Machine Learning (ML) l\u00e0 m\u1ed9t t\u1eadp h\u1ee3p con c\u1ee7a tr\u00ed tu\u1ec7 nh\u00e2n t\u1ea1o (AI) v\u00e0 n\u00f3 \u0111ang nhanh ch\u00f3ng tr\u1edf th\u00e0nh x\u01b0\u01a1ng s\u1ed1ng c\u1ee7a h\u1ea7u h\u1ebft c\u00e1c ph\u1ea7n m\u1ec1m hi\u1ec7n nay. N\u00f3 t\u1ed3n t\u1ea1i d\u01b0\u1edbi nhi\u1ec1u h\u00ecnh th\u1ee9c kh\u00e1c nhau, t\u1eeb chatbot tr\u00ean c\u00e1c trang web v\u00e0 tr\u1ee3 l\u00fd k\u1ef9 thu\u1eadt s\u1ed1 nh\u01b0 Siri v\u00e0 Alexa, \u0111\u1ebfn c\u00e1c thu\u1eadt to\u00e1n \u0111i\u1ec1u khi\u1ec3n ph\u01b0\u01a1ng ti\u1ec7n truy\u1ec1n th\u00f4ng x\u00e3 h\u1ed9i nh\u01b0 Facebook v\u00e0 nhi\u1ec1u ph\u1ea7n m\u1ec1m v\u0103n ph\u00f2ng kh\u00e1c nhau. Machine Learning r\u1ea5t ph\u1ed5 bi\u1ebfn \u0111\u1ebfn m\u1ee9c kh\u00f3 c\u00f3 th\u1ec3 li\u1ec7t k\u00ea t\u1ea5t c\u1ea3 c\u00e1c n\u01a1i m\u00e0 n\u00f3 t\u1ed3n t\u1ea1i d\u01b0\u1edbi d\u1ea1ng k\u1ef9 thu\u1eadt s\u1ed1 v\u00e0 t\u1ea5t c\u1ea3 c\u00e1c t\u00e1c v\u1ee5 m\u00e0 n\u00f3 th\u1ef1c hi\u1ec7n.<\/p>\n
M\u1eb7c d\u00f9 Machine Learning hi\u1ec7n \u0111ang l\u00e0 c\u00f4ng ngh\u1ec7 ti\u00ean ti\u1ebfn trong cu\u1ed9c s\u1ed1ng v\u00e0 c\u00f4ng vi\u1ec7c h\u00e0ng ng\u00e0y c\u1ee7a ch\u00fang ta, nh\u01b0ng n\u00f3 \u0111\u00e3 t\u1ed3n t\u1ea1i trong m\u1ed9t th\u1eddi gian d\u00e0i. L\u1ecbch s\u1eed c\u1ee7a Machine Learning r\u1ea5t h\u1ea5p d\u1eabn v\u00e0 \u0111\u00e1ng ng\u1ea1c nhi\u00ean khi x\u00e9t \u0111\u1ebfn vi\u1ec7c n\u00f3 \u0111\u00e3 b\u1eaft ngu\u1ed3n t\u1eeb r\u1ea5t l\u00e2u. Nh\u1eefng ti\u1ebfn b\u1ed9 d\u01b0\u1eddng nh\u01b0 nhanh nh\u01b0 \u00e1nh s\u00e1ng c\u1ee7a n\u00f3 hi\u1ec7n nay l\u00e0 do c\u00e1c nh\u00e0 khoa Machine Learning t\u00ednh \u0111\u00e3 tr\u1edf n\u00ean gi\u1ecfi h\u01a1n theo th\u1eddi gian trong vi\u1ec7c h\u00ecnh dung ra c\u00e1c \u1ee9ng d\u1ee5ng m\u1edbi v\u00e0 ho\u00e0n thi\u1ec7n to\u00e1n h\u1ecdc trong c\u00e1c m\u00f4 h\u00ecnh v\u00e0 thu\u1eadt to\u00e1n.<\/p>\n
\u0110\u1ec3 \u0111\u00e1nh gi\u00e1 cao nh\u1eefng kh\u1ea3 n\u0103ng m\u00e0 m\u00e1y h\u1ecdc mang l\u1ea1i, tr\u01b0\u1edbc ti\u00ean ch\u00fang ta h\u00e3y c\u00f9ng xem qua nh\u1eefng th\u00e0nh t\u1ef1u m\u00e0 n\u00f3 \u0111\u00e3 \u0111\u1ea1t \u0111\u01b0\u1ee3c b\u1eb1ng c\u00e1ch xem x\u00e9t l\u1ecbch s\u1eed c\u1ee7a m\u00e1y h\u1ecdc.<\/p>\n
Gi\u1ed1ng nh\u01b0 h\u1ea7u h\u1ebft c\u00e1c \u0111\u1ed9t ph\u00e1 c\u00f4ng ngh\u1ec7 v\u00e0 n\u1ec1n t\u1ea3ng m\u00e1y t\u00ednh, Machine Learning kh\u00f4ng th\u1ec3 \u0111\u01b0\u1ee3c quy cho m\u1ed9t c\u00e1 nh\u00e2n ho\u1eb7c t\u1ed5 ch\u1ee9c duy nh\u1ea5t. Thay v\u00e0o \u0111\u00f3, nhi\u1ec1u ng\u01b0\u1eddi \u0111\u00e3 \u0111\u00f3ng g\u00f3p v\u00e0o s\u1ef1 ph\u00e1t tri\u1ec3n v\u00e0 c\u00e1c \u1ee9ng d\u1ee5ng k\u1ebft qu\u1ea3 c\u1ee7a n\u00f3, v\u00e0 nhi\u1ec1u ng\u01b0\u1eddi kh\u00e1c n\u1eefa c\u0169ng s\u1ebd l\u00e0m nh\u01b0 v\u1eady trong t\u01b0\u01a1ng lai.<\/p>\n
C\u00f3 cu\u1ed9c tranh lu\u1eadn v\u1ec1 vi\u1ec7c ai \u0111\u00e3 ph\u00e1t minh ra n\u00f3 v\u00e0 khi n\u00e0o. S\u1ef1 th\u1eadt l\u00e0 c\u00f3 r\u1ea5t \u00edt th\u1ee9 ph\u1ee9c t\u1ea1p nh\u01b0 th\u1ebf n\u00e0y \u0111\u01b0\u1ee3c t\u1ea1o ra t\u1eeb m\u1ed9t t\u1ea7m nh\u00ecn to\u00e0n di\u1ec7n, \u0111\u01a1n l\u1ebb th\u00e0nh m\u1ed9t h\u00ecnh th\u1ee9c kh\u1ea3 thi ho\u00e0n to\u00e0n m\u1edbi \u0111\u1ed1i v\u1edbi b\u1ed1i c\u1ea3nh n\u00e0y. Thay v\u00e0o \u0111\u00f3, nh\u1eefng ng\u01b0\u1eddi kh\u00e1c nhau l\u00e0m vi\u1ec7c \u0111\u1ec3 t\u1ea1o ra c\u00e1c kh\u00eda c\u1ea1nh, th\u00e0nh ph\u1ea7n, kh\u00e1i ni\u1ec7m, quy tr\u00ecnh, m\u00f4 h\u00ecnh v\u00e0 thu\u1eadt to\u00e1n kh\u00e1c nhau, c\u00f9ng nhau t\u1ea1o n\u00ean c\u00f4ng ngh\u1ec7 \u0111\u01b0\u1ee3c g\u1ecdi l\u00e0 Machine Learning. M\u1ed7i b\u01b0\u1edbc l\u00e0 m\u1ed9t th\u00e0nh t\u1ef1u \u0111\u00e1ng kinh ng\u1ea1c, nh\u01b0ng kh\u00f4ng c\u00f2n nghi ng\u1edd g\u00ec n\u1eefa, t\u1ed5ng th\u1ec3 m\u1ea1nh m\u1ebd h\u01a1n c\u00e1c b\u1ed9 ph\u1eadn.<\/p>\n
T\u1ea5t nhi\u00ean, c\u00f3 nh\u1eefng ng\u01b0\u1eddi n\u1ed5i b\u1eadt ngay c\u1ea3 trong nh\u00f3m nh\u1eefng ng\u01b0\u1eddi l\u00e0m n\u00ean l\u1ecbch s\u1eed m\u00e1y t\u00ednh \u0111\u01b0\u1ee3c k\u00ednh tr\u1ecdng v\u00e0 t\u00e0i n\u0103ng, nh\u1eefng ng\u01b0\u1eddi c\u00f9ng nhau th\u1ed5i tr\u00ed th\u00f4ng minh v\u00e0o nh\u1eefng chi\u1ebfc m\u00e1y t\u00ednh v\u00f4 tri. Ph\u1ea7n b\u00ean d\u01b0\u1edbi n\u00eau b\u1eadt m\u1ed9t s\u1ed1 nh\u00e2n v\u1eadt \u0111\u00e1ng ch\u00fa \u00fd \u0111\u00f3ng vai tr\u00f2 quan tr\u1ecdng trong vi\u1ec7c th\u00fac \u0111\u1ea9y m\u00e1y h\u1ecdc t\u1ea1i nh\u1eefng th\u1eddi \u0111i\u1ec3m quan tr\u1ecdng trong l\u1ecbch s\u1eed c\u1ee7a n\u00f3.<\/p>\n
