直覺并不總是正確，但當(dāng)每次商業(yè)領(lǐng)袖被問及如何決策時(shí)，他們總會(huì)提到直覺的作用，即便在高級(jí)分析工具盛行的當(dāng)下也是如此。

今年7月11日，在舊金山，由前谷歌員工創(chuàng)立的初創(chuàng)企業(yè)Node發(fā)布了所謂“下一波人工智能浪潮”：人工直覺。Node視之為劃時(shí)代的工具。

Node的創(chuàng)始人及首席執(zhí)行官法倫·法塔米表示，團(tuán)隊(duì)能夠教會(huì)計(jì)算機(jī)產(chǎn)生人類獨(dú)有的知覺。她還表示，計(jì)算機(jī)編程的直覺可以幫助商業(yè)領(lǐng)袖對(duì)未來做出更好的決策，甚至可以預(yù)測(cè)出員工想跳槽。

《財(cái)富》雜志與法塔米就人工直覺話題進(jìn)行了對(duì)話，也討論了計(jì)算機(jī)與直覺的聯(lián)系能否比人類更緊密。

《財(cái)富》：人類的直覺通常來源于過往經(jīng)驗(yàn)。如何才能在某行業(yè)引入人工直覺，并讓人工直覺具備人類積累多年才能夠達(dá)到的智慧呢？

法塔米：人工直覺與大腦相似，能夠分析大量不同的信息，區(qū)別在于人工直覺可以分析的信息規(guī)模更大，還能夠從不同的結(jié)果中學(xué)習(xí)，然后基于結(jié)果進(jìn)行預(yù)測(cè)。隨著時(shí)間的推移，人工直覺也會(huì)越發(fā)智能和準(zhǔn)確。

只需提供你所關(guān)心的人員或公司的樣本數(shù)據(jù)集合，系統(tǒng)就能夠從中提取預(yù)測(cè)所需的信息并構(gòu)建模型，生成高度精確的預(yù)測(cè)結(jié)果。有了人工智能，人們不再需要定義什么是“最優(yōu)解”，人工智能會(huì)通過查看樣本集合，自主分析數(shù)據(jù)，自動(dòng)給出答案。

人類的直覺有時(shí)都不準(zhǔn)確，為什么還要聽計(jì)算機(jī)的直覺呢？

關(guān)于人工直覺的問題可以這么理解：我們每天做決定時(shí)都會(huì)用到直覺，對(duì)吧？要不要采訪，晚餐吃什么，相親時(shí)要不要帶兩個(gè)朋友。在這些情境中我們都會(huì)用到直覺，具體情境決定了最終做出怎樣的決策，以及要考慮哪些因素。隨著時(shí)間的推移，人的直覺會(huì)不斷發(fā)展提升，Node的人工智能也一樣，可以從結(jié)果中不斷學(xué)習(xí)不斷進(jìn)步，而且不只針對(duì)個(gè)案，使用該平臺(tái)的每家企業(yè)和個(gè)人用戶都能夠從中受益。

企業(yè)如何使用人工直覺協(xié)助決策？能夠?qū)W到什么?

人工直覺可以為每個(gè)Node賦能的應(yīng)用、用戶和案例提供獨(dú)到的智能決策。例如，新客戶很可能在哪？哪些潛在客戶可能與你做一筆大買賣，或者帶來新機(jī)會(huì)？又或者哪名員工可能會(huì)離職。

作為經(jīng)理，了解關(guān)鍵員工會(huì)不會(huì)離職是一項(xiàng)非常重要的工作。越早知道員工有離職想法越好，知道得越早就能夠采取措施避免走到離職那一步。人工直覺也可以幫助企業(yè)決定投資哪家初創(chuàng)公司。

你跟一些客戶合作進(jìn)行了測(cè)試，效果如何?

從商業(yè)成果的角度來看，我們發(fā)現(xiàn)該系統(tǒng)不僅能夠準(zhǔn)確預(yù)測(cè)并找到更多的潛在客戶，例如有可能迅速轉(zhuǎn)化的潛在客戶，還可以幫助客戶找出傳統(tǒng)策略發(fā)掘不了的新市場(chǎng)。這就是人工直覺技術(shù)的力量。其本質(zhì)就是將數(shù)據(jù)轉(zhuǎn)化為決策，既能夠根據(jù)特定背景分析具體案例，又可以吸取終端用戶最成功的直覺經(jīng)驗(yàn)。

作為預(yù)測(cè)行業(yè)的從業(yè)者，你對(duì)企業(yè)使用人工直覺的前景有什么看法？

現(xiàn)在的情況是，企業(yè)要么創(chuàng)新，要么衰亡。無(wú)論是企業(yè)產(chǎn)品及核心價(jià)值層面，下一波大型科技企業(yè)都會(huì)將人工智能放在首位。對(duì)于死守傳統(tǒng)系統(tǒng)小修小補(bǔ)、幾乎無(wú)法適應(yīng)而難以跟上節(jié)奏的企業(yè)，只有投入數(shù)百萬(wàn)美元的資金及多年的時(shí)間才能夠避免從科技戰(zhàn)爭(zhēng)中淘汰出局。

