{"id":3499,"date":"2013-08-19T13:11:05","date_gmt":"2013-08-19T06:11:05","guid":{"rendered":"http:\/\/science-technology.vn\/?p=3499"},"modified":"2013-08-19T13:11:05","modified_gmt":"2013-08-19T06:11:05","slug":"khu-vuc-nong-tiep-2","status":"publish","type":"post","link":"https:\/\/science-technology.vn\/?p=3499","title":{"rendered":"Khu v\u1ef1c “n\u00f3ng” ti\u1ebfp"},"content":{"rendered":"

M\u1ed9t sinh vi\u00ean vi\u1ebft cho t\u00f4i: \u201cTh\u1ea7y \u0111\u00e3 khuy\u00ean ch\u00fang em \u0111i theo xu h\u01b0\u1edbng c\u00f4ng nghi\u1ec7p \u0111\u1ec3 ch\u1ecdn l\u0129nh v\u1ef1c h\u1ecdc t\u1eadp d\u1ef1a tr\u00ean nhu c\u1ea7u c\u1ee7a c\u00f4ng nghi\u1ec7p v\u00e0 ph\u00e1t tri\u1ec3n k\u0129 n\u0103ng \u0111\u1ec3 ch\u00fang em c\u00f3 th\u1ec3 c\u00f3 \u0111\u01b0\u1ee3c vi\u1ec7c l\u00e0m t\u1ed1t khi t\u1ed1t nghi\u1ec7p. Em l\u00e0 sinh vi\u00ean n\u0103m th\u1ee9 hai trong khoa h\u1ecdc m\u00e1y t\u00ednh cho n\u00ean em \u0111\u00e3 ch\u1ecdn \u0111\u00fang l\u0129nh v\u1ef1c h\u1ecdc t\u1eadp nh\u01b0ng em c\u1ea7n ph\u00e1t tri\u1ec3n lo\u1ea1i k\u0129 n\u0103ng n\u00e0o v\u00e0 em n\u00ean h\u1ed9i t\u1ee5 v\u00e0o khu v\u1ef1c n\u00e0o? C\u00e1i g\u00ec l\u00e0 khu v\u1ef1c “n\u00f3ng”?”<\/span><\/p>\n

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\u0110\u00e1p: L\u00e0 sinh vi\u00ean Khoa h\u1ecdc m\u00e1y t\u00ednh, b\u1ea1n n\u00ean d\u00f9ng “Google” hay “Bing” \u0111\u1ec3 t\u00ecm \u0111i\u1ec1u b\u1ea1n \u0111ang t\u00ecm. C\u1ee9 g\u00f5 v\u00e0o \u201cIndustry trends\u201d, hay \u201cJob market trends\u201d th\u00ec b\u1ea1n s\u1ebd c\u00f3 m\u1ecdi th\u00f4ng tin b\u1ea1n c\u1ea7n. B\u1ea1n n\u00ean t\u00edch c\u1ef1c h\u01a1n trong l\u1eadp k\u1ebf ho\u1ea1ch ngh\u1ec1 nghi\u1ec7p c\u1ee7a b\u1ea1n thay v\u00ec ch\u1edd \u0111\u1ee3i ai \u0111\u00f3 cho b\u1ea1n l\u1eddi khuy\u00ean.<\/p>\n

Ng\u00e0y nay khu v\u1ef1c “n\u00f3ng” l\u00e0: \u1ee9ng d\u1ee5ng di \u0111\u1ed9ng, t\u00ednh to\u00e1n m\u00e2y, Robotics, v\u00e0 t\u1ef1 \u0111\u1ed9ng ho\u00e1 v\u0103n ph\u00f2ng. (T\u00f4i \u0111\u00e3 vi\u1ebft nhi\u1ec1u blog v\u1ec1 nh\u1eefng c\u00f4ng ngh\u1ec7 n\u00e0y). T\u1ea5t c\u1ea3 ch\u00fang \u0111\u1ec1u y\u00eau c\u1ea7u k\u0129 n\u0103ng C\u00f4ng ngh\u1ec7 th\u00f4ng tin (CNTT) cho n\u00ean n\u1ebfu b\u1ea1n ch\u1ecdn c\u00e1c khu v\u1ef1c Khoa h\u1ecdc m\u00e1y t\u00ednh, K\u0129 ngh\u1ec7 ph\u1ea7n m\u1ec1m, hay Qu\u1ea3n l\u00ed h\u1ec7 th\u00f4ng tin, b\u1ea1n ch\u1ecdn \u0111\u00fang l\u0129nh v\u1ef1c h\u1ecdc t\u1eadp r\u1ed3i, d\u1ef1a tr\u00ean nhu c\u1ea7u c\u00f4ng nghi\u1ec7p. \u0110i\u1ec1u b\u1ea1n c\u1ea7n l\u00e0 ph\u00e1t tri\u1ec3n k\u0129 n\u0103ng trong c\u00e1c khu v\u1ef1c n\u00e0y \u0111\u1ec3 ch\u1eafc r\u1eb1ng b\u1ea1n s\u1ebd c\u00f3 kh\u1ea3 n\u0103ng c\u00f3 \u0111\u01b0\u1ee3c vi\u1ec7c l\u00e0m t\u1ed1t khi t\u1ed1t nghi\u1ec7p. Tuy nhi\u00ean, n\u1ebfu b\u1ea1n mu\u1ed1n ti\u1ebfn h\u01a1n n\u1eefa vi\u1ec7c h\u1ecdc t\u1eadp b\u1eb1ng c\u00e1ch ti\u1ebfp t\u1ee5c \u0111i v\u00e0o ch\u01b0\u01a1ng tr\u00ecnh th\u1ea1c s\u0129 th\u00ec b\u1ea1n c\u1ea7n xem x\u00e9t t\u1edbi c\u00e1c khu v\u1ef1c “n\u00f3ng” kh\u00e1c.<\/p>\n

