Over the past time I collected some interesting mechanistic interpretability papers - trying to understand the information processing in AI systems.
Since I'm not an expert, I delegated some of the work to AI itself 🙃
Why I find it interesting? Well, the field of "AI neuroscience" is emerging. This, firstly, brings two fields closer together (neuroAI doesn't count). Second, I believe both understanding of AI and the brain can be advanced by testing theories on the systems where everything can be measured and controlled.
Of course, LLMs are far from natural biological nervous systems, but I believe there are fundamental information processing principles that are shared.
💡Some insights: > Activations in RNNs mirror the statistics of their input data > Apparently chunking of computations is present akin to brain's hierarchical processing > "Grandmother cell" are real but sparse, distributed processing is more likely to be happening
Over the past time I collected some interesting mechanistic interpretability papers - trying to understand the information processing in AI systems.
Since I'm not an expert, I delegated some of the work to AI itself 🙃
Why I find it interesting? Well, the field of "AI neuroscience" is emerging. This, firstly, brings two fields closer together (neuroAI doesn't count). Second, I believe both understanding of AI and the brain can be advanced by testing theories on the systems where everything can be measured and controlled.
Of course, LLMs are far from natural biological nervous systems, but I believe there are fundamental information processing principles that are shared.
💡Some insights: > Activations in RNNs mirror the statistics of their input data > Apparently chunking of computations is present akin to brain's hierarchical processing > "Grandmother cell" are real but sparse, distributed processing is more likely to be happening
Have a look, it's fun 🙂
BY the last neural cell
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This provided opportunity to their linked entities to offload their shares at higher prices and make significant profits at the cost of unsuspecting retail investors. What distinguishes the app from competitors is its use of what's known as channels: Public or private feeds of photos and videos that can be set up by one person or an organization. The channels have become popular with on-the-ground journalists, aid workers and Ukrainian President Volodymyr Zelenskyy, who broadcasts on a Telegram channel. The channels can be followed by an unlimited number of people. Unlike Facebook, Twitter and other popular social networks, there is no advertising on Telegram and the flow of information is not driven by an algorithm. On Feb. 27, however, he admitted from his Russian-language account that "Telegram channels are increasingly becoming a source of unverified information related to Ukrainian events." As the war in Ukraine rages, the messaging app Telegram has emerged as the go-to place for unfiltered live war updates for both Ukrainian refugees and increasingly isolated Russians alike. In this regard, Sebi collaborated with the Telecom Regulatory Authority of India (TRAI) to reduce the vulnerability of the securities market to manipulation through misuse of mass communication medium like bulk SMS.
from ye
