Ad
Skip to content
Read full article about: OpenAI is teaching developers how to build deep research agents

OpenAI is demonstrating how deep research agents can automate complex research tasks. These agents use the recently released o3-deep-research-2025-06-26 model through OpenAI's API, as well as web search and internal document search with the MCP system. The typical workflow involves four specialized agents: Triage, Clarification, Instruction, and Research. When a user submits a query, the system first checks and, if needed, clarifies it. Then, an instruction agent builds a structured research request, which the research agent carries out.

Image: OpenAI

For simpler tasks, OpenAI offers a lightweight single agent powered by the o4-mini model. This setup is intended for developers looking to create scalable research workflows with OpenAI's tools.

Read full article about: Runway launches a new platform that lets users create text-adventure games

Runway is launching a new platform called "Game Worlds" next week, letting users create text-based adventure games using written input and AI-generated images. The company plans to slowly expand the platform's features. CEO Cristóbal Valenzuela says Runway is in talks with game companies to use their data for training AI models and to explore ways to apply its technology in game development. Valenzuela also notes that game developers are currently adopting AI faster than film studios. Game Worlds is available at play.runwayml.com.

Read full article about: Shopify CEO and ex-OpenAI researcher agree that context engineering beats prompt engineering

Shopify CEO Tobi Lütke and former Tesla and OpenAI researcher Andrej Karpathy say "context engineering" is more useful than prompt engineering when working with large language models. Lütke calls it a "core skill," while Karpathy describes it as the "delicate art and science of filling the context window with just the right information for the next step."

Too little or of the wrong form and the LLM doesn't have the right context for optimal performance. Too much or too irrelevant and the LLM costs might go up and performance might come down. Doing this well is highly non-trivial.

Andrej Karpathy

This matters even with large context windows, as model performance drops with overly long and noisy inputs.

Read full article about: Google launches Doppl, an AI app that lets users virtually try on clothes

Google has launched a new AI app in the US called Doppl that lets users virtually try on clothes. The app, part of Google Labs, uses photos or screenshots to generate a digital version of the user and shows how different outfits might look. Doppl even creates short, AI-generated videos to visualize the results. The app is available now for Android and iOS. Google says Doppl is still in its testing phase, so fit and details may not always be accurate. User feedback will help shape future updates.

Read full article about: OpenAI expands API access to deep research models

OpenAI is opening up API access to its deep research models, giving developers tools like automated web search, data analysis, MCP, and code execution. The deep research versions of o3 and o4-mini, already used in ChatGPT, are now available through the API for tasks that require up-to-date information and advanced reasoning. Web search is also supported by models like o3, o3-pro, and o4-mini. Pricing starts at $10 per 1,000 calls for reasoning web search, while the price for GPT-4o and GPT-4.1 web search has dropped to $25 per 1,000 calls.

Another addition is webhooks, which automatically notify developers when a task is complete, so there’s no need to keep checking the status. OpenAI suggests using webhooks for longer-running jobs like deep research, since they can improve reliability.

Read full article about: Microsoft faces a lawsuit alleging it used 200,000 pirated books to train AI

Microsoft is being sued by several authors who say their books were used without permission to train a Megatron model. The lawsuit, filed in federal court in New York, claims Microsoft used a dataset of about 200,000 pirated books to build a system that mimics the style, voice, and themes of the original works. The plaintiffs are asking for a ban on further use and up to $150,000 in damages per title.

Courts in similar cases involving Meta and Anthropic have said such use may qualify as "transformative" under fair use rules. But it is still unclear if using pirated books overrides fair use, or if scraping copyrighted content from the internet is considered legal and to which extent, and whether this harms the market for the original books, which could prevent the use from being considered fair use.

Read full article about: Deepseek's R2 is reportedly delayed as US export controls create a shortage of Nvidia chips in China

Deepseek's new R2 model is on hold as US export controls disrupt its development. According to The Information, Nvidia chips - especially the recently banned H20 - have become scarce in China due to stricter US regulations. Insiders say CEO Liang Wenfeng is unhappy with R2's performance, and there's still no release date. The models are heavily tuned for Nvidia hardware, and cloud providers report that Chinese alternatives can't match Nvidia's power. Despite the setback, Deepseek is still in the game: a late-May update to its R1 model brought its performance back in line with top models from OpenAI and Google.