From: redpointai
Synthetic Data in AI
The success of synthetic data has been somewhat unexpected in the AI field [00:30:45]. It addresses concerns about running out of tokens for training large language models [00:32:38]. Society produces vast amounts of data daily [00:33:07], and while not all of it is high quality, it can still be learned from, albeit requiring more quantity for lower quality data [00:33:20].
A paper suggesting that synthetic data cannot be used to train language models on their own data is considered flawed and based on unrealistic scenarios [00:34:46]. When implemented correctly, synthetic data is highly powerful [00:35:17]. Combining synthetic data with smarter algorithms like KTO (Kahneman-Tversky Optimization) and APO (Anchored Preference Optimization) can significantly reduce the need for manual data annotation and heavy computational resources [00:35:20].
Furthermore, the concept of synthetic data is inherently linked to agents, as one agent might train another [00:43:33].
Multimodal Systems in AI Development
Early in his career, the speaker focused on grounding language in perceptual information, which laid the foundation for multimodal systems [00:09:35]. An example of this is trying to understand the meaning of a word like “cat” more deeply by integrating pictures of cats into machine learning and NLP systems [00:09:43].
The field of multimodal AI models is still in its nascent stages, with much potential yet to be explored [00:33:52]. Video data, for instance, offers a massive untapped resource for training [00:33:56]. By training on extensive video content, such as cat videos, multimodal AI models can develop a much better understanding of concepts and the world, moving beyond relying solely on linguistic behaviors (text produced on the internet) as a proxy for observation [00:34:01].
Multimodality is considered a significant way to incorporate even more data into AI training [00:34:38]. The speaker anticipates that multi-agent systems, which are related to this systems approach, will be the next major trend in AI [00:40:33].