{"id":2222,"date":"2013-07-05T12:17:20","date_gmt":"2013-07-05T05:17:20","guid":{"rendered":"http:\/\/science-technology.vn\/?p=2222"},"modified":"2013-07-05T12:17:20","modified_gmt":"2013-07-05T05:17:20","slug":"hoc-cua-may","status":"publish","type":"post","link":"https:\/\/science-technology.vn\/?p=2222","title":{"rendered":"H\u1ecdc c\u1ee7a m\u00e1y"},"content":{"rendered":"

\u201cH\u1ecdc c\u1ee7a m\u00e1y\u201d\u00a0l\u00e0 l\u0129nh v\u1ef1c khoa h\u1ecdc li\u00ean quan t\u1edbi thi\u1ebft k\u1ebf v\u00e0 ph\u00e1t tri\u1ec3n c\u00e1c thu\u1eadt to\u00e1n cho ph\u00e9p m\u00e1y t\u00ednh h\u1ecdc v\u00e0 \u0111\u00e1p \u1ee9ng d\u1ef1a tr\u00ean c\u01a1 s\u1edf d\u1eef li\u1ec7u c\u1ee7a n\u00f3. M\u00e1y t\u00ednh c\u00f3 th\u1ec3 t\u1ef1 n\u00f3 h\u1ecdc d\u1ef1a tr\u00ean c\u00e1c v\u00ed d\u1ee5 (d\u1eef li\u1ec7u) \u0111\u1ec3 n\u1eafm b\u1eaft m\u1ed9t s\u1ed1 \u0111i\u1ec1u b\u1eb1ng vi\u1ec7c d\u00f9ng ph\u1ea7n m\u1ec1m ph\u1ee9c t\u1ea1p d\u1ef1a tr\u00ean ph\u00e2n b\u1ed1 x\u00e1c su\u1ea5t. M\u1ed7i l\u00fac n\u00f3 ph\u1ea1m sai l\u1ea7m, n\u00f3 h\u1ecdc kh\u00f4ng l\u00e0m l\u1ea1i \u0111i\u1ec1u \u0111\u00f3 l\u1ea7n n\u1eefa cho n\u00ean qua th\u1eddi gian h\u1ecdc, n\u00f3 c\u00f3 th\u1ec3 \u0111\u00e1p \u1ee9ng t\u01b0\u01a1ng \u1ee9ng v\u1edbi h\u00ecnh m\u1eabu t\u01b0\u01a1ng t\u1ef1 nh\u01b0 h\u00e0nh vi con ng\u01b0\u1eddi.<\/span><\/p>\n

Y\u1ebfu t\u1ed1 then ch\u1ed1t c\u1ee7a nghi\u00ean c\u1ee9u vi\u1ec7c h\u1ecdc c\u1ee7a m\u00e1y l\u00e0 ph\u00e1t tri\u1ec3n c\u00e1c thu\u1eadt to\u00e1n ph\u1ea7n m\u1ec1m t\u1ef1 \u0111\u1ed9ng ho\u00e1 nh\u1eadn d\u1ea1ng c\u00e1c h\u00ecnh m\u1eabu ph\u1ee9c t\u1ea1p v\u00e0 ra quy\u1ebft \u0111\u1ecbnh th\u00f4ng minh d\u1ef1a tr\u00ean d\u1eef li\u1ec7u qu\u00e1 kh\u1ee9. Ch\u1eb3ng h\u1ea1n, m\u1ed9t ch\u01b0\u01a1ng tr\u00ecnh m\u00e1y t\u00ednh \u0111\u01b0\u1ee3c n\u00f3i l\u00e0 h\u1ecdc t\u1eeb kinh nghi\u1ec7m E \u0111\u1ed1i v\u1edbi m\u1ed9t l\u1edbp nhi\u1ec7m v\u1ee5 T n\u00e0o \u0111\u00f3 v\u00e0 \u0111o hi\u1ec7u n\u0103ng P n\u1ebfu hi\u1ec7u n\u0103ng \u1edf c\u00e1c nhi\u1ec7m v\u1ee5 trong T, \u0111\u01b0\u1ee3c \u0111o b\u1edfi P, c\u1ea3i thi\u1ec7n b\u1eb1ng kinh nghi\u1ec7m E.<\/p>\n

