Honeywell International Inc. (HON) Partners with Chevron to Revolutionize Oil Refining Operations with AI-Enhanced Technologies for Improved Efficiency and Safety

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We recently compiled a list of the 35 Trending AI Stocks on Latest News and Analyst Ratings. In this article, we are going to take a look at where Honeywell International Inc. (NASDAQ:HON) stands against the other trending AI stocks.

Two years after the public debut of ChatGPT, the generative AI landscape has evolved rapidly, igniting substantial investments in artificial intelligence and lifting valuations for startups and major tech companies alike. This surge in interest has primarily centered on cloud-based AI, where services like OpenAI's models operate on extensive data infrastructures. However, as these models grow in complexity, the demand for larger and more advanced data centers intensifies, leading to a race among companies to construct expansive facilities. Significant investments are projected, with estimates suggesting that major players will collectively spend around $160 billion in capital expenditures next year, primarily for acquiring powerful GPUs and related infrastructure necessary for training AI models. Top executives have even forecasted that global data center investments could double to $2 trillion within the next few years. Nevertheless, the sustainability of this spending spree raises questions about whether the revenue generated from AI applications can match the high costs of development and infrastructure.

Read more about these developments by accessing 10 Best AI Data Center Stocks and 10 Buzzing AI Stocks According to Goldman Sachs.

Amid these challenges, a new trend in edge AI is emerging. This concept involves running AI algorithms directly on personal devices like smartphones and computers rather than relying on centralized cloud servers. Edge AI offers numerous benefits, including real-time response capabilities without requiring a high-speed internet connection and enhanced privacy since user data remains on personal devices. Analysts project that nearly 50% of smartphones will have generative AI capabilities by 2027, a significant increase from the current 4%. However, implementing edge AI presents technical hurdles, primarily due to existing devices lacking the necessary computing power and memory to support large AI models. For instance, running OpenAI's GPT-4 model, which contains approximately 1.8 trillion parameters, is not feasible on typical smartphones today. Nevertheless, smaller, task-specific AI models are gaining traction, as they require less training data and can outperform larger, more generalized models in certain applications. These lightweight models are often open-source and designed for specific functions, making them easier to implement on consumer devices.