शैडोइंग अभ्यास: Don’t Start with AI, Start with the Problem - वीडियो के साथ अंग्रेजी बोलना सीखें

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हर मोड पूरी स्क्रीन का अभ्यास कक्ष खोलता है।

44 वाक्य
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-To build good AI products, we should start with three major steps, identifying problems that users experience, identifying how we might go about solving those problems, then identifying the technology that can help.
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The challenge is that these days, we so often start with selecting the technology and find a problem for it to solve later.
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With AI, this bad reverse order is even worse.
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More often than not, with AI, people are pressured to use AI for something, anything.
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In UX, we call this problem solutioneering.
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It's so common that we included it as our UX slogan number 18.
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Instead, we should be collecting issues that do exist, problems that users do experience.
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A good AI strategy begins with identifying unmet user needs, business challenges, or market opportunities, and then considering where AI might be a viable solution along with other alternatives.
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Let's talk about an example.
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Imagine a team at a FinTech company.
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The wrong way, the solutioneering way, starts with some sort of pressure from above.
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"We need to use AI to look innovative." The team decides to add a generic AI chatbot to their main credit card page.
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After months of work, they launch the chatbot, but users don't use it.
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Why? Because maybe the page already has a clear comparison table and customers can find what they need faster without talking to a bot.
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In this situation, the AI chatbot is a classic solution that solves no real user problem.
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A solution looking for a problem.
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Let's flip that.
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Let's take a look at an example of how we should approach building useful AI products.
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Step one, identify the user problem.
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Let's imagine that the team analyzes user data and sees that plenty of people abandon their online mortgage application halfway through.
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Through a few customer interviews, they quickly learn why.
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Customers are confused by financial jargon like APR or interest rate and feel anxious they're making the wrong choice.
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That's the problem.
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Step two, identify how to solve it.
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The goal is to reduce confusion and anxiety.
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They could create a glossary page, make explainer videos, or offer a live chat with a loan officer.
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Step three, identify the technology.
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This is where AI could actually help.
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A well-trained AI assistant could offer instant, in-context explanations for confusing terms 24-7.
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Success can be defined and would be easy to measure.
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A decrease in the number of abandoned mortgage applications.
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See the difference?
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We didn't start with AI.
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We started with a real user problem and found that AI was a fitting tool that might solve it.
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AI is just a tool that can solve problems.
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It shouldn't be assumed to be part of the solution unless you've started with the problems first and understood them clearly.
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Not only should we have identified legitimate problems, but ideally, we've had a discussion on how we'd recognize success by doing it.
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As much as we want to start with AI, we want to create good experiences.
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Start by identifying problems.
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Then, just maybe, AI could help solve those problems.
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-Thanks for watching.
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If you want to see more of our UX videos, take a look at these over here and consider subscribing to our channel.
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On our website nngroup.com, you can access our free library of over 2,000 articles.
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You can also register for one of our UX courses that offer live hands-on UX training.

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इस पाठ के बारे में

इस पाठ में, आप सीखेंगे कि उपयोगकर्ता की समस्याओं की पहचान कैसे करना है और एआई (AI) का उपयोग करते समय सही दिशा में कैसे आगे बढ़ना है। आप यह समझेंगे कि तकनीक का चुनाव करने से पहले आपके पास स्पष्ट रूप से परिभाषित समस्याएं होनी चाहिए। इस वीडियो में बताए गए उदाहरणों के माध्यम से, आप जानेंगे कि कैसे अच्छी एआई रणनीति बनाने के लिए उपयोगकर्ता की आवश्यकताओं को समझना जरूरी है। यह सामग्री अंग्रेजी बोलने का अभ्यास करने के लिए अत्यधिक उपयोगी है, खासकर अंग्रेजी शैडोइंग तकनीक के संदर्भ में।

मुख्य शब्दावली और वाक्यांश

  • समस्या पहचानना (Identifying problems)
  • उपयोगकर्ता अनुभव (User experience)
  • शब्दावली पृष्ठ (Glossary page)
  • ग्राहक साक्षात्कार (Customer interviews)
  • उपयोगकर्ता की आवश्यकता (User needs)
  • एआई सहायक (AI assistant)
  • सफलता मापना (Measuring success)
  • अवहेलना (Abandonment)

अभ्यास टिप्स

यह वीडियो एक निश्चित गति और स्वर में है, जिसे ध्यान में रखते हुए आप अंग्रेजी शैडोइंग अभ्यास कर सकते हैं। यहाँ कुछ चिकित्सीय सुझाव दिए गए हैं:

  • सुनें और बोलें: वीडियो को ध्यान से सुनें और उसके बाद उसकी नकल करें। यह आपकी उच्चारण और प्रवाह को सुधारने में मदद करेगा।
  • दौहराए जाएँ: किसी भी वाक्य को कई बार सुनें और बोलें। यह सुनिश्चित करेगा कि आप शब्दों और वाक्यों को सही तरीके से समझें।
  • ध्यान दें: मात्र एक बार सुनने से संतुष्ट न हों। पूरी ऑडियो को सुनें, विशेष रूप से उन हिस्सों पर ध्यान दें जहाँ उपयोगकर्ता के अनुभव के बारे में बात की जा रही है।
  • नोट्स लें: महत्वपूर्ण शब्द और वाक्यांश लिखें, जिन्हें आप अपने अभ्यास में शामिल करना चाहेंगे।
  • समय का प्रबंधन करें: नियमित अभ्यास के लिए एक निश्चित समय निर्धारित करें। यह shadowspeaks तकनीक को प्रभावी बनाने में मदद करेगा।

इस तकनीक को अपनाने से न केवल आपकी अंग्रेजी बोलने का अभ्यास बेहतर होगा, बल्कि आप समस्याओं की पहचान करने और उनका समाधान खोजने में भी कुशल हो जाएंगे।

इस वीडियो का व्याकरण

वक्ता जिन संरचनाओं का सबसे अधिक प्रयोग करता है, वीडियो के असली शब्दों के साथ:

संरचनावीडियो में
Passive voice be + past participle — ज़ोर इस पर कि क्या होता है, न कि कौन करता हैare pressured · can be defined · be assumed
Present perfect have/has + past participle — बीता हुआ काम जिसका असर अभी भी हैyou've started · have identified

शैडोइंग तकनीक क्या है?

शैडोइंग (Shadowing) एक विज्ञान-समर्थित भाषा सीखने की तकनीक है जो मूल रूप से पेशेवर दुभाषिया प्रशिक्षण के लिए विकसित की गई थी। विधि सरल लेकिन शक्तिशाली है: आप मूल अंग्रेज़ी ऑडियो सुनते हैं और तुरंत इसे ज़ोर से दोहराते हैं — जैसे वक्ता की छाया 1-2 सेकंड की देरी से। शोध से पता चलता है कि यह उच्चारण सटीकता, स्वर, लय, जुड़ी हुई ध्वनियाँ, सुनने की समझ और बोलने की प्रवाहशीलता में काफ़ी सुधार करता है।

शैडोइंग तकनीक: पूरी चरण-दर-चरण गाइड पढ़ें →