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13 articles
This article explains the neurobiological mechanisms behind AI addiction, exploring how large language models trigger dopamine responses and create compulsive usage patterns similar to substance addiction.
Ollama has raised $65M in Series B funding, bringing its total to $88M, as its open-model runner reaches nearly 9 million developers worldwide.
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.
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 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 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.
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.
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.
Large Language Models excel at coding and math but often fail on casual questions, revealing a fundamental limitation in current AI systems.
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.
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.
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.
