Girls Who Invest’s Post

Our Pattern Fellows Program was fortunate to learn all about artificial intelligence last week. We had amazing guest speakers, including Andrew Sica, a senior technical staff member working on AI at IBM; Brad Johnsmeyer from Ecohome; and Jason Scott, who was a founding member of the AI practice in the law firm of Gordon Rees Scully Mansukhani. We learned about the broad applicability of artificial intelligence, emerging uses across industry sectors, and some of the sticky legal and practical questions that are still to be answered. I'll be the first one to admit holes in my knowledge game - this is moving faster and farther than I realized!

It's new, it's filling up with Behavioural Science and Machine Learning talks, and you can find them here: https://lnkd.in/eeSwiiW4 Here's the playlist for the BSCI-AI Ideation Workshop:

Is open sourcing crucial for AI tools in coding and testing? We've discussed this question with Eli Hooten, director of Engineering at Sentry. He says that LLMs are poised to benefit from open source contributions 👇 Full interview with Eli Hooten: https://lnkd.in/eCbwRAyU

Join the Bayesian revolution! I'm thrilled to share my article in the April edition of The Actuary, produced in collaboration with Bradley Shearer. As machine learning and AI become increasingly popular within the actuarial world, it is our responsibility to ensure that we are clearly communicating the stories that our models are telling. In this article, we explore probabilistic programming, an approach to implementing Bayesian methods which is built with interpretability at its core. https://lnkd.in/g6ri6hed

These 3 incredible LLMs are going to provide companies with incredible options to deploy GenAI applications.

Reminder: the deadline for submission to HumaneIntelligence's first Algorithmic Bias Bounty Challenge is tonight (July 15) at 11:59pm ET! All Tech Is Human was honored to partner with Dr. Rumman Chowdhury, Theodora Skeadas, and the incredible team at HI on this first challenge, worth $10k in prizes for all experience levels, and we at ATIH had a fantastic time hosting a hackathon last week for 200+ attendees and challenge participants in NYC! This challenge builds on the evaluation and dataset from the recently released Generative AI Red Teaming Challenge: Transparency Report (download link and a livestream detailing the report's findings are both in the comments below), and if you’re just getting started, Kristi Arbogast released a series of fantastic tutorials for beginners (link in comments). If you missed this one, fear not! There will be 9 more –  follow Humane Intelligence to stay up to date.

📢 Check out this insightful article by Sabine Van der Linden on the differences between perplexity, OpenAI, and Claude! Gain a better understanding of these concepts and how they can be applied in everyday life. Don't miss out: @SabineVdL

Last one as we work through the modules of this interesting new course by Curtis Evans - https://lnkd.in/g5Q9xb-4 - Fundamentals of Generative AI for Beginners. Building large language models (LLMs) can be expensive and their output can be biased. In Part 4, you'll tackle some important design considerations for building LLMs with integrity, including: 🔧 how to build using quality data with optimized parameters 🔧 how to use suitable architectures to build 🔧 how to optimize model training 🔧 how to test models, evaluate them, and deploy them In addition, you'll learn about some important ethical considerations surrounding the building and use of these models to avoid harmful outputs. Put on your builder's hat, and let's go!

"Predicting Deepfake Enjoyment: A Machine Learning Perspective" Our paper is live now in the Springer LNCS! I expect to present this work at 2024.hci.international in Washington DC, USA (1-4 July). If you're around and up for a chat, feel free join. In this study, we explore people's engagement with non-deceptive deepfake content. In a wonderful amalgamation of psychological research and ML methods, we find out the root causes behind deepfake enjoyment and sharing behavior. Link attached.

Chapter #1 of our Runbook: A DareData Tech Session here: https://lnkd.in/d2SVCr9c