#large-language-models

#large-language-models

The environmental audit by Mistral reveals that the majority of CO2 emissions and water consumption arise during model training and inference, not from construction or end-user equipment.

"RNGD provides a compelling combination of benefits: excellent real-world performance, a dramatic reduction in our total cost of ownership, and a surprisingly straightforward integration."

Despite impressive capabilities, large language models have yet to produce a genuine breakthrough. They lack fundamental aspects of human thought, remaining static and unable to learn from experience.

We show that LLMs - Gemma 3, GPT4o and o1-preview - exhibit a pronounced choice-supportive bias that reinforces and boosts their estimate of confidence in their answer, resulting in a marked resistance to change their mind.

Retrieval Augmented Generation (RAG) combines the power of Large Language Models (LLMs) with a custom knowledge base, enabling precise and contextually relevant responses from customers.

The Model Context Protocol (MCP) is an open standard that enables large language models to interact with external tools and data through a standardized interface.

The research shows that large language models consistently advise women to ask for lower salaries than men, despite identical qualifications. For instance, a difference in advice led to a gap of $120K a year between genders in some fields.

The study found that when large language models are prompted to respond as humans would, they rate the emotions depicted in images similarly to human volunteers.

"Nvidia's multi-million-token context window is an impressive engineering milestone, but for most companies, it's a solution in search of a problem," said Wyatt Mayham, CEO and cofounder at Northwest AI Consulting. "Yes, it tackles a real limitation in existing models like long-context reasoning and quadratic scaling, but there's a gap between what's technically possible and what's actually useful."

Rising demand among marketers for AI search expertise drives agencies to create specialist units to assist clients in understanding technology's impact on consumer habits.

Fine-tuning large language models requires huge GPU memory, leading to challenges in acquiring larger models, but QDyLoRA addresses this by enabling dynamic low-rank adaptation.

Without understanding AI tools’ inner workings, you risk frustration and subpar results. Mastering foundational principles transforms your collaboration with this technology.

Kagi's approach aims to redefine the search experience both for personal and professional contexts by prioritizing user needs and the ethical implications of search algorithms.

Are large language models (LLMs) our new operating systems? If so, they are changing the definition of what we consider to be software.

Prefill performance is assessed using FlashAttention and FlashInfer kernels, focusing on optimizing attention kernels for improved throughput and reduced latency in serving systems.

This study highlights the critical issue of bias amplification in large language models (LLMs), demonstrating its impact predominantly through the lens of political bias in U.S. media.

The findings revealed a significant positive correlation between the M-IoU scores and the ratings from both individual coders, highlighting the reliability of our M-IoU metric in evaluating praise.

As my method of work is all about intertwining physical with digital, I decided to literally build physical models that convey synthetic thoughts modeling my current state of mind.

Integrating AI requires careful budgeting as costs vary widely depending on model type, usage patterns, and the necessary infrastructure.