TLDR AI 2023-03-16

GPT-4 IS EXCITING AND SCARY

The article discusses the author's experience testing GPT-4 by asking it a variety of questions — to help with a tax problem, to come up with a new word, to plan a birthday party. The author found that GPT-4 was capable of a wider range of tasks, more fluid in its responses, and seemed to have more guardrails in place than its predecessor. GPT-4 also scored high on a variety of tests, including the Uniform Bar Exam and the Biology Olympiad. While the article acknowledges the positive potential of GPT-4, it also discusses the negative side — the thought of AI being smarter than humans, ethical implications of such technology, and the potential for misuse. Also, another correction from yesterday’s newsletter: GPT-4 can take both _IMAGES_ and text as inputs, but not video. Sorry for the brain fart! Maybe I should have had GPT-4 proofread it :)

ADEPT AI RAISES $350M IN SERIES B FUNDING

Adept has raised $350M in new funding as part of their Series B led by General Catalyst and Spark Capital. Adept is a research and product AI lab that automates software processes for developers. It's similar to robotic process automation (RPA), or software robots that use a combination of automation, computer vision, and machine learning to automate repetitive tasks like filing forms and responding to emails. Adept is creating general intelligence by allowing humans and computers to collaborate creatively.

GOVERNMENTS

REINFORCEMENT LEARNING FROM PRIVACY FEEDBACK

IN LARGE LANGUAGE MODELS

This paper proposes a solution to the challenge of fine-tuning and task-specific prompt engineering that can limit the generalization abilities of Large Language Models (LLMs). The proposed method, UPRISE, uses a lightweight and versatile retriever to automatically retrieve prompts for a given zero-shot task input, and demonstrates universality in a cross-task and cross-model scenario. The method is tested on a diverse set of tasks, using a small frozen LLM for tuning and testing on much larger LLMs, and is shown to mitigate the hallucination problem in experiments with ChatGPT, suggesting potential to improve even the strongest LLMs.

DEEPMIM: DEEP SUPERVISION FOR MASKED IMAGE MODELING

This paper introduces DeepMIM, a deep supervision technique that significantly boosts the representation capability of each layer in Vision Transformers for masked image modeling. The results show that DeepMIM accelerates model convergence, expands attention diversities, and achieves state-of-the-art performance on various downstream tasks.

PIP INSTALL PYTORCH 2.0

Announced in December, this new version of pytorch is now stable and available for easy installation. With a slew of new features, speed improvements, and interfaces - it’s an exciting time to be using the most popular deep learning framework out there.

EDIT-A-VIDEO: A TEXT-TO-VIDEO APPROACH FOR VIDEO EDITING

This paper presents Edit-A-Video, a framework for video editing based on text-to-video (TTV) models adapted from diffusion-based text-to-image (TTI) models. The proposed framework inflates the 2D model into a 3D model, and inverts the source video into the noise to edit with a target text prompt and attention map injection, while also mitigating the background inconsistency problem through a novel mask blending method. Experimental results show the superiority of the proposed method in terms of background consistency, text alignment, and video editing quality compared to baselines.

GOOGLE PARTNERS WITH GRETEL TO ADD SYNTHETIC DATA INTO VERTEX AI

HOW SIRI, ALEXA, AND GOOGLE ASSISTANT LOST THE AI RACE

Virtual assistants like Siri, Alexa, and Google Assistant had more than a decade head start to become indispensable. But they were hampered by clunky design and miscalculations, leaving room for chatbots like ChatGPT to rise.

HERE’S WHAT IT WOULD TAKE TO SLOW OR STOP AI

LINKEDIN IS ADDING AI TOOLS

LLAMA-RS

LLaMA-rs is a Rust port of LLaMA.

GPT-4-FOR-CODE

This GitHub repo contains a few impressive examples of GPT-4 coding.