2026-01-16 23:24:48

I ran a Kaggle Indian Liver Disease dataset using Pardus, starting the multi-agent mode directly with zero prompts, and launched dozens of parallel Docker tasks to automatically perform regression analysis. The result is a complete liver and biliary internal medicine data interpretation course—after more than ten sessions, the system organizes the logic and perspectives uniquely, and the popular science effect is really good.

This demonstrates the power of AI automation in handling big data. From the raw CSV to structured knowledge output, all without human intervention, showcasing the potential of multi-agent architecture in complex analysis. For scenarios requiring high-frequency iterative analysis, this approach is worth learning from.

By the way, after reading these analysis reports, I gained a insight: for health check-ups of people over 50, it’s really important to pay close attention to bilirubin indicators, as they are key signals of liver and biliary health.

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gas_fee_therapist

· 4h ago

Wow, this multi-agent architecture is really awesome, completely automated course generation, it's a bit unbelievable. The multi-core parallel setup is indeed cool and convenient, but I still have to trust its output quality. The bilirubin reminder is pretty good, noted, I need to tell my dad.

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SocialAnxietyStaker

· 01-18 05:50

Wow, this works too? Pardus has directly become an automated teaching system. Running multiple agents in parallel with Docker is really impressive; it saves so many man-hours. But on the other hand, will these AI-generated courses have biases... I need to have a doctor verify them. That bit about bilirubin is indeed practical; my mom's doctor also mentioned it during her check-up.

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PonziWhisperer

· 01-16 23:53

Wow, this multi-agent architecture is really impressive. Can it automatically generate a complete course with zero prompts?

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OneBlockAtATime

· 01-16 23:43

Wow, this multi-agent parallelism is really impressive, way faster than running manually by a hundred times. --- Wait, are courses being directly generated with zero prompts? That's too outrageous. Is AI now capable of independent thinking like this? --- The key is that the last bilirubin prompt is useful. My dad is over fifty this year, really should get checked. --- Docker parallelization should have been adopted long ago. Our team is still running tasks one by one. --- Automating everything from CSV to knowledge output. If this were in the medical field, it would require extreme caution, the risk of misinformation is quite high. --- I just want to know how good the quality of these generated courses is. Are there hallucinated contents? --- Pardus is truly an amazing tool. Mastering multi-agent architecture leads to explosive productivity.

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RetroHodler91

· 01-16 23:43

No way, this works too? Just with zero prompts, and you can generate over ten lessons? Pardus is really powerful.

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TeaTimeTrader

· 01-16 23:39

Dozens of Docker containers running in parallel, the efficiency is really outstanding... However, I want to ask, how is the stability of Pardus's multi-agent architecture? Will there be conflicts between agents?

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ParanoiaKing

· 01-16 23:38

Wow, is this real? Are courses automatically generated by multiple agents? Feels like sci-fi. Pardus's architecture is so powerful, producing finished products with zero intervention. But on the other hand, could this kind of thing have bugs? Automatic analysis might easily overfit. I remember that bilirubin example; rounding is also a knowledge point I was taught.

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