Trong v\u00e0i n\u0103m t\u1edbi, khu v\u1ef1c “n\u00f3ng” s\u1ebd l\u00e0 : T\u1ef1 \u0111\u1ed9ng ho\u00e1 c\u00f4ng vi\u1ec7c tri th\u1ee9c d\u00f9ng ph\u00e2n t\u00edch \u201cBig Data\u201d \u0111\u1ec3 nh\u1eadn d\u1ea1ng c\u00e1c h\u00ecnh m\u1eabu n\u00e0o \u0111\u00f3 hay th\u00f4ng tin c\u00f3 gi\u00e1 tr\u1ecb trong d\u1eef li\u1ec7u \u0111\u00f4ng \u0111\u1ea3o \u0111\u01b0\u1ee3c thu th\u1eadp v\u00e0 c\u00e1c thu\u1eadt to\u00e1n \u201ch\u1ecdc m\u00e1y\u201d \u0111\u1ec3 \u201ch\u1ecdc\u201d t\u1eeb nh\u1eefng ph\u00e2n t\u00edch n\u00e0y v\u00e0 r\u00fat ra k\u1ebft lu\u1eadn. \u0110\u00e2y th\u1ef1c s\u1ef1 l\u00e0 th\u1ebf h\u1ec7 ti\u1ebfp c\u1ee7a c\u00f4ng ngh\u1ec7 “tr\u00ed tu\u1ec7 nh\u00e2n t\u1ea1o” v\u00e0 m\u1ed9t s\u1ed1 ng\u01b0\u1eddi g\u1ecdi l\u00e0 \u201cA.I 2.0\u201d. M\u1ed9t v\u00ed d\u1ee5 c\u1ee7a \u0111i\u1ec1u n\u00e0y l\u00e0 “m\u00e1y t\u00ednh th\u00f4ng minh” hi\u1ec3u c\u00e2u h\u1ecfi c\u1ee7a b\u1ea1n v\u00e0 c\u00f3 kh\u1ea3 n\u0103ng cho b\u1ea1n c\u00e2u tr\u1ea3 l\u1eddi \u0111\u00fang. V\u00e0i n\u0103m tr\u01b0\u1edbc, IBM \u0111\u00e3 x\u00e2y d\u1ef1ng m\u1ed9t \u201cm\u00e1y t\u00ednh th\u00f4ng minh\u201d c\u00f3 t\u00ean \u201cWatson\u201d v\u00e0 \u0111\u00e3 d\u1ea1y cho n\u00f3 tr\u1ea3 l\u1eddi h\u00e0ng ngh\u00ecn c\u00e2u h\u1ecfi t\u1eeb m\u1ecdi ng\u01b0\u1eddi. (N\u1ebfu b\u1ea1n mu\u1ed1n xem c\u00e1ch n\u00f3 tr\u1ea3 l\u1eddi c\u00e1c c\u00e2u h\u1ecfi, b\u1ea1n c\u00f3 th\u1ec3 l\u00ean YouTube v\u00e0 g\u00f5 Watson Computer hay Jeopardy th\u00ec b\u1ea1n c\u00f3 th\u1ec3 th\u1ea5y to\u00e0n th\u1ec3 phi\u00ean tr\u00ecnh di\u1ec5n v\u1ec1 c\u00e1ch Watson \u0111\u00e1nh b\u1ea1i nh\u1eefng ng\u01b0\u1eddi gi\u1ecfi nh\u1ea5t b\u1eb1ng vi\u1ec7c tr\u1ea3 l\u1eddi m\u1ecdi c\u00e2u h\u1ecfi nhanh h\u01a1n con ng\u01b0\u1eddi). B\u00e2y gi\u1edd Watson \u0111\u01b0\u1ee3c \u0111\u1eb7t trong b\u1ec7nh vi\u1ec7n cho n\u00ean n\u00f3 c\u00f3 th\u1ec3 “h\u1ecdc” c\u00e1ch c\u00e1c b\u00e1c s\u0129 ch\u1eefa tr\u1ecb b\u1ec7nh nh\u00e2n \u0111\u1ec3 cho trong t\u01b0\u01a1ng lai g\u1ea7n, n\u00f3 c\u00f3 th\u1ec3 gi\u00fap tr\u1ea3 l\u1eddi c\u00e1c c\u00e2u h\u1ecfi y t\u1ebf t\u1eeb b\u1ec7nh nh\u00e2n. T\u00f4i tin T\u1ef1 \u0111\u1ed9ng ho\u00e1 c\u00f4ng vi\u1ec7c tri th\u1ee9c s\u1ebd r\u1ea5t l\u1edbn trong v\u00e0i n\u0103m t\u1edbi, \u0111\u1eb7c bi\u1ec7t cho sinh vi\u00ean CNTT ng\u01b0\u1eddi mu\u1ed1n theo \u0111u\u1ed5i b\u1eb1ng c\u1ea5p th\u1ea1c s\u0129 hay ti\u1ebfn s\u0129 trong khu v\u1ef1c n\u00e0y b\u1edfi v\u00ec c\u00e1c ti\u1ebfn b\u1ed9 trong ph\u1ea7n m\u1ec1m, \u0111\u1eb7c bi\u1ec7t c\u00e1c k\u0129 thu\u1eadt h\u1ecdc m\u00e1y nh\u01b0 h\u1ecdc s\u00e2u v\u00e0 m\u1ea1ng n\u01a1 ron, l\u00e0 y\u1ebfu t\u1ed1 then ch\u1ed1t c\u1ee7a t\u1ef1 \u0111\u1ed9ng ho\u00e1 c\u00f4ng vi\u1ec7c tri th\u1ee9c v\u00ec m\u00e1y t\u00ednh s\u1ebd \u0111\u01b0\u1ee3c l\u1eadp tr\u00ecnh \u0111\u1ec3 ph\u00e2n t\u00edch d\u1eef li\u1ec7u v\u00e0 r\u00fat ra k\u1ebft lu\u1eadn khi n\u00f3 h\u1ecdc nhi\u1ec1u h\u01a1n v\u00e0 tr\u1edf n\u00ean th\u00f4ng minh h\u01a1n. M\u00e1y t\u00ednh c\u00e0ng x\u1eed l\u00ed d\u1eef li\u1ec7u l\u1edbn th\u00f4ng minh, thu\u1eadt to\u00e1n c\u1ee7a ch\u00fang c\u00e0ng tr\u1edf n\u00ean \u0111\u01b0\u1ee3c c\u1ea3i ti\u1ebfn h\u01a1n v\u00ec ch\u00fang “h\u1ecdc” nhanh.<\/p>\n

