#LLMs

Ollama raises $65M as its open-model runner hits nearly 9M developers

Ollama has raised $65M in Series B funding, bringing its total to $88M, as its open-model runner reaches nearly 9 million developers worldwide.

The KV Cache Compression Race: TurboQuant vs OSCAR vs EpiCache

As KV cache memory outpaces model weights in large language models, three compression techniques—TurboQuant, OSCAR, and EpiCache—are emerging as key contenders. While each offers distinct methods for optimization, they are seen as complementary rather than competitive.

George Hotz says coding agents will be "one of the most costly mistakes" in software development

Programmer George Hotz warns that AI coding agents will become one of the industry's most costly mistakes, citing their inability to handle code details reliably. His critique highlights the growing divide in the tech community over AI's role in software development.

The Rise of LLMs Is Not an Accident

The rise of large language models is fundamentally altering consumer behavior and trust, signaling a major shift in marketing strategy. Industry veterans are observing how AI is reshaping decision-making logic and brand interaction.

Graphon AI exits stealth with $8.3M to build the data layer that LLMs are missing

Graphon AI has exited stealth with $8.3 million in seed funding, aiming to build a missing data layer for LLMs using a mathematical concept called graphons.

Build a Modular Skill-Based Agent System for LLMs with Dynamic Tool Routing in Python

A new tutorial demonstrates how to build a modular skill-based agent system for LLMs using dynamic tool routing in Python, enabling scalable and flexible AI agent architectures.

The LoRA Assumption That Breaks in Production

LoRA, a widely used technique for fine-tuning large language models, assumes all updates are similar — a premise that fails in real-world production environments. This limitation is now prompting a reevaluation of its effectiveness in complex, diverse applications.

LLMs crush coding and math but choke on casual questions, and that's not a contradiction

Large Language Models excel at coding and math but often fail on casual questions, revealing a fundamental limitation in current AI systems.

Paged Attention in Large Language Models LLMs

Paged Attention emerges as a key solution to the GPU memory bottleneck in large language models, enabling more efficient memory usage and higher concurrency in AI inference systems.

This AI Paper Introduces TinyLoRA, A 13-Parameter Fine-Tuning Method That Reaches 91.8 Percent GSM8K on Qwen2.5-7B

Researchers from Meta, Cornell, and CMU introduce TinyLoRA, a 13-parameter fine-tuning method that achieves 91.8% accuracy on GSM8K using Qwen2.5-7B.

Investors bet $1 billion on Yann LeCun's vision for AI beyond LLMs

Yann LeCun has raised $1 billion for his new startup AMI Labs, marking Europe's largest seed funding round ever. Investors are betting on his vision for AI beyond LLMs.

Talk like a graph: Encoding graphs for large language models