Encord Releases Revolutionary AI Training Method That Outperforms Rivals Using 17x Fewer Parameters

Encord unveils breakthrough EBind methodology that trains powerful multimodal AI models on single GPUs in hours rather than weeks, with their 1.8 billion-parameter system outperforming competitors using 17 times more parameters by prioritizing data quality over computational brute force.

• Encord releases the world's largest open-source multimodal dataset and introduces EBind methodology to democratize AI training for smaller companies
• The EBind method enables training of multimodal AI models on a single GPU within hours instead of weeks, focusing on data quality over raw computing power
• Encord's 1.8 billion-parameter model reportedly outperforms rival models with up to 17 times more parameters while using significantly less computational resources