TLDR AI

TLDR AI 2023-04-10

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01HEADLINES & LAUNCHES

GOOGLE CEO SUNDAR PICHAI SAYS SEARCH TO INCLUDE CHAT AI

Google plans to add conversational artificial-intelligence features to its flagship search engine, Chief Executive Officer Sundar Pichai said, as it deals with pressure from chatbots such as ChatGPT and wider business issues. Advances in AI would supercharge Google’s ability to answer an array of search queries, Mr. Pichai said in an interview with The Wall Street Journal. He dismissed the notion that chatbots posed a threat to Google’s search business, which accounts for more than half of revenue at parent Alphabet Inc.

archive.ph3 min read

02RESEARCH & INNOVATION

ML PAPERS OF THE WEEK

Another great list of papers to refer to regularly. There is lots of hype circulating online at the moment and so it is good to get back to the source sometimes and understand the trends. There are many lists like this one, but it seems high quality and thoughtfully curated.

github.comGitHub repository

FULL PROOF GENERATION WITH PROOF REPAIR

One common problem with generative language models is their propensity to hallucinate. Folks have pointed out that sometimes code these models generate is subtly wrong, but looks plausible. The act of verifying is sometimes more important than generating in this case. Verification is hard though, especially for code. This paper studies proof generation which can be checked by a formal system. There are lots of great insights in this work, my favorite is that when given error messages, the system can prove 1.5% more proofs.

arxiv.org24 min read

03ENGINEERING & RESOURCES

AUTOMATICALLY GENERATE LANGCHAIN TOOLS OR CHATGPT PLUGINSno link

[/%E2%80%8B%E2%80%8Bhttps://github.com/hey-pal/toolkit-ai?utm_source=tldrai]

source unknownGitHub repository

INST-INPAINT: INSTRUCTING TO REMOVE OBJECTS WITH DIFFUSION MODELS

Introducing Inst-Inpaint, a novel inpainting framework that seamlessly removes objects from images based on natural language input, eliminating the need for time-consuming binary masks. Using the GQA-Inpaint dataset, the framework outperforms GAN and diffusion-based baselines, demonstrating quantitative and qualitative improvements.

instinpaint.abyildirim.comGitHub repository

04MISCELLANEOUS