SETI Institute’s Post

Even if you don't want to read the whole nineteen-page paper I think you may be interested in my quick 30 second overview of it. https://lnkd.in/eVppq7_H

I'm a particular fan of this InnerDrive & Bradley Busch article: Specific Retrieval Questions. I often find that retrieval is just lumped together as one big thing... 'recalling prior learning', but there's more to it. Are you using specific or open questions? If push came to shove, I think specific questions are both more important, and also easily to use more effectively. But this isn't to say that open retrieval questions are not also crucial. Anyway, check out the article because it does walk you through the pros and cons, and literature, around specific retrieval questions. https://lnkd.in/gPjsYSDU

What can you learn from the Modern Artificial Intelligence Primer? As Catherine Ordun shares, it is “...a boot camp in a PDF where you can get dangerously smart reading the content.” Join Catherine and the other authors for a deep dive on the report. https://lnkd.in/gvfa3h8v

Low Rank Adaptation is a fundamental tool in being able to fine tune LLMs and serve them at scale. This article describes the theory, and the practice. https://buff.ly/3wzlRrt Author: https://buff.ly/3JVGHEn

Speaking about artificial intelligence. Speaking about technology itself. Isn’t this just amazing. This is part of what I want to achieve with NIPPYSKY. Simple but mind blowing innovations.

Imagine a social network in which we know the number of connections for every person. The question is: what is the largest number of relationships we can pick in this network so that no two relationships share a common person (among the picked ones)? I have found the old bounds rather weak and unsatisfactory. Along with my former student Shubha Raj Kharel (who I am very proud of) we managed to develop a bootstrapping method that gives much stronger bounds, which then mathematician friends Peter Erdos and Tamas Robert Mezei managed to expand upon significantly. We also answer a question related to this, that was open since 2004. The result is the linked paper, which is so far my fastest math paper to appear (submitted Oct 8-th ).

Research workflows can be a real challenge. I remember spending countless hours trying to connect the dots between different platforms. It was inefficient and exhausting. I wrote a Medium post explores how Simplifine can simplify this process. https://lnkd.in/dcxBUfZZ

Excited to share that our paper “Persuasive explanations for path reasoning recommendations” has been published in Journal of Intelligent Information Systems. Existing path-based explanation generation approaches have made significant strides in leveraging knowledge graphs, but they have often neglected the persuasiveness of explanations. This paper introduces a personalized approach to enhance recommendation systems by considering both recommendation utility and the persuasiveness of explanations. Through experiments on a real-world movie recommendation dataset, utilizing recent path reasoning recommender system baselines, we have demonstrated the effectiveness of our approach in providing relevant recommendation lists with personalized persuasive explanations. https://lnkd.in/d78qwycV

One of the best projects I've worked on in the past thirty years! Read about it in The Scholarly Kitchen - "The success of the duplicate submission checker application, including its automated content feeds from editorial systems, led to the decision to develop this application into an automated background screening for submitted content that screens for a variety of signals, depending on the choice of the publishers. For example, publishers can screen incoming submissions for duplications, check if references appear in the Retraction Watch database, and run the content through the Papermill Alarm tool all in one go." https://lnkd.in/eEqd6zav

I was recently asked. How do you remember so many things?   A simple hack I use is repetition.   Repetition can help with information retention especially when you go back to the content over and over again.   In so doing, you not only retain what you’ve learned, but also, give time for your brain to absorb it.   In memory research, this is known as the “spacing effect”.   To read more, check out this article: https://lnkd.in/gx5fuEpN