Khu v\u1ef1c kh\u00e1c \u00a0\u201cN\u00f3ng\u201d s\u1ebd l\u00e0: D\u00e3y Genom c\u1ee7a c\u00f4ng ngh\u1ec7 sinh h\u1ecdc hay genom th\u1ebf h\u1ec7 ti\u1ebfp n\u01a1i c\u00f4ng ngh\u1ec7 m\u00e1y t\u00ednh nh\u01b0 ph\u00e2n t\u00edch Big Data \u0111\u01b0\u1ee3c d\u00f9ng \u0111\u1ec3 nh\u1eadn di\u1ec7n c\u00e1c h\u00ecnh m\u1eabu v\u00e0 c\u00e1c \u0111\u1eb7c tr\u01b0ng \u0111\u1eb7c bi\u1ec7t c\u1ee7a d\u00e3y gen v\u00e0 v\u1eadt li\u1ec7u gen \u0111\u1ec3 kh\u00e1m ph\u00e1 c\u00e1c b\u1ec7nh tr\u01b0\u1edbc khi ch\u00fang x\u1ea3y ra hay t\u00ecm c\u00e1c manh m\u1ed1i v\u1ec1 b\u1ec7nh nh\u01b0 \u0111\u00e1i \u0111\u01b0\u1eddng, ung th\u01b0, m\u1ea5t tr\u00ed v.v. Tr\u01b0\u1edbc khi \u1ee9ng d\u1ee5ng c\u00f4ng ngh\u1ec7 th\u00f4ng tin (CNTT) h\u1ec7 genom c\u1ee7a con ng\u01b0\u1eddi ph\u1ea3i m\u1ea5t 13 n\u0103m v\u00e0 2.7 t\u1ec9 \u0111\u00f4 la \u0111\u1ec3 l\u00e0m (D\u1ef1 \u00e1n Genome con ng\u01b0\u1eddi 1990). Ng\u00e0y nay trong ph\u00f2ng th\u00ed nghi\u1ec7m c\u1ee7a t\u00f4i \u1edf Carnegie Mellon, ch\u1ec9 m\u1ea5t v\u00e0i gi\u1edd v\u00e0 v\u00e0i ngh\u00ecn \u0111\u00f4 la \u0111\u1ec3 d\u00f9ng x\u1eed l\u00ed t\u00ednh to\u00e1n nhanh v\u00e0 thu\u1eadt to\u00e1n Big Data. Ch\u1eb3ng m\u1ea5y ch\u1ed1c c\u00e1c b\u1ec7nh vi\u1ec7n s\u1ebd c\u00f3 kh\u1ea3 n\u0103ng d\u00f9ng c\u00f4ng ngh\u1ec7 m\u1edbi n\u00e0y \u0111\u1ec3 ch\u1ea9n \u0111o\u00e1n nhi\u1ec1u b\u1ec7nh tr\u01b0\u1edbc khi ch\u00fang x\u1ea3y ra v\u00e0 m\u1ecdi ng\u01b0\u1eddi c\u00f3 th\u1ec3 l\u1ea5y h\u00e0nh \u0111\u1ed9ng ph\u00f2ng ng\u1eeba cho n\u00ean m\u1ed9t s\u1ed1 b\u1ec7nh c\u00f3 th\u1ec3 kh\u00f4ng x\u1ea3y ra cho h\u1ecd. T\u01b0\u1edfng t\u01b0\u1ee3ng r\u1eb1ng m\u1ed9t m\u00e1y ph\u00e2n t\u00edch c\u00f3 th\u1ec3 n\u00f3i cho b\u1ea1n r\u1eb1ng b\u1ea1n s\u1ebd c\u00f3 80% ung th\u01b0 ph\u1ed5i l\u00fac b\u1ea1n 30 tu\u1ed5i cho n\u00ean b\u1ea1n s\u1ebd ph\u1ea3i c\u00f3 h\u00e0nh \u0111\u1ed9ng \u0111\u1eb7c bi\u1ec7t nh\u01b0 b\u1ecf thu\u1ed1c l\u00e1 v\u00e0 u\u1ed1ng thu\u1ed1c \u0111\u1eb7c bi\u1ec7t \u0111\u1ec3 gi\u1ea3m c\u01a1 h\u1ed9i n\u00e0y. Ng\u00e0y nay \u1ee9ng d\u1ee5ng c\u1ee7a c\u00f4ng ngh\u1ec7 t\u00ednh to\u00e1n nh\u01b0 ph\u00e2n t\u00edch Big Data, H\u1ecdc m\u00e1y v\u00e0 th\u1ed1ng k\u00ea c\u00f3 nhu c\u1ea7u cao v\u00e0 t\u00f4i ngh\u0129 ch\u00fang s\u1ebd r\u1ea5t l\u1edbn trong t\u01b0\u01a1ng lai g\u1ea7n.<\/p>\n