V\u00e0i th\u00e1ng tr\u01b0\u1edbc \u0111\u00e2y, m\u1ed9t m\u00e1y t\u00ednh h\u1ecdc m\u00e1y c\u00f3 t\u00ean Watson \u0111\u00e3 nh\u1edb tr\u00ean 200 tri\u1ec7u trang d\u1eef li\u1ec7u \u0111\u1ec3 cho c\u00e2u tr\u1ea3 l\u1eddi \u0111\u00fang \u0111\u1eafn trong tr\u00f2 ch\u01a1i \u201cJeopardy-L\u00e2m nguy\u201d v\u00e0 \u0111\u00e3 \u0111\u00e1nh b\u1ea1i ng\u01b0\u1eddi ch\u01a1i tr\u00f2 \u0111\u1ed1 ch\u1eef gi\u1ecfi nh\u1ea5t th\u1ebf gi\u1edbi. M\u00e1y t\u00ednh n\u00e0y \u0111\u01b0\u1ee3c IBM x\u00e2y d\u1ef1ng c\u00f3 tr\u00ean 2,500 l\u00f5i b\u1ed9 x\u1eed l\u00ed song song, t\u1eebng l\u00f5i c\u00f3 th\u1ec3 th\u1ef1c hi\u1ec7n t\u1edbi 33 t\u1ec9 ph\u00e9p to\u00e1n trong m\u1ed9t gi\u00e2y. N\u00f3 c\u00f3 v\u00e0i tri\u1ec7u m\u00e3 ph\u1ea7n m\u1ec1m v\u00e0 m\u1ea5t h\u01a1n n\u0103m n\u0103m l\u1eadp tr\u00ecnh t\u1ea1i ti\u1ec7n nghi c\u1ee7a Carnegie Mellon v\u00e0 IBM.<\/p>\n

V\u00e0i n\u0103m tr\u01b0\u1edbc, phi\u00ean b\u1ea3n tr\u01b0\u1edbc \u0111\u00e2y c\u1ee7a n\u00f3 c\u00f3 t\u00ean l\u00e0 Xanh L\u1edbn “Big Blue” \u0111\u00e3 h\u1ecdc m\u1ecdi n\u01b0\u1edbc \u0111i c\u00f3 th\u1ec3 trong c\u1edd Vua v\u00e0 \u0111\u00e3 \u0111\u00e1nh b\u1ea1i k\u00ec th\u1ee7 Garry Kasparov, v\u00f4 \u0111\u1ecbch th\u1ebf gi\u1edbi. K\u1ec3 t\u1eeb \u0111\u00f3, \u201cBig Blue\u201d \u0111\u00e3 \u0111\u00e1nh b\u1ea1i m\u1ecdi ng\u01b0\u1eddi ch\u01a1i c\u1edd Vua trong v\u00e0i gi\u00e2y, v\u00ec n\u00f3 c\u00f3 th\u1ec3 d\u1ef1 \u0111o\u00e1n m\u1ecdi n\u01b0\u1edbc \u0111i c\u1ee7a b\u1ea1n. C\u1edd Vua l\u00e0 tr\u00f2 ch\u01a1i chi\u1ebfn l\u01b0\u1ee3c v\u00e0 t\u00ednh to\u00e1n cho n\u00ean c\u00f3 th\u1ec3 vi\u1ebft ch\u01b0\u01a1ng tr\u00ecnh ph\u1ea7n m\u1ec1m cho n\u00f3. Tuy nhi\u00ean, tr\u1ea3 l\u1eddi nh\u1eefng c\u00e2u h\u1ecfi \u0111\u01b0\u1ee3c l\u1ef1a ch\u1ecdn ng\u1eabu nhi\u00ean l\u00e0 th\u00e1ch th\u1ee9c kh\u00e1c.<\/p>\n

