Over the past year and a half. tech companies have reduced the price of their AI models by 280x. Thanks to this. access to them is no longer limited to wealthy global companies. but everyone can use the capabilities of artificial intelligence. Moreover. smaller platforms are increasingly catching up with their larger predecessors in terms of performance.
AI operating prices are falling steeply
According to a report released by Stanford HAI. the payment for using AI models at the GPT-3.5 level has decreased from $20 to just $0.07 per million tokens since the end of 2022. Prices for large language models (LLMs) have decreased by 9x to 900x per year. depending on the complexity of the tasks.
This is changing the return on job function email list investment (ROI) of AI in marketing. Tools that were once too expensive can now be affordable for even mid-sized businesses.
The price difference between the most powerful AI models is also decreasing. While it was 11.9% a year ago. it has now fallen to just over 5%.
The report also shows that AI models
Getting smaller while maintaining the same performance. As recently as 2022. 540 billion parameters were needed for a model to achieve 60% accuracy on AI reasoning tests using the MMLU benchmark. This is a set of questions from a variety of disciplines that examine the ability of language models to understand. reason. and answer questions.
By 2025. models up to 124x smaller how to turn an online store into your main sales channel can do the same job. This means that advanced AI tools are now available with less processing power and at lower cost.
What are the benefits for traders?
These changes give online entrepreneurs some potential benefits:
Thanks to price reductions. mass content creation within content marketing. including its optimization for search. is significantly more accessible. More complex tasks can be automated inexpensively without compromising the quality of the outputs.
Advanced AI models can process b2b marketing up to 1-2 million text fragments – tokens at a time. This allows for better analysis of entire websites to obtain competitor statistics.
The continuous improvement of retrieval-augmented generation (RAG). which uses AI models to crawl the web in real time. allows for strategies to be built that ensure brand authenticity and expertise in AI outputs.