The technology has advanced by leaps and bounds in recent years, developing different tools that can facilitate various daily tasks. An example of this is **chatbots**, those **[software programs](https://noticiasambientales.com/innovacion/las-limitaciones-de-los-chatbots-de-ia-que-pueden-y-no-pueden-hacer/)** that simulate conversations with users, generally through text or voice. However, a chatbot query contaminates or consumes the same amount of energy as a full phone charge.
These programs are **designed with artificial intelligence (AI)**, which is used to understand natural language and respond to questions or perform tasks in an automated way, such as customer service or appointment management.
In fact, among the most common **functions and applications** are **customer service, sales, marketing, assistance in various areas, and user empowerment**, so that users can obtain information or perform actions more quickly and easily. On the other hand, they contribute to cost reduction by automating tasks and processes, not to mention that they can be personalized, adapting to the needs and preferences of the user.
In summary, **chatbots are tools that allow automated communication with users**, mimicking human conversation and providing quick and efficient responses or services.
## The pollution caused by chatbots
### **Grok, the most ecological chatbot**
According to an analysis by TRG Datacenters, Grok AI is the most environmentally efficient AI model. Each query generates only **0.17 grams of CO₂**, a carbon footprint similar to a Google search. Grok stands out for its optimized architecture, which minimizes energy use without compromising performance.
### **Google’s Gemini: power with efficiency**
In second place is **Gemini**, Google’s model, with **1.6 grams of CO₂ per query**. Thanks to its specialized infrastructure and the use of renewable energies, it manages to maintain a low carbon footprint compared to other models. Each question asked to Gemini pollutes the same as watching a 10-minute YouTube video.
### **Meta and Claude: in the middle of the road**
The **LLaMA** model, from Meta, generates **3.2 grams of CO₂** for each response. Although Meta invests in clean energy, the growth of its AI infrastructure could increase its emissions in the future. The environmental impact of LLaMA is comparable to sending 10 simple emails.
**Claude AI**, from Anthropic, ranks fourth with **3.5 grams per query**. Its focus on security and reliability seems to require more computing power, which increases its energy consumption. This emission is equivalent to watching a short video and sending an email.
### **Perplexity and GPT-4, the least sustainable**
**Perplexity AI** records **4 grams of CO₂** per query, mainly due to its integrated search functions. Complex queries further increase its energy consumption. Each interaction has a similar impact to charging a phone one to two times.
The **[most polluting model](https://noticiasambientales.com/energia/impacto-ambiental-de-chatgpt-el-costo-oculto-de-generar-imagenes-ghibli/)** is **ChatGPT with GPT-4**, reaching **4.32 grams of CO₂ per response**. Its complexity and capacity generate a footprint 25 times greater than Grok. A single GPT-4 response is equivalent to **21 emails or almost a full phone charge**. This means that this chatbot pollutes more than the others.
## The challenge of balancing innovation and sustainability
TRG Datacenters emphasize the urgent need to make AI more energy efficient. “The adoption of AI continues to grow. Improving hardware, optimizing models, and expanding the use of renewable energies in data centers are key steps to reduce emissions,” they explained.
With artificial intelligence consolidating as a key technology in multiple sectors, this study makes it clear that the future of innovation must also be green.
## **How many types of chatbots exist?**
According to experts, there are different types of chatbots such as:
– **Rule-based:** They use predefined conversation flows and rules to respond to questions, they are simpler but less flexible.
– **AI-based:** They use natural language processing (NLP) and machine learning (ML) techniques to better understand user questions and offer more accurate responses.
– **Generative:** They can generate new content, such as text, images, or sound, in response to the user’s query.
**Chatbots have evolved and integrated into various platforms and channels**, such as websites, messaging applications, smart speakers, and social networks. Their ability to understand natural language and automate communication has made them increasingly popular and useful for various industries and applications.
Source: TRG Datacenters.
