AI & Sustainability
We don't just talk about AI benefits. We also talk about the costs.
AI's Energy Hunger
A single ChatGPT query consumes about 50 times more energy than a Google search. Training GPT-3 produced 552 tons of CO2 - as much as 120 cars in a year.
We believe: If you propagate AI, you must also talk about this side. Not to cause panic, but to enable responsible use.
The Numbers
Energy-Efficient Prompting
Precise not iterative
One good prompt replaces four bad ones. Formulate your query completely.
The right tool
For simple translations you don't need GPT-4. DeepL is faster and more efficient.
Cache and reuse
Save good answers. Create templates for recurring tasks.
Use smaller models
GPT-3.5 or Claude Haiku are enough for simple tasks - and use less energy.
Keep Perspective
Yes, AI consumes energy. But: If AI makes an employee more efficient, that might save commuting, office space, paper. The overall balance can be positive - if we use AI wisely.
The tech industry is investing massively in more efficient chips and renewable energy. Energy consumption per query is constantly decreasing. But that doesn't absolve us from the responsibility to use it mindfully.
Finding the Balance
We're not advocating for abstinence. We're advocating for conscious use. Use AI where it brings real value - and save resources where it's not necessary.
Häufige Fragen
No. But use it purposefully. A well-formulated prompt that delivers the desired result is better than ten iterations.
Smaller models consume less. Claude Haiku, GPT-3.5 or specialized tools like DeepL are more efficient than the large models.
Google, Microsoft and Amazon have committed to carbon neutrality. OpenAI and Anthropic are working on more efficient models. Development is heading in the right direction - but it's not there yet.