Khu v\u1ef1c “n\u00f3ng” kh\u00e1c s\u1ebd l\u00e0 \u1ee9ng d\u1ee5ng c\u1ee7a ph\u00e2n t\u00edch Big Data trong c\u00f4ng nghi\u1ec7p d\u1ea7u v\u00e0 kho\u00e1ng s\u1ea3n. B\u1eb1ng vi\u1ec7c thu th\u1eadp th\u00f4ng tin t\u1eeb nhi\u1ec1u ngu\u1ed3n nh\u01b0 c\u00e1c d\u1eef li\u1ec7u c\u1ea3m bi\u1ebfn v\u00e0 d\u1eef li\u1ec7u tr\u00edch r\u00fat v\u1eadt t\u01b0 n\u0103ng l\u01b0\u1ee3ng, c\u00f3 th\u1ec3 v\u1ebd b\u1ea3n \u0111\u1ed3 m\u1ecdi tr\u1eef l\u01b0\u1ee3ng kho\u00e1ng s\u1ea3n c\u0169ng nh\u01b0 c\u00e1c m\u1ecf d\u1ea7u tr\u00ean tr\u00e1i \u0111\u1ea5t v\u00e0 l\u00e0m t\u0103ng vi\u1ec7c kh\u00e1m ph\u00e1 v\u00e0 t\u1ec9 l\u1ec7 ph\u1ee5c h\u1ed3i. Thay v\u00ec khoan ng\u1eabu nhi\u00ean t\u00ecm d\u1ea7u v\u00e0 kho\u00e1ng s\u1ea3n nh\u01b0 n\u00f3 v\u1eabn \u0111\u01b0\u1ee3c l\u00e0m ng\u00e0y nay, ph\u00e2n t\u00edch Big Data v\u00e0 c\u00f4ng ngh\u1ec7 t\u00ednh to\u00e1n c\u00f3 th\u1ec3 \u0111\u01b0\u1ee3c \u00e1p d\u1ee5ng \u0111\u1ec3 gi\u00fap ng\u00e0nh c\u00f4ng nghi\u1ec7p d\u1ea7u v\u00e0 kho\u00e1ng s\u1ea3n t\u00ecm v\u1ecb tr\u00ed ch\u00ednh x\u00e1c c\u1ee7a c\u00e1c m\u1ecf d\u1ea7u, kh\u00ed v\u00e0 tr\u1eef l\u01b0\u1ee3ng kho\u00e1ng s\u1ea3n v\u00e0 gi\u1ea3m chi ph\u00ed th\u0103m d\u00f2 v\u00e0 v\u1eadn h\u00e0nh \u0111\u00e1ng k\u1ec3. Theo m\u1ed9t \u0111i\u1ec1u tra c\u1ee7a c\u00f4ng nghi\u1ec7p d\u1ea7u, v\u00ec d\u00f9ng ph\u00e2n t\u00edch Big Data trong n\u0103m 2012 \u0111\u1ec3 ph\u00e2n t\u00edch c\u00e1c c\u1ea3m bi\u1ebfn v\u00e0 d\u1eef li\u1ec7u tr\u00edch r\u00fat v\u1eadt t\u01b0, h\u1ecd \u0111\u00e3 c\u00f3 kh\u1ea3 n\u0103ng t\u00ecm \u0111\u01b0\u1ee3c 80% ch\u00ednh x\u00e1c h\u01a1n v\u00e0 gi\u1ea3m chi ph\u00ed xu\u1ed1ng h\u00e0ng t\u1ec9 \u0111\u00f4 la. C\u00e1c c\u00f4ng ti d\u1ea7u v\u00e0 nh\u00e0 cung c\u1ea5p n\u0103ng l\u01b0\u1ee3ng \u0111\u00e3 th\u1ea5y r\u1eb1ng c\u00f3 c\u01a1 h\u1ed9i kh\u1ed5ng l\u1ed3 trong vi\u1ec7c t\u0103ng ti\u1ebfn khai th\u00e1c d\u1ea7u v\u00e0 kh\u00ed v\u00e0 qu\u00e1 tr\u00ecnh ph\u1ee5c h\u1ed3i ch\u1ec9 b\u1eb1ng vi\u1ec7c d\u00f9ng c\u00f4ng ngh\u1ec7 m\u1edbi n\u00e0y. Do \u0111\u00f3 nh\u1eefng c\u00f4ng ti n\u00e0y c\u1ea7n nhi\u1ec1u c\u00f4ng nh\u00e2n CNTT chuy\u00ean m\u00f4n trong ph\u00e2n t\u00edch Big Data \u0111\u1ec3 gi\u00fap h\u1ecd tr\u00edch r\u00fat th\u00f4ng tin c\u00f3 ngh\u0129a t\u1eeb d\u1eef li\u1ec7u kh\u1ed5ng l\u1ed3 \u0111\u01b0\u1ee3c thu th\u1eadp. Ch\u1eb3ng h\u1ea1n c\u00f4ng ti Shell Oil c\u00f3 nhi\u1ec1u petabytes d\u1eef li\u1ec7u \u0111\u1ecba l\u00ed nh\u01b0ng kh\u00f4ng c\u00f3 \u0111\u1ee7 c\u00f4ng nh\u00e2n c\u00f3 th\u1ec3 ph\u00e2n t\u00edch ch\u00fang. Ng\u01b0\u1eddi ph\u00e1t ng\u00f4n d\u1ea7u ho\u1ea3 n\u00f3i v\u1edbi nh\u00e0 ph\u00e2n t\u00edch Ph\u1ed1 Wall: \u201cB\u1eb1ng vi\u1ec7c c\u00f3 \u0111\u1ee7 c\u00f4ng nh\u00e2n trong ph\u00e2n t\u00edch Big Data, ch\u00fang t\u00f4i c\u00f3 th\u1ec3 t\u00ecm \u0111\u01b0\u1ee3c \u0111\u00edch x\u00e1c \u0111i\u1ec1u ch\u00fang t\u00f4i t\u00ecm v\u00e0 gi\u1ea3m chi ph\u00ed v\u1eadn h\u00e0nh h\u00e0ng t\u1ec9 cho t\u1edbi ngh\u00ecn t\u1ec9 \u0111\u00f4 la trong m\u01b0\u1eddi n\u0103m t\u1edbi. Ch\u00fang t\u00f4i r\u1ea5t sung s\u01b0\u1edbng v\u1ec1 ti\u1ec1m n\u0103ng c\u1ee7a c\u00f4ng ngh\u1ec7 m\u1edbi n\u1ed5i l\u00ean n\u00e0y gi\u00fap cho ch\u00fang t\u00f4i n\u00e2ng cao n\u0103ng su\u1ea5t, t\u00ednh sinh l\u1eddi v\u00ec n\u00f3 s\u1ebd ho\u00e0n to\u00e0n l\u00e0m thay \u0111\u1ed5i c\u00e1ch c\u00f4ng vi\u1ec7c c\u1ee7a ch\u00fang t\u00f4i \u0111\u01b0\u1ee3c l\u00e0m.\u201d<\/p>\n