B\u1ea5t ch\u1ea5p nh\u1eefng cu\u1ed9c tranh lu\u1eadn \u0111ang di\u1ec5n ra, s\u1ef1 \u0111\u1ed3ng thu\u1eadn chung l\u00e0 m\u00e1y h\u1ecdc \u0111\u00e3 tr\u1edf th\u00e0nh m\u1ed9t th\u1ef1c th\u1ec3 \u0111\u01b0\u1ee3c bi\u1ebft \u0111\u1ebfn v\u00e0 do \u0111\u00f3 \u0111\u01b0\u1ee3c Arthur Samuel, m\u1ed9t nh\u00e0 khoa Machine Learning t\u00ednh l\u00e0m vi\u1ec7c t\u1ea1i IBM, ch\u00ednh th\u1ee9c ph\u00e1t minh v\u00e0o n\u0103m 1952. Samuel \u0111\u00e3 \u0111\u1eb7t t\u00ean cho c\u00e1ch ti\u1ebfp c\u1eadn m\u1edbi n\u00e0y \u0111\u1ed1i v\u1edbi m\u00e1y t\u00ednh: m\u00e1y h\u1ecdc.<\/p>\n
Machine Learning t\u1eebng l\u00e0 b\u01b0\u1edbc \u0111\u1ec7m tr\u00ean con \u0111\u01b0\u1eddng ph\u00e1t tri\u1ec3n AI, ch\u1eb7ng \u0111\u01b0\u1eddng d\u00e0i h\u01b0\u1edbng \u0111\u1ebfn vi\u1ec7c t\u1ea1o ra AI t\u1ed5ng qu\u00e1t<\/a> , h\u00ecnh th\u1ee9c m\u00e0 c\u00e1c b\u1ed9 phim khoa h\u1ecdc vi\u1ec5n t\u01b0\u1edfng v\u00e0 ch\u01b0\u01a1ng tr\u00ecnh truy\u1ec1n h\u00ecnh \u0111\u00e3 l\u00e0m cho n\u1ed5i ti\u1ebfng v\u00e0 quen thu\u1ed9c.<\/p>\n Tuy nhi\u00ean, Machine Learning c\u00f3 tr\u1ecdng t\u00e2m v\u00e0 kh\u1ea3 n\u0103ng h\u1eb9p h\u01a1n nhi\u1ec1u so v\u1edbi AI n\u00f3i chung. Cu\u1ed1i c\u00f9ng, ng\u01b0\u1eddi ta nh\u1eadn ra r\u1eb1ng s\u1ebd nhanh h\u01a1n v\u00e0 d\u1ec5 h\u01a1n (m\u1eb7c d\u00f9 v\u1eabn kh\u00f4ng d\u1ec5) khi ph\u00e1t tri\u1ec3n Machine Learning th\u00e0nh c\u00e1c t\u1ea3i tr\u1ecdng t\u1ee9c th\u1eddi v\u00e0 \u0111a d\u1ea1ng h\u01a1n l\u00e0 ch\u1ec9 h\u01b0\u1edbng \u0111\u1ebfn s\u1ef1 ph\u00e1t tri\u1ec3n c\u1ee7a AI.<\/p>\n Machine Learning c\u00f3 t\u1eadp h\u1ee3p con ri\u00eang c\u1ee7a n\u00f3, \u0111\u01b0\u1ee3c g\u1ecdi l\u00e0 h\u1ecdc s\u00e2u<\/a> , th\u1eadm ch\u00ed c\u00f2n h\u1eb9p h\u01a1n ML v\u00ec n\u00f3 chuy\u00ean bi\u1ec7t h\u01a1n nhi\u1ec1u. AI t\u1ed5ng qu\u00e1t l\u00e0 t\u1eadp h\u1ee3p con nh\u1ecf h\u01a1n c\u1ee7a AI t\u1ef1 nh\u1eadn th\u1ee9c, m\u1ed9t d\u1ea1ng th\u1ef1c s\u1ef1 m\u1ea1nh m\u1ebd nh\u01b0ng ho\u00e0n to\u00e0n mang t\u00ednh t\u01b0\u01a1ng lai.<\/p>\n M\u1ed9t th\u00f4ng tin th\u00fa v\u1ecb trong l\u1ecbch s\u1eed v\u1ec1 Machine Learning: H\u1ecdc s\u00e2u \u0111\u01b0\u1ee3c ph\u00e1t minh v\u00e0o n\u0103m 1943, ch\u00edn n\u0103m tr\u01b0\u1edbc khi Machine Learning xu\u1ea5t hi\u1ec7n. C\u00f3 m\u1ed9t s\u1ed1 tranh lu\u1eadn v\u1ec1 vi\u1ec7c ai \u0111\u00e3 ph\u00e1t minh ra h\u1ecdc s\u00e2u v\u00ec n\u00f3 b\u1eaft ngu\u1ed3n t\u1eeb m\u00f4 h\u00ecnh c\u1ee7a Walter Pitts v\u00e0 Warren McCulloch v\u00e0o n\u0103m 1943. N\u00f3 kh\u00f4ng \u0111\u01b0\u1ee3c bi\u1ebft \u0111\u1ebfn r\u1ed9ng r\u00e3i v\u1edbi c\u00e1i t\u00ean “h\u1ecdc s\u00e2u” cho \u0111\u1ebfn khi Gregory Hinton \u0111\u1ed5i t\u00ean nghi\u00ean c\u1ee9u m\u1ea1ng n\u01a1-ron th\u00e0nh bi\u1ec7t danh \u0111\u00f3 v\u00e0o n\u0103m 2006.<\/p>\n V\u00e0o nh\u1eefng n\u0103m 1970, Machine Learning \u0111\u00e3 ph\u00e1t tri\u1ec3n th\u00e0nh m\u1ed9t ng\u00e0nh ri\u00eang v\u00e0 hi\u1ec7n nay n\u00f3 h\u1ed7 tr\u1ee3 ph\u1ea7n l\u1edbn ph\u1ea7n m\u1ec1m tr\u00ean th\u1ebf gi\u1edbi. Trong m\u1ed9t b\u01b0\u1edbc ngo\u1eb7t tr\u1edb tr\u00eau trong l\u1ecbch s\u1eed v\u00e0 b\u1ed1i c\u1ea3nh c\u1ee7a Machine Learning v\u00e0 AI, ng\u00e0y nay n\u00f3 th\u01b0\u1eddng \u0111\u01b0\u1ee3c g\u1eafn nh\u00e3n l\u00e0 AI cho m\u1ee5c \u0111\u00edch ti\u1ebfp th\u1ecb v\u00ec h\u1ea7u h\u1ebft ng\u01b0\u1eddi ti\u00eau d\u00f9ng kh\u00f4ng quen thu\u1ed9c v\u1edbi thu\u1eadt ng\u1eef v\u00e0 kh\u00e1i ni\u1ec7m Machine Learning.<\/p>\n Ng\u01b0\u1eddi \u0111\u1ea7u ti\u00ean v\u00e0 c\u00f3 th\u1ec3 n\u00f3i l\u00e0 \u0111\u01b0\u1ee3c c\u00f4ng ch\u00fang bi\u1ebft \u0111\u1ebfn nhi\u1ec1u nh\u1ea5t trong l\u1ecbch s\u1eed Machine Learning v\u00e0 AI l\u00e0 Alan Turing, ng\u01b0\u1eddi \u0111\u00e3 t\u1ea1o ra B\u00e0i ki\u1ec3m tra Turing \u0111\u1ec3 x\u00e1c \u0111\u1ecbnh xem m\u00e1y m\u00f3c c\u00f3 th\u1ef1c s\u1ef1 c\u00f3 th\u1ec3 suy ngh\u0129 hay kh\u00f4ng. N\u00f3 \u0111\u00e3 tr\u1edf th\u00e0nh m\u1ed9t chu\u1ea9n m\u1ef1c n\u1ed5i ti\u1ebfng \u0111\u1ec3 \u0111o l\u01b0\u1eddng xem m\u1ed9t c\u1ed7 m\u00e1y c\u00f3 \u0111\u1ee7 tr\u00ed th\u00f4ng minh \u0111\u1ec3 kh\u00f4ng ch\u1ec9 suy ngh\u0129 nh\u01b0 con ng\u01b0\u1eddi m\u00e0 c\u00f2n \u0111\u00e1nh l\u1eeba ng\u01b0\u1eddi ta tin r\u1eb1ng n\u00f3 c\u0169ng l\u00e0 con ng\u01b0\u1eddi. \u0110\u1ecbnh ngh\u0129a n\u00e0y \u0111\u00e3 t\u1ea1o ra m\u1ed9t s\u1ed1 c\u00e1ch \u0111\u1ec3 b\u1eaft ch\u01b0\u1edbc suy ngh\u0129 c\u1ee7a con ng\u01b0\u1eddi m\u1ed9t c\u00e1ch nh\u00e2n t\u1ea1o v\u00e0 c\u0169ng \u0111\u1ec3 ki\u1ec3m tra hi\u1ec7u qu\u1ea3 c\u1ee7a suy ngh\u0129 v\u00e0 h\u00e0nh \u0111\u1ed9ng c\u1ee7a n\u00f3.