OpenAI Unveils A New ChatGPT Agent For ‘Deep Research’ Analysis And Reporting
Utilizing the upcoming 03 model, Deep Research analyses vast amounts of data to provide comprehensive reports, initially available to ChatGPT Pro users with plans to extend to other tiers soon.
OpenAI is announcing a new AI Agent designed to help people conduct in-depth, complex research using ChatGPT, the company’s AI-powered chatbot platform. Appropriately enough, it’s called deep research.
OpenAI said in a blog post published Sunday that this new capability was designed for people who do intensive knowledge work in areas like finance, science, policy, and engineering and need thorough, precise, and reliable research. It could also be useful, the company added, for anyone making purchases that typically require careful research, like cars, appliances, and furniture.
Basically, ChatGPT deep research is intended for instances where you don’t just want a quick answer or summary, but instead need to assiduously consider information from multiple websites and other sources.
OpenAI said it’s making deep research available to ChatGPT Pro users today, limited to 100 queries per month, with support for Plus and Team users coming next, followed by Enterprise. OpenAI is targeting a Plus rollout in about a month from now, the company said, and the query limits for paid users should be significantly higher soon. It’s a geo-targeted launch; OpenAI had no release timeline to share for ChatGPT customers in the U.K., Switzerland, and the European Economic Area.
To use ChatGPT deep research, you’ll just select Deep Research in the composer and then enter a query, with the option to attach files or spreadsheets. (It’s a web-only experience for now, with mobile and desktop app integration to come later this month.) Deep research could then take anywhere from 5 to 30 minutes to answer the question, and you’ll get a notification when the search completes.
Currently, ChatGPT deep research’s outputs are text-only. But OpenAI said that it intends to add embedded images, data visualizations, and other analytic outputs soon. Also on the roadmap is the ability to connect more specialized data sources, including subscription-based and internal resources, OpenAI added.
More on OpenAI’s Deep Reasoning model on TechCrunch
DeepSeek, China, OpenAI, NVIDIA, xAI, TSMC, Stargate, And AI Megaclusters
In episode #459 Lex Fridman speaks with Dylan Patel, Founder of SemiAnalysis, a research and analysis company specializing in semiconductors, GPUs, CPUs, and AI hardware, and Nathan Lambert, a research scientist at the Allen Institute for AI (Ai2) and the author of a blog on Artificial Intelligence called Interconnects.
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The Vatican Releases ‘Antiqua Et Nova’ Essay On Artificial Intelligence
In what most would consider a halcyon time for artificial intelligence, an anachronistic source has just added their two cents to the ethos around the AI revolution. The Vatican, on Jan. 28, released a significant broadside addressing the potential and risks of AI in a new high-tech world.
It’s a very interesting look at these new technologies through the lens of religion, and of Catholicism in particular, with a focus on human worth and human dignity. Now, I should specify that there is no single “author” on this paper, though much of that it covers is reportedly based on ideas put forth by the pope in recent years. Instead, the article is signed by Cardinal Víctor Fernández, prefect of the Dicastery for the Doctrine of the Faith, as well as Cardinal José Tolentino de Mendonça, prefect of the Dicastery for Culture and Education.
To Be Human
As the paper discusses relativity between humans and artificial intelligence entities, the writers routinely return to the innate value of humanity, starting with this qualifying statement:
“The church encourages the advancement of science technology, the arts, and other forms of human endeavor, viewing them as part of the collaboration of men and women with God and perfecting the visible creation,” they write. “God gave skill to human beings, that he might be glorified in his marvelous works.”
The writers proceed to talk about AI “imitating the human intelligence that designed it,” also noting the power of AI to eclipse the products of many human endeavors.
“AI can be trained on the results of human creativity and then generate new ‘artifacts’ with a level of speed and skill that often rivals or surpasses what humans can do, such as producing text or images indistinguishable from human compositions,” they write. “This raises critical concerns about AI’s potential role in the growing crisis of truth in the public forum. Moreover, this technology is designed to learn and make certain choices autonomously, adapting to new situations and providing solutions not foreseen by its programmers, and thus, it raises fundamental questions about ethical responsibility and human safety, with broader implications for society as a whole. This new situation has prompted many people to reflect on what it means to be human and the role of humanity in the world.”
More on the Vatican’s Antiqua Et Nova AI essay on Forbes
Implementing AI In The Real World — With Kyndryl's Antoine Shagoury
Antoine Shagoury is the Chief Technology Officer of Kyndryl, a global technology services provider spun out from IBM. He joins our show to discuss the real-world implementation of AI in enterprise environments.
Tune in to hear how companies are actually deploying AI agents and what it takes to move beyond proof of concepts to real deployment. We also cover the shift in AI decision-making from IT to business leaders, critical data management challenges, and Kindle's strategic partnership with NVIDIA. Hit play for an insider's perspective on turning AI from buzzword to business reality.
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Artificial Intelligence Agents Could Birth The First One-Person Unicorn — But At What Societal Cost?
