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# Introduction
what to do things Like electricity, wheat, mobile phones, and the Internet? Arguably, for many, they have become what we call Commodityi.e., “is a resource or good that has complete or substantial fungibility (or is considered necessary only for a modern way of life).”
Most of the examples mentioned became objects at certain points in history. In the late 90s, for example, mobile phones were still a burgeoning novelty – at least, as far as I can remember. Yet who can imagine living without one in the present century?
Fast forward to the present day, and looking at the language model tech wave that has permeated our lives for the past 3 to 4 years, this article analyzes a set of objective facts. This adds a pinch of personal thoughts to the following question: Are language models the new commodity we can’t live without?
# Review the facts
Just a few years ago, a modern language model was considered a luxury tech asset, but today it has become a ubiquitous solution that many organizations can no longer afford.
There are several facts about the current market reality that explain this widespread access to language models:
- Declining Cost: This may seem counterintuitive in the modern global context of rising prices for almost everything, but one exception to this norm is the cost of “raw intelligence” solutions. An example is the cost of processing 1 million tokens (about 750K words) in Frontier models, which even a few years ago cost tens of dollars, but now can cost tens. St.
- Free Access Revolution: Open-weighted models have played an important role in breaking down the barrier of exclusion. Language model families like Meta’s Llama or Mistral have shown based on public benchmarks that they can equal or even outperform many commercial alternatives.
- Zero Cost: Nowadays, any user can download language model tools like Olama for free and run highly capable models locally on their machine. This completely eliminates the need for paid subscriptions or API quota usage, as well as the reliance on third-party services. As a result, access to AI as a basic and free resource has become the new norm.
“In the late ’90s, for example, mobile phones were still a burgeoning novelty – at least, as far back as I can remember. Yet in the current century, who could imagine living without them?”
# Searching for factual scenes
Basic AI capabilities may have become a commodity, but having a model with its “personality” that goes the extra mile with complex, sophisticated tasks just isn’t seen as such. Many foundation models—which are based on an upward, general-purpose approach, and which represent an initial, large-scale pre-training phase before a model is adapted to specific tasks—can generate free text responses or code, but there is still a significant difference between the human’s natural narrative and the model’s conversational style, which is sometimes still verbose and uses robotic vocabulary. Many of the outputs produced by these models still require final refinement, and this is a differentiating factor across domains.
On another note, many users don’t invest in the models themselves, but in the experience that comes with them. Having a free text generation engine on our own computer sounds great, but businesses need to charge for a solution that optimizes that model to interact with your documents, code, or workflow in a specific way. We’re still relatively far from the point where everyone will accept outsourcing (often paid for) language model solutions rather than doing this work themselves.
# Delivery of judgment
Based on the facts that show how the role and access to language models have evolved in recent years, almost independently, we can think that these factors have pushed such models to become the new commodity of the current decade. But there are still other aspects such as reliability, fully guaranteed privacy, and compatibility with specific application domains (such as medical or legal reasoning), which are still not within everyone’s reach, yet. Premium Goods, and making the term “commodity” somewhat debatable in the landscape of language patterns.
Iván Palomares Carrascosa He is a leader, author, speaker, and consultant in AI, Machine Learning, Deep Learning and LLMs. He trains and guides others in using AI in the real world.