<\/p>\n Arthur Samuel \u0111\u00e3 n\u00f3i \u1edf tr\u00ean, ng\u01b0\u1eddi \u0111\u00e3 \u0111\u1eb7t t\u00ean cho c\u00f4ng ngh\u1ec7 th\u00f4ng minh n\u00e0y l\u00e0 m\u00e1y h\u1ecdc, c\u0169ng \u0111\u00e3 ph\u00e1t tri\u1ec3n m\u1ed9t ch\u01b0\u01a1ng tr\u00ecnh d\u1ef1a tr\u00ean m\u00e1y h\u1ecdc \u0111\u1ec3 ch\u01a1i c\u1edd \u0111am. L\u00e0 m\u1ed9t l\u01b0u \u00fd th\u00fa v\u1ecb trong l\u1ecbch s\u1eed m\u00e1y h\u1ecdc v\u00e0 tr\u00ed tu\u1ec7 nh\u00e2n t\u1ea1o, n\u00f3 \u0111\u01b0\u1ee3c cho l\u00e0 tr\u00f2 ch\u01a1i \u0111\u1ea7u ti\u00ean, ho\u1eb7c \u00edt nh\u1ea5t l\u00e0 m\u1ed9t trong nh\u1eefng tr\u00f2 ch\u01a1i \u0111\u1ea7u ti\u00ean m\u00e0 m\u00e1y c\u00f3 th\u1ec3 ch\u01a1i.<\/p>\n Tr\u00f2 ch\u01a1i l\u00e0 m\u1ed9t c\u00e1ch \u0111\u01a1n gi\u1ea3n \u0111\u1ec3 minh h\u1ecda c\u00e1ch m\u00e1y c\u00f3 th\u1ec3 h\u1ecdc v\u00e0 ph\u1ea3n \u1ee9ng v\u1edbi h\u00e0nh \u0111\u1ed9ng v\u00e0 ph\u1ea3n \u1ee9ng c\u1ee7a con ng\u01b0\u1eddi. N\u00f3 h\u1ecdc tr\u00f2 ch\u01a1i th\u00f4ng qua th\u1ef1c h\u00e0nh \u2013 gi\u1ed1ng nh\u01b0 con ng\u01b0\u1eddi \u2013 b\u1eb1ng c\u00e1ch s\u1eed d\u1ee5ng thu\u1eadt to\u00e1n minimax. M\u1eb7c d\u00f9 \u0111\u00e2y l\u00e0 m\u1ed9t s\u1ef1 ph\u00e1t tri\u1ec3n s\u1edbm h\u01a1n trong l\u1ecbch s\u1eed thu\u1eadt to\u00e1n Machine Learning, lo\u1ea1i thu\u1eadt to\u00e1n n\u00e0y v\u1eabn \u0111\u01b0\u1ee3c s\u1eed d\u1ee5ng trong l\u00fd thuy\u1ebft tr\u00f2 ch\u01a1i v\u00e0 ra quy\u1ebft \u0111\u1ecbnh t\u1ef1 \u0111\u1ed9ng \u0111\u1ec3 l\u1ef1a ch\u1ecdn n\u01b0\u1edbc \u0111i ti\u1ebfp theo t\u1ed1i \u01b0u cho ng\u01b0\u1eddi ch\u01a1i ho\u1eb7c ng\u01b0\u1eddi d\u00f9ng.<\/p>\n Nh\u01b0ng Frank Rosenblatt m\u1edbi l\u00e0 ng\u01b0\u1eddi \u0111\u01b0\u1ee3c ghi nh\u1eadn l\u00e0 ng\u01b0\u1eddi \u0111\u1ea7u ti\u00ean thi\u1ebft k\u1ebf m\u1ea1ng n\u01a1-ron cho m\u00e1y t\u00ednh. \u0110\u00e2y l\u00e0 n\u1ed7 l\u1ef1c ban \u0111\u1ea7u nh\u1eb1m m\u00f4 ph\u1ecfng c\u00e1c qu\u00e1 tr\u00ecnh suy ngh\u0129 c\u1ee7a con ng\u01b0\u1eddi. M\u1eb7c d\u00f9 l\u00e0 m\u1ed9t ti\u1ebfn b\u1ed9 v\u01b0\u1ee3t b\u1eadc, nh\u01b0ng ph\u1ea3i \u0111\u1ebfn n\u0103m 1967, m\u1edbi c\u00f3 ng\u01b0\u1eddi vi\u1ebft ra m\u1ed9t thu\u1eadt to\u00e1n c\u00f3 th\u1ec3 nh\u1eadn d\u1ea1ng c\u00e1c m\u1eabu. Machine Learning v\u1ec1 b\u1ea3n ch\u1ea5t l\u00e0 m\u1ed9t m\u00e1y d\u00f2 m\u1eabu. N\u00f3 c\u00f3 th\u1ec3 nhanh ch\u00f3ng t\u00ecm ra c\u00e1c m\u1eabu trong l\u01b0\u1ee3ng d\u1eef li\u1ec7u kh\u1ed5ng l\u1ed3, h\u1ecdc h\u1ecfi t\u1eeb c\u00e1c m\u1eabu \u0111\u00f3, r\u1ed3i x\u00e1c \u0111\u1ecbnh k\u1ebft qu\u1ea3 d\u1ef1a tr\u00ean c\u00e1c m\u1eabu m\u00e0 n\u00f3 t\u00ecm th\u1ea5y.<\/p>\n Th\u1eadt v\u00f4 c\u00f9ng kh\u00f3 \u0111\u1ec3 ghi nh\u1eadn b\u1ea5t k\u1ef3 ai trong s\u1ed1 nh\u1eefng ng\u01b0\u1eddi n\u00e0y l\u00e0 nh\u00e0 ph\u00e1t minh. C\u00e0ng kh\u00f3 h\u01a1n khi b\u1ea1n xem x\u00e9t r\u1eb1ng \u0111\u00e2y ch\u1ec9 l\u00e0 m\u1ed9t s\u1ed1 \u00edt trong s\u1ed1 r\u1ea5t nhi\u1ec1u ng\u01b0\u1eddi \u0111\u00e3 \u0111\u00f3ng g\u00f3p v\u00e0o s\u1ef1 \u0111\u1ed5i m\u1edbi \u0111\u00e1ng kinh ng\u1ea1c n\u00e0y.<\/p>\n Machine Learning l\u1ea7n \u0111\u1ea7u ti\u00ean \u0111\u01b0\u1ee3c th\u1ef1c hi\u1ec7n khi con ng\u01b0\u1eddi ph\u00e1t hi\u1ec7n ra r\u1eb1ng c\u00e1c con s\u1ed1 v\u00e0 v\u1eadt th\u1ec3 c\u00f3 th\u1ec3 bi\u1ec3u di\u1ec5n nh\u1eefng th\u1ee9 t\u1ed3n t\u1ea1i trong th\u1ebf gi\u1edbi th\u1ef1c. \u0110\u00e2y l\u00e0 d\u1eef li\u1ec7u \u0111\u1ea7u ti\u00ean. V\u00e0 Machine Learning h\u1ecdc t\u1eeb d\u1eef li\u1ec7u v\u00e0 c\u0169ng l\u1ea5y d\u1eef li\u1ec7u t\u1eeb \u0111\u00f3.<\/p>\n Machine Learning d\u1ef1a tr\u00ean to\u00e1n h\u1ecdc v\u00e0 c\u00e1c m\u00f4 h\u00ecnh c\u1ee7a n\u00f3 th\u01b0\u1eddng ho\u1ea1t \u0111\u1ed9ng v\u1edbi d\u1eef li\u1ec7u bi\u1ec3u di\u1ec5n c\u00e1c th\u1ef1c th\u1ec3 ho\u1eb7c h\u00e0nh \u0111\u1ed9ng trong th\u1ebf gi\u1edbi th\u1ef1c. Theo \u0111\u1ecbnh ngh\u0129a n\u00e0y, ng\u01b0\u1eddi ta c\u00f3 th\u1ec3 n\u00f3i r\u1eb1ng Machine Learning tr\u1edf n\u00ean kh\u1ea3 thi ngay khi ai \u0111\u00f3 \u0111\u1ebfm m\u1ed9t th\u1ee9 g\u00ec \u0111\u00f3 v\u00e0 ghi l\u1ea1i s\u1ed1 \u0111\u00f3, c\u00f3 th\u1ec3 l\u00e0 b\u1eb1ng c\u00e1ch ghi ch\u00fa c\u00f3 ch\u1ee7 \u0111\u00edch tr\u00ean t\u01b0\u1eddng hang \u0111\u1ed9ng ho\u1eb7c nh\u1eefng vi\u00ean s\u1ecfi trong t\u00fai.