OpenAI Deep Research launched; Deepseek’s fall

OpenAI launches Deep Research: An AI agent for advanced research

This week, OpenAI launched a new AI agent called Deep Research. Like the first AI agent it released, called Operator, Deep Research is an AI agent capable of autonomously executing complex tasks from end to end based on an initial set of user instructions. However, unlike Operator, Deep Research is designed for in-depth, extensive workflows, which is why it is branded as a researcher and has capabilities similar to that of a human doing advanced research in various fields. The AI agent can take anywhere from 5 to 30 minutes to return results depending on the task’s complexity, similar to the extended amount of time it takes a human to complete complex research.

“Deep research is built for people who do intensive knowledge work in areas like finance, science, policy, and engineering and need thorough, precise, and reliable research. It can be equally useful for discerning shoppers looking for hyper-personalized recommendations on purchases that typically require careful research, like cars, appliances, and furniture,” OpenAI said in its announcement.

In OpenAI’s demo, Deep Research was showcased conducting comprehensive market research for a product and identifying the best skis for a user based on their specifications. 

Deep Research is exclusively available to GPT Pro users who pay $200 per month for OpenAI’s premium services. However, OpenAI says both Operator and Deep Research will be available to all tiers of OpenAI subscribers in the future.

I see the release of Deep Research as a direct response to the uproar last week over DeepSeek’s entry into the market. When DeepSeek made headlines, it triggered doubts about whether U.S.-based AI companies like OpenAI could justify their sky-high valuations. OpenAI’s move seems like a counterattack to the negative sentiment that Deep Seek cast over U.S. tech companies, a way to shift the conversation back in their favor and remind the world why they remain a dominant force in AI.

DeepSeek’s rapid rise and fall: From AI disruptor to global security threat

Last week, DeepSeek took the AI world by storm, making headlines for allegedly matching OpenAI’s performance while spending just $6 million to develop its generative AI model compared to the multi-billions OpenAI has spent. The news rattled the tech industry and raised concerns about U.S.-based AI firms’ valuations and competitiveness. 

But this week? DeepSeek has almost completely disappeared from the conversation. DeepSeek has been banned from government devices in South Korea, Australia, and Taiwan due to national security concerns. Microsoft (NASDAQ: MSFT) is investigating whether DeepSeek used OpenAI research and data without authorization, and corporations, as well as government agencies, worry that user data entered into DeepSeek is being funneled directly to China, creating a security risk.

All of these elements, along with doubts regarding whether DeepSeek was truly able to create its model for the amount of money and amount of computing infrastructure that they said it used, created the perfect storm for the Chinese competitor to get publicly disparaged and practically wiped from our memories in just one weeks time.

On top of that, an AI research team at UC Berkeley was able to replicate DeepSeek’s core capabilities for just $30. While this lends some credibility to DeepSeek’s claim of achieving a low-cost AI breakthrough, it also reinforces the statement made by OpenAI CEO Sam Altman that being a copycat is easier than being a pioneer. OpenAI in particular had to spend billions forging the path that companies like DeepSeek can now easily follow.

Regardless, I don’t think we will hear much more about DeepSeek in the United States. The U.S. has a vested interest in making sure United States-based AI companies remain dominant forces and are most likely playing a role in suppressing foreign inventions like DeepSeek. I expect that to continue as well, whether it be through direct intervention, trade restrictions, or negative PR. It’s clear that foreign AI firms—especially those from China—face significant roadblocks to global expansion set in place by the United States.

Google removes AI weapons ban

Google (NASDAQ: GOOGL) has quietly revised its AI ethics policy, removing a key clause that previously prohibited the company from pursuing AI applications for weapons and surveillance. This change represents a significant shift in Google’s stance on AI development.

Shortly after the update, Google released a blog post justifying its decision, “Since we first published our AI Principles in 2018, the technology has evolved rapidly… AI has moved from a niche research topic in the lab to a technology that is becoming as pervasive as mobile phones and the internet itself. We believe that companies, governments, and organizations should work together to create AI that protects people, promotes global growth, and supports national security,” said the portion of the announcement that addressed its AI ethics.

While some Google employees probably joined the company due to its original commitment to ethical AI and are probably now disillusioned by this change, from a business standpoint, the move makes sense.

The market for national defense is massive, and government contracts are typically lucrative. The AI sector is notoriously expensive, with major players spending billions on infrastructure, training, and operational costs, while many of them have yet to turn a profit on their big investments. Expanding into the defense sector gives AI firms a financially stable customer base with deep pockets and a clear incentive to invest in and use their AI systems.

Beyond financial incentives, there’s another reality: if Google doesn’t build these AI-driven national defense systems, one of its competitors will. The AI industry is clearly at a point where the competition is intense, and each competitors’ product is only better, or worse, by a very narrow margin. If companies choose not to explore key revenue streams like national defense, they risk losing market share to one of their competitors willing to go that route.

In order for artificial intelligence (AI) to work right within the law and thrive in the face of growing challenges, it needs to integrate an enterprise blockchain system that ensures data input quality and ownership—allowing it to keep data safe while also guaranteeing the immutability of data. Check out CoinGeek’s coverage on this emerging tech to learn more why Enterprise blockchain will be the backbone of AI.

Watch: Demonstrating the potential of blockchain’s fusion with AI

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