V\u1ec1 c\u0103n b\u1ea3n m\u1ecdi th\u1ee9 \u0111ang c\u00f3 nhu c\u1ea7u cao ng\u00e0y nay v\u00e0 trong t\u01b0\u01a1ng lai g\u1ea7n s\u1ebd y\u00eau c\u1ea7u c\u00f4ng nh\u00e2n tri th\u1ee9c c\u00f3 k\u0129 n\u0103ng trong c\u00f4ng ngh\u1ec7 th\u00f4ng tin. Khi nhi\u1ec1u ng\u00e0nh c\u00f4ng nghi\u1ec7p \u0111ang b\u1eaft \u0111\u1ea7u nh\u1eadn ra ti\u1ec1m n\u0103ng c\u1ee7a CNTT \u0111\u1ec3 c\u1ea3i ti\u1ebfn t\u00ednh hi\u1ec7u qu\u1ea3, n\u0103ng su\u1ea5t c\u1ee7a h\u1ecd, v\u00e0 t\u0103ng l\u1ee3i nhu\u1eadn, n\u00f3 s\u1ebd d\u1ea7n t\u1edbi nhu c\u1ea7u l\u1edbn v\u1ec1 nhi\u1ec1u c\u00f4ng nh\u00e2n v\u00e0 vi\u1ec7c thi\u1ebfu h\u1ee5t k\u0129 n\u0103ng CNTT c\u00f3 th\u1ec3 l\u00e0 l\u1ef1c ch\u00ednh trong thay \u0111\u1ed5i s\u1ee9c m\u1ea1nh kinh t\u1ebf trong c\u1ea1nh tranh to\u00e0n c\u1ea7u. Ph\u00e2n t\u00edch d\u1eef li\u1ec7u l\u1edbn l\u00e0 d\u1eabn l\u00e1i ch\u00ednh trong t\u01b0\u01a1ng lai, n\u1ebfu b\u1ea1n l\u00e0 sinh vi\u00ean CNTT (Khoa h\u1ecdc m\u00e1y t\u00ednh, K\u0129 ngh\u1ec7 ph\u1ea7n m\u1ec1m hay Qu\u1ea3n l\u00ed h\u1ec7 th\u00f4ng tin) b\u1ea1n c\u00f3 th\u1ec3 c\u00e2n nh\u1eafc theo \u0111u\u1ed5i b\u1eb1ng th\u1ea1c s\u0129 v\u00ec n\u00f3 y\u00eau c\u1ea7u tri th\u1ee9c chuy\u00ean s\u00e2u \u0111\u1ec3 l\u00e0m vi\u1ec7c trong c\u00e1c khu v\u1ef1c n\u00e0y.<\/p>\n