我們?cè)谧龅氖菐椭髽I(yè)利用現(xiàn)有資源釋放自身能力。每個(gè)工程師都能夠使用Node構(gòu)建最先進(jìn)的預(yù)測(cè)模型，從而實(shí)現(xiàn)其應(yīng)用最初想實(shí)現(xiàn)的目標(biāo)。

我們已經(jīng)習(xí)慣了使用人工智能助手，例如Siri和Alexa。在您看來，未來人工直覺會(huì)不會(huì)走進(jìn)人類日常生活，協(xié)助決策或提醒某些事項(xiàng)？

下一波創(chuàng)新浪潮將來自企業(yè)。這也就意味著，未來每個(gè)人都可以擁有自己的人工直覺助手，助手的任務(wù)就是幫助人們發(fā)現(xiàn)機(jī)會(huì)，甚至在沒有想起來搜索的時(shí)候就把機(jī)會(huì)呈現(xiàn)在眼前。可能是給“這本書能夠改變?nèi)松瑧?yīng)該讀一讀”，也可能是“這個(gè)工作機(jī)會(huì)不錯(cuò)，值得一試”，我認(rèn)為這是長(zhǎng)遠(yuǎn)發(fā)展的方向，也能夠切實(shí)改善每個(gè)人的生活。（財(cái)富中文網(wǎng)）

譯者：Charlie

審校：夏林

Gut feelings aren’t always correct, but ask any business leader how they make decisions, and intuition almost always plays a role—even in the age of advanced analytics.

Positioning itself as a tool of the times, Node, a San Francisco based startup founded by an ex-Google employee, announced on July 11 what it calls the next wave of artificial intelligence: artificial intuition.

Node founder and CEO Falon Fatemi says her team has been able to teach a computer the uniquely human sensation of having a hunch. Not only that, but she says that computer-programmed gut feelings can help business leaders make better decisions about the future, even predicting when an employee is looking for a new job.

Fortune talked to Fatemi about artificial intuition and whether a computer can be more in touch with its intuition than humans.

Fortune: When humans have a hunch, it’s usually based on past experiences. How can you bring artificial intuition into a business and teach it the same wisdom that humans who have worked there for years already have?

Fatemi: It is kind of like how our human brains can analyze a lot of different points of information, but this thing can do it at scale, learn from those outcomes, and then drive predictions. It just gets smarter and better over time.

All that it requires is a set of examples of people or companies that represent the outcome that you care about. That number of examples can help the system pick up enough of a predictive sniff to then build a model and be able to generate predictions of a very high accuracy. Artificial intelligence does not require you to try and define what “best” means. It figures it out by just looking at a set of examples and analyzing that data in an autonomous fashion.

Human intuition isn’t always accurate. Why should people listen to a computer’s gut feeling?

The way to think about artificial intuition is like this: You use your intuition every day to make decisions, right? Whether you should take that interview, what you should eat for dinner, whether you should set up two friends on a blind date. You’re using your intuition in all of these situations, but the context of the situation determines which decision you make, and what factors drive that decision. Just like your personal intuition evolves and improves over time, Node’s AI learns from the outcomes it drives to get better—not just for each use-case, but for each company and each user that leverages the platform.

What are some ways businesses can lean on artificial intuition to help them make decisions? What can they learn from it?

Artificial intuition makes intelligent decisions that are unique to each application, user, and use-case that’s Node-powered. So for example, who your next customer is likely to be; being able to have the Node system be able to show you which of your prospects are likely to result in that next big deal or opportunity; or which employee is likely to leave their job.

As a manager, it’s really important to know if a key employee might be leaving the job. You’d want to know that today so that you could do something today to prevent that outcome from happening, or perhaps which new start-up that you should invest in.

You have been testing this with some customers. What have you learned from the results?

What we’ve seen, from a business outcomes perspective, is the system is not only able to predict accurately and find more prospects—such as those best prospects that are likely to convert very quickly—but the system has actually been able to navigate and identify new markets of opportunity that were previously untapped by those customers using traditional heuristics-based methods. And that’s the power of this technology. It essentially turns data into decisions—both the context-specific that it’s analyzing within an application, and also learning from the intuition that the end-users have as to where they’re most successful.

You’re in the business of making predictions. How do you see companies using artificial intuition in the future?

We’re in a situation where enterprises need to innovate or die. The next wave of big tech companies are all going to be AI-first, both in terms of their products and their core DNA. For the organizations that frankly cannot keep up because they built legacy system on top of legacy system, and their ability to adapt is frankly near impossible—they’re going to spend millions of dollars and years just trying to engage in this talent war.

What we are doing is we are democratizing the ability for all of these companies with their existing resources. Any engineer can [use Node] to build a cutting-edge prediction model around the business outcomes that their applications were initially built to drive.

We are already used to using artificially intelligent assistants, like Siri and Alexa. Do you envision a future where artificial intuition might also help us make decisions or warn us about something in our personal lives?

The next wave of innovation is going to come from the enterprise. What that’s going to mean is that in the future, everyone should have their own artificial intuition agent whose job is to identify opportunities to you and put those in front of you before you even know to search for them. Whether it’s “here’s the next book you should read that is going to change your life” or “here is the next job opportunity you should take a look at,” I think that’s longer term where this can go, and really empower all of us.