<\/p>\n C\u00e1c ph\u01b0\u01a1ng ph\u00e1p thu th\u1eadp v\u00e0 l\u01b0u tr\u1eef d\u1eef li\u1ec7u t\u1ed1t h\u01a1n \u0111\u00e3 xu\u1ea5t hi\u1ec7n, c\u0169ng nh\u01b0 c\u00e1c m\u00e1y m\u00f3c c\u00f3 th\u1ec3 th\u1ef1c hi\u1ec7n c\u00e1c ph\u00e9p t\u00ednh c\u1ea7n thi\u1ebft. N\u0103m 1642, m\u1ed9t thi\u1ebfu ni\u00ean \u1edf Ph\u00e1p \u0111\u00e3 ch\u1ebf t\u1ea1o ra m\u00e1y t\u00ednh c\u01a1 h\u1ecdc \u0111\u1ea7u ti\u00ean. L\u1ea7n \u0111\u1ea7u ti\u00ean, m\u1ed9t c\u1ed7 m\u00e1y ch\u1ee9 kh\u00f4ng ph\u1ea3i con ng\u01b0\u1eddi th\u1ef1c hi\u1ec7n ph\u00e9p t\u00ednh. H\u1ec7 nh\u1ecb ph\u00e2n hi\u1ec7n \u0111\u1ea1i \u0111\u00e3 \u0111\u01b0\u1ee3c t\u1ea1o ra.<\/p>\n M\u00e1y ch\u01a1i c\u1edd \u0111\u1ea7u ti\u00ean xu\u1ea5t hi\u1ec7n v\u00e0o n\u0103m 1770 v\u00e0 ngay l\u1eadp t\u1ee9c l\u00e0m b\u1ed1i r\u1ed1i ng\u01b0\u1eddi ch\u00e2u \u00c2u trong nhi\u1ec1u th\u1eadp k\u1ef7 sau \u0111\u00f3. N\u0103m 1834, l\u1eadp tr\u00ecnh th\u1ebb \u0111\u1ee5c l\u1ed7, \u0111\u01b0\u1ee3c coi r\u1ed9ng r\u00e3i l\u00e0 “cha \u0111\u1ebb c\u1ee7a m\u00e1y t\u00ednh”, \u0111\u00e3 \u0111\u01b0\u1ee3c ph\u00e1t minh.<\/p>\n M\u1ed9t ng\u01b0\u1eddi ph\u1ee5 n\u1eef \u0111\u00e3 t\u1ea1o ra thu\u1eadt to\u00e1n \u0111\u1ea7u ti\u00ean v\u00e0o n\u0103m 1842. Nh\u1edd \u0111\u00f3, Ada Lovelace \u0111\u00e3 tr\u1edf th\u00e0nh l\u1eadp tr\u00ecnh vi\u00ean m\u00e1y t\u00ednh \u0111\u1ea7u ti\u00ean tr\u00ean th\u1ebf gi\u1edbi. C\u00f4ng tr\u00ecnh nghi\u00ean c\u1ee9u v\u1ec1 \u0111\u1ea1i s\u1ed1 c\u1ee7a m\u1ed9t nh\u00e0 huy\u1ec1n m\u00f4n \u0111\u00e3 gi\u00fap CPU tr\u1edf n\u00ean kh\u1ea3 thi nh\u01b0ng ph\u1ea3i h\u01a1n m\u1ed9t th\u1ebf k\u1ef7 sau, con ng\u01b0\u1eddi m\u1edbi ph\u00e1t minh ra CPU.<\/p>\n N\u0103m 1927, AI xu\u1ea5t hi\u1ec7n l\u1ea7n \u0111\u1ea7u trong phim \u1ea3nh. Nh\u01b0ng Alan Turing kh\u00f4ng h\u00ecnh th\u00e0nh n\u00ean “Universal Machine” cho \u0111\u1ebfn n\u0103m 1936, m\u1ed9t l\u1ea7n n\u1eefa ch\u1ee9ng minh r\u1eb1ng c\u00e1c nh\u00e0 v\u0103n khoa h\u1ecdc vi\u1ec5n t\u01b0\u1edfng c\u00f3 xu h\u01b0\u1edbng ti\u00ean \u0111o\u00e1n ho\u1eb7c \u00edt nh\u1ea5t l\u00e0 sinh ra tr\u01b0\u1edbc th\u1eddi \u0111\u1ea1i c\u1ee7a h\u1ecd.<\/p>\n V\u00e0 c\u1ee9 th\u1ebf, l\u1ecbch s\u1eed c\u1ee7a m\u00e1y h\u1ecdc v\u1eabn ti\u1ebfp di\u1ec5n, \u0111\u01b0\u1ee3c x\u00e2y d\u1ef1ng t\u1eebng ph\u1ea7n qua nhi\u1ec1u th\u1ebf k\u1ef7.<\/p>\n G\u1ea7n \u0111\u00e2y, m\u00e1y h\u1ecdc \u0111\u01b0\u1ee3c \u00e1p d\u1ee5ng cho nhi\u1ec1u lo\u1ea1i d\u1eef li\u1ec7u kh\u00e1c nhau. V\u00ed d\u1ee5, ng\u00e0y nay \u0111\u00f4i khi n\u00f3 \u0111\u01b0\u1ee3c gh\u00e9p n\u1ed1i v\u1edbi c\u00e1c c\u00f4ng ngh\u1ec7 kh\u00e1c nh\u01b0 th\u1ecb gi\u00e1c m\u00e1y t\u00ednh \u0111\u1ec3 nh\u1eadn d\u1ea1ng c\u00e1c m\u1eabu trong h\u00ecnh \u1ea3nh, t\u1eeb ch\u1ee5p X-quang y t\u1ebf \u0111\u1ebfn nh\u1eadn d\u1ea1ng khu\u00f4n m\u1eb7t trong video. C\u00e1c thu\u1eadt to\u00e1n hi\u1ec7n nay c\u0169ng hi\u1ec3u \u0111\u01b0\u1ee3c c\u00e1c truy v\u1ea5n ng\u00f4n ng\u1eef t\u1ef1 nhi\u00ean.<\/p>\n S\u1ebd th\u1ef1c t\u1ebf h\u01a1n nhi\u1ec1u n\u1ebfu t\u00ecm hi\u1ec3u l\u1ecbch s\u1eed Machine Learning t\u1eeb nh\u1eefng th\u1ee9 c\u00f3 li\u00ean quan tr\u1ef1c ti\u1ebfp h\u01a1n v\u00e0 n\u1eb1m \u1edf \u0111\u00e2u \u0111\u00f3 xa h\u01a1n tr\u00ean d\u00f2ng th\u1eddi gian gi\u1eefa c\u00e1c d\u1ea1ng d\u1eef li\u1ec7u \u0111\u1ea7u ti\u00ean v\u00e0 nhi\u1ec1u \u1ee9ng d\u1ee5ng ng\u00e0y nay.