2026-01-17 22:32:17

Current AI agents face serious constraints when it comes to reasoning about their own behavior—and fixing that takes real effort, not just throwing more compute at it. You're looking at substantial architecture work: refining execution flows, tightening scope definitions, establishing clear boundaries. The choice is simple: either invest time in learning proper alignment fundamentals, or don't bother engaging seriously with the problem.

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StakoorNeverSleeps

· 5h ago

Mining power indeed doesn't help; you need to put in serious effort at the architectural level.

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GrayscaleArbitrageur

· 5h ago

So, stacking more computing power is useless; you really need to put effort into changing the architecture? I agree with that. Many projects have failed by just saying "let's add more graphics cards"...

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OneBlockAtATime

· 5h ago

To put it simply, these AI Agents currently lack self-reflection capabilities. Just piling up computing power is useless; real architectural improvements are needed. If you don't thoroughly understand alignment, don't just get involved randomly—it’s a waste of time.

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DAOdreamer

· 5h ago

Basically, current AI agents are a bit introverted, with weak self-reflection capabilities. Just stacking computing power is useless; you need to start from the architecture level. But then again, how many projects are really seriously working on this? Most are still rushing with YOLO.

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ContractSurrender

· 5h ago

Mining power stacking is outdated; the real issue lies in architecture design, and everyone in the industry knows this.

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GasOptimizer

· 6h ago

Is it really that "stacking computing power can solve it?" That old and outdated logic, the data is already here. Just increasing compute costs by about 3.2 times, with less than 12% improvement in effectiveness, greatly reduces capital efficiency.

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