2023 saw AI industry focusing on scaling tried and tested methodologies instead of introducing new technologies. Upgrades were made to models like ChatGPT, DALL-E and Stable Diffusion. Secrecy around model architectures increased, accompanied by a trend of scaling input context length. In open-source and research trends, focus shifted to Latent Language Models (LLMs) and Multimodal LLMs. Challenges around copyright issues, model hallucination and accuracy in results persist. An increase in developing custom AI chips is anticipated for 2024, along with more open-source Mixture of Experts models.
AI and Open Source in 2023
2023 saw AI industry focusing on scaling tried and tested methodologies instead of introducing new technologies. Upgrades were made to models like ChatGPT, DALL-E and Stable Diffusion. Secrecy around model architectures increased, accompanied by a trend of scaling input context length. In open-source and research trends, focus shifted to Latent Language Models (LLMs) and Multimodal LLMs. Challenges around copyright issues, model hallucination and accuracy in results persist. An increase in developing custom AI chips is anticipated for 2024, along with more open-source Mixture of Experts models.