<\/p>\n H\u1ea7u h\u1ebft m\u1ecdi ng\u01b0\u1eddi s\u1ebd ch\u1ec9 ra s\u1ef1 xu\u1ea5t hi\u1ec7n c\u1ee7a \u00fd t\u01b0\u1edfng v\u1ec1 m\u1ea1ng n\u01a1-ron nh\u01b0 m\u1ed9t \u0111i\u1ec3m kh\u1edfi \u0111\u1ea7u t\u1ef1 nhi\u00ean cho c\u00e2u chuy\u1ec7n v\u1ec1 ngu\u1ed3n g\u1ed1c c\u1ee7a m\u00e1y h\u1ecdc. V\u00ec v\u1eady, t\u1eeb th\u1eddi \u0111i\u1ec3m \u0111\u00f3, d\u00f2ng th\u1eddi gian sau \u0111\u00e2y v\u1ec1 qu\u00e1 tr\u00ecnh ti\u1ebfn h\u00f3a c\u1ee7a m\u00e1y h\u1ecdc cho \u0111\u1ebfn tr\u1ea1ng th\u00e1i hi\u1ec7n t\u1ea1i c\u1ee7a n\u00f3 b\u1eaft \u0111\u1ea7u:<\/p>\n 1943<\/strong> \u2013 \u00dd t\u01b0\u1edfng v\u1ec1 m\u1ea1ng n\u01a1-ron nh\u00e2n t\u1ea1o xu\u1ea5t ph\u00e1t t\u1eeb nghi\u00ean c\u1ee9u v\u1ec1 c\u00e1ch c\u00e1c n\u01a1-ron trong n\u00e3o ng\u01b0\u1eddi ho\u1ea1t \u0111\u1ed9ng theo ch\u1ee9c n\u0103ng \u0111\u01b0\u1ee3c m\u00f4 t\u1ea3 v\u00e0o th\u1eddi \u0111i\u1ec3m \u0111\u00f3 l\u00e0 \u201cch\u1ee7 ngh\u0129a k\u1ebft n\u1ed1i\u201d. \u0110\u00e2y l\u00e0 n\u0103m m\u00e0 nh\u00e0 sinh l\u00fd h\u1ecdc th\u1ea7n kinh Warren McCulloch v\u00e0 nh\u00e0 to\u00e1n h\u1ecdc Walter Pitts s\u1eed d\u1ee5ng c\u00e1c m\u1ea1ch \u0111i\u1ec7n \u0111\u01a1n gi\u1ea3n \u0111\u1ec3 sao ch\u00e9p h\u00e0nh vi c\u1ee7a n\u01a1-ron th\u00f4ng minh.<\/p>\n 1949<\/strong> \u2013 M\u1ed9t cu\u1ed1n s\u00e1ch c\u00f3 t\u1ef1a \u0111\u1ec1 The Organization of Behavior<\/em> \u0111\u01b0\u1ee3c xu\u1ea5t b\u1ea3n. \u0110\u00f3ng g\u00f3p c\u1ee7a n\u00f3 n\u1eb1m \u1edf \u0111\u1ec1 xu\u1ea5t r\u1eb1ng c\u00e1c \u0111\u01b0\u1eddng d\u1eabn th\u1ea7n kinh \u0111\u01b0\u1ee3c t\u0103ng c\u01b0\u1eddng qua m\u1ed7i l\u1ea7n s\u1eed d\u1ee5ng. \u0110i\u1ec1u n\u00e0y r\u1ea5t quan tr\u1ecdng \u0111\u1ec3 hi\u1ec3u v\u00e0 \u0111\u1ecbnh l\u01b0\u1ee3ng c\u00e1c qu\u00e1 tr\u00ecnh ph\u1ee9c t\u1ea1p trong n\u00e3o ng\u01b0\u1eddi.<\/p>\n 1950<\/strong> \u2013 C\u00e1c nh\u00e0 nghi\u00ean c\u1ee9u b\u1eaft \u0111\u1ea7u c\u1ed1 g\u1eafng d\u1ecbch c\u00e1c m\u1ea1ng l\u01b0\u1edbi n\u00e3o b\u1ed9 th\u00e0nh c\u00e1c h\u1ec7 th\u1ed1ng t\u00ednh to\u00e1n. Alan Turing c\u0169ng ph\u00e1t tri\u1ec3n B\u00e0i ki\u1ec3m tra Turing c\u1ee7a m\u00ecnh c\u00f9ng n\u0103m n\u00e0y, m\u1ed9t b\u00e0i ki\u1ec3m tra s\u1ebd tr\u1edf th\u00e0nh chu\u1ea9n m\u1ef1c \u0111\u1ec3 \u0111\u00e1nh gi\u00e1 m\u1ee9c \u0111\u1ed9 th\u00f4ng minh c\u1ee7a m\u00e1y m\u00f3c.<\/p>\n 1951<\/strong> \u2013 C\u1ed7 m\u00e1y \u0111\u1ea7u ti\u00ean \u0111\u01b0\u1ee3c x\u00e2y d\u1ef1ng b\u1eb1ng m\u1ea1ng n\u01a1-ron nh\u00e2n t\u1ea1o b\u1edfi Dean Edmonds v\u00e0 Marvin Minsky d\u1ef1a tr\u00ean m\u00f4 h\u00ecnh c\u1ee7a Hebb v\u00e0 g\u1ecdi l\u00e0 m\u00e1y SNARC.<\/p>\n 1952<\/strong> \u2013 Arthur Samuel g\u1ecdi nh\u1eefng quy tr\u00ecnh \u0111i\u1ec7n to\u00e1n m\u1edbi sao ch\u00e9p suy ngh\u0129 c\u1ee7a con ng\u01b0\u1eddi n\u00e0y l\u00e0: Machine Learning v\u00e0 s\u1eed d\u1ee5ng n\u00f3 \u0111\u1ec3 ph\u00e1t tri\u1ec3n m\u1ed9t ch\u01b0\u01a1ng tr\u00ecnh m\u00e1y t\u00ednh ch\u01a1i c\u1edd \u0111am.<\/p>\n 1954<\/strong> – M\u1ea1ng l\u01b0\u1edbi Hebbian \u0111\u1ea7u ti\u00ean k\u1ebft n\u1ed1i n\u1ec1n t\u1ea3ng t\u00e2m l\u00fd v\u00e0 th\u1ea7n kinh c\u1ee7a vi\u1ec7c h\u1ecdc \u0111\u00e3 \u0111\u01b0\u1ee3c tri\u1ec3n khai th\u00e0nh c\u00f4ng t\u1ea1i MIT.<\/p>\n 1957<\/strong> \u2013 Perceptron \u0111\u01b0\u1ee3c Frank Rosenblatt ph\u00e1t minh, ch\u1ee7 y\u1ebfu \u0111\u1ec3 nh\u1eadn d\u1ea1ng h\u00ecnh \u1ea3nh, b\u1eb1ng c\u00e1ch s\u1eed d\u1ee5ng m\u00f4 h\u00ecnh Hebb v\u00e0 c\u00e1c thu\u1eadt to\u00e1n Machine Learning ban \u0111\u1ea7u c\u1ee7a Samuel.<\/p>\n 1959<\/strong> \u2013 M\u1ed9t m\u1ea1ng n\u01a1-ron nh\u00e2n t\u1ea1o \u0111\u00e3 h\u1ecdc c\u00e1ch l\u00e0m cho c\u00e1c cu\u1ed9c g\u1ecdi \u0111i\u1ec7n tho\u1ea1i r\u00f5 r\u00e0ng h\u01a1n, s\u1eed d\u1ee5ng c\u00e1c m\u00f4 h\u00ecnh ADALINE v\u00e0 MADALINE c\u1ee7a Stanford. ADALINE \u0111\u01b0\u1ee3c ph\u00e1t tri\u1ec3n \u0111\u1ec3 nh\u1eadn d\u1ea1ng c\u00e1c m\u1eabu nh\u1ecb ph\u00e2n. N\u00f3 c\u00f3 th\u1ec3 d\u1ef1 \u0111o\u00e1n th\u00e0nh c\u00f4ng bit ti\u1ebfp theo trong khi \u0111\u1ecdc c\u00e1c bit ph\u00e1t tr\u1ef1c tuy\u1ebfn t\u1eeb \u0111\u01b0\u1eddng d\u00e2y \u0111i\u1ec7n tho\u1ea1i. MADALINE \u0111\u00e3 s\u1eed d\u1ee5ng b\u1ed9 l\u1ecdc th\u00edch \u1ee9ng \u0111\u1ec3 lo\u1ea1i b\u1ecf ti\u1ebfng vang tr\u00ean \u0111\u01b0\u1eddng d\u00e2y \u0111i\u1ec7n tho\u1ea1i v\u00e0 l\u00e0 m\u1ea1ng n\u01a1-ron \u0111\u1ea7u ti\u00ean \u0111\u01b0\u1ee3c s\u1eed d\u1ee5ng \u0111\u1ec3 gi\u1ea3i quy\u1ebft m\u1ed9t v\u1ea5n \u0111\u1ec1 th\u1ef1c t\u1ebf. C\u1ea3 hai v\u1eabn \u0111ang \u0111\u01b0\u1ee3c s\u1eed d\u1ee5ng cho \u0111\u1ebfn ng\u00e0y nay.<\/p>\n 1968<\/strong> \u2013 B\u1ed9 phim 2001: A Space Odyssey c\u1ee7a Stanley Kubrick \u0111\u00e3 th\u00fac \u0111\u1ea9y m\u1ea1nh m\u1ebd kh\u00e1i ni\u1ec7m AI n\u00f3i chung v\u00e0 AI c\u00f3 kh\u1ea3 n\u0103ng t\u1ef1 nh\u1eadn th\u1ee9c.<\/p>\n 1975<\/strong> \u2013 M\u1ea1ng nhi\u1ec1u l\u1edbp v\u00e0 kh\u00f4ng gi\u00e1m s\u00e1t \u0111\u1ea7u ti\u00ean \u0111\u01b0\u1ee3c ph\u00e1t tri\u1ec3n.