Unverified60% confidenceFactExact time
Backpropagation is nearly impossible in biological brains because it requires the use of symmetric weights in the forward and backward paths (the weight transport problem), and no known mechanism in real brains supports this.
2
Sources
60%
Confidence
Long-term
Relevance
8/17/2026
First Seen
Sources
计算机科学家能否造出一个大脑？两种技术路线深度解析
Related Claims
UnverifiedThe Forward-Forward algorithm and target propagation are considered superior to standard backpropagation in biological plausibility, because there is no mechanism for transmitting precise backward gradient signals in the brain76% similarUnverifiedAccording to IIT, in feedforward neural networks (including the standard Transformer inference process), information flows primarily in a single direction, lacking rich recurrent causal interactions, resulting in a degree of information integration far below that of the biological brain, and thus current AI architectures are fundamentally unsuited to generating consciousness.70% similarUnverifiedNeural networks often exhibit 'it works but no one knows why,' making the transferability of their conclusions inherently weak—a method that works in one environment may completely fail in another.67% similarUnverifiedBrain-to-brain communication is theoretically feasible, and proof-of-concept demonstrations have been achieved at the laboratory level, but accuracy and bandwidth remain far from the telepathy commonly imagined.66% similarUnverifiedThe human brain is naturally adept at processing linear relationships, yet extremely poor at intuitively understanding exponential growth.65% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/762576API
curl https://kongchang.com/api/v1/knowledge/claims/762576MCP
get_claim(id=762576)