AI Hype Fades

Introduction to AI Hype

OpenAI is in court, Microsoft doesn’t want to be part of the Musk v. Altman trial, and Elon Musk can’t stop violating the Clean Air Act. Meanwhile, top US AI research institutes and tech giants support a national AI research cloud. The Roman Catholic Church has joined IBM and Microsoft to work on AI ethics. But despite all the hype, AI isn’t the big smartphone selling point that Apple and other tech giants think.

The lack of enthusiasm from consumers was evident when Apple announced its new line of iPhones with AI features. The reaction from the collective world of consumer technology has been muted. The only thing that generated some excitement was the addition of a new camera shutter button on the side of the phone.

The State of AI Development

AI has now passed its “wonderment phase”. Two years ago, we were amazed that ChatGPT, DALL-E, and other generative AI systems could create coherent writing and realistic images from just a few words in a text prompt. But now, AI needs to show that it can actually be productive. Since their introduction, the models driving these experiences have become much more powerful – and exponentially more expensive.

Google, NVidia, Microsoft, and OpenAI recently met at the White House to discuss AI infrastructure, suggesting these companies are doubling down on the technology. According to Forbes, the industry is US$500 billion short of making back the massive investments in AI hardware and software, and the US$100 billion in AI revenue projected to be made in 2024 is not even close to this figure.

The Push for AI Adoption

Apple still has to enthusiastically push AI features into their products for the same reason that Google, Samsung, and Microsoft are doing it – to give consumers a reason to buy a new device. Before AI, the industry was trying to create hype around virtual reality and the Metaverse, an effort that probably peaked with the introduction of the Apple Vision Pro headset in 2023.

After the Metaverse failed to take off, tech companies needed something else to drive sales, and AI has become the new shiny thing. But it remains to be seen whether consumers will take to the AI-based features included in phones such as photo-editing and writing assistants. This is not to say that current AI is not useful. AI technologies are used in billion-dollar industry applications, in everything from online advertisement to healthcare and energy optimisation.

The Future of AI

Generative AI has also become a useful tool for professionals in many fields. According to a survey, 97% of software developers have used AI tools to support their work. Many journalists, visual artists, musicians, and filmmakers have adopted AI tools to create content more quickly and more efficiently.

Yet most of us are not actually prepared to pay for a service that draws funny cartoon cats or summarises text – especially since attempts at AI-supported search have shown to be prone to errors. Apple’s approach to deploying artificial intelligence seems to mostly be a mishmash of existing functions, many of which are already built into popular third-party apps.

Industry Context

The AI industry is not isolated, and its development is influenced by the broader tech landscape. The rise of cloud computing, the growth of big data, and the increasing demand for automation have all contributed to the current state of AI. As the industry continues to evolve, it will be important to consider the interplay between AI and other technologies, such as the Internet of Things, 5G networks, and quantum computing.

The market size for AI is significant, with estimates suggesting that it will reach US$190 billion by 2025. However, the adoption curve for AI is not uniform, and different industries are adopting the technology at different rates. For example, the healthcare industry has been relatively slow to adopt AI, while the finance industry has been more aggressive in its adoption.

Technical Mechanics

Under the hood, AI systems rely on complex algorithms and large amounts of data to function. The development of these systems requires significant expertise in areas such as machine learning, natural language processing, and computer vision. As AI becomes more ubiquitous, it will be important to consider the technical implications of its deployment, including issues related to data privacy, security, and bias.

The use of AI in smartphones, for example, raises important questions about data privacy and security. As AI-powered features become more prevalent, it will be important to ensure that user data is protected and that AI systems are designed with security in mind.

Downstream Implications

The impact of AI will be felt across a wide range of industries, from healthcare and finance to education and transportation. As AI becomes more ubiquitous, it will be important to consider the downstream implications of its deployment, including issues related to job displacement, social inequality, and environmental sustainability.

For example, the use of AI in healthcare could lead to significant improvements in patient outcomes, but it could also displace certain types of jobs. Similarly, the use of AI in finance could lead to increased efficiency and productivity, but it could also exacerbate existing social inequalities.

What to Watch

The next few months will be crucial in determining the future of AI. Will consumers take to AI-based features in their smartphones? Will tech companies be able to make back their investments in AI hardware and software? What will be the impact of AI on various industries, from healthcare to energy optimisation? These are the questions that we should be watching, as the world of AI continues to evolve.