Since the release of OpenAI’s ChatGPT late last year, Artificial intelligence (AI) has quickly evolved into what seems to…
Since the release of OpenAI’s ChatGPT late last year, Artificial intelligence (AI) has quickly evolved into what seems to be a commonly used word to denote a more sophisticated intrusion into the use of technology.
Although artificial intelligence (AI) has long played a role in mankind’s quest for a more advanced way of living, largely due to the solutions offered by tech giants like Apple, Microsoft, Google, and even Meta, it has recently sparked greater attention and worry.
The fuss has not only gone beyond casual chats, it has also been impactful enough to convince large tech companies and multinationals to invest more in its research and incorporate its mechanics into their operations and consumer-focused products.
Google, Microsoft, and even Meta are just a few of the large IT companies that have fully embraced this initiative. These large corporations are jostling among each other about who provides the best user experiences and technological solutions to the real-life problems of their users. They also aim to make the solution they provide even more artificial by incorporating a more intelligent machine or algorithm, all in a bid to outdo the other.
This jostling among these rival big tech companies is to be expected. With generative AI seeming to be the new oil of the tech industry, these big technology companies are now rushing to work similar capabilities into their own products. But with all the fuss around generative AI by Google, Meta and even Microsoft, why is Apple seemingly silent?
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Google, Microsoft and the major pushers
Google’s Bard was developed as a type of competition for ChatGPT and Microsoft, which is now a significant investor in the ongoing research and development of AI. Microsoft’s investment into OpenAI’s burgeoning adventure has seen it include ChatGPT in its office suite, which includes Word, Outlook, and PowerPoint, to increase users’ effectiveness and productivity.
Analyzing Apple’s seeming silence
Contrary to belief, Apple is actually heavily invested in AI and has been for many years. However, Apple’s approach to AI is somewhat different from that of other tech companies. Instead of using AI primarily for cloud-based services like Amazon and Microsoft, Apple focuses on integrating AI into its hardware and software products.
For example, Apple’s virtual assistant, Siri, uses AI to understand and respond to natural language commands. Apple also uses AI in its camera software to improve image processing and facial recognition capabilities. Additionally, Apple has developed its own AI-specific hardware, such as the Neural Engine in its A-series chips, to optimize AI performance on its devices.
Apple is known as a “fast follower”; it likes to wait until new technologies have matured, then jump in with its own Apple-flavored version. So far, the company has treated AI as an enabling technology that it deploys behind the scenes to make its devices and apps work better.
At Apple’s annual AI summit a few months ago, employees were reportedly given information about the company’s large language model and other AI tools. In response to the growing popularity of chatbots like ChatGPT, Apple engineers, including those from the Siri team, have supposedly been experimenting with language-generation ideas every week.
AI for several years now, but DA Davidson analyst Tom Forte predicts that it’s not the company’s style to launch a big, splashy AI product of its own. Instead, he says, it’s more likely to be used in the background.
“As one of the biggest companies in the world, Apple is doing something around AI, but it will not be as buzzy as ChatGPT. When Apple uses AI, they do so more to enhance their technology,” said Forte.
One reason why Apple may not appear to be as heavily invested in AI as other companies is that it prioritizes user privacy. Apple has implemented strict data privacy policies and uses on-device processing for many AI applications, rather than sending user data to the cloud for analysis. This approach can limit the amount of data that Apple has access to for training and improving its AI models.