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Artificial intelligence has already begun to change the way we conduct research, and now OpenAI has just released the latest update to ChatGPT, which it says will open up “deep research” to almost everyone.
The new deep research tool is rolling out to ChatGPT Pro subscribers today, just days after the launch of the 03-mini reasoning model.
“Today, we’re launching Deep Research in ChatGPT, a new agent capability that can conduct multi-step research on complex tasks on the internet,” a blog post reads, promising that the model can “do in just tens of minutes what would take a human hours to do.OpenAI  ChatGPT’s powerful “deep research” upgrade gets open source copies in just 24 hours
I just tested ChatGPT’s new o3-mini model, rating its problem-solving and reasoning abilities with 7 prompts — and the results blew my mind
This new agent “can work independently for you,” “finding, analyzing, and synthesizing hundreds of online sources to create research analyst-level synthesis reports” based on a series of prompts.
It’s powered by the upcoming ChatGPT o3 model and is aimed at finance, science, policy, and engineering research, but OpenAI also says it can also be used to make purchasing decisions and help with detailed product research (which could be another warning for Google).
Using the new tool is simple, too. Users simply select “Drill down” in the ChatGPT message editor and enter a query, with the option to attach additional context via files and spreadsheets.
Doing so will see the cited articles in the sidebar, where you can also track your progress. OpenAI says it can take anywhere from five minutes to half an hour to complete a deep dive task.
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About two weeks ago, Wall Street panicked when Chinese startup DeepSeek released an AI system that was far more effective than its American rivals.Investors, who have poured trillions of dollars into tech stocks over the past few years, wondered whether the tens of billions of dollars tech companies have spent on new data centers suddenly looked overextended.
But the biggest tech companies made clear in recent earnings reports that they don’t think they’re overextended in building new data centers.
Amazon hinted Thursday that its capital spending, which includes data center construction and other projects like warehouses, could exceed $100 billion this year. Microsoft said its spending could exceed $80 billion. Alphabet said it would spend $75 billion, while Meta reiterated plans for $65 billion in capital expenditures.
Combined, they could spend about $100 billion more on these projects than they did last year.
Executives urged patience. The problem, they said, is that customer demand for artificial intelligence outstrips the company’s capabilities. The only way to meet demand is to develop as many products as quickly as possible.
“Every time I see someone else doing something better, I say, ‘Ah, we should do that,’ ” Meta CEO Mark Zuckerberg told employees at a companywide meeting last week, according to a recording obtained by The New York Times. Competition is good, but we need to make sure we can win.”
Here are some keys to understanding this consumer-driven moment in the tech industry:
Tech companies need more data centers than they have now.
Many companies say they are constrained by the availability of chips, land and electricity to build data centers, so they are racing to open more. Microsoft, Alphabet and Amazon have all said their cloud sales could be higher if there was enough capacity. Cloud services are the quintessential way to deliver artificial intelligence to customers.
Alphabet Chief Financial Officer Anat Ashkenazi told investors that Alphabet is seeing “demand that exceeds our available capacity.” “So we’re going to work on that and make sure we can provide more capacity.”
Microsoft has been saying it has been constrained for some time, and previously told investors that pressure would ease early this year. But last week, when the company reported its latest earnings, executives told investors it might take until the summer to have enough capacity to meet all the demand. Shares of the company fell about 5% in after-hours trading after the report was released.
Greater efficiency, they say, will expand the use of and demand for AI
While many people think of data centers as expensive, power-hungry places to develop advanced AI systems, they are also where AI is deployed. Those are two different steps: training the model that underpins ChatGPT, and asking ChatGPT for recipe suggestions.
The industry calls deploying AI “inference”; a growing number of tech companies say their businesses are booming in this area.
Microsoft CEO Satya Nadella told investors last week that as costs fall, “AI I will become more pervasive.”
Amazon CEO Andy Jassy told investors Thursday that while a world where every application includes AI may be hard to imagine, “it’s a world we’ve been thinking about.” At the heart of that vision, he said, is inference.
He believes that lowering the cost of inference will follow the pattern of previous technology trends: As systems become cheaper to deploy, customers will “get excited about other things they can build that they previously thought were too expensive, and they usually end up spending more money on.”
These companies say they have to think long-term.
Cloud providers are used to giving customers the illusion of endless supply, which means they have to juggle having enough data centers online to play the video you want or answer your chatbot query. But they also can’t build too much in advance, which would tie up billions of dollars that could be deployed elsewhere. Balancing the two — especially when securing data center land, chips and electricity can take years — is a big challenge for these companies.
Executives say they can adjust how their investments are used, between building and deploying AI  models and between serving their own core businesses and customers. Nadella said Microsoft’s infrastructure is “very flexible.” Ashkenazy said Google is flexible, too. For example, it can “repurpose capacity” to serve Google Search instead of cloud customers.
Zuckerberg said Meta was working on DeepSeek and how it could improve efficiency, but that investing heavily in data centers would be a strategic advantage against smaller, more nimble rivals.
“We serve over a billion people — that’s a lot of people, so more and more machines are going to be used to run inference,” he told employees.
Whatever the reason, cutting into profits — even the huge profits of tech giants — is unlikely to excite investors.

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The U.S. Commerce Department is investigating whether DeepSeek, a Chinese company whoseAI models have stunned the tech world with their performance, used chips banned from export by the U.S., according to people familiar with the matter.
China’s DeepSeek last week launched a free assistant that it said uses less data and costs a fraction of the U.S. model. Within days, it became the most downloaded app on Apple’s App Store and raised concerns about the U.S. lead in AI, sparking a sell-off that wiped out about $1 trillion in market value from U.S. tech stocks.
Current restrictions on Nvidia’s AI processors are aimed at blocking its most advanced chips from entering China.
Organized smuggling of AI chips into China has been traced to countries including Malaysia, Singapore and the United Arab Emirates, the sources said.
The U.S. Commerce Department and DeepSeek did not immediately respond to requests for comment.
An Nvidia spokesman said many of the company’s customers have business entities in Singapore and use them to make products for shipment to the U.S. and the West.
Nvidia said: “We insist that our partners comply with all applicable laws, and we will take appropriate action if we receive any information to the contrary.”
DeepSeek said it used Nvidia’s H800 chip, which can be legally purchased in 2023. Reuters could not determine whether DeepSeek used other regulated chips that are not allowed to be shipped to China.
DeepSeek also apparently has Nvidia’s lower-performance H20 chips, which can still be legally shipped to China. The United States has considered controlling these products during the Biden administration, and new Trump officials are also discussing it.
Dario Amodei, CEO of artificial intelligence company Anthropic, said earlier this week that “a significant portion of DeepSeek’s AI chip inventory appears to be chips that are not banned (but should be banned), chips that have been shipped before they were banned, and some chips that appear to be very likely smuggled.”
The United States has implemented a series of restrictions banning the export of AI chips to China and plans to restrict exports to many other countries.

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