雖然人工智能技術(shù)還需要繼續(xù)完善，但其將會越來越多的走進我們的工作及生活，其表現(xiàn)為：
大數(shù)據(jù)：大型非結(jié)構(gòu)化數(shù)據(jù)集培訓強大的機器智能，現(xiàn)在有大量的出現(xiàn)。例如，語言翻譯和圖像，面部，行為和情感識別 - 基于預測的分析在有充足數(shù)據(jù)支持的條件下變得更加準確。尤其對于社交媒體，其有大量的數(shù)據(jù)集可利用。據(jù)報告所指出，F(xiàn)acebook面部識別領域有所成功，而谷歌在機器翻譯領域通過搜集大量的多語種文檔而獲得優(yōu)勢。展望未來人工智能必將在大數(shù)據(jù)中得到重要的應用。
軟件和硬件的進步：神經(jīng)網(wǎng)絡和并行處理將是人工智能的重要發(fā)展工具，因為它們更接近于人類大腦的工作方式。特別是，基于GPU計算的出現(xiàn)可以大大加快神經(jīng)網(wǎng)絡的處理能力。 總之，深度學習軟件和并行處理硬件現(xiàn)在提供了一個功能強大的[機器智能]平臺。
云計算的商業(yè)模式：云計算是機器學習商業(yè)模式的強大動力，據(jù)報告：“我們基本上看到機器智能與云計算經(jīng)濟的重合?！痹朴嬎阒?，大多數(shù)人工智能的工作是孤立的，成本比較高，但與云計算相結(jié)合后，機器學習能力，如識別人臉或語言翻譯，會既便宜又好用
Three reasons why AI is taking off right now (and what you need to do about it)
From ZDNet
Three factors are combining to create a tipping point after which the use of artificial intelligence will become commonplace.
According to the Leading Edge Forum - the research arm of tech vendor CSC - while there is still plenty of work to do, the three main ingredients needed for AI to take off are now in place:
Big Data: Large unstructured data sets are handy for training powerful machine intelligence and there are now plenty of these around. Initiatives such as language translation and image, facial, activity and emotion recognition - are based on predictive analytics that get more accurate as the data behind them gets richer. And the rise of big data - and social media in particular - means there are lots of data sets to exploit. As the report notes, Facebook enjoys a huge head start in facial recognition because it can already match our names and faces, just as Google has important advantages in machine translation because it has aggregated the best set of multilingual documents.
"Looking ahead, new and established MI companies will use millions of internet images, videos and podcasts of people smiling, laughing, frowning, talking, arguing, holding hands, walking, playing football and so on as the basis for unprecedented emotion and activity recognition capabilities. MI is now clearly among the most important Big Data applications."
Software and hardware advances: It's long been known that neural networks and parallel processing would be important development tools of AI because they more closely resemble the way the human brain works. In particular, the emergence of GPU-based computing can greatly accelerate neural network processing capabilities - and if more processing power is needed there are the vast cloud computing resources of Amazon, Microsoft, Google. "Taken together, deep learning software and parallel processing hardware now provide a powerful [machine intelligence] platform," the report said.
Cloud business models: The emergence of machine learning business models based on the use of the cloud is the single biggest reason that the field is so energized today, the report said: "We are essentially seeing the merger of machine intelligence with cloud economics."
Before the cloud, most AI work was isolated and relatively high cost, but the economics of the cloud mean machine learning capabilities, such as recognizing faces or translating languages, will cheap and easy to use
"It is this realization that is triggering both the explosion of highly specialized MI start-ups, as well as the major machine intelligence pushes at Google, Facebook, Microsoft,Apple, IBM and their various global rivals."
The researchers set out a 10 point plan for organisations that want to prepare for machine intelligence:
1. Embrace the idea that machine intelligence will matter to your organization.
2. Identify which forms could be most important to your firm.
3. Check out relevant start-ups and developments.
4. Understand which parts of your firm could be safely run by algorithms.
5. Determine which internal and external data sets have the most potential.
6. Assess the extent to which your firm's key professional expertisecan be automated.
7. Try out deep learning, neural computing and other technologies.
8. Map the relevant MI services and technologies to your firm's value chain.
9. Develop machine intelligence experts in your organisation.
10. Factor AI advances into your strategic planning.
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