Trong th\u00e1ch th\u1ee9c n\u00e0y, Watson s\u1ebd ph\u1ea3i h\u1ecdc m\u1ecdi th\u1ee9 c\u00f3 th\u1ec3 \u0111\u1ec3 cho n\u00f3 c\u00f3 th\u1ec3 tr\u1ea3 l\u1eddi \u0111\u01b0\u1ee3c nh\u1eefng c\u00e2u h\u1ecfi m\u00e0 ng\u01b0\u1eddi th\u01b0\u1eddng c\u00f3 th\u1ec3 h\u1ecfi b\u1eb1ng vi\u1ec7c d\u00f9ng ng\u00f4n ng\u1eef t\u1ef1 nhi\u00ean nh\u01b0 ti\u1ebfng Anh. Ch\u1eb3ng h\u1ea1n: \u201cPh\u1ed1 X \u1edf New York l\u00e0 \u1edf \u0111\u00e2u?\u201d hay \u201cTh\u1ee7 \u0111\u00f4 c\u1ee7a Uganda l\u00e0 \u1edf \u0111\u00e2u.\u201d N\u00f3 c\u00f3 th\u1ec3 tr\u1ea3 l\u1eddi c\u00e1c c\u00e2u h\u1ecfi m\u01a1 h\u1ed3 nh\u01b0 \u201cTh\u1eeba s\u1ed1 Rh l\u00e0 g\u00ec\u201d hay \u201cS\u00e1ch n\u00e0o c\u00f3 ng\u01b0\u1eddi \u0111\u00e0n b\u00e0 c\u00f3 t\u00ean Scarlett ng\u01b0\u1eddi l\u1ea5y m\u1ed9t ng\u01b0\u1eddi c\u00f3 t\u00ean l\u00e0 Butler\u201d (\u0110\u00e1p: Cu\u1ed1n theo chi\u1ec1u gi\u00f3) hay n\u00f3 c\u00f3 th\u1ec3 tr\u1ea3 l\u1eddi: \u201cC\u1ea7u th\u1ee7 b\u00f3ng \u0111\u00e1 c\u00f3 t\u00ean Pel\u00e9 \u0111\u01b0\u1ee3c sinh ra \u1edf th\u00e0nh ph\u1ed1 n\u00e0o?\u201d M\u1ecdi ng\u01b0\u1eddi th\u1eadm ch\u00ed c\u00f3 th\u1ec3 h\u1ecfi l\u1eddi b\u00e0i h\u00e1t \u0111\u01b0\u1ee3c \u01b0a chu\u1ed9ng c\u1ee7a nh\u00f3m Beatles cho t\u1edbi c\u00e1c n\u1ed1t c\u1ee7a b\u1ea3n giao h\u01b0\u1edfng nh\u1ea1c c\u1ed5 \u0111i\u1ec3n n\u00e0o \u0111\u00f3.\u201d<\/p>\n

