Artificial Intelligence (AI) is advancing at an incredible rate. AI models are getting smarter and much more affordable. Venture capital firm Andreessen Horowitz is calling this shift “LLMflation,” a term that highlights how the costs of running large language models (LLMs) are falling year after year.
AI is now within reach for more companies, from startups to established enterprises, allowing them to leverage this powerful technology in ways that were previously too costly.
The trend says the costs of running AI models drop tenfold yearly. Known as inference costs, these are the expenses involved in getting an AI model to produce results, whether generating text, making predictions, or recognizing images. In simpler terms, it’s the cost of using AI to perform specific tasks.
Lower inference costs mean companies can achieve the same powerful results at a fraction of the previous expense.
Just three years ago, running a large language model like GPT3 cost about $60 per million tokens. Today, the same process costs around $0.06 per million tokens—a staggering 1,000x reduction in cost.
What’s Behind the Drop in AI Costs?
Several key advancements are driving down the cost of running AI:
1. Better Hardware for AI
New hardware is being developed specifically to run AI models more efficiently. Semiconductor companies are designing advanced chips that make processing AI tasks faster and with less energy possible.
Intel’s Gaudi 3 chip is designed to compete with Nvidia’s chips. This chip performs AI tasks more efficiently, reducing costs and energy use.
2. Smarter Software
Software developers are making AI models run smoothly with fewer resources. Techniques like model quantization simplify the way models work, so they require less computing power.
This means the AI can operate at a lower cost without sacrificing quality.
Amazon Web Services (AWS) recently launched a toolkit to make AI tasks run twice as fast at half the cost. It uses methods like speculative decoding and quantization to reduce the overall expense.
3. The Rise of Open Source AI Models
The rise of open-source AI models is a significant contributor to this democratization.
Researchers are making their AI models available to the public for free or minimal cost. They’re creating a community where high-quality AI solutions are accessible to people with lower financial resources. The inclusivity fuels competition and creates affordable options for businesses, making everyone feel part of the AI revolution.
The open-source approach is fueling competition and creating more affordable options for businesses.
Cohere recently launched a Command R model designed to summarize meetings or analyze data. It’s much cheaper to run than other popular models, making it accessible to smaller businesses.
4. Creative Cost Cutting Strategies
Companies around the world are developing new strategies to make AI more affordable. In China, for example, AI firms are reducing their dependence on the latest, most expensive hardware by using optimized software and smaller datasets. These approaches, along with others like efficient resource allocation and strategic partnerships, are making AI accessible even in regions where resources may be more limited.
Why Cheaper AI Matters for Businesses and Society
An affordable AI opens up new possibilities for businesses of all sizes. Here’s why this matters:
1. AI for Small and Medium Sized Businesses
The democratization of AI is not just a trend but a revolution reshaping the business landscape. Lower inference costs mean that even smaller businesses can now afford to deploy AI tools into their operations, potentially transforming the way they serve their customers.
2. Better Products and Services for Consumers
When companies can afford to use AI, they can offer significantly improved products and services to their customers. This potential for AI to enhance our daily experiences is a reason for optimism about the future, making us all look forward to the innovative solutions AI will bring to our lives.
3. Innovation Across Industries
Cheaper AI is fueling innovation across a wide range of sectors. From education to entertainment to finance, AI is helping companies create new solutions and improve existing processes. We will likely see more AI-driven apps, tools, and services that make life easier and more efficient.
Conclusion: The Future of AI looks Bright and Affordable.
The drop in AI inference costs is more than a trend; it’s a revolution. We’ll see AI become a part of our daily lives in more ways, from smarter customer service experiences to faster healthcare diagnoses and more personalized shopping recommendations.
For enterprises, this is a unique opportunity to leverage AI to grow and innovate. As AI becomes more affordable, it’s no longer just a tool for tech giants. It’s becoming a tool for everyone.
Key Takeaway: Lower AI costs are democratizing access to this powerful technology. Businesses across industries can now afford to harness the potential of AI.