MindCast

Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer

# Summary This paper introduces T5 (Text-to-Text Transfer Transformer), a unified framework for text-based tasks. The authors propose converting all NLP tasks into a text-to-text format, where the inp...

ZeRO: Memory Optimizations Toward Training Trillion Parameter Models

# Summary This paper introduces ZeRO (Zero Redundancy Optimizer), a set of memory optimization techniques designed to enable training of extremely large (trillion parameter) deep learning models. ZeR...

Scaling Laws for Neural Language Models

<h2 class="text-2xl font-bold mb-4">Summary</h2> This paper, published by OpenAI, investigates the relationship between the performance of neural language models (NLMs) and three key factors: model s...

Switch Transformers: Scaling to Trillion Parameter Models with Simple and Efficient Sparsity

<h2 class="text-2xl font-bold mb-4">Summary</h2> The paper introduces Switch Transformers, a novel architecture designed to scale language models to trillions of parameters. It leverages a mixture-of...

GLaM: Efficient Scaling of Language Models with Mixture-of-Experts

<h2 class="text-2xl font-bold mb-4">Summary</h2> The paper introduces GLaM (Generalist Language Model), a large language model that utilizes a Mixture-of-Experts (MoE) architecture to achieve efficie...

Improving language models by retrieving from trillions of tokens

<h2 class="text-2xl font-bold mb-4">Summary</h2> This DeepMind paper introduces Retro (Retrieval-augmented Transformer), a language model architecture that improves performance by retrieving informat...

Scaling Language Models: Methods, Analysis & Insights from Training Gopher

<h2 class="text-2xl font-bold mb-4">Summary</h2> This paper details the training and analysis of Gopher, a large language model (LLM) developed by DeepMind. It explores the scaling laws of LLMs, inve...

PaLM: Scaling Language Modeling with Pathways

<h2 class="text-2xl font-bold mb-4">Summary</h2> The paper introduces PaLM (Pathways Language Model), a large-scale language model developed by Google. PaLM is trained using the Pathways system, whic...

Scaling Instruction-Finetuned Language Models

<h2 class="text-2xl font-bold mb-4">Summary</h2> This paper investigates the impact of scaling instruction-tuned language models, focusing on the Flan-T5 and PaLM families. It explores how the perfor...

Resurrecting Recurrent Neural Networks for Long Sequences

<h2 class="text-2xl font-bold mb-4">Summary</h2> This research paper from DeepMind likely explores improvements to recurrent neural networks (RNNs) specifically designed to handle long sequences, pos...

Mamba: Linear-Time Sequence Modeling with Selective State Spaces

<h2 class="text-2xl font-bold mb-4">Summary</h2> This paper introduces Mamba, a novel state space model (SSM) for sequence modeling that achieves linear-time processing of sequences. Mamba addresses ...

Transformers are SSMs: Generalized Models and Efficient Algorithms Through Structured State Space Duality

<h2 class="text-2xl font-bold mb-4">Summary</h2> This research paper, published in May 2024 by researchers from CMU and Princeton, explores the relationship between Transformers and Structured State ...

Deep Learning