This Week in AI

OpenAI Deep Research: An AI Agent for Advanced Research

OpenAI Deep Research: A AI agent for advanced Research

OpenAI launched Deep Research, an AI agent designed to support advanced research. Like its first AI agent, called Operator. Deep Research can execute complex tasks autonomously from beginning to end, based on a set of initial user instructions. Deep Research, unlike Operator, is designed to perform in-depth, comprehensive workflows. This is why it’s branded as a research agent and has capabilities that are similar to those of a human performing advanced research in different fields. The AI agent may take up to 30 minutes depending on the complexity of the task to return results, similar to how long it takes humans to complete complex research.

Deep research is designed for people who perform intensive knowledge work, such as finance, science and policy, or engineering, and require thorough, precise and reliable research. OpenAI stated that it can be useful for discerning consumers looking for hyper-personalized suggestions on purchases like cars, appliances and furniture, which require careful research.

showed Deep Research conducting extensive market research and identifying the most suitable skis for an individual based on their specific specifications.

Deep Research will only be available to GPT Pro subscribers who pay $200 a month for OpenAI premium services. OpenAI has stated that both Operator and Deep Research are available to all OpenAI subscribers.

Deep Research is a direct reaction to the uproar caused by DeepSeek entering the market last week. OpenAI’s valuations were questioned when DeepSeek hit the headlines. OpenAI’s decision seems to be a counterattack against the negative sentiment Deep Seek cast on U.S. tech firms, a way of shifting the conversation in their favor and reminding the world why they are still a dominant force within AI.

DeepSeek’s rapid rise and Fall: From AI disruptors to global security threats

DeepSeek made headlines last week for allegedly matching OpenAI’s performance, despite spending only $6 million on its generative AI model (GenAI), compared to the multiple billions OpenAI spent. The news shook the tech industry, and raised concerns over the valuations and competitiveness of U.S. AI firms. But this week? DeepSeek is almost completely absent from the conversation. DeepSeek is banned on government devices in South Korea (South Korea), Australia (Australia), and Taiwan (Taiwan) due to national security concerns. Microsoft ( NASDAQ:MSFT) is investigating whether DeepSeek has used OpenAI data and research without authorization. Corporations and government agencies are concerned that data entered into DeepSeek will be sent directly to China and create a security threat.

These elements, as well as doubts about whether DeepSeek could create its model with the amount of money and computing infrastructure they claimed it used, created a perfect storm that allowed the Chinese competitor to be publicly disparaged and virtually erased from our memories within a week.

A team of AI researchers at UC Berkeley were able to duplicate DeepSeek’s core abilities for only $30. This gives some credence to DeepSeek’s claim that it has achieved a low-cost AI advancement, but it also confirms the statement by OpenAI CEO Sam Altman, that being a copycat rather than a pioneer is easier. OpenAI, in particular, had to spend billions on paving the way that companies like DeepSeek now follow.

I don’t believe we will hear about DeepSeek much more in the U.S. The U.S. is interested in ensuring that U.S. AI companies remain dominant and are likely to be playing a part in suppressing foreign inventions such as DeepSeek. I expect this to continue, whether through direct intervention or trade restrictions, as well as negative PR. It’s evident that foreign AI companies, especially those from China, face significant roadblocks in their global expansion. These were set up by the U.S. NASDAQ: GOOGL () has quietly revised their AI ethics policy. The company has removed an important clause that had previously prohibited it from pursuing AI applications in weapons and surveillance. This change marks a significant shift for Google’s AI development policy.

Soon after the update, Google published a In a blog post defending its decision, the company wrote: “Since our AI Principles were first published in 2018, technology has evolved quickly… AI has gone from a niche topic of research in the lab to becoming a technology as ubiquitous as mobile phones and internet itself. The section of the announcement that dealt with its AI ethics stated that “we believe that companies, governments and organizations should collaborate to create AI that promotes global development, supports national security, and protects people.”

Although some Google employees may have joined the company because of its original commitment to ethical AI, and are now likely disillusioned with this change, it makes business sense.

Government contracts are usually lucrative and the market for national defence is huge. The AI industry is notoriously costly, with major players investing billions in infrastructure, training and operational costs. Many of them are yet to make a profit from their large investments. Expanding into the defence sector provides AI firms with a financially stable client base that has deep pockets, and a clear motivation to invest in their AI systems and use them.

Aside from financial incentives, another reality is that if Google does not build these AI-driven systems for national defense, one of Google’s competitors will. The AI industry has reached a point of intense competition, where each competitor’s product is only marginally better or worse than the other. If companies do not explore key revenue streams, such as national defense, they run the risk of losing market share to a competitor who is willing to take that route.

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