Is it Moore’s Law, or more’s law?
Anyone keeping an eye on the generative artificial intelligence (AI) landscape could be forgiven for confusing the two.
This, as another week has gone by, and with it another hyper-rapid clip of advances in the commercialization of generative AI solutions, and even a new executive order from California Governor Gavin Newsom, around the need for regulation of the innovative technology.
Were it any other technology, the rapid pace of change we are seeing within AI would require a least a year or more to make it to market.
Already, after China became the first major market economy last month to pass regulations policing AI, the nation’s biggest tech firms debuted their own adherent products just weeks later — this one.
And as generative AI technology continues to add more fuel its rocket ship trajectory, these are the stories and moonshots that PYMNTS has been tracking.
Generative AI can generate, well, anything. And while the possibilities are endless, they also run the gamut – from widely positive and productively impactful, to dangerous and geared toward criminal goals. After all, genAI is a tool, and in the absence of a firm regulatory framework, the utility of a tool depends entirely on the hand that wields it.
That’s why Google has announced a new policy mandating advertisers for the upcoming U.S. election to disclose when the ads they wish to display across any of Google’s platforms (excluding YouTube) have been manipulated or created using AI.
Meta Platforms, the parent company of Instagram and Facebook, and X, formerly known as Twitter, both of which have faced allegations of spreading political misinformation, have not yet announced any specific rules around AI-generated ad content.
Complicating matters somewhat is the fact that PYMNTS Intelligence has found there doesn’t yet exist a truly foolproof method to detect and expose AI-generated content.
“One of the questions that is immediately raised [around AI] is how do you draw the line between human-generated and AI-generated content,” John Villasenor, professor of electrical engineering, law, public policy and management at UCLA and faculty co-director of the UCLA Institute for Technology, Law and Policy, explained to PYMNTS on Friday (Sept. 8).
And as generative AI tools are increasingly leveraged by bad actors to fool ID authorization protocols and scam unsuspecting consumers, it is becoming incumbent on organizations to upgrade their own defenses with AI capabilities. Phishing attacks alone have seen a 150% increase year over year as a result of new AI-driven techniques.
The technology is already proving to be both a blessing and a hindrance for payments security, and as reported here on Tuesday (Sept. 5), payments firm ThetaRay recently raised $57 million to boost its AI-powered financial crime detection capabilities.
While the “artificial” element of AI has its darker side, it is the “intelligence” aspect of the technology that enterprises and platforms want to capitalize on and integrate.
Apple is reportedly spending millions of dollars a day building out its generative AI capabilities across several product teams, including its voice assistant Siri, and there exists an attractive white space opportunity for AI to make today’s smart assistants a whole lot smarter.
Chipmaker Qualcomm is working with Meta to make that company’s Llama 2-based artificial AI implementations available on smartphones and PCs, and the Qualcomm’s CEO said on Tuesday (Sept. 5) he sees AI as potentially reviving the smartphone market, where global sales are at their lowest levels in a decade.
Elsewhere, video communications company Zoom announced that it is making its own generative AI assistant free to paid users; while the buzzy, well-funded AI startup Anthropic on Thursday (Sept. 7) introduced a paid plan for the Pro version of its AI assistant, Claude.
Not to be outdone, customer experience management platform Sprinklr has integrated its AI platform with Google Cloud’s Vertex AI in order to let retail companies elevate contact center efficiency with generative AI capabilities that support service agents.
This, while Casey’s General Stores announced on Wednesday (Sept. 6) that the convenience retailer is turning to conversational voice AI ordering technology in an ongoing push to gain share from quick-service restaurants (QSRs).
IBM also announced on Thursday (Sept. 7) that it is releasing new enhancements to its AI platform, watsonx, and giving developers a preview next week at the company’s TechXchange event in Las Vegas.
And IBM isn’t the only tech company hosting a developer conference. Generative AI pioneer OpenAI announced Wednesday (Sept. 6) that its first “DevDay” developer conference will take place this November.
Generative AI is also getting utilized for specialized purposes.
CFOs are increasingly tapping the tool to help optimize their working capital and treasury management approaches; while consumer brand data platform Alloy.ai on Thursday (Sept. 7) announced the addition of new predictive AI features to its own forecasting and supply chain solution.
And over in the healthcare sector, the industry is reportedly allocating over a tenth of its annual spend (10.5%) on AI and machine learning innovations.
As for what the health industry hopes to achieve with this investment? Hopefully the cure to its zettabyte-sized data fragmentation problems.
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