TechnicalAI glossary
Inference
The moment the already-trained model responds to your request. That's what you pay for when you use an AI API.
In other words
The concert, after years of rehearsal.
Alyriaz articles that mention it
- Anthropic tells its investors it was profitable in the second quarter, with gross margins above 80%
According to the Financial Times, Anthropic has told its investors it is targeting profitability in the second quarter, with gross margins above 80% on $11.5 billion in revenue. We explain why the margin is the decisive figure.
- Qualcomm and Amazon team up on inference chips
Qualcomm and AWS have announced a collaboration to jointly design chips dedicated to inference. We analyse what this tie-up reveals about the reshaping of the silicon market.
- OpenAI publishes the first results from its in-house chip
OpenAI has published the first results from its in-house inference accelerator, touted as delivering strong speed and efficiency. We analyse what this move reveals about the balance of power in infrastructure.
- Nvidia is putting into production a chip that does only one thing: respond fast
Nvidia has announced that its inference accelerator, born from its acquisition of Groq, is entering production. Here’s why a chip specialised in responding rather than training is a significant signal.
- DeepSeek raises prices by 93%: has the price war hit rock bottom?
DeepSeek raised the price of its Flash model by 93% on 14 August, while other players are still cutting theirs. We analyse what this reversal reveals about the real economics of inference.
- Training and inference: the two costs of AI that everyone keeps confusing
There's a lot of talk about the cost of training models, but rarely about the cost of their daily use. We explain the difference between training and inference, why the latter now dominates the AI economy, and what that implies.