Summary in Plain Language
This article is a personal experience by a tech blogger who actually tested OpenAI’s new Astra model. It doesn’t follow the online hype that claims “AI can handle 3D modeling and audio editing in one sentence and will soon replace all professionals.” Instead, it exposes the “editing tricks” behind many popular videos: while Astra can indeed simplify the use of professional software, it’s essentially a tool that enhances capabilities, not a magic wand that creates results out of thin air. The blogger shares funny stories about how using Astra for 3D modeling went wrong and explains the common issue where users tell Astra what to do but don’t provide the necessary details. The article concludes that AI hasn’t eliminated the need for professional skills; it has merely shifted the barrier from “learning to use software” to “having the knowledge to make informed decisions.” As a result, the value of experts becomes even more apparent.
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Detailed Explanation
1. The “miraculous Astra operations” you see online are often just the edited version of the process
Videos showing how you can create beautiful 3D characters with just one command are similar to food bloggers showing a cake they made in 10 seconds. What’s not shown is the blogger’s work behind the scenes: how many paid plugins they installed, how many pre-made materials they used, how many versions of the script they tried, and how many reference examples they fed to the AI. All these details are omitted, leaving you with the impression that modeling is easier than drinking water.
When the blogger tried using Astra, saying “create a delicate girl” resulted in a completely unrecognizable image. Even when given a reference image from the game “Farewell My Concubine,” the AI’s output was off-topic. This is because the blogger didn’t understand the basics of modeling and could only vaguely describe what was wrong (whether it was the proportions, the materials, or the overall approach). Such vague feedback is almost worthless to an AI. If ordinary people believe these edited videos, they will likely fail when they try it themselves and end up feeling anxious about being the only one who can’t benefit from AI.
2. Astra’s real power lies in its invisible “全能 assistant” capabilities
Many people think Astra’s strength lies in simulating the graphical user interface of software, but that’s just the basic level. When testing the audio editing software Audacity, the blogger noticed that Astra automatically switched between different tools to complete a task: if the graphical interface wasn’t enough, it used command-line commands, Python scripts, and the FFmpeg tool to process the audio and video. This is like having an untrained assistant who can handle multiple tasks without training. Previously, you’d need to learn how to use several software programs and understand how to transfer data between them; now, Astra can decide which tool is best for the task without any guidance from you.
3. Why does Astra often “just talk and not act”? It’s become more cautious
Users complain that Astra, unlike the older Sol model, now waits for confirmation before taking action. The blogger found this to be a deliberate design change by OpenAI. The older model would start working without asking questions, but Astra is designed to directly work with your local files and software. To prevent accidental data loss, it waits for clear instructions. If it detects unclear requirements or conflicts with local settings, it stops. Since Astra has replaced the old model as the default option, users who are used to giving commands to an “impatient assistant” find it slow and inefficient.
4. The need for professional skills hasn’t disappeared; it’s just shifted
The myth that AI will replace designers, modelers, and editors has been debunked. The previous barrier was learning how to use software, but now the new barrier is having the knowledge to use that software effectively and knowing how to provide precise instructions to the AI. While you don’t need to learn how to use software, you do need to understand the field and know how to give accurate instructions to the AI.
5. The “useless” logs generated by AI could become valuable evidence of originality
Previously, authenticity was determined by the final product. Now, since AI-generated works are increasingly similar, it’s harder to tell who copied from whom. The blogger found that Astra leaves behind a lot of logs and intermediate files, which could prove the work’s originality. These logs show the entire creative process and are more convincing than a single final image. In the future, copyright verification may rely on these logs, so don’t delete them immediately after use.
In summary, while AI has made some tasks easier, it has also raised new barriers, requiring a deeper understanding of the relevant fields and skills. The “elimination of professional skills” by AI is a myth; it has merely shifted the focus from software usage to expertise.