of demand. That’s what brought Octavia Carbon here.
Last year, the startup began harnessing some of that excess energy to remove CO2 from the air. The company says the method is efficient, affordable, and—crucially—scalable. But the project also faces fierce opposition.
Read the full story on the future of Kenya’s “Great Carbon Valley.”
—Diana Kruzman
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.)
+ Fred Again’s Tiny Desk Concert is a masterclass in intimate performance.
+ Here’s a delightful look at how we’re all linked through geography and shared heritage.
+ Take a short, peaceful break to watch Tokyo’s cherry blossoms from a bird’s eye view.
+ There’s something oddly satisfying about watching an industrial shredder turn everyday items into confetti.
On Friday, Chinese AI firm DeepSeek released a preview of V4, its long-awaited new flagship model. Notably, the model can process much longer prompts than its last generation, thanks to a new design that helps it handle large amounts of text more efficiently. Like DeepSeek’s previous models, V4 is open source, meaning it is available for anyone to download, use, and modify.
V4 marks DeepSeek’s most significant release since R1, the reasoning model it launched in January 2025. R1, which was trained on limited computing resources, stunned the global AI industry with its strong performance and efficiency, turning DeepSeek from a little-known research team into China’s best-known AI company almost overnight. It also helped set off a wave of open-weight model releases from other Chinese AI firms.
DeepSeek has kept a relatively low profile since then—but earlier this month, it effectively teased V4’s release when it added “expert” and “flash” modes to the online version of its model, prompting speculation that the updates were tied to a bigger upcoming release.
While the company has become a powerful symbol of China’s AI ambitions, its big return to cutting-edge frontier models comes after months of scrutiny—including major personnel departures, delays to previous model launches, and growing scrutiny from both the US and Chinese governments.
So, will V4 shake the AI field the way R1 did? Almost certainly not, but here are three big reasons why this release matters.
As with R1 before it, DeepSeek claims that V4’s performance rivals the best models available at a fraction of the price. This is great news for developers and for companies using the tech, because it means they can access frontier AI capabilities on their own terms, and without worrying about skyrocketing costs.
The new model comes in two versions, both of which are available on DeepSeek’s website and in its app, with API access also open to developers. V4-Pro is a larger model built for coding and complex agent tasks, and V4-Flash is a smaller version designed to be faster and cheaper to run. Both versions offer reasoning modes, in which the model can carefully parse a user’s prompt and show each step as it works through the problem.
For V4-Pro, DeepSeek charges $1.74 per million input tokens and $3.48 per million output tokens, a fraction of the cost of comparable models from OpenAI and Anthropic. V4-Flash is even cheaper, at about $0.14 per million input tokens and about $0.28 per million output tokens, making it one of the cheapest top-tier models available. This would make it a very appealing model to build applications on.
In terms of performance, V4 is, perhaps unsurprisingly, a huge jump from R1—and it seems to be a strong alternative to just about all the latest big AI models. On the major benchmarks, according to results shared by the company, DeepSeek V4-Pro competes with leading closed-source models, matching the performance of Anthropic’s Claude-Opus-4.6, OpenAI’s GPT-5.4, and Google’s Gemini-3.1. And compared to other open-source models, such as Alibaba’s Qwen-3.5 or Z.ai’s GLM-5.1, DeepSeek V4 exceeds them all on coding, math, and STEM problems, making it one of the strongest open-source models ever released.
DeepSeek also says that V4-Pro now ranks among the strongest open-source models on benchmarks for agentic coding tasks and performs well on other tests that measure ability to carry out multistep problems. Its writing ability and world knowledge also leads the field, according to benchmarking results shared by the company.
In a technical report released alongside the model, DeepSeek shared results from an internal survey of 85 experienced developers: More than 90% included V4-Pro among their top model choices for coding tasks.
DeepSeek says it has specifically optimized V4 for popular agent frameworks such as Claude Code, OpenClaw, and CodeBuddy.
One of the key innovations of V4 is its long context window—the amount of text the model can process at once. Both versions can handle 1 million tokens, which is large enough to fit all three volumes of The Lord of the Rings and The Hobbit combined. The company says this context window size is now the default across all DeepSeek services and it matches what is offered by cutting-edge versions of models like Gemini and Claude.
