In the realm of generative AI, open-source projects have emerged as powerful tools that democratize access to cutting-edge models and foster collaborative development. They enable researchers, developers, and enthusiasts to experiment, improve upon existing models, and create novel applications that benefit society as a whole. In this article, I want to briefly review the key open-source projects and discuss their potential as well as safety risks. Hugging Face: A Hub of Open-Source AI Models Hugging Face stands out as a prime hub for open-source models in various AI domains. Hosting over 200 ..read more

Midjourney Evolution. V1 – V5.1 In 2015, a research paper from Stanford University and UC Berkeley introduced diffusion models, coming originally from statistical physics, into the field of machine learning. According to the paper summary, “the essential idea is to systematically and slowly destroy the structure in a data distribution through an iterative forward diffusion process. We then learn a reverse diffusion process that restores structure in data, yielding a highly flexible and tractable generative model of the data.” That’s the basic idea used by the latest diffusion models, like DALL ..read more

Creativity as envisioned by Midjourney. Generated by the author This article was originally published on the author’s blog and re-published to TOPBOTS with permission from the author. In recent weeks, people have used large language models (LLMs) to generate a variety of creative content, such as books, flash fiction, rap battles, and music chords. But is it possible to measure the level of creative process more broadly in these models? Human creativity has long fascinated psychologists and researchers. Starting in the 1950s, researchers created a series ..read more

In the rapidly evolving field of artificial intelligence, natural language processing has become a focal point for researchers and developers alike. As a testament to the remarkable progress in this area, several groundbreaking language models have emerged in recent years, pushing the boundaries of what machines can understand and generate. In this article, we will delve into the latest advancements in the world of large-scale language models, exploring enhancements introduced by each model, their capabilities, and potential applications. We’ll start with a seminal BERT model from 2018 and fin ..read more

This article was originally published on the author’s blog and re-published to TOPBOTS with permission from the author. There’s a quote about how in polite society, you should never talk about three things: politics, religion, and money. In this article, I break polite conventions to determine how an AI would respond to all three of those topics. As AI tools become more and more integrated into our lives (such as writing news articles or being used in mental health chatbots), it’s important (and curious) to know if these tools generate outputs that reflect certain political ..read more

Image generated by ArtMyko using Midjourney The belief that science means observable and repeatable experiments, which began with Descartes in the seventeenth century, is, to this extent, over. Global understanding is, by contrast, based on computational models supported by a knowledge infrastructure. — How to See the World, Nicolas Mirzoeff The Arabic numeral system permitted numbers to be manipulated easily, which led to mathematics and its role as the tool to validate science. In fact, the history of science is in large part the history of new mathematics validating new fundamentals in sc ..read more

This article is based on the chapter from the Interpretable AI book by Ajay Thampi. Take 35% off Interpretable AI or any other product from Manning by entering bltopbots23 into the discount code box at checkout at manning.com. Diagnostics+ AI – Diabetes Progression Imagine that you’re developing an AI-powered app that will help you diagnose illnesses: Diagnostics+. The clinic that has commissioned you to make the app would now like to venture into diabetes and determine the progression of the disease for their patients one year after the baseline measurement is taken. This is shown in Fig ..read more

Credit: [1] “…it is the scale of physics where life emerges, but that life itself is a broader phenomenon recurring across different scales, from chemistry to cells to societies–which more generally concerns the interactions of information (an abstract property) with matter.” [2] In Part 1 of this series I discussed how artificial intelligence (AI) has advanced to the point where it creates new data for analysis, abstracts the insights from the synthetic data and takes on much of the cognitive role previously reserved for humans. In Part 2 of the series we probed furth ..read more

How popular LLMs score along human cognitive skills (source: semantic embedding analysis of ca. 400k AI-related online texts since 2021) Disclaimer: This article was written without the support of ChatGPT. In the last couple of years, Large Language Models (LLMs) such as ChatGPT, T5 and LaMDA have developed amazing skills to produce human language. We are quick to attribute intelligence to models and algorithms, but how much of this is emulation, and how much is really reminiscent of the rich language capability of humans? When confronted with the natural-sounding, confident outputs of these m ..read more

Credit: DALL-E 2 “The contemplation in natural science of a wider domain than the actual leads to a far better understanding of the actual.” — Sir Arthur Eddington In Part 1 of this series, I said “I will refrain from saying that Generative Artificial Intelligence (AI) is the basis for a third school of epistemology”. A recent article I read explored the challenges in Generative AI from the perspective of metaphysics. My resolve about no new school of epistemology is weakening and this new article explains why. Neural Networks and Deep Learning algorithms, combined with syntheti ..read more