AI News #19

Efficient Infinite Context Transformers with Infini-attention

  • An infinite-context-window transformer that uses “compressive memory”, which is a set of parameters that store a compressed version of old context.
  • Paper

OSWorld

  • An environment to test the ability of multimodal agents to perform complex tasks in operating systems like Ubuntu, MacOS, and Windows.
  • Project page
  • Paper

Finding Visual Task Vectors

  • Replace attention heads with “task vectors”, that allow few-shot computer vision models to become zero-shot models.
  • Paper
  • GitHub

Scaling Laws for Data Filtering

  • Explores the tradeoff between compute, quality of data, and number of times each sample is seen during training (a.k.a epochs).
  • Paper
  • GitHub

Rho-1: Not All Tokens Are What You Need

  • Train on only the “important” tokens:
    1. Train a reference model on all tokens.
    2. Compute the reference model’s loss for every token in the dataset.
    3. Train the target model on the tokens where it has a higher loss than the reference model.
  • Paper

LLM2Vec

  • Introduces a method for transforming any decoder-based LLM into a text embedding model.
  • Paper

SpatialTracker

Memory-Augmented Large Multimodal Model for Long-Term Video Understanding

  • Store visual features of past frames in a compressed memory bank. Results in significantly less memory consumption when applying multimodal models to long videos.
  • Project page
  • Paper

ResearchAgent

  • An LLM agent that “automatically generates problems, methods, and experiment designs”.
  • Paper

New GPT-4 Turbo

The latest iteration of GPT-4 Turbo outperforms Claude 3 on various benchmarks.

Mistral 8x22B

A 176 billion parameter model released by Mistral.

Rerank 3

  • Cohere announced Rerank 3, their latest model for ranking documents for retrieval augmented generation.
  • Announcement

Udio

MTIAv2

  • Meta announced version 2 of the Meta Training and Inference Accelerator (MTIA).
  • Announcement

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