Tr\u1ea3 l\u1eddi c\u00e2u h\u1ecfi (QA) \u0111\u00e3 t\u1eebng l\u00e0 m\u01a1 \u01b0\u1edbc c\u1ee7a l\u0129nh v\u1ef1c Tr\u00ed tu\u1ec7 nh\u00e2n t\u1ea1o (AI). X\u00e2y d\u1ef1ng ch\u01b0\u01a1ng tr\u00ecnh cho n\u00f3 l\u00e0 kh\u00f3 kh\u0103n h\u01a1n nhi\u1ec1u so v\u1edbi c\u1edd Vua. N\u00f3 \u0111i xa v\u00e0 s\u00e2u h\u01a1n \u0111i\u1ec1u \u0111\u1ed9ng c\u01a1 t\u00ecm nh\u01b0 Google l\u00e0m khi ki\u1ec3m c\u01a1 s\u1edf d\u1eef li\u1ec7u c\u1ee7a n\u00f3 v\u1ec1 c\u00e1c t\u1eeb kho\u00e1. Ch\u1eb3ng h\u1ea1n: Google s\u1ebd cho b\u1ea1n 300,000 trang s\u00e1nh \u0111\u00fang v\u1edbi vi\u1ec7c t\u00ecm c\u00e1c t\u1eeb \u201cGreyhound\u201d v\u00e0 \u201cAfrican country,\u201d v\u1edbi \u0111i\u1ec1u \u0111\u00f3 r\u1ed3i b\u1ea1n c\u00f3 th\u1ec3 ph\u1ea3i t\u00ecm th\u00eam trong ch\u00fang \u0111\u1ec3 ra \u0111i\u1ec1u b\u1ea1n c\u1ea7n. Nh\u01b0ng Watson c\u00f3 th\u1ec3 n\u00f3i cho b\u1ea1n trong kh\u00f4ng \u0111\u1ea7y m\u1ed9t gi\u00e2y r\u1eb1ng hai t\u1eeb \u201cGreyhound\u201d v\u00e0 \u201cAfrican country\u201d c\u00f3 li\u00ean quan t\u1edbi m\u1ed9t n\u01b0\u1edbc c\u00f3 t\u00ean l\u00e0 Ai C\u1eadp. (Greyhound l\u00e0 m\u1ed9t ki\u1ec3u ch\u00f3 c\u00f3 ngu\u1ed3n g\u1ed1c t\u1eeb Ai C\u1eadp).<\/p>\n

Khi I.B.M. v\u00e0 t\u1ed5 c\u00e1c nh\u00e0 nghi\u00ean c\u1ee9u CMU b\u1eaft \u0111\u1ea7u c\u00f4ng vi\u1ec7c c\u1ee7a h\u1ecd v\u00e0o n\u0103m 2006, Watson c\u00f3 th\u1ec3 tr\u1ea3 l\u1eddi ch\u1ec9 15 ph\u1ea7n tr\u0103m c\u00e1c c\u00e2u h\u1ecfi. N\u00f3 ti\u1ebfp t\u1ee5c h\u1ecdc t\u1eeb m\u1ecdi s\u00e1ch trong th\u01b0 vi\u1ec7n qu\u1ed1c h\u1ed9i M\u0129, \u0111\u1ecdc m\u1ecdi s\u00e1ch t\u1eeb c\u00e1c th\u01b0 vi\u1ec7n \u1edf ch\u00e2u \u00c2u, m\u1ecdi cu\u1ed1n b\u00e1ch khoa to\u00e0n th\u01b0, t\u1eeb \u0111i\u1ec3n, t\u1eeb \u0111\u1ed3ng ngh\u0129a, c\u01a1 s\u1edf d\u1eef li\u1ec7u, c\u00e1c ph\u00e2n lo\u1ea1i, Kinh Th\u00e1nh, k\u1ecbch \u0111o\u1ea1n phim, ti\u1ec3u thuy\u1ebft v\u00e0 k\u1ecbch. M\u1ecdi l\u00fac, n\u00f3 tr\u1ea3 l\u1eddi sai, n\u00f3 nh\u1edb v\u00e0 qua th\u1eddi gian qua suy di\u1ec5n l\u1eadp lu\u1eadn, n\u00f3 h\u1ecdc c\u00e2u tr\u1ea3 l\u1eddi \u0111\u00fang. (\u0110\u00e2y l\u00e0 \u0111i\u1ec1u tr\u00ed tu\u1ec7 nh\u00e2n t\u1ea1o t\u1ea5t c\u1ea3 l\u00e0 g\u00ec.) \u0110\u1ec3 hi\u1ec3u c\u00e2u h\u1ecfi, m\u00e1y ph\u1ea3i h\u1ecdc v\u00e0 ph\u00e2n t\u00edch ng\u00f4n ng\u1eef t\u1ef1 nhi\u00ean (ng\u00f4n ng\u1eef m\u00e0 con ng\u01b0\u1eddi s\u1eed d\u1ee5ng), \u0111\u00e1nh gi\u00e1 ngu\u1ed3n, \u0111\u1ec1 \u0111\u1ea1t c\u00e1c gi\u1ea3 thuy\u1ebft, ki\u1ec3m c\u01a1 s\u1edf d\u1eef li\u1ec7u, thu th\u1eadp nhi\u1ec1u th\u00f4ng tin, g\u1ed9p c\u00e1c k\u1ebft qu\u1ea3, v\u00e0 x\u1ebfp h\u1ea1ng c\u00e2u tr\u1ea3 l\u1eddi t\u1ed1t nh\u1ea5t m\u00e0 c\u00f3 y\u1ebfu t\u1ed1 t\u1ef1 tin th\u1ed1ng k\u00ea cao nh\u1ea5t \u0111\u1ec3 t\u00ecm ra c\u00e2u tr\u1ea3 l\u1eddi th\u00edch h\u1ee3p nh\u1ea5t.<\/p>\n

