For those old enough to remember the horror movies of the 1980s, there was a cartoonish vibe to many of the monsters inhabiting the stories. Not in all of them. Freddie Krueger and Pinhead were frightening, but for every “Alien” there was a “Gremlin,” and for every “Dawn of the Dead” zombie there was a Stay Puft Marshmallow Man from “Ghostbusters.”
They were cute and fun, but not really that scary.
To celebrate the Halloween season – and no doubt hopefully to pull in some new users – BestCasinoSites.net took more than a dozen classic horror movie characters and applied AI image technology to give them a more modern look, one that for most of them is decidedly more menacing.
Pumpkinhead, Rancor from “Return of the Jedi,” the werewolf in “An American Werewolf in London,” and, yes, Stay Puft, along with Fluffy the Crate Beast from “Creepshow” and Stripe the Gremlin all got a modern makeover using AI image generating technology from Midjourney, a research lab that developed its namesake AI generative AI text-to-image program and released it to open beta last year.
Even the original horror film character, Nosferatu, a silent-film adaptation of Bram Stoker’s classic 19th-century novel “Dracula” was pulled into the modern age.
From Movies to Business
Checking out the AI-created images can be fun – and for many nostalgic – but they also highlight what the technology can do in the business world, according to Chris Gonsalves, chief research officer for Channelnomics.
And the first thing they can do is let business leaders get more familiar with what they can do with generative AI – in this case, with such image-generating programs as Midjourney, OpenAI’s Dall-E and DreamStudio from Stable Diffusion – and help explain how the large language models (LLMs) the tools are based on work, Gonsalves told Techstrong.
“What gets us jazzed about generative AI images are these kinds of things,” he said. “That kind of thing is what gets the creative juices cooking.”
The use and innovation of generative AI tools has exploded since late November 2022, when OpenAI released ChatGPT. Statista is predicting that the generative AI market will grow from $44.89 billion this year to $207 billion by 2030. Global consultancy McKinsey estimates that the technology could add $2.6 trillion to $4.4 trillion in value to the global economy every year.
In addition, McKinsey says about 75% of the value generative AI will deliver touches on four areas – customer operations, marketing and sales, software engineering and R&D, echoing what Gonsalves has found in his research.
Generative AI and Medical Imaging
He noted the high use of generative AI image-generative tools by health care facilities to compile and analyze medical images to detection patterns that people normally wouldn’t see.
“Anyone in an organization that isn’t doing this isn’t long for the job,” Gonsalves said. “It’s a known fact that AI is just better at detecting patterns than we are.”
Generative AI tools can find 1,000 markers in images of lung tissue and generate prognoses, outcomes and treatment plans.
“There are markers in there that may not have been able to be detected at all,” he said.
Content marketing is another place where image-generating programs are making their mark, enabling firms to create images that tell a better story than photos that are readily available can, and to create storyboards for videos. Then there are the blog heroes, the oversized banner images at the top of a company’s website to offer visitors the first glimpse – the first impression – of what the company is and what it has to offer.
“It demonstrates what the company is all about,” Gonsalves said.
Better, Cheaper Training Videos
Dall-E, Midjourney, and similar tools also have a role to play in training videos and for field services teams. Animated videos created using generative AI can often deliver a training visual representative that is easier for users to follow than filmed videos.
For the company, they also can be cheaper to create, he said. It can be expensive to bring together actors, camera operators and other players to film a video. Having one person create a training video using AI tools is more cost-effective.
In addition, they’re faster and cheaper to update when product changes are made. Rather than bringing in a full crew to film another video, it only takes an engineer or two to tweak the existing AI-based animated video and fall in line with the changes.
Software Development and SBOMs
In software development, generative AI not only can create code, but also can help visualize the development process, creating flowcharts and visuals not only for how a program works, but also how the software works together, Gonsalves said.
The technology also is useful in creating software bills-of-materials (SBOMs), the listing of components that make up a piece of software similar to the list of ingredients on a package of food. SBOMs are crucial to ensuring the security in software that increasingly is, essentially, a collection of code from multiple sources.
But it’s not just what the components are, he said, but also how they’ve changed, how they tie together, their interdependence, and so on. Taking all that text and creating images that illustrate all that is much faster and creates a better visual than a group of people sitting down and mapping it out on paper.
So while modern images of 1980s movie creatures may be fun to look at, the text-to-image generative AI technology behind them is playing an increasingly larger role in digitally transforming modern business.
