London Commute Agent, From Concepts to Pretty Maps
Author(s): Anders Ohrn Originally published on Towards AI. Source: Image by Author A hope for Large Language Models (LLMs) is that they will close the gap between what is meant (the semantics) and its formulation (the syntax). That includes calling software functions …
Empirical Techniques for Enhanced Predictive Modeling: Beyond Traditional ARMA
Author(s): Shenggang Li Originally published on Towards AI. This member-only story is on us. Upgrade to access all of Medium. A Non-Parametric Approach for Robust Forecasting and Data Analysis Across Domains Photo by XinYing Lin on Unsplash The ARMA model is a …
#49 Why Become an LLM Developer?
Author(s): Towards AI Editorial Team Originally published on Towards AI. Good morning, AI enthusiasts! This week, I am super excited to finally announce that we released our first independent industry-focus course: From Beginner to Advanced LLM Developer. Put a dozen experts (frustrated …
Google Launches New AI ‘Learning Companion’ Tool
Author(s): Get The Gist Originally published on Towards AI. Plus: Amazon Develops Its Own Custom AI Chips This member-only story is on us. Upgrade to access all of Medium. Welcome to Get The Gist, where every weekday we share an easy-to-read summary …
Exploring DNA Classification with Next-Generation Sequencing (NGS) and Machine Learning
Author(s): Souradip Pal Originally published on Towards AI. Unlocking insights into DNA sequences using machine learning and bioinformatics techniques. This member-only story is on us. Upgrade to access all of Medium. DNA is often described as the blueprint of life, encoding the …
Faster Knowledge Distillation Using Uncertainty-Aware Mixup
Author(s): Tata Ganesh Originally published on Towards AI. Photo by Jaredd Craig on Unsplash In this article, we will review the paper titled “Computation-Efficient Knowledge Distillation via Uncertainty-Aware Mixup” [1], which aims to reduce the computational cost associated with distilling the knowledge …
27 Equations Every Data Scientist Needs to Know
Author(s): Julia Originally published on Towards AI. This member-only story is on us. Upgrade to access all of Medium. Everybody’s talking about AI, but how many of those who claim to be “experts” can actually break down the math behind it? It’s …
#48 Interpretability Might Not Be What Society Is Looking for in AI
Author(s): Towards AI Editorial Team Originally published on Towards AI. Good morning, AI enthusiasts! This week, we are diving into some very interesting resources on the AI ‘black box problem’, interpretability, and AI decision-making. Parallely, we also dive into Anthropic’s new framework …
Game Theory Made Simple
Author(s): Igor Novikov Originally published on Towards AI. Looking smart 😂. Image created by AI tool DALL·E 3 — the author has the provenance and copyright Many of you, I bet, heard about game theory at some point in your life. If …
Can CatBoost with Cross-Validation Handle Student Engagement Data with Ease?
Author(s): Talha Nazar Originally published on Towards AI. Understanding student engagement is essential in the digital age of online education, internships, and competitions. But what if we could predict a student’s engagement level before they begin? This story explores CatBoost, a powerful …
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