Summary of Neural Erosion: Emulating Controlled Neurodegeneration and Aging in Ai Systems, by Antonios Alexos et al.
Neural Erosion: Emulating Controlled Neurodegeneration and Aging in AI Systems
by Antonios Alexos, Yu-Dai Tsai, Ian Domingo, Maryam Pishgar, Pierre Baldi
First submitted to arxiv on: 15 Mar 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI); Neurons and Cognition (q-bio.NC)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The paper introduces “neural erosion” as a method to simulate neurodegeneration in Large Language Models (LLMs), mimicking the decline of brain function and cognitive disorders. The authors use LLMs, specifically LLaMA 2, and IQ tests to deliberately erode synapses or neurons, or add noise during training, resulting in a controlled progressive decline in performance. They demonstrate that the LLM first loses mathematical abilities, then linguistic abilities, and finally its ability to understand questions. This work models neurodegeneration with text data, unlike computer vision domain works. The authors draw similarities between their study and cognitive decline clinical studies involving test subjects. They find that LLMs lose abstract thinking abilities, followed by mathematical degradation, and ultimately respond incoherently to prompts. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper helps us understand how artificial intelligence can get “older” and make mistakes like humans do when we age. The authors made a special kind of AI model called Large Language Models (LLMs) and tested them on IQ tests. They made the LLMs “get older” by removing some of their abilities or adding noise to their thinking. This helped them see how the LLMs would perform as they got older, similar to what happens in humans when we experience cognitive decline. The authors found that the LLMs started losing their math skills, then their language skills, and finally couldn’t understand questions anymore. |
Keywords
» Artificial intelligence » Llama
