large
Can large language models figure out the real world?
Back in the 17th century, German astronomer Johannes Kepler figured out the laws of motion that made it possible to accurately predict where our solar system’s planets would appear in the sky as they orbit the sun. But it wasn’t until decades later, when Isaac Newton formulated the universal laws of gravitation, that the underlying…
Australia’s Large Language Model Landscape: Technical Assessment
Key Points No flagship, globally competitive, locally developed LLM (such as GPT-4, Claude 3.5, LLaMA 3.1) has yet emerged from Australia. Australian research and commerce currently rely primarily on international LLMs, which are frequently used but have measurable limitations on Australian English and cultural context. Kangaroo LLM is the only major open-source, locally developed LLM…
Large Language Models LLMs vs. Small Language Models SLMs for Financial Institutions: A 2025 Practical Enterprise AI Guide
No single solution universally wins between Large Language Models (LLMs, ≥30B parameters, often via APIs) and Small Language Models (SLMs, ~1–15B, typically open-weights or proprietary specialist models). For banks, insurers, and asset managers in 2025, your selection should be governed by regulatory risk, data sensitivity, latency and cost requirements, and the complexity of the use…
Analysis of large data acquisitions
Digital acquisition instruments like oscilloscopes and digitizers are incorporating increasingly large acquisition memories. Acquisition memories with lengths in the gigasample (GS) range are commonly available. The advantage of long-acquisition memories is that they can capture longer-time records. They also support higher sampling rates at any given record duration, providing better time resolution. The downside of…
Meet SmallThinker: A Family of Efficient Large Language Models LLMs Natively Trained for Local Deployment
The generative AI landscape is dominated by massive language models, often designed for the vast capacities of cloud data centers. These models, while powerful, make it difficult or impossible for everyday users to deploy advanced AI privately and efficiently on local devices like laptops, smartphones, or embedded systems. Instead of compressing cloud-scale models for the…
Implementing Self-Refine Technique Using Large Language Models LLMs
This tutorial demonstrates how to implement the Self-Refine technique using Large Language Models (LLMs) with Mirascope, a powerful framework for building structured prompt workflows. Self-Refine is a prompt engineering strategy where the model evaluates its own output, generates feedback, and iteratively improves its response based on that feedback. This refinement loop can be repeated multiple…
REST: A Stress-Testing Framework for Evaluating Multi-Problem Reasoning in Large Reasoning Models
Large Reasoning Models (LRMs) have rapidly advanced, exhibiting impressive performance in complex problem-solving tasks across domains like mathematics, coding, and scientific reasoning. However, current evaluation approaches primarily focus on single-question testing, which reveals significant limitations. This article introduces REST (Reasoning Evaluation through Simultaneous Testing) — a novel multi-problem stress-testing framework designed to push LRMs beyond isolated problem-solving…
Thought Anchors: A Machine Learning Framework for Identifying and Measuring Key Reasoning Steps in Large Language Models with Precision
Understanding the Limits of Current Interpretability Tools in LLMs AI models, such as DeepSeek and GPT variants, rely on billions of parameters working together to handle complex reasoning tasks. Despite their capabilities, one major challenge is understanding which parts of their reasoning have the greatest influence on the final output. This is especially crucial for…
Unpacking the bias of large language models
Research has shown that large language models (LLMs) tend to overemphasize information at the beginning and end of a document or conversation, while neglecting the middle. This “position bias” means that, if a lawyer is using an LLM-powered virtual assistant to retrieve a certain phrase in a 30-page affidavit, the LLM is more likely to…
Don't Trash Your Old Tech: You Can Recycle Your Phone and Large Appliances Free
You’ve just gotten a shiny new phone — now what do you do with the old one? It might be tempting to shove your e-waste into a corner or toss it into a junk drawer but eventually it all starts to pile up. Before long, you’ll have to figure out where to dispose of your outdated…