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Tiếp nối với phần 1, phần 2 chúng mình sẽ tiếp tục có những từ vựng 'khủng' sẽ xuất hiện nhiều trong các đề thi.Các bạn nhớ luyện đọc hàng ngày và take note những từ tâm đắc để áp dụng khi đi thi IELTS thật tốt nhé!

The Return of Artificial Intelligence

It is becoming acceptable again to talk of computers performing human tasks such as problem-solving and pattern-recognition

man wearing Sony PlayStation VR

It is becoming acceptable again to talk of computers performing human tasks such as problem-solving and pattern-recognition

A After years in the wildness, the term ‘artificial intelligence’ (AI) seems poised to make a comeback. AI was big in the 1980s but vanished in the 1990s. It re-entered public consciousness with the release of AI, a movie about a robot boy. This has ignited public debate about AI, but the term is also being used once more within the computer industry. Researchers, executives and marketing people are now using the expression without irony or inverted commas. And it is not always hype. The term is being applied, with some justification, to products that depend on technology that was originally developed by AI researchers. Admittedly, the rehabilitation of the term has a long way to go, and some firms still prefer to avoid using it. But the fact that others are starting to use it again suggests that AI has moved on from being seen as an over-ambitious and under-achieving field of research

B The field was launched, and the term ‘artificial intelligence’ coined, at a conference in 1956, by a group of researchers that included Marvin Minsky, John McCarthy, Herbert Simon and Alan Newell, all of whom went on to become leading figures in the field. The expression provided an attractive but informative name for a research programme that encompassed such previously disparate fields as operations research, cybernetics, logic and computer science. The goal they shared was an attempt to capture or mimic human abilities using machines. That said, different groups of researchers attacked different problems, from speech recognition to chess-playing, in different ways; AI unified the field in name only. But it was a term that captured the public imagination

C Most researchers agree that AI peaked around 1985. A public reared on science-fiction movies and excited by the growing power of computers had high expectations. For years AL researchers had implied that a breakthrough was just around the corner. Marvin Minsky said in 1967 that within a generation the problem of creating ‘artificial intelligence’’ would be substantially solved. Prototypes of medical-diagnosis programs and speech recognition software appeared to be making progress. It proved to be a false dawn. Thinking computers and household robots failed to materialize, and a backlash ensued. ‘There was undue optimism in the early 1980s’ says David Leake, a researcher at Indiana University. ‘Then when people realized these were hard problems, there was retrenchment. By the late 1980s, the term AI was being avoided by many researchers, who opted instead to align themselves with specific sub-disciplines such as neural networks, agent technology, case-based reasoning, and so on.’

D Ironically, in some ways AI was a victim of its own success. Whenever an apparently mundane problem was solved, such as building a system that could land an aircraft unattended, the problem was deemed not to have been AI in the first place. ‘If it works, it can’t be AI’, as Dr. Leake characterizes it. The effect of repeatedly moving the goal-posts in this way was that AI came to refer to ‘blue-sky’ research that was still years away from commercialization. Researchers joked that AI stood for ‘almost implemented’. Meanwhile, the technologies that made it on to the market, such as speech recognition, language translation and decision-support software, were no longer regarded as AI. Yet all three once fell well within the umbrella of AI research.

E But the tide may now be turning, according to Dr. Leake, HNC software of San Diego, backed by a government agency, reckon that their new approach to artificial intelligence is the most powerful and promising approach ever discovered. HNC claim that their system, based on a cluster of 30 processors, could be used to spot camouflaged vehicles on a battlefield or extract a voice signal from a noisy background – tasks humans can do well, but computers cannot. ‘Whether or not their technology lives up to the claims made for it, the fact that HNC are emphasising the use of AI is itself an interesting development,’ says Dr. Leake

F Another factor that may boost the prospects for AI in the near future is that investors are now looking for firms using clever technology, rather than just a clever business model, to differentiate themselves. In particular, the problem of information overload, exacerbated by the growth of e-mail and the explosion in the number of web pages, means there are plenty of opportunities for new technologies to help filter and categorize information – classic AI problems. That may mean that more artificial intelligence companies will start to emerge to meet this challenge

G The 1969 film, 2001: A Space Odyssey, featured an intelligent computer called HAL 9000. As well as understanding and speaking English, HAL could play chess and even learned to lipread. HAL thus encapsulated the optimism of the 1960s that intelligent computers would be widespread by 2001. But 2001 has been and gone, and there is still no sign of a HAL-like computer. Individual systems can play chess or transcribe speech, but a general theory of machine intelligence still remains elusive. It may be, however, that the comparison with HAL no longer seems quite so important, and AI can now be judged by what it can do, rather than by how well it matches up to a 30-year-old science-fiction film. ‘People are beginning to realise that there are impressive things that these systems can do,’ says Dr. Laeke hopefully