Ng\u00e0y nay cu\u1ed9c chi\u1ebfn v\u1ec1 c\u00f4ng nh\u00e2n c\u00f3 k\u0129 n\u0103ng \u0111\u00e3 b\u1eaft \u0111\u1ea7u nh\u01b0ng n\u00f3 s\u1ebd m\u1ea1nh h\u01a1n n\u1eefa trong t\u01b0\u01a1ng lai g\u1ea7n v\u00ec m\u1ecdi n\u01b0\u1edbc \u0111\u00e3 ph\u00e1t tri\u1ec3n nh\u01b0 M\u0129, Anh, \u0110\u1ee9c v\u00e0 Ph\u00e1p \u0111\u1ec1u \u0111\u00e3 th\u00f4ng qua lu\u1eadt di tr\u00fa \u0111\u1ec3 cho ph\u00e9p c\u00f4ng nh\u00e2n c\u00f3 k\u0129 n\u0103ng t\u1edbi v\u00e0 l\u00e0m vi\u1ec7c. Tuy nhi\u00ean m\u1ed9t s\u1ed1 n\u01b0\u1edbc b\u1eaft \u0111\u1ea7u ch\u1ed1ng l\u1ea1i vi\u1ec7c “ch\u1ea3y n\u00e3o” n\u00e0y b\u1eb1ng vi\u1ec7c ph\u00e1t tri\u1ec3n \u0111\u00e0o t\u1ea1o chuy\u00ean s\u00e2u ri\u00eang c\u1ee7a h\u1ecd trong c\u00e1c khu v\u1ef1c n\u00e0y \u0111\u1ec3 ng\u0103n c\u1ea3n nh\u1eefng ng\u01b0\u1eddi c\u00f3 k\u0129 n\u0103ng c\u1ee7a h\u1ecd kh\u1ecfi ra \u0111i (Trung Qu\u1ed1c, \u1ea4n \u0110\u1ed9, Nga, Nh\u1eadt B\u1ea3n v.v.). M\u1ed9t nh\u00e0 ph\u00e2n t\u00edch Ph\u1ed1 Wall vi\u1ebft: \u201cTrong qu\u00e1 kh\u1ee9 c\u01b0\u1eddng qu\u1ed1c kinh t\u1ebf d\u1ef1a tr\u00ean v\u1ed1n nh\u01b0ng ng\u00e0y nay v\u00e0 trong t\u01b0\u01a1ng lai n\u00f3 s\u1ebd d\u1ef1a tr\u00ean k\u0129 n\u0103ng, \u0111\u1eb7c bi\u1ec7t \u1ee9ng d\u1ee5ng c\u1ee7a k\u0129 n\u0103ng CNT trong nhi\u1ec1u ng\u00e0nh c\u00f4ng nghi\u1ec7p nh\u01b0 vi\u1ec5n th\u00f4ng, ch\u1ebf t\u1ea1o, Robotics, ch\u0103m s\u00f3c s\u1ee9c kho\u1ebb, d\u01b0\u1ee3c v\u00e0 ng\u00e0nh c\u00f4ng nghi\u1ec7p d\u1ea7u kh\u00ed. N\u01b0\u1edbc n\u00e0o c\u00f3 nhi\u1ec1u c\u00f4ng nh\u00e2n CNTT s\u1ebd l\u00e0 ng\u01b0\u1eddi th\u1eafng trong c\u01b0\u1eddng qu\u1ed1c kinh t\u1ebf v\u00e0 cu\u1ed9c chi\u1ebfn v\u1ec1 t\u00e0i n\u0103ng s\u1ebd lan r\u1ed9ng kh\u1eafp ho\u00e0n c\u1ea7u. V\u1edbi to\u00e0n c\u1ea7u ho\u00e1, c\u00e1c c\u00f4ng ti s\u1ebd t\u1eadp trung v\u00e0o ch\u1ed7 h\u1ecd c\u00f3 th\u1ec3 t\u00ecm \u0111\u01b0\u1ee3c t\u00e0i n\u0103ng v\u00e0 thi\u1ebft l\u1eadp v\u1eadn h\u00e0nh c\u1ee7a h\u1ecd \u1edf \u0111\u00f3. Do \u0111\u00f3, CNTT s\u1ebd l\u00e0 y\u1ebfu t\u1ed1 t\u1ea1o kh\u1ea3 n\u0103ng then ch\u1ed1t cho th\u1ecbnh v\u01b0\u1ee3ng kinh t\u1ebf trong nhi\u1ec1u n\u0103m t\u1edbi v\u00ec m\u1ecdi ng\u00e0nh c\u00f4ng nghi\u1ec7p s\u1ebd c\u1ea7n nh\u1eefng c\u00f4ng nh\u00e2n tri th\u1ee9c n\u00e0y.\u201d<\/p>\n