<\/p>\n 1979<\/strong> \u2013 Xe \u0111\u1ea9y Stanford \u0111\u01b0\u1ee3c ph\u00e1t minh \u0111\u1ec3 gi\u1ea3i quy\u1ebft v\u1ea5n \u0111\u1ec1 l\u00e1i xe t\u1ef1 h\u00e0nh tr\u00ean m\u1eb7t tr\u0103ng t\u1eeb tr\u00e1i \u0111\u1ea5t. Ng\u01b0\u1eddi ph\u00e1t tri\u1ec3n xe, m\u1ed9t sinh vi\u00ean t\u1ed1t nghi\u1ec7p Stanford, \u0111\u00e3 s\u1eed d\u1ee5ng m\u00e1y \u1ea3nh v\u00e0 \u0111i\u1ec1u khi\u1ec3n t\u1eeb xa \u0111\u1ec3 \u0111i\u1ec1u khi\u1ec3n xe quanh m\u1ed9t c\u0103n ph\u00f2ng \u0111\u1ea7y ch\u01b0\u1edbng ng\u1ea1i v\u1eadt, ph\u1ea7n l\u1edbn l\u00e0 gh\u1ebf.<\/p>\n 1981<\/strong> \u2013 Kh\u00e1i ni\u1ec7m H\u1ecdc t\u1eadp d\u1ef1a tr\u00ean gi\u1ea3i th\u00edch<\/em> (EBL) \u0111\u01b0\u1ee3c Gerald Dejong gi\u1edbi thi\u1ec7u. N\u00f3 t\u01b0\u01a1ng \u0111\u01b0\u01a1ng v\u1edbi vi\u1ec7c s\u1eed d\u1ee5ng ML \u0111\u1ec3 ph\u00e2n t\u00edch d\u1eef li\u1ec7u \u0111\u00e0o t\u1ea1o \u0111\u1ec3 t\u1ef1 t\u1ea1o ra m\u1ed9t quy t\u1eafc chung nh\u1eb1m x\u00e1c \u0111\u1ecbnh v\u00e0 lo\u1ea1i b\u1ecf d\u1eef li\u1ec7u kh\u00f4ng quan tr\u1ecdng ho\u1eb7c kh\u00f4ng li\u00ean quan. H\u00e3y ngh\u0129 v\u1ec1 n\u00f3 nh\u01b0 l\u00e0 t\u1ef1 l\u00e0m s\u1ea1ch.<\/p>\n 1982<\/strong> \u2013 C\u00e1c b\u1ed9 phim l\u1ea1i th\u00fac \u0111\u1ea9y k\u1ef3 v\u1ecdng c\u1ee7a c\u00f4ng ch\u00fang v\u1ec1 ML v\u00e0 AI l\u1ea7n n\u1eefa, l\u1ea7n n\u00e0y d\u01b0\u1edbi d\u1ea1ng c\u00e1c b\u1ea3n sao trong Blade Runner. C\u00e1c nh\u00e0 khoa h\u1ecdc hi\u1ec7n \u0111ang \u0111\u01b0\u1ee3c th\u00f4ng b\u00e1o r\u1eb1ng c\u00f4ng ch\u00fang kh\u00f4ng ch\u1ec9 mong \u0111\u1ee3i ph\u1ea7n m\u1ec1m th\u00f4ng minh b\u1eaft ch\u01b0\u1edbc b\u1ed9 n\u00e3o con ng\u01b0\u1eddi, m\u00e0 c\u00f2n mong \u0111\u1ee3i c\u01a1 th\u1ec3 bao b\u1ecdc v\u00e0 huy \u0111\u1ed9ng ch\u00fang sao ch\u00e9p ch\u1eb7t ch\u1ebd c\u01a1 th\u1ec3 con ng\u01b0\u1eddi v\u1edbi si\u00eau n\u0103ng l\u1ef1c.<\/p>\n 1985<\/strong> \u2013 M\u1ed9t m\u1ea1ng l\u01b0\u1edbi th\u1ea7n kinh c\u00f3 t\u00ean NETtalk \u0111\u00e3 t\u1ef1 h\u1ecdc c\u00e1ch ph\u00e1t \u00e2m \u0111\u00fang c\u00e1c t\u1eeb m\u1edbi v\u1edbi t\u1ed1c \u0111\u1ed9 20.000 t\u1eeb m\u1edbi m\u1ed7i tu\u1ea7n. Ban \u0111\u1ea7u, n\u00f3 n\u00f3i ti\u1ebfng v\u00f4 ngh\u0129a khi c\u1ed1 g\u1eafng h\u1ecdc n\u00f3i nh\u01b0ng n\u00f3 ti\u1ebfp t\u1ee5c h\u1ecdc cho \u0111\u1ebfn khi c\u00f3 th\u1ec3 ph\u00e1t \u00e2m c\u00e1c t\u1eeb m\u1edbi g\u1ea7n nh\u01b0 kh\u00f4ng t\u1ed1n ch\u00fat c\u00f4ng s\u1ee9c n\u00e0o.<\/p>\n 1997<\/strong> \u2013 C\u1ed7 m\u00e1y Deep Blue c\u1ee7a IBM \u0111\u00e3 \u0111\u00e1nh b\u1ea1i \u0111\u1ea1i ki\u1ec7n t\u01b0\u1edbng c\u1edd vua Garry Kasparov.<\/p>\n 1999<\/strong> \u2013 Tr\u1ea1m l\u00e0m vi\u1ec7c th\u00f4ng minh CAD c\u1ee7a \u0110\u1ea1i h\u1ecdc Chicago \u0111\u00e3 ph\u00e2n t\u00edch 22.000 \u1ea3nh ch\u1ee5p nh\u0169 \u1ea3nh v\u00e0 ch\u1ee9ng minh \u0111\u1ed9 ch\u00ednh x\u00e1c cao h\u01a1n 52% trong ch\u1ea9n \u0111o\u00e1n ung th\u01b0 so v\u1edbi c\u00e1c b\u00e1c s\u0129 X-quang.<\/p>\n 2006<\/strong> \u2013 Gregory Hinton \u0111\u1ed5i t\u00ean nghi\u00ean c\u1ee9u m\u1ea1ng n\u01a1-ron th\u00e0nh \u201ch\u1ecdc s\u00e2u\u201d. Ng\u00e0y nay, c\u00e1c c\u00f4ng ty Internet l\u1edbn s\u1eed d\u1ee5ng c\u00e1c k\u1ef9 thu\u1eadt c\u1ee7a \u00f4ng \u0111\u1ec3 c\u1ea3i thi\u1ec7n c\u00e1c c\u00f4ng c\u1ee5 nh\u01b0 g\u1eafn th\u1ebb h\u00ecnh \u1ea3nh v\u00e0 nh\u1eadn d\u1ea1ng gi\u1ecdng n\u00f3i.<\/p>\n 2009<\/strong> – Netflix t\u00ecm c\u00e1ch c\u1ea3i thi\u1ec7n c\u00e1c \u0111\u1ec1 xu\u1ea5t phim v\u00e0 ch\u01b0\u01a1ng tr\u00ecnh truy\u1ec1n h\u00ecnh cho kh\u00e1ch h\u00e0ng b\u1eb1ng c\u00e1ch trao gi\u1ea3i th\u01b0\u1edfng tr\u1ecb gi\u00e1 1 tri\u1ec7u \u0111\u00f4 la cho b\u1ea5t k\u1ef3 ai c\u00f3 th\u1ec3 v\u01b0\u1ee3t qua thu\u1eadt to\u00e1n c\u1ee7a h\u1ecd trong x\u1ebfp h\u1ea1ng phim c\u1ee7a ng\u01b0\u1eddi ti\u00eau d\u00f9ng. Nh\u00f3m c\u00e1c nh\u00e0 khoa h\u1ecdc AT&T c\u1ee7a BellKor \u0111\u00e3 mang v\u1ec1 gi\u1ea3i th\u01b0\u1edfng l\u1edbn, nh\u01b0ng ch\u1ec9 h\u01a1n m\u1ed9t ch\u00fat. H\u1ecd ch\u1ec9 h\u01a1n nh\u1eefng ng\u01b0\u1eddi chi\u1ebfn th\u1eafng \u1edf v\u1ecb tr\u00ed th\u1ee9 hai v\u00e0i ph\u00fat.<\/p>\n 2010<\/strong> \u2013 Kinect c\u1ee7a Microsoft theo d\u00f5i 20 \u0111\u1eb7c \u0111i\u1ec3m c\u1ee7a con ng\u01b0\u1eddi v\u1edbi t\u1ed1c \u0111\u1ed9 30 l\u1ea7n m\u1ed7i gi\u00e2y, cho ph\u00e9p tr\u00f2 ch\u01a1i v\u00e0 m\u00e1y t\u00ednh \u0111\u1ea7u ti\u00ean \u0111i\u1ec1u khi\u1ec3n th\u00f4ng qua chuy\u1ec3n \u0111\u1ed9ng v\u00e0 c\u1eed ch\u1ec9.