While every lab races to become the next Anthropic—focusing on coding, enterprise AI, and ever-better PDFs, PPTs, and spreadsheets—it’s still refreshing to see GPT-Image-2 powering more creative and playful applications, like this: Given the incredibly high NPS scores that Lego Rocky Space Friend earns on date nights, you can easily imagine just how impressive a low-hallucination, research-enabled, fully multimodal reasoning image model would be. And naturally, it’s excellent for education too. (tweet) sau cultura pop: or sharp, polished infographics: And naturally, the GPT-Image-2 + Codex combination, which is accessible as a skill inside Codex, allowing you to iteratively generate assets while you code. And just like that, Claude Design—the previous Current Thing—has vanished from the discussion entirely. In essence, closing the loop means victory. However, that’s not exactly the point we’re trying to make. The core question we are examining is whether models such as Nano Banana, GPT-Image-2, or GPT OSS 120B Imagine represent an essential allocation of limited GPU resources when one is deliberately avoiding distractions and single-mindedly chasing AGI while striving to meet the revenue, efficiency, and funding targets required for survival. The emerging consensus is clear: they are.
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