Revolutionizing gene editing with AI
In a revolutionary move in biopharma, Profluent, an ai-first protein engineering company, has developed the world's first open-source, ai-generated gene ...
Tag: models
Nota AI researchers present LD-Pruner: a novel performance-preserving structured pruning method for compressing latent diffusion LDM models
Generative models have emerged as transformative tools in several domains, including computer vision and natural language processing, by learning data ...
Google's TransformerFAM revolutionizes long context processing
Google researchers have introduced TransformerFAM, a novel architecture that will revolutionize long context processing in large language models (LLM). By ...
OpenBezoar: A family of small, cost-effective, open-source AI models trained on mixed-instruction data
The recent success of fine-tuning the instruction of pre-trained large language models (LLMs) for downstream tasks has attracted great interest ...
Talk to your slide deck using multimodal foundation models hosted on Amazon Bedrock – Part 2
In Part 1 of this series, we presented a solution that used the amazon Titan Multimodal Embeddings model to convert ...
Unleashing the recovery power of large language models: Insights from needle-in-a-haystack testing.
The rise of large language models (LLM) has revolutionized natural language processing (NLP), enabling significant advances in text generation and ...
How Snowflake Text Embedding Models Are Changing the Game
Introduction Text embedding plays a crucial role in modern ai workloads, particularly in the context of enterprise search and retrieval ...
Reka launches Reka Core: the next generation of multimodal language models in text, images and videos
Reka is a California-based ai startup that is setting new standards in the industry. Reka has recently launched its most ...
Pushing RL Boundaries: Integrating Foundational Models, e.g. LLMs and VLMs, into Reinforcement Learning | by Elahe Aghapour & Salar Rahili | Apr, 2024
In-Depth Exploration of Integrating Foundational Models such as LLMs and VLMs into RL Training LoopAuthors: Elahe Aghapour, Salar RahiliOverview:With the ...
Understanding Overfitting in ConvNets
Introduction Overfitting in ConvNets is a challenge in deep learning and neural networks, where a model learns too much from ...
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