5 Common Mistakes to Avoid When Training LLMs
Training large language models (LLMs) is an involved process that requires planning, computational resources, and domain expertise.
Training large language models (LLMs) is an involved process that requires planning, computational resources, and domain expertise.
In this post, I’ll show you how to use Amazon Bedrock—with its fully managed, on-demand API—with your Amazon SageMaker trained or fine-tuned model. Amazon Bedrock is a fully managed service that offers a choice of high-performing foundation models (FMs) from leading AI companies such as AI21 Labs, Anthropic, Cohere, Meta, Mistral AI, Stability AI, and …
The exponential growth of machine learning models brings with it ever-increasing datasets. This data deluge creates a significant bottleneck in the Machine Learning Operations (MLOps) lifecycle, as traditional data preprocessing methods struggle to scale. The preprocessing phase, which is critical for transforming raw data into a format suitable for model training, can become a major …
Read more “Distributed data preprocessing with GKE and Ray: Scaling for the enterprise”
Adobe and HKUST researchers unveil TransPixar, a breakthrough AI system that creates transparent visual effects from text prompts.Read More
As hurricane-force winds fan the most destructive wildfires in California history across bone-dry foothills, communities face the dual threat of natural forces and a warming world.
Among the marvels of the human brain is its ability to generalize. We see an object, like a chair, and we know it’s a chair, even when it’s a slightly different shape, or it’s found in an unexpected place or in a dimly lit environment.
Explore key takeaways from our recent webinar on how AI can transform ABM strategies with workflow automation, personalization at scale, and more.
Generative AI applications are gaining widespread adoption across various industries, including regulated industries such as financial services and healthcare. As these advanced systems accelerate in playing a critical role in decision-making processes and customer interactions, customers should work towards ensuring the reliability, fairness, and compliance of generative AI applications with industry regulations. To address this …
Foundation models such as Gemini have revolutionized how we work, but sometimes they need guidance to excel at specific business tasks. Perhaps their answers are too long, or their summaries miss the mark. That’s where supervised fine-tuning (SFT) comes in. When done right, it unlocks incredible precision to tailor Gemini for specialized tasks, domains, and …
Read more “Supervised Fine Tuning for Gemini: A best practices guide”
According to Meta, memory layers may be the the answer to LLM hallucinations as they don’t require huge compute resources at inference time.Read More