open ai gpt

重點 (Top highlight)

“設(shè)計師”插件 (The ‘Designer’ plugin)

A couple days ago, a tweet shared by Jordan Singer turned the heads of thousands of designers. With the capabilities of GPT-3 (from OpenAI), he shared a sample of what he was able to create: a Figma plugin (called ‘Designer’) that has the ability to generate a functional prototype from raw text. If you haven’t seen it yet, you can view the video of his demo above.

幾天前， 喬丹·辛格(Jordan Singer)分享的一條推文吸引了成千上萬名設(shè)計師的目光。 借助GPT-3(來自O(shè)penAI)的功能，他分享了自己能夠創(chuàng)建的示例：Figma插件(稱為“ Designer”)，它能夠從原始文本生成功能性原型。 如果您還沒有看過，可以在上方觀看他的演示視頻。

As you can see, what’s written in the described raw text accounts for all the desired functionality and visual/graphical characteristics. Singer keys in:

如您所見，所描述的原始文本中的內(nèi)容說明了所有所需的功能和視覺/圖形特性。 歌手輸入：

“An app that has a navigation bar with a camera icon, “Photos” title, and a message icon, a feed of photos with each photo having a user icon, a photo, a heart icon, and a chat bubble icon”

“具有導(dǎo)航欄的應(yīng)用程序，其中帶有帶有照相機圖標(biāo)，“照片”標(biāo)題和消息圖標(biāo)的導(dǎo)航欄，每張照片具有用戶圖標(biāo)，照片，心形圖標(biāo)和聊天氣泡圖標(biāo)的照片供稿”

Clicks Design — done.

單擊設(shè)計-完成。

The plugin works its magic and then voila — Everything written in appears as requested. He wanted a photo? He got it. He wanted a ‘heart’ icon? No problem. A feed of photos? Done. AI in this example, was not only able to correctly identify the UI elements to be used in the design, but to also intelligently discern the placement of it on the layout as well. So, without a single line of code (in the conventional sense), we have here a very early look into what’s possible in the years to come, as the technology continues to evolve for UX Design.

該插件發(fā)揮了神奇的作用，然后瞧瞧-寫入的所有內(nèi)容均按要求顯示。 他想要一張照片嗎？ 他明白了。 他想要一個“心臟”圖標(biāo)嗎？ 沒問題。 提要照片嗎？ 做完了 在此示例中，AI不僅能夠正確識別要在設(shè)計中使用的UI元素，而且還可以智能地識別其在布局上的位置。 因此，在沒有一行代碼的情況下(按照常規(guī)意義)，隨著UX設(shè)計技術(shù)的不斷發(fā)展，我們將在很短的時間內(nèi)對未來幾年的可能性進行研究。

The responses and retweets were fast and furious. After wading through the comment section on that tweet, it was clear that the collective sentiment in the community was divided. You would read everything from:

回復(fù)和轉(zhuǎn)推既快速又憤怒。 在瀏覽了有關(guān)該推文的評論部分之后，很明顯社區(qū)中的集體情感是分歧的。 您將從以下內(nèi)容中讀取所有內(nèi)容：

“We’re going to get automated — it’s just a matter of time.”

“我們將實現(xiàn)自動化-這只是時間問題。”

to

至

“Graphic designers are probably still significantly safer than UX “designers”

“圖形設(shè)計師可能仍然比UX“設(shè)計師”安全得多。

to

至

“If all you’re able to create through this is an app that looks like a knockoff of Instagram, we have nothing to freak out about.”

“如果您能通過此程序創(chuàng)建的所有應(yīng)用程序看起來像是Instagram仿制品，那么我們就沒什么好擔(dān)心的。”

And as we speak, the discussions continue. But, regardless of where you stand, or how you view this, it’s first worth noting that this isn’t anything new in particular.

在我們發(fā)言時，討論仍在繼續(xù)。 但是，無論您身在何處或如何看待它，首先要注意的是， 這并不是什么新鮮事物。

之前我們已經(jīng)看到過更多極端的技術(shù)示例 (We’ve seen even more extreme examples of technology like this before)

生成設(shè)計 (Generative design)

Although this new plugin has surprised, scared and even inspired some of us, the above demonstration is not the first of its kind. In fact, we’ve already seen even more extreme, sophisticated outputs of AI-powered, computational design in related fields, like architecture.

盡管這個新插件使我們中的某些人感到驚訝，害怕甚至受到啟發(fā)，但上述演示并不是同類中的第一個。 實際上，我們已經(jīng)在架構(gòu)等相關(guān)領(lǐng)域中看到了AI驅(qū)動的計算設(shè)計的更極端，更復(fù)雜的輸出。

If we take a moment to consider Generative design, this process allows designers and engineers to input constraints into an AI system that then automatically generates all structural permutations.