T\u1ea5t nhi\u00ean, c\u00e2u tr\u1ea3 l\u1eddi \u0111\u00fang ch\u1ec9 l\u00e0 m\u1ed9t \u0111i\u1ec1u c\u00f3 t\u00ednh th\u1ed1ng k\u00ea, v\u1ea5n \u0111\u1ec1 c\u1ee7a th\u01b0\u1eddng xuy\u00ean v\u00e0 c\u00f3 th\u1ec3. Trong v\u00e0i gi\u00e2y m\u00e1y x\u1eed l\u00ed v\u00f4 t\u1eadn kh\u1ea3 n\u0103ng d\u1ef1a tr\u00ean h\u01a1n 100 thu\u1eadt to\u00e1n h\u1ed9i t\u1ee5 v\u00e0o gi\u1ea3i ph\u00e1p m\u00e0 n\u00f3 c\u00f3 th\u1ec3 cung c\u1ea5p ra c\u00e2u tr\u1ea3 l\u1eddi. Watson c\u00f3 th\u1ec3 tr\u1ea3 l\u1eddi \u0111\u01b0\u1ee3c m\u1ecdi c\u00e2u h\u1ecfi kh\u00f4ng? V\u1eabn c\u00f2n ch\u01b0a \u0111\u00e2u. T\u1eeb c\u1ee7a con ng\u01b0\u1eddi l\u00e0 r\u1ea5t kh\u00f3, m\u1ed9t s\u1ed1 c\u00e2u c\u00f3 th\u1ec3 c\u00f3 nhi\u1ec1u ngh\u0129a v\u00e0 \u0111i\u1ec1u \u0111\u00f3 g\u00e2y l\u1eabn l\u1ed9n cho m\u00e1y. Nh\u01b0ng qua th\u1eddi gian, m\u00e1y s\u1ebd h\u1ecdc v\u00e0 d\u1ef1 \u0111o\u00e1n ngh\u0129a \u0111\u00fang.<\/p>\n

