Attributional inference, the ability to predict latent intentions behind observed actions, is a critical yet underexplored capability for large language models ...
Large Language Models (LLMs) struggle to reason over large-scale enterprise spreadsheets containing thousands of numeric rows, multiple linked sheets, and embed...
With last month’s web redesign, the Gemini app gained a “My Stuff” folder, and Google is now updating it with a dedicated “Documents” list of your Deep Research...
Automating Infrastructure-as-Code (IaC) is challenging, and large language models (LLMs) often produce incorrect configurations from natural language (NL). We p...
Artificial Intelligence (AI) systems have shown good success at classifying. However, the lack of explainability is a true and significant challenge, especially...
Google says that generated videos should also now be more consistent with thereference images they’re based on. | Image: Google / The Verge Google is making its...
Reinforcement Learning (RL) remains a central optimisation framework in machine learning. Although RL agents can converge to optimal solutions, the definition o...
While quantum annealing (QA) has been developed for combinatorial optimization, practical QA devices operate at finite temperature and under noise, and their ou...
Dataflows were rightly? considered 'the slowest and least performant option' for ingesting data into Power BI/Microsoft Fabric. However, things are changing rap...
Neural Combinatorial Optimization (NCO) has mostly focused on learning policies, typically neural networks, that operate on a single candidate solution at a tim...
When an enterprise LLM retrieves a product name, technical specification, or standard contract clause, it's using expensive GPU computation designed for complex...
By rolling out ChatGPT Enterprise company-wide, Zenken has boosted sales performance, cut preparation time, and increased proposal success rates. AI-supported w...