 <\/p>\n

—English version—<\/p>\n

 <\/p>\n

The next “Hot” areas<\/p>\n

A student wrote to me: \u201cYou have advised us to follow industry trends to select field of study based on industry\u2019s needs and develop skills so we can get good jobs when graduate. I am a second year student in computer science so I already select the right field of study but what kind of skills do I need to develop and which area should I focus on? What are the \u201cHot\u201d areas?”<\/p>\n

 <\/p>\n

Answer: As a Computer Science student, you should learn to use \u201cGoogle\u201d or \u201cBing\u201d to search for what you are looking for. Just type in \u201cIndustry trends\u201d, or \u201cJob market trends\u201d then you will have all information that you need. You should be more active in your career planning rather than wait for someone to give you advice.<\/p>\n

Today the \u201cHot\u201d areas are: Mobile applications, Cloud computing, Robotics, and Office Automation. (I have written many blogs on these technologies already). All of them require Information Technology (IT) skills so if you selected Computer Science, Software Engineering, or Information Systems Management areas, you are selecting the right fields of study, based on industry needs. What you need is to develop skills in these areas to make sure that you will be able to get good jobs when graduate. However, if you want to further your study by continue to go into the MS programs then you may want to consider the next \u201cHot\u201d areas.<\/p>\n

In the next few years, the \u201cHot\u201d areas will be: Knowledge Work Automation which uses \u201cBig Data\u201d analytics to identify certain patterns or valuable information in the massive data collected and \u201cMachine Learning\u201d algorithms to \u201clearn\u201d from these analytics and draw conclusions. This is really the next generation of \u201cArtificial Intelligence\u201d technology and some people called \u201cA.I 2.0\u201d. An example of this is a \u201csmart computer\u201d that understands your questions and be able to give you the correct answers. Few years ago, IBM built a \u201csmart computer\u201d named \u201cWatson\u201d and taught it to answer thousands of questions from people. (If you want to see how it answers questions, you can go to YouTube and type Watson Computer or Jeopardy then you can see the entire show on how Watson defeats the best people by answering all questions faster than a human being). Now Watson is placed in hospital so it can \u201clearn\u201d how doctors are treating patients so in the near future, it can helps answer medical questions from patients. I believe Knowledge Work Automation will be very big in the next few years, especially to IT students who want to pursue a Master or PhD degree in this area because advances in software, especially machine-learning techniques such as deep learning and neural networks, are key factors of knowledge work automation as computers will be programmed to analyze data and draw conclusions as it learn more and get smarter. The more smart computers process big data, the more refined their algorithms will become as they are \u201clearning\u201d fast.<\/p>\n

