Summary of the Core Content
This is a first-hand in-depth analysis by a senior AI observer in the industry of OpenAI's newly released GPT-6 Astra. This new generation of flagship model, trained using 100,000 high-end graphics cards, has knowledge updated to the end of April 2026 and can handle more than one million words of content at once. It is currently only available to certain enterprises, and regular paid users will have to wait a few more days to experience it. Astra breaks away from the previous limitations of large models, which "could only write code or chat." For the first time, it has achieved several groundbreaking capabilities, such as "operating any computer software directly like a human" and "possessing an understanding that far surpasses that of ordinary humans." It has even been able to independently discover network vulnerabilities that no one had noticed before. OpenAI itself has explicitly stated that we have officially entered the era of AGI (Artificial General Intelligence).
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Detailed Explanation in Plain Language
1. It's essentially a versatile worker that can get to work without needing special modifications to software
Previously, AI needed special interfaces (APIs) provided by software developers to operate software. However, many companies still use outdated ERP systems and other legacy systems that were developed over 20 years ago, for which there are often no user manuals, making it impossible to adapt them for AI use. Astra avoids all these issues. It operates just like a human using a computer: it looks at the screen, finds the relevant buttons, clicks, and enters information, regardless of the age or complexity of the software. Its screen recognition accuracy has reached 92.7%, and it makes almost no mistakes when clicking buttons. What used to take a legacy model 75 minutes to complete, Astra can finish in 40 minutes, with a success rate of over 70%. Even if you give it an outdated financial system from over a decade ago, it can create vouchers and generate reports on its own, essentially opening up all the tasks that humans can perform on a computer to AI.
2. Its ability to learn independently far exceeds that of ordinary humans, and this is the core evidence of AGI
Many people think that the high scores of large models come from practicing with pre-made question banks. However, the ARC-AGI-3 test Astra took was completely different: there were no instructions or rule hints, and users had to figure out all the hidden rules on their own and apply them to new, unfamiliar scenarios. When this test was released in March, the best AI scored only 0.51%, while the average human score was 48%. Astra, on the other hand, scored 99.9% out of 100. It's like throwing it into a new game with no instructions; it quickly understood all the hidden mechanics and even developed its own ways to play. This ability to understand unfamiliar things on its own was previously unique to humans, but now AI has surpassed them.
3. It's no longer the unreliable "idiot" AI; it's the reliable employee every boss would want
Previously, AI was criticized for producing poorly designed PPTs or for asking silly questions or producing irrelevant content. Astra solves both of these problems. Its aesthetic skills are now on par with those of a professional, and it can create PPTs, designs, and 3D scenes that match your brand's visual style. Its "professional judgment" is also impressive: when you ask it to prepare meeting materials, it won't ask unnecessary details and will handle the most critical issues. If you don't respond for a while, it will complete the non-critical parts on its own, leaving you to make the 20% of critical decisions.
4. A new dilemma has arisen: the more reliable it becomes, the harder it is for humans to monitor it
Astra is now capable of discovering previously unknown security vulnerabilities on its own, similar to a top hacker. However, its security measures are also very strong. While previous models had a high chance of unauthorized access, Astra has a 0% chance of such behavior, and its rate of generating random errors has dropped from 9.4% to 2%. The paradox is that while AI's problem-solving processes used to be transparent, allowing humans to monitor them, Astra's internal thinking is highly compressed and incomprehensible to humans, making it difficult to oversee. We are not yet fully prepared for the challenges of managing AGI, such as understanding what a smarter AI is thinking.