1. Elon Musk warns: AI's real data is running out!
The magnate claims that humanity has reached the 'data peak', which poses an uncertain future for artificial intelligence. Are we reaching the limit of what we can learn from real data?
2. Will synthetic data be the solution or the problem?
Musk bets on synthetic data to feed AI. However, these could carry great risks: less creativity, bias, and failures. Is it a breakthrough or a dangerous shortcut for artificial intelligence?
3. The tech giants are already doing it: Microsoft, Meta, OpenAI...
The largest companies are already integrating synthetic data into their models. Are we about to witness a revolution in AI or are we opening a Pandora's box with these artificial approaches?
4. Synthetic data: cheaper, but less intelligent?
The cost of creating AI models plummets when using synthetic data, but at what price? The generated intelligence may not be as advanced as that which comes from real data. Is it a short-term saving that could affect quality in the long term?
5. Does AI need more data, or a new way of thinking?
The depletion of real data raises a fundamental question: does AI simply need more data or is it time to completely rethink how we create and process that data?
6. Can synthetic data surpass human limitations?
60% of AI data by 2024 will be synthetic, according to Gartner. But if the models are trained with artificial data, will they really learn enough to overcome human limitations?
7. The threat of bias: the hidden danger of synthetic data
Synthetic data is not just a cost issue. The risk of bias in models could be even greater, with serious consequences if the training data is already biased. Are we willing to face those consequences for cheaper AI?