Another \u201cHot\u201d area will be: Biotechnology\u2019s Genomics sequence or the next generation genomics where computer technology such as Big Data analytics are use to identify patterns and special characteristics of gene sequences and genetic materials to discover diseases before they happens or finding cures for diseases such as Diabetics, Cancers, Alzheimer etc. Before the application of Information Technology (IT) a human genome took 13 years and 2.7 billion to do (The Human Genome project 1990). Today in my laboratory at Carnegie Mellon, it only take few hours and about few thousand dollars using fast computing processing and Big Data algorithms. Soon hospitals will be able to use this new technology to diagnostic many diseases before they happen and people can take prevention actions so some diseases may not happen to them. Imagine that a computer analytics machine can tell you that you will have 80% of having lung cancer by the time you reach 30 years old so you will have to take special action such as quit smoking and take special medicines to reduce the chance. Today the application of computing technology such as Big Data analytics, Machine learning and Statistics are in high demand and I think they will be very big in the near future.<\/p>\n

Another \u201cHot\u201d area will be the application of Big Data analytics into the Oil and Mineral industries. By collecting information from many sources such as sensors data and energy materials extractions data, it is possible to map out all mineral deposits as well as oil fields on earth and increase discovery and recoverability rates. Instead of randomly drill for oil and mineral as it is used today, Big Data analytics and computing technology can be applied to help oil and mineral industries to find the exact location of oil fields, gas and mineral deposits and reduce discovery and operating cost significantly. According to the Oil industry survey, since the use of Big Data analytics in 2012 to analyze sensors and material extraction data, they were able to get 80% more accurate and reduce costs by billions of dollars. Oil companies and energy providers have found that there are huge opportunities in advancing oils and gas exploration and recovery process just by using this new technology. Therefore these companies need more IT workers who are specializing in Big Data analytics to help them extract meaningful information from their huge data collected. For example Shell Oil Company has over several petabytes of geological data collected but do not have enough workers who can analyze them. An oil spokesperson told Wall Street analysts: \u201cBy having enough workers in Big Data analytics, we can find exactly what we are looking for and reduce our operating cost by billion to trillion dollars in the next ten years. We are very happy about the potential of this emerging technology to help us raise our productivity, profitability as it will completely change the way our work is done.\u201d<\/p>\n

Basically everything that is in high demand today and in the near future will require knowledge workers with skills in Information Technology. As more industries are beginning to realize the potential of applying IT to improve their effectiveness, productivity and increase profits, it will drive massive demand for more workers and the IT skill shortage could be a major force in changing the economic power in the global competitiveness. Big Data analytics are the main driver in the future, if you are IT students (Computer Science, Software Engineering or Information Systems Management) you may consider to pursue a MS degree as it does require advance knowledge to work in these areas.<\/p>\n

Today the war for skilled workers already began but it will get more intense in the near future as all developed countries such as the U.S. UK, Germany, and France, already passed immigration laws to allow skilled workers to come and work. However some countries began to resist this \u201cBrain drain\u201d issue by developing their own advanced trainings in these areas to prevent their skilled people from leaving (China, India, Russia, Japan etc.). One Wall Street Analyst wrote: \u201cIn the past economic power is based on capital but today and in the future it will be based on skills, especially the application of IT skills in several industries such as Telecommunication, Manufacturing, Robotics, Healthcares, Pharmaceutical and Oil and Gas industries. Which country has more IT workers will be the winner in the economic power and the war for talents will spread across the globe. With globalization, companies will be concentrating on where they can find talents and establish their operating there. Therefore, IT will be the key enabler for economic prosperity for many years to come as every industry will need these knowledge workers.\u201d<\/p>\n","protected":false},"excerpt":{"rendered":"

M\u1ed9t sinh vi\u00ean vi\u1ebft cho t\u00f4i: \u201cTh\u1ea7y \u0111\u00e3 khuy\u00ean ch\u00fang em \u0111i theo xu h\u01b0\u1edbng c\u00f4ng nghi\u1ec7p \u0111\u1ec3 ch\u1ecdn l\u0129nh v\u1ef1c h\u1ecdc t\u1eadp d\u1ef1a tr\u00ean … <\/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-3499","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\/3499","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=3499"}],"version-history":[{"count":2,"href":"https:\/\/science-technology.vn\/index.php?rest_route=\/wp\/v2\/posts\/3499\/revisions"}],"predecessor-version":[{"id":3501,"href":"https:\/\/science-technology.vn\/index.php?rest_route=\/wp\/v2\/posts\/3499\/revisions\/3501"}],"wp:attachment":[{"href":"https:\/\/science-technology.vn\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=3499"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/science-technology.vn\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=3499"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/science-technology.vn\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=3499"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}