Thanks to the advent of cloud computing and distributed digital infrastructure, the one-person micro-enterprise is far from a novel concept. Cheap on-demand compute, remote collaboration, payment processing APIs, social media, and e-commerce marketplaces have all made it easier to “go it alone” as an entrepreneur.
But what about scaling that one-person business into something meatier — an enterprise of unicorn proportions?
Historically, this would have been an unfathomably tough task, due to the skills and resources required, not only to scale a product but also to grow and maintain a sufficiently bountiful customer base. But AI agents could unshackle the would-be solo-preneurs of the world.
AI agents are all about embedding human workflows into software, freeing the human to do more in less time. Agents can be assigned tasks, and they can make decisions with varying degrees of autonomy. Multiple AI agents could even collaborate on complementary tasks, paving the way for getting some real work done entirely autonomously.
In an interview last year with Reddit co-founder Alexis Ohanian, OpenAI’s Sam Altman predicted this exact scenario. “In my little group chat with my tech CEO friends, there’s this betting pool for the first year that there is a one-person billion-dollar company,” Altman said. “Which would have been unimaginable without AI — and now [it] will happen.”
In a discussion at the World Economic Forum’s annual meeting in Davos last week, a panel of entrepreneurs and investors also discussed the prospect of entrepreneurs and investors also discussed the prospect of the single-person billion-dollar enterprise — and, more importantly, what this might mean for the future of employment.
More on AI enabling a one-person unicorn on TechCrunch
Inside A Warehouse Run By AI Robots
Take a tour of a fully automated ecommerce warehouse run by AI robots. To learn more about supply chain robotics and warehouse automation, watch our case study:
Brightpick Autopicker is the only autonomous mobile robot (AMR) in the world that robotically picks and consolidates orders directly in the warehouse aisles, like a human with a cart.
The AMR uses AI to reliably pick everything from ambient and chilled groceries to pharmaceuticals, medical devices, packaged goods, cosmetics, electronics, polybagged apparel and more. Brightpick Autopicker is powered by proprietary 3D machine vision and artificial intelligence (AI), which have been trained on more than a billion picks to date and use machine learning to improve with each pick.
The versatile robot also offers Goods-to-Person (G2P) picking for heavy or hard-to-pick items. The AMR automatically takes those items to a Goods-to-Person station, ensuring 100% pick reliability at all times. This enables customers to maximize their labor savings with robotic picking without worrying about every single SKU being robotically pickable.
The AMRs work with standard shelving and totes, enabling fast deployment and end-to-end supply chain automation in any warehouse, including existing logistics operations. Unlike other fulfillment automation solutions such as shuttle systems (e.g. Exotec) or cube ASRS (e.g. Autostore), Brightpick robots do not need any fixed infrastructure, grids or conveyors to operate. As such, the AI robots serve as an attractive Locus Robotics, Autostore and Exotec alternative.
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European Union Is Betting $56 Million On Open-Source Artificial Intelligence
For years, the European Union has been quicker to regulate artificial intelligence than invest in it. Now, with the battle for AI supremacy heating up thanks to a powerful new open source model from China’s DeepSeek built for a fraction of the price of its U.S. rivals, it’s stepping off the sidelines. This morning Brussels announced plans to develop an open source AI model of its own, with $56 million in funding to do it.
The investment will fund top researchers from a handful of companies and universities across EU countries as they develop a large language model that can work with the trading bloc’s 30 languages. The project will also tap into supercomputers from companies like Spain’s Mare Nostrum and Italy’s Leonardo, both of which have received funding from the EU.
The budget is a tiny fraction of the money pouring into leading American AI labs like OpenAI, which is reportedly raising up to $25 billion at a $300 billion valuation, or even one of Europe’s hottest AI unicorns, Mistral, which raised $640 million last year. But given DeepSeek’s breakthrough, what once sounded like chump change in the AI space could go much, much further: the EU’s backing for the project is 10 times what Deepseek claims to spend on training its own R1 model. “I think Europe should be now seen to be in the race again,” says project coordinator Jan Hajič, professor of computational linguistics at Prague’s Charles University.
The project aims to fund an open source LLM that European companies and governments can build on top of, assured that it was built with the EU’s values baked in. Open source models can allow users to make tweaks and modifications while OpenAI and Anthropic’s AI are walled gardens. “There’s a need for open source models that are aligned in terms of languages, values and with society at large,” says Peter Sarlin, cofounder of Finnish AI lab AMD Silo. (Mistral, which is based in Paris and was valued at over $6.2 billion last year, has made a similar pitch, but it’s not participating in the project.)
More on the EU’s Open Source bet on Forbes
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How does AI distinguish between cats and dogs? Discover the magic of semi-supervised learning! IBM Fellow, Martin Keen delves into AI training with both labeled and unlabeled data, using techniques like the wrapper method and clustering. Perfect for enhancing your AI models with cutting-edge algorithms and innovative methods.
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