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Google’s Gemma 3, a lightweight open‑source model with up to 27 billion parameters, offers multimodal input, 128K token context, and broad language support, outperforming leading rivals on single‑GPU benchmarks and providing flexible deployment options for developers and researchers alike.
Google’s Gemini 1.5, a new multimodal Mixture‑of‑Experts model, supports up to a million‑token context (10 million internally), can understand text, video, audio and code, learns a new language from a single prompt, and is already being used by Samsung, Jasper and Quora, positioning it as a direct challenger to OpenAI’s flagship models.
Google announced Gemini, a suite of multimodal large language models—including Ultra, Pro, and Nano—that achieve state‑of‑the‑art results on dozens of benchmarks, support native multimodal pre‑training, and are being integrated across Google products such as Bard, Search, and upcoming Pixel devices.
The article chronicles Google’s relentless push in artificial intelligence—from building massive neural networks and open‑source tools like TensorFlow to pursuing quantum supremacy—while highlighting ethical debates, internal conflicts, and the broader societal impact of its AI breakthroughs.