如果我們花一點時間考慮生成設(shè)計 ，則此過程允許設(shè)計人員和工程師將約束輸入到AI系統(tǒng)中，然后自動生成所有結(jié)構(gòu)排列。

Collaboration between Autodesk and Airbus to design and 3D print a groundbreaking new partition for the A320.Autodesk與空中客車公司之間的合作，以設(shè)計和3D打印A320的突破性新分區(qū)。

Teams only need to select what they believe to be is the perfect solution from all its variants — based on the performance data. After having selected a design, the system produces outputs from the results of these tests. Then with these results, the system automatically creates updates towards subsequent iterations. Without being limited to what the human mind is capable of conceiving at any given time, the system can do it all for you.

團隊只需根據(jù)性能數(shù)據(jù)從所有變體中選擇他們認(rèn)為是最佳的解決方案。 選擇設(shè)計后，系統(tǒng)將根據(jù)這些測試的結(jié)果產(chǎn)生輸出。 然后，根據(jù)這些結(jié)果，系統(tǒng)會自動創(chuàng)建針對后續(xù)迭代的更新。 不受限于任何給定時間的人類思維能力，系統(tǒng)可以為您完成所有工作。

Autodesk — Generative Design overviewAutodesk-生成設(shè)計概述

Now that may have completely knocked the wind out of your sails, or you may feel totally inspired. Regardless of how approach it, a conclusion as we come to see, is that these new technologies render design to becoming less and less a specialty skill in this particular sense. The barriers that prevent the creation of great design is diminishing; and it’s terrifying to think that, considering so much of our identity is tied to our craft and our abilities to produce. Naturally, questions like the following emerge:

現(xiàn)在，這可能完全消除了風(fēng)，或者您可能會感到完全受啟發(fā)。 無論采用何種方法，我們都會得出一個結(jié)論，即這些新技術(shù)使設(shè)計在這種特定意義上的專業(yè)技能越來越少。 阻礙創(chuàng)造出色設(shè)計的障礙正在減少； 想到如此多的身份與我們的Craft.io和生產(chǎn)能力息息相關(guān)，這真是令人恐懼。 當(dāng)然，會出現(xiàn)類似以下的問題：

“Will designers have a job in the next few years?”

“設(shè)計師將在未來幾年找到工作嗎？”

“Will we be made irrelevant?”

“我們會變得無關(guān)緊要嗎？”

“Do I need to learn to understand how AI works?”

“我需要學(xué)習(xí)了解AI的工作原理嗎？”

“If engineers hold user interviews and conduct usability tests, are we all doomed?”

“如果工程師進行用戶訪談并進行可用性測試，我們注定要失敗嗎？”

The answer to the above is not so black and white. When we think about what technology effectively allows for, there’s no denying that a lot of what constitutes the domain of design can be deferred to a machine.

上面的答案不是那么黑白。 當(dāng)我們考慮技術(shù)有效地支持什么時，不可否認(rèn)的是，構(gòu)成設(shè)計領(lǐng)域的許多內(nèi)容都可以歸結(jié)到機器上。

“那么我們對人工智能和自動化的態(tài)度應(yīng)該是什么？ 作為設(shè)計師，我們?nèi)绾伪３謨r值和身份不變？” (“So what should our posture be towards AI and automation? How do we keep our value and identities as designers intact?”)

The AEC team at Autodesk who are developing the AI-powered generative design technology, adopted a very forward-thinking mindset that I found incredibly profound. Meyer says,

正在開發(fā)以AI為動力的生成設(shè)計技術(shù)的Autodesk的AEC團隊采用了一種非常具有前瞻性的思維方式，我發(fā)現(xiàn)這是極其深刻的。 邁耶說，

“You’re not mastering the tool any longer, you’re mastering the problem — and letting the computer do all the work.” — Caleb Meyer, Project Industrial Designer

“您不再需要掌握該工具，而是可以解決問題，讓計算機完成所有工作。” —項目工業(yè)設(shè)計師Caleb Meyer

By shifting its focus away from individual capabilities and towards technological ones, they’re able to channel their efforts towards things that mattered more to them than their own abilities — the problem. If you put your focus and energy towards creating the best possible experiences, you will never be irrelevant. We can recognize AI and its abilities to automate, as a partnership towards our work as designers.