V\u1ea5n \u0111\u1ec1 kh\u00f4ng ph\u1ea3i l\u00e0 li\u1ec7u m\u00e1y c\u00f3 th\u1ec3 h\u1ecdc nh\u01b0 con ng\u01b0\u1eddi hay tr\u1ea3 l\u1eddi c\u00e2u h\u1ecfi m\u1ed9t c\u00e1ch \u0111\u00fang \u0111\u1eafn. S\u1edbm hay mu\u1ed9n \u0111i\u1ec1u \u0111\u00f3 s\u1ebd \u0111\u01b0\u1ee3c th\u1ef1c hi\u1ec7n nh\u01b0ng ch\u00fang ta c\u00f3 th\u1ec3 l\u00e0m g\u00ec v\u1edbi c\u00e1i m\u00e1y th\u00f4ng minh nh\u01b0 Watson? C\u00f4ng ngh\u1ec7 n\u00e0y s\u1ebd \u0111\u01b0\u1ee3c s\u1eed d\u1ee5ng \u0111\u1ec3 l\u00e0m g\u00ec? Li\u1ec7u c\u00f3 kh\u1ea3 n\u0103ng m\u00e1y s\u1ebd h\u1ecdc ph\u00e2n bi\u1ec7t \u0111\u00fang t\u1eeb sai kh\u00f4ng? B\u1edfi v\u00ec ch\u00fang ta \u0111ang \u0111\u1ea1t t\u1edbi m\u1ee9c \u0111\u1ed9 kh\u00e1c c\u1ee7a c\u00f4ng ngh\u1ec7, ch\u00fang ta \u0111\u00e3 t\u1ea1o ra m\u00e1y c\u00f3 th\u1ec3 h\u1ecdc v\u00e0 ngh\u0129. C\u00e1i g\u00ec s\u1ebd l\u00e0 \u0111i\u1ec1u ti\u1ebfp theo? Ng\u00e0y nay IBM \u0111ang l\u00e0m vi\u1ec7c \u0111\u1ec3 th\u01b0\u01a1ng m\u1ea1i ho\u00e1 c\u00f4ng ngh\u1ec7 n\u00e0y cho c\u00f4ng nghi\u1ec7p v\u00e0 doanh nghi\u1ec7p. Trong t\u01b0\u01a1ng lai g\u1ea7n, ch\u00fang ta c\u00f3 l\u1ebd s\u1ebd d\u00f9ng n\u00f3 cho nhi\u1ec1u nhi\u1ec7m v\u1ee5 th\u01b0\u1eddng ng\u00e0y c\u1ee7a ch\u00fang ta nh\u01b0 \u0111i\u1ec1u ch\u00fang ta d\u00f9ng iPods, iPhone hay iPads ng\u00e0y nay.<\/p>\n

H\u1ecdc c\u1ee7a m\u00e1y v\u00e0 C\u00f4ng ngh\u1ec7 ng\u00f4n ng\u1eef l\u00e0 l\u0129nh v\u1ef1c k\u00edch \u0111\u1ed9ng b\u00ean trong khoa Khoa h\u1ecdc m\u00e1y t\u00ednh t\u1ea1i CMU, c\u00f9ng v\u1edbi Robotics, ch\u00fang gi\u00fap t\u1ea1o ra Watson v\u00e0 m\u1edf c\u00e1nh c\u1eeda cho ti\u1ebfn b\u1ed9 c\u1ee7a c\u00f4ng ngh\u1ec7 trong th\u1ebf k\u1ec9 21 nh\u01b0ng c\u00e1i g\u00ec s\u1ebd l\u00e0 bi\u00ean gi\u1edbi ti\u1ebfp? C\u00e1i g\u00ec s\u1ebd l\u00e0m \u00edch l\u1ee3i cho x\u00e3 h\u1ed9i ch\u00fang ta nh\u1ea5t v\u1edbi c\u00f4ng ngh\u1ec7 n\u00e0y? Nh\u1eefng c\u00e2u h\u1ecfi n\u00e0y s\u1ebd \u0111\u01b0\u1ee3c tr\u1ea3 l\u1eddi b\u1edfi c\u00e1c sinh vi\u00ean t\u01b0\u01a1ng lai c\u1ee7a ch\u00fang ta ng\u01b0\u1eddi ti\u1ebfp t\u1ee5c th\u00fac \u0111\u1ea9y c\u00f4ng ngh\u1ec7 l\u00ean m\u1ee9c m\u1edbi.<\/p>\n

