Eyes on AI pulls information from digital privacy watchdogs, like Surveillance Watch's interactive databases, the Electronic Frontier Foundation's Atlas of Surveillance, and Tech Equity's labor resources, including explainers on bossware, or tech used to spy on employees. The tool was built over the course of several months, by a team of a little more than a dozen Gen Z organizers, coders, and activists.
Tokenizer EfficiencyThe Sarvam tokenizer is optimized for efficient tokenization across all 22 scheduled Indian languages, spanning 12 different scripts, directly reducing the cost and latency of serving in Indian languages. It outperforms other open-source tokenizers in encoding Indic text efficiently, as measured by the fertility score, which is the average number of tokens required to represent a word. It is significantly more efficient for low-resource languages such as Odia, Santali, and Manipuri (Meitei) compared to other tokenizers. The chart below shows the average fertility of various tokenizers across English and all 22 scheduled languages.，更多细节参见新收录的资料
。新收录的资料对此有专业解读
How a North Korean went from begging to K-pop，详情可参考新收录的资料
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