Why the newest LLMs use a MoE (Mixture of Experts) architecture
Mixture of Experts (MoE) architecture is defined by a mix or blend of different “expert” models working together to complete a specific problem.
Mixture of Experts (MoE) architecture is defined by a mix or blend of different “expert” models working together to complete a specific problem.
By feeding LLMs the necessary domain knowledge, prompts can be given context and yield better results. RAG can decrease hallucination along with several other advantages.
The scale and complexity of LLMs The incredible abilities of LLMs are powered by their vast neural networks which are made up of billions of… Read More »Quantization and LLMs – Condensing models to manageable sizes
The concept of diffusion Denoising diffusion models are trained to pull patterns out of noise, to generate a desirable image. The training process involves showing… Read More »Diffusion and denoising – Explaining text-to-image generative AI
Sometimes, something happens right before your eyes, but it takes time (months, years?) to realize its significance. In February 2019, I wrote a blog titled… Read More »Creating AlphaStar: The Start of the AI Revolution?
Discover the differences between AI, machine learning, and deep learning in this comprehensive guide. Learn how each technology works, their key applications, and the skills required for a career in data science.
This week, there was (yet another) game changing announcement from the folks at Deepmind named Gato Gato is a cool cat 🙂 It leads us… Read More »Why Gato from Deepmind is a game changer
How exactly do you define Artificial Intelligence(AI)? This looks like a back to basics/ back to school question – but the answer is not that… Read More »How exactly do you define Artificial Intelligence(AI)?
Deep Learning has shown tremendous success, but what makes it so special? What are neural networks, and how do they work? What are the differences… Read More »DSC Webinar Series: Deep Learning – Introduction to Neural Networks
In this latest Data Science Central webinar, we will cover the principles for training your neural network including activation and loss functions, batch sizes, data… Read More »DSC Webinar Series: Deep Learning – Training your Neural Network