(M\u1ed9t trong nh\u1eefng ng\u01b0\u1eddi b\u1ea1n c\u1ee7a t\u00f4i t\u1ea1i CMU \u0111\u00e3 g\u1ee3i \u00fd r\u1eb1ng Watson c\u00f3 th\u1ec3 thay th\u1ebf th\u1ea7y gi\u00e1o \u1edf tr\u01b0\u1eddng ph\u1ed5 th\u00f4ng s\u01a1 c\u1ea5p. Tr\u1ebb em bao gi\u1edd c\u0169ng t\u00f2 m\u00f2 v\u00e0 h\u0103m h\u1edf h\u1ecdc, ch\u00fang h\u1ecfi \u0111\u1ee7 m\u1ecdi lo\u1ea1i c\u00e2u h\u1ecfi m\u00e0 c\u00f3 th\u1ec3 l\u00e0m cho th\u1ea7y gi\u00e1o ph\u00e1t m\u1ec7t. Ng\u01b0\u1ee3c l\u1ea1i, Watson ki\u00ean nh\u1eabn v\u00e0 kh\u00f4ng bao gi\u1edd m\u1ec7t. N\u00f3 l\u00e0m vi\u1ec7c b\u1ea9y ng\u00e0y v\u00e0 hai m\u01b0\u01a1i t\u01b0 gi\u1edd m\u00e0 kh\u00f4ng y\u00eau c\u1ea7u ngh\u1ec9 gi\u1ea3i lao. N\u00f3 c\u0169ng kh\u00f4ng \u0111\u00f2i t\u0103ng l\u01b0\u01a1ng. Th\u1eadt l\u00e0 \u00fd t\u01b0\u1edfng th\u00fa v\u1ecb!)<\/p>\n

 <\/p>\n

—-English vesrsion—-<\/p>\n

 <\/p>\n

Machine Learning<\/p>\n

\u201cMachine Learning\u201d\u00a0is a scientific field concerned with the design and development of algorithms that allow computers to learn and response based on data from its databases. A computer can learn by itself based on examples (data) to capture certain things using sophisticated software based on probability distribution. Each time it makes mistake, it learns not to do it again so over a period of learning, it can response according to a pattern similar to human behavior.<\/p>\n

The key factor of machine learning research is to develop software algorithms that automatically recognize complex patterns and make intelligent decisions based on past data. For example, a computer program is said to learn from experience E with respect to some class of tasks T and performance measure P. If its performance at tasks in T, as measured by P, improves with experience E.<\/p>\n

Few months ago, the machine learning computer called Watson has memorize over\u00a0200 million pages of data to correctly give answers in the game \u201cJeopardy\u201d and defeated the world\u2019s best quiz game persons. This computer built by IBM has over 2,500 parallel processor cores, each can perform up to 33 billion operations in a second. It has several millions of software code and took more than five years to program at Carnegie Mellon and IBM facilities.<\/p>\n

Few years ago, its previous version named \u201cBig Blue\u201d has learned every possible moves in Chess and defeated Garry Kasparov, the world\u2019s Chess champion. Since then, \u201cBig Blue\u201d has defeated everybody who play Chess in matter of few seconds, as it can predicted all of your moves. Chess is a game of strategy and calculation so it is possible to write a software program for it. However, answering randomly selected questions is different challenge.<\/p>\n

In this challenge, Watson will have to learn everything possible so it can answer questions that a common person can ask using the natural language such as English. For example: \u201cWhere is X street in New York?\u201d or \u201cWhat is the capital of Uganda\u201d. It can answer ambiguous questions such as \u201cWhat is the Rh factor\u201d or \u201cWhat book has a woman named Scarlett who married a person named Butler\u201d (Answer: Gone with the Wind) or it can answer: \u201cWhat city the Soccer player named Pel\u00e9 was born?\u201d People can even ask for lyrics from the Beatles\u2019 songs to the notes of certain classical music symphony\u201d.<\/p>\n

