{"id":26036,"date":"2022-12-27T11:06:31","date_gmt":"2022-12-27T11:06:31","guid":{"rendered":"https:\/\/mailinvest.blog\/index.php\/2022\/12\/27\/dall-e-2-chatgpt-to-push-ai-into-the-forefront-of-2023\/"},"modified":"2022-12-27T11:06:31","modified_gmt":"2022-12-27T11:06:31","slug":"dall-e-2-chatgpt-to-push-ai-into-the-forefront-of-2023","status":"publish","type":"post","link":"https:\/\/mailinvest.blog\/index.php\/2022\/12\/27\/dall-e-2-chatgpt-to-push-ai-into-the-forefront-of-2023\/","title":{"rendered":"Dall-E 2, ChatGPT to Push AI Into the Forefront of 2023"},"content":{"rendered":"

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After years in which artificial intelligence-generated content was known more for its comic absurdity<\/a>\u2014only occasionally drifting into disconcerting realism<\/a>\u20142022 was the year that generative AI finally graduated into a full-fledged creative force.<\/p>\n

A host of realistic image generators led by research group OpenAI\u2019s Dall-E 2 made it easy for anyone to create lifelike visuals<\/a> with a simple text prompt. Meanwhile, OpenAI\u2019s ChatGPT put a conversational interface on the organization\u2019s state-of-the-art text generation system, allowing users to simply instruct a machine what to write and receive a detailed and rhetorically sound\u2014if not always factually correct\u2014passage in seconds. <\/p>\n

These new systems, trained on datasets that span hundreds of millions of images and pages of text, respectively, have already led to widespread experimentation among brands, agencies, burgeoning startups<\/a> and creative tool integrations<\/a>.<\/p>\n

But experts say 2023 will be the year that brand marketers and agencies start to get serious about how synthetic content of this sort can actually be deployed to serve bottom lines and augment human creativity. That proliferation will also come with a bevy of new risks that marketers will need to confront, from machine copyright infringements<\/a> to concerns around vetting content authenticity.<\/p>\n

Mark Curtis, head of innovation at Accenture Song and author of the firm\u2019s yearly tech trends report, said generative AI is likely the most important technological shift he\u2019s cataloged in the last five to 10 years. <\/p>\n

\u201cThe things that agencies should be doing is beyond experimenting with this; they should be calculating now what it means for their business,\u201d Curtis said. \u201cIt is a tool humans will use to kickstart creative thinking or to create the base level of something, which they then adapt continuously, or to move more quickly. \u2026 It is not an answer to everything, but it does radically shift the economics of a lot of what we do in creativity.\u201d<\/p>\n

A robot writing revolution<\/strong><\/h4>\n

OpenAI, the Microsoft-backed research lab that has been leading the charge on developing the generative AI models that provide the backbone for the technology in the past few years, released ChatGPT late this year. <\/p>\n

The new program builds on the group\u2019s previous large language models, namely GPT-3<\/a>, by making the tool more conversational. Rather than typing the beginning of a passage and having the tool complete it, users can now direct ChatGPT what to write with simple text directives. The results are often uncannily realistic in terms of mimicking the syntax and style of a given type of writing.<\/p>\n

For instance, one could ask ChatGPT to write about itself in the style of an Adweek article. The results sound natural enough to pass for a story like this, if perhaps the bot is exaggerating its own accuracy as a customer service tool.<\/p>\n

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ChatGPT is overselling its own capabilities a bit here.<\/span>OpenAI\/Adweek<\/cite><\/figcaption><\/figure>\n

Like GPT-3, ChatGPT has a host of uses, from testing different iterations of copy for a digital ad to creating lifelike customer service chatbots and better contextual search tools. Some of these capabilities depend on the ability to curb some of the machine\u2019s unpredictability and inaccuracies, a perennial problem since at least the release of GPT-2 in 2019. But various startups and developers are already working to make it more sensitive to the actual content of what it spits out or building tools that circumvent its oversights.<\/p>\n

Zach Kula, group strategy director at BBDO, said the industry should be thinking about this tool less in terms of how it could replace humans and more about the various ways it could revolutionize how creatives do their jobs. He said it\u2019s clear from his experimentation with the tool that it\u2019s not about to put agencies out of business.<\/p>\n

\u201cIn my mind, it doesn\u2019t appear that many of the people commenting on this have even used the tool,\u201d Kula said. \u201cIf they did, it would be\u00a0obvious it\u2019s not even close to replacing creative thinking. In fact, I\u2019d say it exposes how valuable true creative thinking actually is. It puts the difference between original creative thought and eloquently constructed database information in plain sight.\u201d<\/p>\n

Ethical and practical risks<\/strong><\/h4>\n

In addition to possible upsides, though, generative AI also has a host of risks that any marketers implementing it need to be aware of, including the potential for accidental copyright infringement<\/a> or plagiarism. Brands will also likely have to play defense against fake content like auto-generated user reviews or defamatory content generated at scale, according to research firm Gartner.<\/p>\n

Gartner predicts that by 2027, 80% of enterprise marketers will establish a dedicated content authenticity function to root out AI-generated misinformation. The firm also projects that 70% of enterprise CMOs will list accountability in ethical AI among their top concerns as more regulations and risks develop.<\/p>\n

As the tools to create synthetic content become more adept, the risk of synthetic content produced on a mass scale\u2014whether in the form of text, image or deepfake video\u2014increases, and marketers will likely have to think about how to protect against this type of misinformation in the future, according to Gartner analyst Bern Elliot.<\/p>\n

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\u201cFoundation models lower the cost of content creation, which means it becomes easier to create deepfakes that closely resemble the original,\u201d Elliot said. \u201cThis includes everything from voice and video impersonation to fake art, as well as targeted attacks. The serious ethical concerns involved could harm reputations or cause political conflicts.\u201d<\/p>\n

Video as the next frontier<\/strong><\/h4>\n

Experts say it\u2019s likely that technology like voice cloning<\/a>, synthetic imagery and generated copy could align in the next year to allow marketers to create full realistic-seeming videos out of whole cloth with AI. Those capabilities could make it easier for marketers to make targeted, personalized video ads aimed at different segments at scale.<\/p>\n

While current examples of this technology are still rudimentary, Curtis said the pace of the technology is accelerating so fast that it\u2019s hard to know what the state of the tech will look like a year from now.<\/p>\n

\u201cNow it\u2019s beginning to head toward video, and then it\u2019ll go 3D,\u201d Curtis said. \u201cWe\u2019ve had to continuously rewrite this trend over the last month and a half because new stuff was coming up. And and I worry that everything we\u2019re going to say is going to be irrelevant by February.\u201d<\/p>\n<\/p><\/div>\n