Tonight: It's not a great time for the meme stock set. Plus: Artists found out their work was being used to train AI, and they are furious. Let's get into it. By CNN Business Staff |
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It's been a rough year for stock traders, what with the bear markets, the rate hikes, the inflation, the revolving door of political crises at home and abroad — all in all, quite the hangover from the Fed-fueled party that was 2021. Everyone's hurting in their own ways, of course, but retail traders — regular people who trade on their own via apps like Robinhood — appear especially glum, CNN Business' Nicole Goodkind writes. Let's step back: In the heyday of 2020, lots of folks were bored, scared and holed up in their living rooms with their phones. Critically, they also had stimulus checks burning a hole in their bank accounts. For many, that meant it was time to join the ranks of stock pickers. Traffic on trading apps shot up. Meme stocks were born. An army of retail traders managed to short squeeze the life out of one Wall Street's most powerful hedge funds. But for those who joined during in the thrilling bull market of 2020 and 2021, this year's slump appears to have soured the mood. The market downturn this year has knocked about $15 trillion off the valuations of publicly traded companies. Retail traders have had enough, and they are headed for the exits. Robinhood's stock is has fallen about 45% this year as its user growth has slowed dramatically. The company said in August that it would cut 23% of its full-time staff, its second round of layoffs this year. The average daily number of retail trades handled at Charles Schwab fell to 5.5 million in the third quarter, far from the 8.4 million it reported in early 2021, at the height of the GameStop mania. Bottom line: A loss of retail investors isn't, like, the end of the world. But it's concerning because it could spell a longer downturn as regular people shun equities. The silver lining here may be that those hordes of mostly young, green investors who'd never experienced a bear market are learning the hard way to exercise caution and make smarter choices. Like, don't just buy this stock because someone you've never met on Reddit implored you to HODL or accused you of having paper hands. "Some are undoubtedly pulling out of the market and buying bonds, but it seems like retail investors are mostly taking a wait-and-see approach to equities, holding onto Big Tech stocks and rotating into more stable, dividend-paying sectors like energy," said Thomas Mason, senior analyst at S&P Global Market Intelligence. |
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An image created by CNN's Rachel Metz with input from artist Erin Hanson, using the AI platform Stable Diffusion. It resembles Hanson's work, particularly with its colors and simulated brush strokes. |
By Rachel Metz Erin Hanson has spent years developing the vibrant color palette and chunky brushstrokes that define the vivid oil paintings for which she is known. But during a recent interview with her, I showed Hanson my attempts to recreate her style with just a few keystrokes.
Using Stable Diffusion, a popular and publicly available open-source AI image generation tool, I had plugged in a series of prompts to create images in the style of some of her paintings of California poppies on an ocean cliff and a field of lupin.
"That one with the purple flowers and the sunset," she said via Zoom, peering at one of my attempts, "definitely looks like one of my paintings, you know?"
With Hanson's guidance, I then tailored another detailed prompt: "Oil painting of crystal light, in the style of Erin Hanson, light and shadows, backlit trees, strong outlines, stained glass, modern impressionist, award-winning, trending on ArtStation, vivid, high-definition, high-resolution." I fed the prompt to Stable Diffusion; within seconds it produced three images.
"Oh, wow," she said as we pored over the results, pointing out how similar the trees in one image looked to the ones in her 2021 painting "Crystalline Maples." "I would put that on my wall," she soon added.
Hanson, who's based in McMinnville, Oregon, is one of many professional artists whose work was included in the data set used to train Stable Diffusion, which was released in August by London-based Stability AI. She's one of several artists interviewed by CNN Business who were unhappy to learn that pictures of their work were used without someone informing them, asking for consent, or paying for their use.
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"Crystalline Maples", a 2021 oil painting by Erin Hanson. |
Once available only to a select group of tech insiders, text-to-image AI systems are becoming increasingly popular and powerful. These systems include Stable Diffusion, from a company that recently raised more than $100 million in funding, and DALL-E, from a company that has raised $1 billion to date.
These tools, which typically offer some free credits before charging, can create all kinds of images with just a few words, including those that are clearly evocative of the works of many, many artists (if not seemingly created by the same artist). Users can invoke those artists with words such as "in the style of" or "by" along with a specific name. And the current uses for these tools can range from personal amusement to more commercial cases.
In just months, millions of people have flocked to text-to-image AI systems and they are already being used to create experimental films, magazine covers and images to illustrate news stories. An image generated with an AI system called Midjourney recently won an art competition at the Colorado State Fair, and caused an uproar among artists.
But as artists like Hanson have discovered that their work is being used to train AI, it raises an even more fundamental concern: that their own art is effectively being used to train a computer program that could one day cut into their livelihoods. Anyone who generates images with systems such as Stable Diffusion or DALL-E can then sell them (the specific terms regarding copyright and ownership of these images varies).
"I don't want to participate at all in the machine that's going to cheapen what I do," said Daniel Danger, an illustrator and print maker who learned a number of his works were used to train Stable Diffusion.
Read the full story and see more examples of AI-generated art here.
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