Question Answering (QA) has been the dream of Artificial Intelligence (AI) field. It is considerably more difficult to develop algorithms than chess. It goes much farther and deeper than what search engines like Google do when it check its database for keywords. For example: Google will give you 300,000 page matches for a search of the terms \u201cGreyhound\u201d and \u201cAfrican country,\u201d which you can then have to search them more to find what you need. But Watson can tell you in less than a seconds that the two word \u201cGreyhound\u201d and \u201cAfrican country\u201d is related to a country named Egypt. (Greyhound is a type of dog original from Egypt).<\/p>\n

When I.B.M. and the team of CMU researchers began their work in 2006, Watson could answer only 15 percent of the questions. It continue to learn from every books in the U.S congress libraries, read all books from libraries in Europe, all encyclopedias, dictionaries, thesauri, databases, taxonomies, the Bibles, movie scripts, novels and plays. Every time, it answers wrong, it memorizes and over time through reasoning deduction, it learns the correct answer. (This is what Artificial Intelligence is all about). To understand the questions, the machine has to learn and analyze natural language (the language that human use), appraise sources, propose hypotheses, check the database, collect several information, merge the results, and rank the best answers that has the highest statistical confident factor to find the most appropriate answer.<\/p>\n

Of course, the correct answer is only a statistical thing, a matter of frequency and likelihood. Within few seconds the machine process countless possibilities based on over 100 algorithms converge on a solution than it can provide the answer. Could Watson answer every questions? Not yet. Human words are very difficult, some simple sentence may have several meanings and it will confuse the machine. But over time, the machine will learn and predict the correct one.<\/p>\n

The issue is not whether the machine can learn like a human being or answer questions correctly. It will be done sooner or later but what can we do with an intelligent machine like Watson? What this technology will be used for? Is it possible that the machine will learn to distinguish right from wrong? Now that we are reaching another level in technology, we have created a machine that can learn and think. What will be next? Today IBM is working to commercialize this technology to the industry and business. In the near future, we will probably use it for many of our daily tasks just like what we use iPods, iPhone or iPads today.<\/p>\n

Machine Learning and Language Technology are exciting fields within the Computer Science department at CMU, together with Robotics, they helped create Watson and open the door for the advancement of technology in this 21st<\/sup>\u00a0century but what will be the next frontier? What will benefit our society most with this technology? These questions will be answered by our future students who continue to push the technology to the next level.<\/p>\n

(One of my friend at CMU suggested that Watson could replace teachers in elementary school. Children are always curious and eager to learn, they ask all kind of questions that can make teachers tired. On the contrary, Watson is patient and never tired. It works seven days and twenty four hours without asking for a break. It also not ask for raise. Interesting idea!)<\/p>\n

 <\/p>\n","protected":false},"excerpt":{"rendered":"

\u201cH\u1ecdc c\u1ee7a m\u00e1y\u201d\u00a0l\u00e0 l\u0129nh v\u1ef1c khoa h\u1ecdc li\u00ean quan t\u1edbi thi\u1ebft k\u1ebf v\u00e0 ph\u00e1t tri\u1ec3n c\u00e1c thu\u1eadt to\u00e1n cho ph\u00e9p m\u00e1y t\u00ednh h\u1ecdc v\u00e0 \u0111\u00e1p … <\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[26],"tags":[],"class_list":["post-2222","post","type-post","status-publish","format-standard","hentry","category-xu-huong-cong-nghe"],"_links":{"self":[{"href":"https:\/\/science-technology.vn\/index.php?rest_route=\/wp\/v2\/posts\/2222","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/science-technology.vn\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/science-technology.vn\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/science-technology.vn\/index.php?rest_route=\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/science-technology.vn\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=2222"}],"version-history":[{"count":2,"href":"https:\/\/science-technology.vn\/index.php?rest_route=\/wp\/v2\/posts\/2222\/revisions"}],"predecessor-version":[{"id":2224,"href":"https:\/\/science-technology.vn\/index.php?rest_route=\/wp\/v2\/posts\/2222\/revisions\/2224"}],"wp:attachment":[{"href":"https:\/\/science-technology.vn\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=2222"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/science-technology.vn\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=2222"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/science-technology.vn\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=2222"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}