According to rumors, Apple is improving the mobile devices’ generative artificial intelligence (AI) capabilities.
The Financial Times reported on Sunday, August 6, that the corporation has started hiring for dozens of positions to work on large language models (LLMs).
According to the job listings, the tech giant is engaged in “ambitious long-term research projects that will impact the future of Apple and our products.”
In contrast to competitors like Google, which have introduced AI products like chatbots, the report argues that the lists indicate Apple is concentrating on introducing technology like LLMs exclusively to smartphones.
On an earnings call this week, Apple CEO Tim Cook stated, “We view AI and machine learning as core fundamental technologies that are integral to practically every product that we build.”
According to Cook, according to the FT report, the company’s generative AI initiatives are one reason why its third quarter R&D spending was $3.1 billion higher than it was in the corresponding quarter in 2022.
LLM technology is elevating AI “to new heights by expanding its capabilities beyond text to include images, speech, video, and even music.”
Additionally, when businesses develop LLMs, they must deal with the difficulties of gathering and categorizing enormous volumes of data while also comprehending the intricacies of how current models work and how they differ from the status quo.
“Technology giants such as Alphabet and Microsoft and investors such as Fusion Fund and Scale VC are investing in LLMs and forming partnerships,” PYMNTS wrote. “The technology companies’ and investors’ task is a big one. It includes ensuring their LLM protégés gather and train large data sets, called parameters, and fine-tune them so that they execute and generate desired outputs or results.”
As governments attempt to understand AI better, the legislation also comes with all this investment and development.
According to Cary Coglianese, a University of Pennsylvania Law School professor, doing so might be easier said than done.
The professor, also the founding director of the Penn Programme on Regulation, stated that trying to control AI is similar to trying to regulate air or water.
Indeed, those items are already subject to global regulation, but, like AI, they have specific qualities that call for particular supervision strategies.
According to Coglianese, controlling AI will be a complex process that varies based on the kind of algorithm and how it is applied.
“It’s not one static thing. Regulators — and I do mean that plural, we are going to need multiple regulators — they have to be agile, they have to be flexible, and they have to be vigilant,” he said, adding that “a single piece of legislation” won’t solve the problems connected to AI.