<\/p>\n 2011<\/strong> \u2013 Watson c\u1ee7a IBM \u0111\u00e3 th\u1eafng tr\u00f2 ch\u01a1i Jeopardy b\u1eb1ng c\u00e1ch \u0111\u00e1nh b\u1ea1i hai \u0111\u1ed1i th\u1ee7 l\u00e0 con ng\u01b0\u1eddi. N\u00f3 h\u01a1i v\u1ea5p ng\u00e3 m\u1ed9t ch\u00fat nh\u01b0ng v\u1eabn th\u1eafng.<\/p>\n 2012<\/strong> \u2013 M\u1ed9t trong nh\u1eefng m\u1ea1ng n\u01a1-ron c\u1ee7a Google \u0111\u00e3 t\u1ef1 h\u1ecdc c\u00e1ch nh\u1eadn d\u1ea1ng m\u00e8o v\u00e0 ng\u01b0\u1eddi trong c\u00e1c video tr\u00ean YouTube. N\u00f3 kh\u00f4ng ch\u00ednh x\u00e1c 100 ph\u1ea7n tr\u0103m nh\u01b0ng \u0111i\u1ec3m s\u1ed1 v\u1eabn r\u1ea5t ch\u00ednh x\u00e1c \u0111\u1ed1i v\u1edbi m\u1ed9t c\u1ed7 m\u00e1y t\u1ef1 h\u1ecdc. N\u00f3 ph\u00e1t hi\u1ec7n m\u00e8o ch\u00ednh x\u00e1c 74,8 ph\u1ea7n tr\u0103m th\u1eddi gian v\u00e0 khu\u00f4n m\u1eb7t ng\u01b0\u1eddi v\u1edbi \u0111\u1ed9 ch\u00ednh x\u00e1c 81,47 ph\u1ea7n tr\u0103m.<\/p>\n 2013<\/strong> \u2013 Boston Dynamics \u0111\u00e3 t\u1ea1o ra Atlas, m\u1ed9t robot h\u00ecnh ng\u01b0\u1eddi. Tr\u01b0\u1edbc \u0111\u00f3, c\u00f9ng c\u00f4ng ty n\u00e0y \u0111\u00e3 t\u1ea1o ra BigDog, m\u1ed9t robot b\u1ed1n ch\u00e2n gi\u1ed1ng ch\u00f3.<\/p>\n 2014<\/strong> \u2013 Eugene Goostman \u0111\u00e3 th\u00e0nh c\u00f4ng khi t\u1ef1 nh\u1eadn m\u00ecnh l\u00e0 m\u1ed9t thi\u1ebfu ni\u00ean ng\u01b0\u1eddi Ukraine tr\u01b0\u1edbc 33 ph\u1ea7n tr\u0103m gi\u00e1m kh\u1ea3o l\u00e0 con ng\u01b0\u1eddi, tr\u1edf th\u00e0nh c\u1ed7 m\u00e1y th\u00f4ng minh \u0111\u1ea7u ti\u00ean v\u01b0\u1ee3t qua b\u00e0i ki\u1ec3m tra Turing (kho\u1ea3ng 60 n\u0103m sau khi Alan Turing qua \u0111\u1eddi). Goostman l\u00e0 m\u1ed9t chatbot.<\/p>\n \u0110\u00e2y l\u00e0 n\u0103m c\u00f4ng ngh\u1ec7 s\u1ee9c kh\u1ecfe b\u1eaft \u0111\u1ea7u s\u1eed d\u1ee5ng m\u00e1y h\u1ecdc m\u1ed9t c\u00e1ch nghi\u00eam t\u00fac \u0111\u1ec3 c\u1ea3i thi\u1ec7n k\u1ebft qu\u1ea3 c\u1ee7a b\u1ec7nh nh\u00e2n. M\u1ed9t trong nh\u1eefng \u1ee9ng d\u1ee5ng \u0111\u1ea7u ti\u00ean d\u1ef1 \u0111o\u00e1n th\u1eddi gian ch\u1edd ER t\u1eeb m\u00f4 ph\u1ecfng s\u1ef1 ki\u1ec7n d\u1ef1a tr\u00ean c\u00e1c \u0111i\u1ec3m d\u1eef li\u1ec7u nh\u01b0 m\u1ee9c \u0111\u1ed9 nh\u00e2n s\u1ef1, ti\u1ec1n s\u1eed b\u1ec7nh t\u1eadt, t\u00ecnh tr\u1ea1ng b\u1ec7nh t\u1eadt (v\u00ed d\u1ee5, th\u1eddi k\u1ef3 b\u00f9ng ph\u00e1t nh\u01b0 m\u00f9a c\u00fam ho\u1eb7c m\u1ed9t ng\u00e0y h\u00e8 b\u00ecnh th\u01b0\u1eddng kh\u00f4ng c\u00f3 b\u00f9ng ph\u00e1t) v\u00e0 c\u00e1ch b\u1ed1 tr\u00ed b\u1ec7nh vi\u1ec7n.<\/p>\n \u0110\u00e2y c\u0169ng l\u00e0 n\u0103m Facebook ph\u00e1t tri\u1ec3n DeepFace \u0111\u1ec3 nh\u1eadn d\u1ea1ng khu\u00f4n m\u1eb7t.<\/p>\n 2015<\/strong> \u2013 AlphaGo c\u1ee7a Google \u0111\u00e3 gi\u00e0nh chi\u1ebfn th\u1eafng trong tr\u00f2 ch\u01a1i c\u1edd b\u00e0n kh\u00f3 nh\u1ea5t th\u1ebf gi\u1edbi c\u00f3 t\u00ean l\u00e0 C\u1edd v\u00e2y. \u0110i\u1ec1u n\u00e0y c\u00f3 ngh\u0129a l\u00e0 m\u00e1y m\u00f3c \u0111\u00e3 \u0111\u00e1nh b\u1ea1i con ng\u01b0\u1eddi \u1edf m\u1ecdi tr\u00f2 ch\u01a1i c\u1edd b\u00e0n. Vi\u1ec7c \u0111\u01b0a m\u00e1y m\u00f3c \u0111\u1ea5u v\u1edbi con ng\u01b0\u1eddi trong c\u00e1c tr\u00f2 ch\u01a1i kh\u00f4ng c\u00f2n l\u00e0 \u0111i\u1ec1u m\u1edbi l\u1ea1 (hay th\u1ec3 thao) n\u1eefa.<\/p>\n \u0110\u00e2y c\u0169ng l\u00e0 n\u0103m Amazon ra m\u1eaft n\u1ec1n t\u1ea3ng m\u00e1y h\u1ecdc c\u1ee7a ri\u00eang m\u00ecnh v\u00e0 Microsoft \u0111\u00e3 t\u1ea1o ra B\u1ed9 c\u00f4ng c\u1ee5 m\u00e1y h\u1ecdc ph\u00e2n t\u00e1n.<\/p>\n V\u00e0 \u0111\u00f3 l\u00e0 n\u0103m Tesla ra m\u1eaft Autopilot, m\u1ed9t t\u00ednh n\u0103ng b\u00e1n t\u1ef1 \u0111\u1ed9ng cho ch\u1ebf \u0111\u1ed9 l\u00e1i r\u1ea3nh tay tr\u00ean xe \u00f4 t\u00f4 ti\u00eau d\u00f9ng. Autopilot \u0111\u01b0\u1ee3c cung c\u1ea5p d\u01b0\u1edbi d\u1ea1ng b\u1ea3n c\u1eadp nh\u1eadt ph\u1ea7n m\u1ec1m duy nh\u1ea5t cho ch\u1ee7 s\u1edf h\u1eefu Model S ch\u1ec9 sau m\u1ed9t \u0111\u00eam.<\/p>\n 2016<\/strong> \u2013 HAL ra \u0111\u1eddi. Th\u1ef1c ra th\u00ec kh\u00f4ng h\u1eb3n v\u1eady. Nh\u01b0ng m\u1ed9t h\u1ec7 th\u1ed1ng AI c\u00f3 t\u00ean l\u00e0 LipNet \u0111\u00e3 \u0111\u1ecdc \u0111\u01b0\u1ee3c kh\u1ea9u h\u00ecnh mi\u1ec7ng v\u1edbi \u0111\u1ed9 ch\u00ednh x\u00e1c 93,4 ph\u1ea7n tr\u0103m, ngang b\u1eb1ng v\u1edbi c\u1ed7 m\u00e1y h\u01b0 c\u1ea5u c\u00f3 t\u00ean l\u00e0 HAL trong b\u1ed9 phim n\u1ed5i ti\u1ebfng n\u0103m 1968, 2001: A Space Odyssey.