AI is getting cheaper, but whether this benefits consumers the same way it helps large companies is still up for debate. Major tech firms like Google and Microsoft are cutting the costs of their AI models significantly. For example, Google recently slashed the price of its Gemini 1.5 Flash model by over 70%, making it accessible for developers working on AI-powered applications. Similarly, other players like OpenAI and Hugging Face have followed suit by offering cheaper mid-level models with improved performance, thanks to optimization techniques like quantization and pruning.
However, for consumer-based applications, the story is more complex. While the reduced prices of AI models and tools might allow businesses to offer more affordable AI-powered services, this doesn’t always trickle down to end users. Many consumer apps that integrate AI still charge high subscription fees—think of Microsoft Copilot, which adds $30 per user per month to business software subscriptions. This shows that while AI is becoming cheaper to produce, it’s not necessarily becoming cheaper to access for consumers https://www.advisorperspectives.com/articles/2024/08/06/ai-getting-cheaper-wont-fix-everything.
Furthermore, deploying large AI systems at scale can cost companies millions, and they may pass those costs on to users. Even with reduced AI costs, significant upfront investments and infrastructure maintenance keep consumer-facing apps expensive in many cases. Research by Gartner shows that AI projects still carry high risk, with 30% expected to be abandoned due to cost https://www.kyndryl.com/us/en/about-us/news/2024/09/how-cheap-ai-will-change-business.
This is where the idea of an open-source, omni-AI app could truly shine. By leveraging models like LLaMA and open-source APIs, smaller businesses and independent developers can bypass the high costs of proprietary AI systems. These open-source options provide an affordable way to develop AI applications without being tied to expensive tools. As companies like Meta push free, highly capable models into the market, businesses could eventually pass those savings on to consumers.https://economistwritingeveryday.com/2024/08/06/will-the-huge-corporate-spending-on-ai-pay-off/
Open-source platforms could lead to a new wave of affordable AI solutions for both businesses and consumers, cutting down on costs while maintaining innovation. If more apps and services utilize these tools, it could ignite competition that benefits consumers, reducing the high fees we currently see in AI-powered products.
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