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\u867d\u7136 Web3 \u6b63\u5728\u5feb\u901f\u589e\u957f\uff0c\u4f46\u8be5\u884c\u4e1a\u7684\u73b0\u72b6\u4e0e\u5176\u4ed6\u79d1\u6280\u884c\u4e1a\u56e0\u7d20\u76f8\u7ed3\u5408\u662f AI \u6570\u636e\u504f\u89c1\u8d70\u4e0a\u9519\u8bef\u9053\u8def\u7684\u539f\u56e0\u3002\uff0c\u5317\u4eac\u5546\u62a5\u8bb0\u8005\u901a\u8fc7\u77e5\u60c5\u4eba\u58eb\u4e86\u89e3\u5230\uff0c\u201c\u706b\u5e01\u201d\u4e4b\u6240\u4ee5\u8fdb\u884c\u54c1\u724c\u5347\u7ea7\u5e76\u66f4\u540d\uff0c\u662f\u56e0\u4e3a\u80a1\u6743\u8f6c\u8ba9\u534f\u8bae\u91cc\u660e\u786e\u6307\u51fa\uff0c\u5728\u865a\u62df\u8d27\u5e01\u4ea4\u6613\u7684\u5f00\u5c55\u548c\u53c2\u4e0e\u7b26\u5408\u4e2d\u56fd\u7684\u6cd5\u5f8b\u548c\u76d1\u7ba1\u89c4\u5b9a\u524d\uff0c\u65b0\u80a1\u4e1c\u4e0d\u5141\u8bb8\u4f7f\u7528\u201c\u706b\u5e01\u201d\u4e2d\u6587\u54c1\u724c\uff0c\u4e0d\u80fd\u5728\u4e2d\u56fd\u5927\u9646\u5f00\u5c55\u865a\u62df\u8d27\u5e01\u4ea4\u6613\u76f8\u5173\u4e1a\u52a1\u6b27\u6613okex\u4ea4\u6613\u6240\u5b98\u7f51\u4e0b\u8f7d\u3002\uff0c\u5728 GPT-3 \u8bba\u6587 Language Models are Few-Shot Learners \u4e2d\uff0c\u524d\u4e24\u4f4d\u4f5c\u8005\uff08Tom Brown \u548c Ben Mann\uff09\u548c\u6700\u540e\u4e00\u4f4d\u901a\u8baf\u4f5c\u8005\u3001\u9879\u76ee\u8d1f\u8d23\u4eba\uff08Dario Amodei\uff09\u76ee\u524d\u5747\u5728 Anthropic \u5de5\u4f5c\u3002\u8be5\u8bba\u6587\u7684 31 \u540d\u4f5c\u8005\u4e2d\uff0c\u6709 8 \u540d\u76ee\u524d\u5728 Anthropic \u5de5\u4f5c\u3002\uff0c\u800c\u5176\u4f59\u4ea4\u6613\u8cbb\u7528\u5247\u6bd4\u7167\u5e63\u5e63\u4ea4\u6613\uff0c\u5f9eMaker \/ Taker = 0.1000% \/ 0.1000% \u8d77\u8df3\u3002\u3002<\/p>\n

\u6b27\u6613\u4ea4\u6613\u6240app\u5b98\u7f51\u4e0b\u8f7d\u5b89\u5353\u7248\u7684\u300c\u60f3\u60f3\u4e00\u5806\u7528\u6236\u90fd\u53bb\u767b\u8a18\u8aaa\u4ed6\u8ce0\u4e86\u591a\u5c11\u9322\u591a\u5c11\u9322\uff0c\u662f\u8ab0\u3001\u8981\u600e\u9ebc\u6838\u5be6\u7528\u6236\u5230\u5e95\u771f\u7684\u6709\u6c92\u6709\u9019\u7b46\u9322\uff1f\u300d\uff0c\u6469\u6839\u58eb\u4e39\u5229\u6210\u4e3a\u9996\u5bb6\u6b63\u5f0f\u63a5\u5165 GPT-4 \u7684\u91d1\u878d\u673a\u6784\uff0cBNB\u662f\u5e63\u5b89\u81ea\u5df1\u767c\u884c\u7684\u52a0\u5bc6\u8ca8\u5e63\uff0c\u7528BNB\u7e73\u4ed8\u624b\u7e8c\u8cbb\u6642\u53ef\u670975\u6298\u7684\u6298\u6263\uff0c\uff0clHicesrr\u6211\u89ba\u5f97 FTX \u7522\u54c1\u529b\u9084\u662f\u6709\u7684\uff0c\u61c9\u8a72\u9084\u662f\u80fd\u8cfa\u9322\u7684\u4ea4\u6613\u6240\uff0c\u7576\u6642\u5982\u679c\u6c92\u6709\u7533\u8acb\u7834\u7522\u91cd\u7d44\uff0c\u800c\u662f\u4ed6\u9858\u610f\u8ddf\u5ba2\u6236\u5354\u5546\u4e00\u500b\u65b9\u5f0f\u4f86\u8ce0\u511f\u5ba2\u6236\uff0c\u8b93\u7522\u54c1\u7e7c\u7e8c\u71df\u904b\uff0c\u96a8\u5f8c\u7b49\u65b0\u7684\u4e00\u7b46\u8cc7\u91d1\u80fd\u9032\u4f86\uff0c\u6210\u7acb\u4e00\u7b46\u6b3e\u9805\u5c08\u6b3e\u5c08\u7528\uff0c\u90a3\u9ebc\u73fe\u5728\u7684\u4e8b\u4ef6\u53ef\u80fd\u6703\u662f\u53e6\u4e00\u500b\u65b0\u6c23\u8c61\u3002<\/p>\n

\u6b27\u6613\u6700\u65b0\u5730\u5740 \u5408\u7ea6\u4ea4\u6613-\u6b27\u6613OKX \u6b27\u6613\u8bc8\u9a97 <\/p>\n","protected":false},"excerpt":{"rendered":"

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