TLDR AI 2023-03-21

30B INSTRUCTION TUNED MODEL

STABLE DIFFUSION REIMAGINE

CODEPS: ONLINE LEARNING FOR PANOPTIC SEGMENTATION

The paper proposes a solution to the challenge of robotic navigation in new environments by introducing CoDEPS, a continual learning approach that utilizes experience replay and domain mixing to mitigate catastrophic forgetting and adapt to changing conditions. The proposed method achieves state-of-the-art results and addresses the limited storage capacity of robotic systems.

LION: IMPLICIT VISION PROMPT TUNING

The paper proposes LION, an efficient vision model that addresses the heavy computational costs of vision Transformers by using deep implicit models with stable memory costs. LION only inserts two equilibrium implicit layers in the pre-trained main backbone and prunes parameters according to the lottery hypothesis, reducing up to 11.5% of training parameter numbers while achieving higher performance than state-of-the-art baseline VPT on a wide range of datasets, especially under challenging scenes.

DIFFUSIONRET: GENERATIVE TEXT-VIDEO RETRIEVAL WITH DIFFUSION MODEL

The paper introduces DiffusionRet, a diffusion-based text-video retrieval framework that models the correlation between text and video as their joint probability, p(candidates, query), from a generative viewpoint. DiffusionRet optimizes the generator through generation loss and the feature extractor through contrastive loss, leveraging both generative and discriminative methods to achieve superior performance on five commonly used text-video retrieval benchmarks, even in out-domain retrieval settings, and bringing fundamental insights into the related fields.

TRANSFORMER REINFORCEMENT LEARNING V0.4.1 RELEASED

WHICH DATA MADE MY MODEL SMARTER?

Instead of using an additive scalar score to determine how much influence a data instance has on final model performance, what if we used a full training simulator? This enables counter-factual exploration around dataset construction and long term training performance. This method tends to underestimate performance, but does a good job of capturing general dynamics for large language model training runs.

LANGFLOW

A visual graph based editor for LangChain that runs in the browser.

HOW GPT MAY AFFECT THE LABOR MARKET

While GPT models may impact labor markets, the effect is not uniform across jobs. A preliminary look suggests physically active and mentally creative jobs are less likely to be affected by large language models. Not the most convincing methodology, but a good step at this early juncture to understand what our economic future might look like.

DUOLINGO AND OPENAI

Duolingo has introduced two new features powered by OpenAI's GPT-4: Role Play, an AI conversation partner, and Explain my Answer, which provides contextual feedback on mistakes, in a new subscription tier called Duolingo Max. Duolingo turned to GPT-4 after finding that GPT-3 could not confidently handle the complex automated aspects of chats. The team sees the potential of GPT-4 to provide a more effective and engaging learning experience than ever before, which should improve learning outcomes, and it has simplified the entire engineering process, making it faster to bring new features to users.

STANFORD COPIES THE CHATGPT AI FOR LESS THAN $600

BLOOP

Bloop is a code-search engine that uses GPT-4 to answer questions about your code.

SEMANTIC KERNEL

Semantic Kernel (SK) is a lightweight SDK enabling integration of AI LLMs with conventional programming languages.