<\/p>\n \u0110\u00e2y c\u0169ng l\u00e0 n\u0103m m\u00e0 x\u1eed l\u00fd ng\u00f4n ng\u1eef t\u1ef1 nhi\u00ean ra m\u1eaft trong th\u1ebf gi\u1edbi th\u1ef1c. M\u1ed9t nh\u00e0 b\u00e1n l\u1ebb c\u00f3 t\u00ean The North Face \u0111\u00e3 s\u1eed d\u1ee5ng x\u1eed l\u00fd ng\u00f4n ng\u1eef t\u1ef1 nhi\u00ean Watson c\u1ee7a IBM trong chatbot mua s\u1eafm c\u00e1 nh\u00e2n tr\u00ean \u1ee9ng d\u1ee5ng di \u0111\u1ed9ng c\u1ee7a m\u00ecnh.<\/p>\n \u0110\u00e2y c\u0169ng l\u00e0 n\u0103m Google Assistant, m\u1ed9t tr\u1ee3 l\u00fd \u1ea3o h\u1ed7 tr\u1ee3 AI, ra \u0111\u1eddi.<\/p>\n 2017<\/strong> \u2013 Nh\u00f3m Jigsaw c\u1ee7a Alphabet \u0111\u00e3 x\u00e2y d\u1ef1ng m\u1ed9t h\u1ec7 th\u1ed1ng ML \u0111\u1ec3 t\u1ef1 \u0111\u1ed9ng h\u00f3a vi\u1ec7c b\u1eaft gi\u1eef nh\u1eefng k\u1ebb ph\u00e1 ho\u1ea1i cho c\u00e1c c\u00f4ng ty kh\u00f4ng c\u00f3 \u0111\u1ee7 ngu\u1ed3n l\u1ef1c ho\u1eb7c \u00fd ch\u00ed \u0111\u1ec3 ki\u1ec3m duy\u1ec7t c\u00e1c b\u00ecnh lu\u1eadn tr\u00ean trang web.<\/p>\n 2019<\/strong> \u2013 Google AI \u0111\u00e3 gi\u00e0nh chi\u1ebfn th\u1eafng trong vi\u1ec7c ch\u1ea9n \u0111o\u00e1n ch\u00ednh x\u00e1c b\u1ec7nh ung th\u01b0 ph\u1ed5i.<\/p>\n 2020<\/strong> \u2013 Machine Learning, h\u1ecdc s\u00e2u v\u00e0 AI \u0111\u00e3 \u0111\u01b0\u1ee3c so\u1ea1n th\u1ea3o v\u00e0 \u0111\u01b0a ra tuy\u1ebfn \u0111\u1ea7u trong cu\u1ed9c chi\u1ebfn ch\u1ed1ng l\u1ea1i \u0111\u1ea1i d\u1ecbch COVID-19.<\/p>\n 2021<\/strong> – M\u1ed9t con t\u00e0u kh\u00f4ng ng\u01b0\u1eddi l\u00e1i, \u0111\u01b0\u1ee3c \u0111i\u1ec1u khi\u1ec3n b\u1eb1ng AI c\u00f3 t\u00ean l\u00e0 D\u1ef1 \u00e1n Mayflower s\u1ebd gi\u01b0\u01a1ng bu\u1ed3m b\u0103ng qua \u0110\u1ea1i T\u00e2y D\u01b0\u01a1ng.<\/p>\n Ng\u00e0y nay, c\u00f3 nhi\u1ec1u c\u00f4ng c\u1ee5 v\u00e0 khu\u00f4n kh\u1ed5 m\u00e3 ngu\u1ed3n m\u1edf c\u00f3 s\u1eb5n m\u00e0 b\u1ea1n c\u00f3 th\u1ec3 s\u1eed d\u1ee5ng \u0111\u1ec3 cung c\u1ea5p n\u0103ng l\u01b0\u1ee3ng cho c\u00e1c \u1ee9ng d\u1ee5ng Machine Learning. PyTorch l\u00e0 m\u1ed9t khu\u00f4n kh\u1ed5 Machine Learning d\u1ef1a tr\u00ean Python s\u1eed d\u1ee5ng CPU v\u00e0 GPU \u0111\u1ec3 t\u0103ng t\u1ed1c hi\u1ec7u su\u1ea5t x\u1eed l\u00fd c\u1ee7a n\u00f3. B\u1ea1n c\u00f3 th\u1ec3 c\u00e0i \u0111\u1eb7t PyTorch tr\u00ean m\u00e1y ch\u1ee7 Linode Ubuntu 20.04<\/a> v\u00e0 s\u1eed d\u1ee5ng GPU<\/a> ho\u1eb7c c\u00e1c phi\u00ean b\u1ea3n t\u00ednh to\u00e1n CPU chuy\u00ean d\u1ee5ng<\/a> .<\/p>\n","protected":false},"excerpt":{"rendered":" Machine Learning (ML) l\u00e0 m\u1ed9t t\u1eadp h\u1ee3p con c\u1ee7a tr\u00ed tu\u1ec7 nh\u00e2n t\u1ea1o (AI) v\u00e0 n\u00f3 \u0111ang nhanh ch\u00f3ng tr\u1edf th\u00e0nh x\u01b0\u01a1ng s\u1ed1ng c\u1ee7a h\u1ea7u h\u1ebft c\u00e1c ph\u1ea7n m\u1ec1m hi\u1ec7n nay. N\u00f3 t\u1ed3n t\u1ea1i d\u01b0\u1edbi nhi\u1ec1u h\u00ecnh th\u1ee9c kh\u00e1c nhau, t\u1eeb chatbot tr\u00ean c\u00e1c trang web v\u00e0 tr\u1ee3 l\u00fd k\u1ef9 thu\u1eadt s\u1ed1 nh\u01b0 Siri v\u00e0<\/p>\n","protected":false},"author":1,"featured_media":35515,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[101],"tags":[],"class_list":["post-34880","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-big-data"],"_links":{"self":[{"href":"https:\/\/jupitek.maudemo.vip\/index.php\/wp-json\/wp\/v2\/posts\/34880","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/jupitek.maudemo.vip\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/jupitek.maudemo.vip\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/jupitek.maudemo.vip\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/jupitek.maudemo.vip\/index.php\/wp-json\/wp\/v2\/comments?post=34880"}],"version-history":[{"count":0,"href":"https:\/\/jupitek.maudemo.vip\/index.php\/wp-json\/wp\/v2\/posts\/34880\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/jupitek.maudemo.vip\/index.php\/wp-json\/wp\/v2\/media\/35515"}],"wp:attachment":[{"href":"https:\/\/jupitek.maudemo.vip\/index.php\/wp-json\/wp\/v2\/media?parent=34880"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/jupitek.maudemo.vip\/index.php\/wp-json\/wp\/v2\/categories?post=34880"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/jupitek.maudemo.vip\/index.php\/wp-json\/wp\/v2\/tags?post=34880"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}Ai l\u00e0 ng\u01b0\u1eddi ph\u00e1t minh ra m\u00e1y h\u1ecdc?<\/a><\/h3>\n
D\u00f2ng th\u1eddi gian v\u1ec1 s\u1ef1 ph\u00e1t tri\u1ec3n c\u1ee7a m\u00e1y h\u1ecdc<\/a><\/h2>\n
Ph\u1ea7n k\u1ebft lu\u1eadn<\/a><\/h2>\n