While no one has figured out how to make money from generative artificial intelligence, that hasn't stopped Google DeepMind from pushing the boundaries of what's possible with a big pile of inference. The capabilities (and costs) of these models have been on an impressive upward trajectory, a trend exemplified by the reveal of Genie 3. A mere seven months after showing off the Genie 2 "foundational world model," which was itself a significant improvement over its predecessor, Google now has Genie 3.

With Genie 3, all it takes is a prompt or image to create an interactive world. Since the environment is continuously generated, it can be changed on the fly. You can add or change objects, alter weather conditions, or insert new characters—DeepMind calls these "promptable events." The ability to create alterable 3D environments could make games more dynamic for players and offer developers new ways to prove out concepts and level designs. However, many in the gaming industry have expressed doubt that such tools would help.

It's tempting to think of Genie 3 simply as a way to create games, but DeepMind sees this as a research tool, too. Games play a significant role in the development of artificial intelligence because they provide challenging, interactive environments with measurable progress. That's why DeepMind previously turned to games like Go and StarCraft to expand the bounds of AI.

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How many Google AI researchers does it take to screw in a lightbulb ? A recent research paper detailing the technical core behind Google's Gemini AI assistant may suggest an answer, listing an eye-popping 3,295 authors.

It's a number that recently caught the attention of machine learning researcher David Ha (known as "hardmaru" online), who revealed on X that the first 43 names also contain a hidden message. "There’s a secret code if you observe the authors’ first initials in the order of authorship," Ha wrote , relaying the Easter egg: "GEMINI MODELS CAN THINK AND GET BACK TO YOU IN A FLASH."

The paper, titled "Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities," describes Google's Gemini 2.5 Pro and Gemini 2.5 Flash AI models, which were released in March. These large language models, which power Google's chatbot AI assistant, feature simulated reasoning capabilities that produce a string of "thinking out loud" text before generating responses in an attempt to help them solve more difficult problems. That explains "think" and "flash" in the hidden text.

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