Nvidia says it can shrink LLM memory 20x without changing model weights

Nvidia researchers have introduced a new technique that dramatically reduces how much memory large language models need to track conversation history — by as much as 20x — without modifying the mo [...]

DeepSeek drops open-source model that compresses text 10x through images, defying conventions

DeepSeek, the Chinese artificial intelligence research company that has repeatedly challenged assumptions about AI development costs, has released a new model that fundamentally reimagines how large l [...]

New KV cache compaction technique cuts LLM memory 50x without accuracy loss

Enterprise AI applications that handle large documents or long-horizon tasks face a severe memory bottleneck. As the context grows longer, so does the KV cache, the area where the model’s working me [...]

Google's new TurboQuant algorithm speeds up AI memory 8x, cutting costs by 50% or more

As Large Language Models (LLMs) expand their context windows to process massive documents and intricate conversations, they encounter a brutal hardware reality known as the "Key-Value (KV) cache [...]

'Observational memory' cuts AI agent costs 10x and outscores RAG on long-context benchmarks

RAG isn't always fast enough or intelligent enough for modern agentic AI workflows. As teams move from short-lived chatbots to long-running, tool-heavy agents embedded in production systems, thos [...]

We keep talking about AI agents, but do we ever know what they are?

Imagine you do two things on a Monday morning.First, you ask a chatbot to summarize your new emails. Next, you ask an AI tool to figure out why your top competitor grew so fast last quarter. The AI si [...]

Google’s new compression algorithm cut memory stocks within hours of publication

Google published a research blog post on Tuesday about a new compression algorithm for AI models. Within hours, memory stocks were falling. Micron dropped 3 per cent, Western Digital lost 4.7 per cent [...]

New ‘Test-Time Training’ method lets AI keep learning without exploding inference costs

A new study from researchers at Stanford University and Nvidia proposes a way for AI models to keep learning after deployment — without increasing inference costs. For enterprise agents that have to [...]

Self-Authenticating Images Through Simple JPEG Compression

Concerns about the risks posed by tampered images have been showing up regularly in the research over the past couple of years, particularly in light of a new surge of AI-based image-editing framework [...]