Nguồn: Cambridge ielts 5


turned on gray laptop computer

  1. Recognition /ˌrekəɡˈnɪʃn/: sự thừa nhận, ghi nhận
  2. Pattern /ˈpætn/: mẫu vẽ, khuôn, kiểu mẫu
  3. Artificial /ˌɑːtɪˈfɪʃl/: nhân tạo, giả
  4. Poise /pɔɪz/: giữ thăng bằng
  5. Swoop /swuːp/: xà xuống
  6. Consciousness /ˈkɒnʃəsnəs/: sự tỉnh táo, nhận thức
  7. Ignite /ɪɡˈnaɪt/: châm lên
  8. Executive /ɪɡˈzekjətɪv/: Bạn điều hành, quản trị / thành viên điều hành, quản trị
  9. Irony /ˈaɪrəni/: sự mỉa mai, châm biếm
  10. Inverted commas /ɪnˌvɜːtɪd ˈkɒməz/ = quotation marks /kwəʊˈteɪʃn mɑːks/: dấu nháy trên
  11. Hype /haɪp/: cường điệu
  12. Reason = justification /ˌdʒʌstɪfɪˈkeɪʃn/ sự bào chữa, biện hộ
  13. Admittedly /ədˈmɪtɪdli/: phải thú nhận rằng
  14. Rehabilitation /ˌriːəˌbɪlɪˈteɪʃn/: sự hồi phục, tái phục lại
  15. Over-ambitious /ˌəʊvəræmˈbɪʃəs/: quá tham vọng
  16. Motto /ˈmɒtəʊ/: phương châm, khẩu hiệu
  17. Coin /kɔɪn/: đặt ra một từ mới
  18. Figure / ˈfɪɡə(r)/: con số
  19. Indicate /ˈɪndɪkeɪt/: chỉ, dấu hiệu
  20. Encompass /ɪnˈkʌmpəs/: bao gồm, chứa đựng
  21. Cybernetics /ˌsaɪbəˈnetɪks/: điều khiển học
  22. Operation research /ˌɒpəreɪʃənl rɪˈsɜːtʃ/: vận trù học
  23. Disparate /ˈdɪspərət/:hoàn toàn khác nhau
  24. Mimic /ˈmɪmɪk/: nhại lại
  25. Unify /ˈjuːnɪfaɪ/: hợp nhất, thống nhất
  26. Capture /ˈkæptʃə(r)/: bắt giữ, lấy được, chiếm được
  27. Imply /ɪmˈplaɪ/: ngụ ý
  28. Consent /kənˈsent/: sự chấp thuận, bằng lòng
  29. Breakthrough /ˈbreɪkθruː/:bước tiến quan trọng, phát minh quan trọng
  30. Rear /rɪə(r)/: phía sau
  31. Rear on: lớn lên cùng với gì đó
  32. Reveller /ˈrevələ(r)/: người vui chơi ồn ào (say rượu)
  33. Substantially /səbˈstænʃəli/: phần lớn
  34. Prototypes /ˈprəʊtətaɪp/; nguyên mẫu
  35. Dawn /dɔːn/: bình minh, dấu hiệu bắt đầu
  36. The crack of dawn: sáng tinh mơ
  37. Civilization /ˌsɪvəlaɪˈzeɪʃn/: nền văn minh
  38. Materialise /məˈtɪəriəlaɪz/: cụ thể hóa
  39. Backlash /ˈbæklæʃ/: sự phản ứng tiêu cực dữ dội
  40. Conservative /kənˈsɜːvətɪv/: người bảo thủ , tính cách bảo thủ
  41. Riot /ˈraɪət/: cuộc náo loạn
  42. Protest /ˈprəʊtest/: sự phản kháng
  43. Ensure /ɪnˈʃʊə(r)/: tiếp nốim sinh ra từ
  44. Undue /ˌʌnˈdjuː/: quá mức = excessive
  45. Retrenchment /rɪˈtrentʃmənt/: sự cắt giảm chi tiêu
  46. Opt / ɒpt/ = choose : chọn
  47. Align /əˈlaɪn/: thẳng hàng
  48. Reasoning /ˈriːzənɪŋ/: lý lẽ, lập luận
  49. Faulty / ˈfɔːlti/ = defective /dɪˈfektɪv/ không hoàn hảo, có lỗi
  50. Mundane /mʌnˈdeɪn/: tầm thường, vô vị
  51. Unattended /ˌʌnəˈtendɪd/ bỏ mặc, không chịu sự giám sát
  52. Deem /diːm/: tưởng rằng, thấy rằng
  53. Characterise /ˈkærəktəraɪz/: biểu thị đặc điểm
  54. Commercialisation /kəˌmɜːʃəlaɪˈzeɪʃn/: thương mại hóa
  55. Implement /ˈɪmplɪment/: công cụ, dụng cụ / thi hành, thực hiện
  56. Within the umbrella: dưới sự kiểm soát, trong vòng của cái gì đấy
  57. Turn the tide: thay đổi tình thế, lật ngược ván cờ
  58. Reckon /ˈrekən/:nghĩ là, cho là
  59. Cluster /ˈklʌstə(r)/: đám, cụm, đàn
  60. Camouflaged /ˈkæməflɑːʒ/: sự ngụy trang
  61. Battlefield /ˈbætlfiːld/: chiến trường
  62. Encapsulate/ɪnˈkæpsjuleɪt/ = sum up: tổng kết lại
  63. Elusive /ɪˈluːsɪv/; khó nắm bắt, khó nhớ, khó hiểu
  64. Comparison /kəmˈpærɪsn/: sự so sánh
  65. Differentiate /ˌdɪfəˈrenʃieɪt/: phân biệt đối xử

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