通過將重點從個人能力轉(zhuǎn)移到技術(shù)能力，他們能夠?qū)⒆约旱木D(zhuǎn)移到對他們而言比自身能力更重要的事情上-問題。 如果您將精力和精力放在創(chuàng)造最佳體驗上 ，那么您將永遠(yuǎn)沒有關(guān)系。 作為設(shè)計師的合作伙伴，我們可以認(rèn)識到AI及其自動化能力。

反思一下我們?nèi)绾谓邮茏詣踊?#xff0c;以幫助我們專注于最重要的事情-創(chuàng)造性地解決問題 (Reflect on how we’ve already embraced automation to help us focus on what matters most — creative problem solving)

Let’s reflect on the general impact of automation in UX Design, for example. The creative industry welcomed Zeplin.io back in 2015 to automatically spec our high-fidelity designs for us. Gone were the days when the width, height, colours, drop shadows needed to be manually defined — a platform did it all for us. It removed a layer of painstaking labour to our workflow that freed up our time to work on other creative pursuits.

例如，讓我們來思考一下自動化在UX Design中的一般影響。 創(chuàng)意產(chǎn)業(yè)早在2015年就歡迎Zeplin.io為我們自動指定我們的高保真設(shè)計。 需要手動定義寬度，高度，顏色，陰影的日子已經(jīng)一去不復(fù)返了，一個平臺為我們完成了所有工作。 它為我們的工作流程省去了費力的工作，從而騰出了時間來從事其他創(chuàng)造性工作。

In that same vein, the emergence of design systems serving as the overarching framework for consistent, usable experiences effectively did the same for us when Google’s Material Design was first introduced back in 2014. UI components with pre-written code snippets could be re-used, instead of creating from scratch — the design system standardized it all for us. It helped ensure our designs were consistent, usable and visually on brand.

同樣，當(dāng)2014年首次推出Google的Material Design時，出現(xiàn)了用作一致，可用體驗的總體框架的設(shè)計系統(tǒng)，實際上對我們做了同樣的事情。可以重復(fù)使用帶有預(yù)編寫代碼段的UI組件，而不是從頭開始創(chuàng)建-設(shè)計系統(tǒng)為我們實現(xiàn)了所有標(biāo)準(zhǔn)化。 它有助于確保我們的設(shè)計是一致的，可用的并且在品牌上具有視覺效果。

So, as we now consider the automation of the craft itself, AI will expedite our workflow in a way where some of that grunt work will no longer bury us in tedium. This will allow for more creative exploration and imaginative thinking — freeing us to discover new design paradigms. In the case of AI, it’s a matter of harnessing it. Do as what AEC is doing at Autodesk and make it about solving the problem and leave the rest to the machines.

因此，當(dāng)我們現(xiàn)在考慮Craft.io本身的自動化時，人工智能將以某種方式加速我們的工作流程，使某些繁瑣的工作不再將我們埋在乏味中。 這將允許進行更多的創(chuàng)造性探索和富于想象力的思考-使我們能夠發(fā)現(xiàn)新的設(shè)計范例。 就AI而言，這是利用它的問題。 按照AEC在Autodesk中所做的事情做，并解決問題，然后將其余問題留給機器處理。

Upon further reflection of the ‘Designer’ plugin demo, we as the audience were enamoured by the wrong thing. We were enamoured by the tool, instead of the designer himself (in this case, Jordan). What this does, is pigeon hole our discipline to a very specific area in the craft alone, rather than the individual who discerns how to harness the technology behind the keyboard. At the end of the day, the means to value-adding experiences will always get quicker, faster and more efficient. But the empathic human, understanding the needs faced by everyday people, curating that experience in the first place, will always be relevant and depended upon to solve real-world challenges.

在進一步思考“ Designer”插件演示后，我們作為觀眾迷戀了錯誤的事物。 我們迷上了該工具，而不是設(shè)計師本人(在本例中為Jordan)。 這樣做的結(jié)果是，僅在手Craft.io領(lǐng)域的某個特定領(lǐng)域就放飛了我們的學(xué)科，而不是識別如何利用鍵盤背后的技術(shù)的個人。 歸根結(jié)底，增值體驗的手段將永遠(yuǎn)變得越來越快，越來越快，效率越來越高。 但是，善解人意的人，要理解日常人們所面臨的需求，并從頭開始培養(yǎng)這種經(jīng)驗，將始終具有相關(guān)性，并依賴于解決現(xiàn)實世界中的挑戰(zhàn)。

UX Para Minas Pretas (UX For Black Women), a Brazilian organization focused on promoting equity of Black women in the tech industry through initiatives of action, empowerment, and knowledge sharing. Silence against systemic racism is not an option. Build the design community you believe in.UX Para Minas Pretas (UX For Black Women)，這是一個巴西組織，致力于通過采取行動，賦權(quán)和知識共享的舉措來促進科技行業(yè)中的黑人女性平等。 對系統(tǒng)性種族主義保持沉默是不可行的。 建立您相信的設(shè)計社區(qū)。

翻譯自: https://uxdesign.cc/lets-talk-about-that-gpt-3-ai-tweet-that-shook-designers-to-the-core-d2b31ad3d63b

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