But it’s important to know not just that DeepSeek has made this leap, but how it did so. V4 makes significant architectural changes to the company’s former models—especially in the attention mechanism, which is the feature of AI models that helps them understand each part of a prompt in relation to the rest. As the prompt text gets longer, these comparisons become much more costly, making attention one of the main bottlenecks for long-context models.
DeepSeek’s innovation was to make the model more selective about what it pays attention to. Instead of treating all earlier text as equally important, V4 compresses older information and focuses on the parts most likely to matter in the present moment, while still keeping nearby text in full so it does not miss important details.
DeepSeek says this sharply reduces the cost of using long context. In a 1-million-token context, V4-Pro uses only 27% of the computing power required by its previous model, V3.2, while cutting memory use to 10%. The reduction in V4-Flash is even larger, using just 10% of the computing power and 7% of the memory. In practice, this could make it cheaper to build tools that need to work across huge amounts of material, such as an AI coding assistant that can read an entire codebase or a research agent that can analyze a long archive of documents without constantly forgetting what came before.
DeepSeek’s interest in long context windows didn’t start with V4. Over the past year and a half, the company has quietly published a series of papers on how AI models “remember” information, experimenting with compression and mathematical techniques to extend what AI models could realistically handle.
V4 is DeepSeek’s first model optimized for domestic Chinese chips, such as Huawei’s Ascend—a move that has turned the launch into something of a test of whether China’s homegrown AI industry can begin to loosen its dependence on US chip giant Nvidia.
This was largely expected, since The Information reported earlier this month that DeepSeek did not give American chipmakers like Nvidia and AMD early access to V4, though prerelease access is common to allow chipmakers to optimize support of the new model ahead of a launch. Instead, the company reportedly gave early access only to Chinese chipmakers.
On Friday, Huawei said its Ascend supernode products, based on the Ascend 950 series, would support DeepSeek V4. This means that companies and individuals who want to run their own modified version of Deepseek V4 will be able to use Huawei chips easily.
Reuters previously reported that Chinese government officials recommended that DeepSeek integrate Huawei chips in its training process. And this pressure fits a broader pattern in China’s industrial policy: Strategic sectors are often pushed, and sometimes effectively required, to align with national self-reliance goals. But there’s a particular urgency when it comes to AI. Since 2022, US export controls have cut Chinese firms off from Nvidia’s most powerful chips, and they later also restricted access to downgraded China-market versions. Beijing’s response has been to accelerate the push for a domestic AI stack, from chips to software frameworks to data centers.
Chinese authorities have reportedly been pushing data centers and public computing projects to use more domestic chips, including through reported bans on foreign-made chips, sourcing quotas, and requirements to pair Nvidia chips with Chinese alternatives from companies such as Huawei and Cambricon.
Still, replacing Nvidia is not as simple as swapping one chip for another. Nvidia’s advantage lies not only in its chips, but in the software ecosystem developers have spent years building around them. Moving to Huawei’s Ascend chips means adapting model code, rebuilding tools, and proving that systems built around those chips are stable enough for serious use.
To be clear, DeepSeek does not appear to have fully moved beyond Nvidia. The company’s technical report reveals that it is using Chinese chips to run the model for inference, or when someone asks the model to complete a task. But Liu Zhiyuan, a computer science professor at Tsinghua University, told MIT Technology Review that DeepSeek appears to have adapted only part of V4’s training process for Chinese chips. The report does not say whether some key long-context features were adapted to domestic chips, so Liu says V4 may still have been trained mainly on Nvidia chips. Multiple sources who spoke on the condition of anonymity, due to political sensitivity around these issues, told MIT Technology Review that Chinese chips still don’t perform as well as Nvidia chips but are better suited for inference than training.
DeepSeek is also tying the future costs of V4 to this hardware shift. The company says V4-Pro prices could fall significantly after Huawei’s Ascend 950 supernodes begin shipping at scale in the second half of this year.
If that works, V4 could be an early sign that China is successfully building a parallel AI infrastructure.
President Trump recently signed an executive order which aims to increase access to psychedelic drug treatments. He was joined at the signing by podcaster Joe Rogan, who said he’ ha’d messaged the president about research on the psychedelic ibogaine.
In this week’s STATus Report, host Alex Hogan chats with STAT Washington correspondent Daniel Payne about what the executive order does and doesn’t do. Hogan also looks at why ibogaine, and psychedelic drugs more broadly, are increasingly being taken seriously for stubbornly hard-to-treat conditions like addiction, depression, and PTSD.