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first_img Google launched Playground, where you can generate playable games by entering text descriptions

On October 7, Google launched the web platform Playground, where users can describe game ideas in natural language and obtain playable, shareable game versions without writing code. Users can also continue to adjust physical effects, rules, characters, or scenes through dialogue and share their creations via links. This tool is currently open to users over 18 in the United States, with creation permissions tiered according to the user's Google AI subscription level.Games in Playground can run in browsers on mobile phones and laptops. Creators can set their works to private or publish them to the community gallery, and all games must pass a security review, with some categories supporting leaderboards and multiplayer modes. Google refers to it as "an early experiment," and the announcement did not disclose pricing or specify which AI models power the tool.The upgrade path points to Unity Spark, and Google stated that Playground will soon integrate this tool to meet the needs of creators requiring professional-level mechanics and high-fidelity 3D. In a joint statement, Google and Unity announced that Spark will launch later this year, with closed testing starting soon. Previously, DeepMind released the Genie model in 2024, and in January, Google opened Project Genie based on Genie 3 to users of the AI Ultra subscription in the United States.

first_img Google released the Nano Banana 2.1 image model, with the developer call price being about half of the previous generation

Google released its latest image generation and editing model, Nano Banana 2.1, on October 6, and it has been launched in the Gemini app, AI mode of Google Search, Google Ads, as well as developer tools like Google AI Studio, Flow, and Stitch. This model can generate images from text descriptions and edit existing photos.Google stated that this upgrade focuses on three aspects: visual design, mask-based editing (where only the marked area changes), and subject consistency, meaning that characters or objects retain their original features after multiple edits. In the overall preference test for text-to-image generation, Nano Banana 2.1 scored 1050 ELO points, higher than Nano Banana 2's 990 points and Nano Banana Pro's 935 points. The model can handle up to 14 reference images simultaneously, track 4 characters and 10 objects, and output up to 4K resolution with an aspect ratio of up to 8:1. Developers can also set the thinking time before generation and enable fact-checking based on Google Search and Google Image Search.When called through the Google Developer API, the standard 1K image is priced at $0.0336, about half of Nano Banana 2's $0.067; the 4K image is $0.0756, while the previous generation was $0.151, and bulk tasks can enjoy a 50% discount. The above performance data comes from Google's own testing.

first_img Grayscale Research Director: Generation Z starts investing at an average age of 19

Grayscale Research Director Zach Pandl published an article on September 28, 2026, in the company's column The Stack. The article states that among American investors, Generation Z starts investing at an average age of 19, Millennials at 25, Generation X at 32, and Baby Boomers at 35. Based on a retirement age of 65, Generation Z has an investment horizon of 46 years, which is over 50% longer than the 30-year horizon when Baby Boomers started investing.Zach Pandl: Starting to invest earlier not only benefits from compound interest but also expands the capacity to take on risk. When young, labor capital accounts for a larger proportion of wealth, and a longer horizon means more time to recover from fluctuations, as well as more future income available for continued saving and investing, thereby expanding the lifetime risk budget. He believes that the returns on digital assets are both volatile and potentially asymmetric, making them more suitable for longer and more flexible horizons.Zach Pandl also mentioned that for early investors, the cost of recent volatility may be less than the opportunity cost of missing out on long-term upside. With decades available for rebalancing, adding funds, and compounding across cycles, early starters may allocate a higher proportion to digital assets while keeping their lifetime risk balanced. Starting to invest earlier gives investors more time to absorb fluctuations, potentially enhancing the utility of digital assets in long-term portfolios.

first_img The number of users of generative artificial intelligence in our country has surpassed 700 million

On September 29, the Policy and International Cooperation Department of the China Internet Network Information Center released the "Generative Artificial Intelligence Application Development Report (2026)" at the "2026 (Seventh) China Internet Basic Resource Conference." The report shows that by the first half of 2026, the user scale of generative artificial intelligence in China will exceed 700 million, with a penetration rate of over 50.0%. Intelligent Q&A is the main scenario, with 76.0% of users using it to answer questions, while the proportions of users handling images or videos, text, work summaries, meeting minutes, and PPTs are 47.8%, 37.6%, and 32.5%, respectively.The usage of applications such as AI comprehensive assistants and AI efficiency office tools has increased by over 100% year-on-year. 38.7% of internet users have purchased smart hardware online in the past six months, with the purchase ratios of smart wearable devices, smartphones, and tablets being 20.2% and 18.2%, respectively. By June 2026, China's intelligent computing power scale reached 2185 EFLOPS, a year-on-year increase of 177%, and the first domestically produced 100,000 card artificial intelligence supercluster was officially put into use.Deep Exploration, Dark Side of the Moon, and others have successively released multiple trillion-parameter open-source large models, and more than 120,000 high-quality datasets have been established. The application penetration rate of artificial intelligence technology among large-scale manufacturing enterprises has exceeded 30%. In the first half of 2026, there were over 400 humanoid robot complete products, and the total annual production is expected to exceed 100,000 units. During the same period, there were 1,255 instances of investment and financing related to artificial intelligence, totaling approximately 250.14 billion yuan, reaching 78.0% and 182.0% of the total for the entire year of 2025, respectively.

Xiao Hong, the founder of General Intelligence Manus, stated that preparations for a domestic version are underway

The founder of the general-purpose intelligent agent Manus, Xiao Hong, stated that when Manus was born, Codex and Claude Cowork had not yet appeared in the market, and the product positioning has always been a general-purpose intelligent agent. He likened Manus to a computer-selling business, believing that users may primarily purchase computers for work, but if they cannot watch videos or play games, the experience will be quite limited; therefore, it should not be confined to office tasks.Xiao Hong indicated that videos and games are important scenarios for unleashing creativity, which need to be perfected through the local client Manus Studio. The related videos for Cue are entirely produced by Manus Studio, without using video generation models; instead, the agent first writes the code, which is then converted into video. With the help of cloud computers, Manus can also create online games that support user participation with friends.In terms of infrastructure, Manus cloud computers can provide cloud-based Linux, Mac, and Windows environments. Xiao Hong stated that when the agent operates the computer in the cloud, it will not compete with the user for the local mouse cursor, and he anticipates that individuals will be able to control large-scale computing clusters in the future to satisfy curiosity and conduct experiments and explorations in fields such as mathematics and science. He also described Cue as having an independent phone number, email, payment capability, computer, and sufficient intelligence, and stated that if such agents could be regarded as humans, there might be more changes in upper-level interactions. Xiao Hong mentioned that building product experiences in an overseas open ecosystem is relatively easier, and Manus is actively preparing a domestic version.
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