Generative artificial intelligence (AI) just keeps getting bigger.
When you have a successful tech innovation, frequently, the next commercial step is to turn it into a platform.
Right now, the AI landscape is more of an ecosystem — but coming out of OpenAI’s Developer Day on Monday (Nov. 6), it’s becoming apparent that the pioneer wants to move from the iPhone era of its ChatGPT and other AI products to the Apple App Store era.
As one of the first movers in the AI space looks to maintain its early lead, it will need to fend off upstarts and incumbents alike, as well as navigate the increasingly thorny path of burgeoning global regulations.
With AI’s unfolding and new possibilities on the horizon, these are the key stories PYMNTS has been tracking this week.
While AI is a ways away from replacing human labor, the technology is increasingly having a right-now impact in supercharging the existing capabilities of individuals.
Call it the Service-as-Software era. With the announcement of OpenAI’s GPT store, it has officially begun, as AI Agents, GPTs and AI Copilots are helping enterprises and individuals alike handle tasks as disparate as scheduling meetings or travel, editing files, retrieving information, analyzing data and more.
Jeffrey Katzenberg, who co-founded DreamWorks Animation with Steven Spielberg and David Geffen, claimed on Thursday (Nov. 9) that AI is set to revolutionize the entertainment industry, particularly the time and cost that goes into the creation of animated films; while SymphonyAI on Wednesday (Nov. 8) introduced an industrial large language model (LLM) designed to accelerate industrial transformation on a large scale.
On Tuesday (Nov. 7), eBay revealed that its own investments into AI are enhancing the way its customers perceive it, while PYMNTS reported on Monday that tailoring AI solutions by industry is key to scalability.
And increasingly, organizations are finding that infusing generative AI solutions into enterprise developers’ toolkits is helping to streamline software development workflows while making it easier for junior developers and those of all skill levels to write their own code and develop innovative products using text-based prompts.
With many companies undertaking system enhancements across areas like accounts payable (AP) and accounts receivable (AR), the benefits of having AI-generated code on hand can’t be overstated.
“Computers can now behave like humans. They can articulate, they can write and can communicate just like a human can,” Beerud Sheth, CEO at Gupshup, told PYMNTS as part of the AI Effect series. “[But] enterprise use of AI has to be accurate and relevant — and it has to be goal oriented. Consumers can have fun with AI, but in a business chat or within an enterprise workflow, the numbers have to be exact, and the answer has to be right.”
Fueling the generative AI ecosystem is a rising class of startups.
And IBM announced Tuesday it was launching a $500 million venture fund to invest in them.
While an impressive amount, $500 million was the amount that German startup Aleph Alpha raised in its Series B round, the company announced Monday. The startup’s technology is centered around the concept of “data sovereignty,” which emphasizes that data stored in a specific country should be subject to that country’s laws.
Some fortunate few, however, don’t need to rely too heavily on outside funding. Flipkart’s billionaire founder Binny Bansal, who launched the Indian eCommerce firm before selling it to Walmart, is reportedly launching an AI startup of his own.
Even some of the world’s biggest tech companies believe there are still moves to be made to separate themselves from the pack.
Amazon is reportedly working on an ambitious new LLM code named “Olympus” that is rumored to be one of the largest foundation models ever, trained at an alleged two trillion parameters. Enterprise clients want to access top-performing models, and for Amazon to meet future needs securely, seamlessly and competitively, it is better for the company to offer services built from its own models than those that link to another LLM via an application programming interface (API), observers believe.
Regulation of AI, despite a lot of conversation, remains to-date a faraway facet of the environment, particularly given the speed at which the technology is advancing.
That’s why PYMNTS CEO Karen Webster sat down with Shaunt Sarkissian, CEO and founder of AI-ID, on Thursday and asked him to play a game of “AI Regulation Roulette.”
“Anybody thinking about regulation needs to start with an outside-in approach. If you’re looking at concentric circles, go with the farthest thing and create the final boundary,” said Sarkissian, noting that a “final boundary” could be something apocalyptic. Then, by narrowing down the broad boundaries, governments can allow innovation to thrive within those constraints.
Companies are also taking matters into their own hands.
AI’s potential to spread misinformation is one of the most common threats mentioned when people discuss the possible risks posed by the technology, which is why Meta is imposing new controls on AI-generated ads ahead of the 2024 presidential election; and JPMorgan Chase is reportedly working with American regulators as it prepares its inaugural AI projects to make sure proper controls are in place as it tries to get ahead of its competitors.
As the AI landscape matures, it is already seeing its first-ever purpose-built device: a screenless, voice-activated smartphone that comes from Humane and debuted Thursday.
This, as Samsung also announced on Thursday that it was bringing AI to its own Galaxy phones, stating that “Galaxy AI, a comprehensive mobile AI experience…will transform your everyday mobile experience.”
As revealed in the PYMNTS Intelligence report “Consumer Interest in Artificial Intelligence,” consumers interact with about five AI-enabled technologies every week on average, including browsing the web, using navigation apps and reviewing online product recommendations. Nearly two-thirds of Americans want an AI copilot to help them do things like book travel.
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