AI is permeating the lives of millions worldwide, but despite widespread uptake, the technology is proving tricky to monetize amid escalating costs.<\/b><\/p>\n
Generative AI tools like ChatGPT are costly to run, demanding high-end servers, expensive GPUs, and extensive ancillary hardware that guzzle vast power. <\/span><\/p>\n While largely unverified, Dylan Patel from SemiAnalysis told The Information<\/a> that OpenAI allegedly forks out some $700,000 a day<\/a> to run its models, posting losses of almost $500 million in 2022. <\/span><\/p>\n John Hennessy, chairman of Google’s parent company, Alphabet, said a single prompt on Bard costs up to 10 times more than a Google search<\/a>, and analysts believe Google will incur billions in AI-related expenditure over the coming years.\u00a0<\/span><\/p>\n 2023 has acted as a testing ground for AI monetization. Tech giants like Microsoft, Google, and Adobe, among others, are attempting a wide variety of different approaches to create, promote, and price their AI offerings.\u00a0<\/span><\/p>\n Most commercial models like ChatGPT, Bard, and Anthropic\u2019s Claude 2 already restrict users to a certain number of prompts per hour or day, including paid versions like ChatGPT Plus. Adobe is setting monthly usage caps for its Firefly models.<\/span><\/p>\n AI’s immense costs are hitting enterprises, too. Adam Selipsky, the CEO of Amazon Web Services (AWS), commented on prohibitive costs for enterprise users wishing to build AI workloads, \u201cA lot of the customers I\u2019ve talked to are unhappy about the cost that they are seeing for running some of these models.\u201d<\/span><\/p>\n Chris Young, Microsoft\u2019s head of corporate strategy, noted that it\u2019s still early days for enterprises looking to leverage current AI models, stating, \u201cIt will take time for companies and consumers to understand how they want to use AI and what they are willing to pay for it.\u201d\u00a0<\/span><\/p>\n He added, \u201cWe\u2019re clearly at a place where now we\u2019ve got to translate the excitement and the interest level into true adoption.\u201d<\/span><\/p>\n AI doesn\u2019t offer the same economy as conventional software, as it requires specific computations for each task.\u00a0<\/span><\/p>\n When users prompt a model like ChatGPT, it seeks patterns and sequences from its training data in the neural network architecture and calculates a specific answer. Each interaction draws energy, leading to ongoing costs.\u00a0<\/span><\/p>\n Consequently, as adoption grows, so do expenses, posing a challenge to companies offering AI services at flat rates.\u00a0<\/span><\/p>\n For example, Microsoft recently collaborated with OpenAI to introduce GitHub Copilot, aimed at programmers and developers.<\/span><\/p>\n Thus far, its high operational cost means it hasn’t been profitable. <\/span>In the initial months of the year, Microsoft charged a subscription of $10 a month for this AI assistant and incurred an average loss of more than $20 a month for each user. Some users inflicted losses of up to $80 a month, as revealed by a <\/span>source to the WSJ<\/span><\/a>.<\/span><\/p>\n Microsoft\u2019s Copilot suite for Microsoft 365 (confusingly named the same as the GitHub tool) plans to charge an extra $30 monthly. This tool offers capabilities like autonomously drafting emails, crafting PowerPoint presentations, and creating Excel spreadsheets.<\/span><\/p>\nAI models vs software<\/span><\/h2>\n