思考：未來計算機邁向新的里程碑
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????我們正進入一個全新的計算時代。 ????過去半個世紀里，我們已經歷了一系列的計算時代。古典計算時代始于上世紀50年代，并在六七十年代開始加速發展。古典計算機階段，大型主機進行一系列行動，使得銀行、保險公司以及制造企業等大型機構的效率得以大幅提升。通用微型計算機在上世紀70年代風行，緊隨其后出現的是功能強大的UNIX工作站。隨后，個人電腦在1981年憑借IBM個人電腦大獲成功，并迅速發展為客戶服務器計算機模式。互聯網在上世紀90年代再一次顛覆了整個產業。 ????盡管取得了上述進步，但我們的系統已演進到高度復雜的形態，單單維護自身現有的計算機系統就需要各機構投入信息技術預算的70%甚至更多。結果導致只剩下很少的預算可用于想出創新方法來使用計算機技術。更重要的是，IBM以及行業分析機構IDC 近來的一份研究顯示，三分之二的企業信息技術項目都超出了預算，且落后于進度。 ????哪些需要作出改變？ ????公司與個人一樣，希望只要一連上計算機系統，它們就能立即開始運轉。它們希望軟硬件能立即協同工作。它們希望一切事務得到簡化并實現自動化。好消息是，技術將在現有基礎之上繼續發展，而發展方式可能令人吃驚：也就是能“學習”的系統以及能“思考”的系統。 |
????We're entering a whole new era of computing. ????Over the past five decades, we've moved through a series of eras of computing. The era of classical computing began in the 1950s and picked up speed in the 1960s and 1970s. This classical computing, where mainframes operate in a series of actions, enabled large organizations -- such as banks, insurance companies and manufacturing companies -- to operate with greater efficiency. Mini-computers became the rage in the 1970s, followed immediately by high function UNIX workstations. Then, personal computers took off in 1981 with IBM (IBM) PC and quickly evolved into the client-server computing model. The World Wide Web changed the industry yet again throughout the 1990s. ????Despite all the advances, we've evolved highly complex systems that require organizations to spend 70% or more of their IT budgets on just maintaining their existing computer systems. There's very little left over to come up with innovative ways to use much of that technology. What's more, two-thirds of corporate IT projects are delivered over budget and behind scheduled, according to a recent study by IBM and industry analyst firm IDC. ????What needs to change? ????Much like individuals, companies want to be able to plug in their computing systems and have them work "out of the box." They want the hardware and software to work together immediately. They want things simplified and automated. The good news is that technology will evolve on top of the technology base in ways that will likely be startling: systems that can "learn" and systems that can "think." |
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????思考是人類獨有的本領。坦率地說，科學事實上并沒有揭示人類思考的奧秘。我們大腦中有一種非凡的本領，能將某一事物與其他事物聯系起來。比如說，當我們互相交談時，我們的頭腦在我們努力解決問題時不斷跳躍。我們能看到模型、關系以及關聯。人類頭腦的運行方式尚不太清楚，因為它們不像電腦一樣，依次審查事物。 ????全新形式的計算機將不斷涌現。計算機正滲透到我們工作生活中的點點滴滴、方方面面。計算機識別物體的能力越來越強。雖然計算機沒有眼睛，但人們可以通過外部接入的設備向它輸入識別信息，而計算機可以借此識別人物、方位地點或各種東西。計算機還會在許多方面化作無形，以難以預料的方式成為世界的一部分，但有一點很確定，那就是科技一定會更多地出現在人們生活中。將來，我們身邊會出現各種計算機，能幫助我們更加高效地處理各類事務。也許有一天，計算機將和人類的大腦一樣，也會形成一種特定的聯系。 |
????Thinking is something uniquely human. And frankly, science does not really understand how we do it. We have this extraordinary ability in our brains to associate things with one another. As we talk with one another, for instance, our brains leap ahead as we work on solving problems. We see patterns and relationships and associations. It's not quite clear how the human brain works because it does not go through everything in a series, as computers do. ????New computing paradigms are going to emerge. Computing is going into everything, everywhere. Computers are getting better at recognizing things. Computers cannot see, but you will be able to put devices that can feed recognition information into the computer, which can identify people, places or things. Computing will also become in many ways invisible and part of the world in ways that are hard to predict -- except to say that technology will abound even more. It's going to surround us in a way that makes everything that we do more efficient and more effective. There may be a time in the future when computers incorporate a certain type of associations as humans do. |
