AI Power Stock Gains

Investor interest in artificial intelligence is surging, leading many companies to tout their AI product roadmaps. While AI has been around for a while, it became more prominent with the release of ChatGPT and similar apps in late 2022. These apps could write reports, sort through data, and find better ways of doing tasks, leading to a surge in AI-related stocks that have performed well over the past year. AI is a rapidly growing field, with AI-related ETFs outpacing the S&P 500 in 2023.

For example, the Swissquote Bank Themes Trading Robotics & AI AMC was up 25% in 2023. Many investors want to increase their exposure to this market, but finding legitimate AI stocks that generate revenue from generative AI, such as Microsoft and Nvidia, takes a lot of work. For many companies, such as Google parent Alphabet, the rise of generative AI poses both risks and opportunities. Given the emergence of generative AI, it's an excellent time to be cautious amid the hype. In general, look for AI stocks that use artificial intelligence to improve products or gain a strategic edge. Chipmaker Nvidia, perhaps the best-known AI stock, reported revenue of $22.1 billion for Q4 2023, up 22% from the previous quarter and up 265% from the same quarter a year ago, bringing full-year revenue to $60.9 billion, up 126%.. Microsoft, the largest investor in startup OpenAI, the leader in general AI training models, introduced a new technology called Sora on Feb. 15. Sora uses AI to create high-quality videos from text descriptions.

The tool has been given to some researchers and academics to test how it can be misused. Video postings on social media in an election year are one concern. Adobe shares fell on news of the text-to-video generator. Meanwhile, The Information reported that OpenAI is working on a web search product that would directly compete with Google. OpenAI's technology is already embedded into Microsoft's Bing search engine, but Bing has yet to gain market share. Dominant cloud computing firms like Amazon, Microsoft, and Google already sell AI services to corporate customers.

So far, the most significant demand for AI chips has come from cloud computing giants. Nvidia earnings have surged due to frenzied demand for AI chips built into computer servers. There is a general feeling that investors expect a market for "edge AI" — on-device processing of AI apps to emerge. However, "training" AI models are currently the largest market for chipmakers like Nvidia; the market will shift to "inferencing," or running AI applications, in the long term. Qualcomm aims to build Snapdragon AI chips for Android smartphones and the "Internet of things." ARM Holdings is another AI chip maker. ARM stock has gained 70% in 2024. The market suggests say that most enterprise software makers will not materially monetize gen AI until late 2024 or 2025. Meanwhile, Apple topped the $3 trillion market valuation mark in 2023 despite having no immediate answer to ChatGPT. This could shift in 2024, with markets expect an AI upgrade for the iOS mobile operating system.

AI technology uses computer algorithms with software programs that aim to mimic the human ability to learn, interpret patterns, and make predictions. Until recently, machine learning was primarily limited to models that processed data to make predictions. Corporate budgets and R&D on AI projects was remains modest as companies mulled return on investment. Now, many companies are scrambling to launch generative AI pilot programs. But investors are already pushing aside the hype to demand AI stocks to demonstrate progress in growing revenue as exploratory projects translate into tangible demand. New generative AI models process "prompts," such as internet search queries, describing what a user wants. Generative AI technologies independently create text, images, video, and computer programming code. Companies will aim to boost productivity by developing customized AI for specific industries, using proprietary company data to train AI models. AI systems demand immense computing power to locate patterns and make inferences from huge quantities of data. The rush is to develop and fabricate AI chips for data centers, self-driving cars, robotics, smartphones, drones, and other devices.

The million dollar question is whether tech industry leaders will be the big generative AI winners or a new batch of AI up-startups will dominate. Large language models provide the building blocks to develop applications, helping AI systems to become more sophisticated. One key question for investors is whether tech industry incumbents will be the big generative AI winners or a new wave of AI startups will dominate. Large language models provide the building blocks to develop applications, helping AI systems to become more sophisticated.