XDA Developers on MSNOpinion

I started self-hosting LLMs and absolutely loved it

Who needs OpenAI when your home lab can do the thinking for you?

Free Unsloth Repo Upgrades a Used Gaming PC Into an AI Rig

Fine-tune language models locally with Unsloth. This open-source repository cuts VRAM requirements by 70%, letting you train ...
PC Magazine

MacBooks Are the Latest Victim of the Memory Shortage. Here's Why Laptop Prices Keep Rising

Memory costs have exploded in 2026, leading Apple and other computing giants to jack up laptop prices. Against that backdrop, here’s how to save on a new PC this year. From the laptops on your desk to ...
CNBC

Rise in memory chip costs puts pressure on retailers of laptops and smartphones

AI demand is contributing to a memory chip shortage. As a result, the prices of some consumer electronics are beginning to rise. Apple announced it's raising its prices on MacBooks and iPads — passing ...
Forbes

AI’s Hidden Cost: The Global Memory Shortage Threat To Affordable Tech

This voice experience is generated by AI. Learn more. This voice experience is generated by AI. Learn more. Computer memory (DRAM) is becoming a critical bottleneck, poised to reshape consumer ...
Crypto Briefing

Tether AI open-sources TurboQuant, reducing LLM KV cache memory use by 5x

Tether AI just released TurboQuant as open-source software, delivering a tool that compresses the memory footprint of large language model inference by up to five times. The technology targets a ...
VentureBeat

MeMo's memory model lets teams upgrade their LLM without retraining it — and performance jumps 26%

Enabling LLMs to acquire new knowledge after training remains a major hurdle for enterprise AI — current solutions are either too expensive, too slow, or constrained by context window limits. MeMo, a ...
The Motley Fool

The Roundhill Memory ETF (DRAM) Packages Micron, Sandisk, Samsung, and SK Hynix in 1 Ticker for Just $60. But There's a Catch.

Hyperscale AI workloads require up to 10 times more DRAM to keep GPU clusters humming without latency bottlenecks. HBM has become a must-have resource, powering everything from large language model ...
SiliconANGLE

Tensormesh taps Nvidia, AMD and CoreWeave for funding to fix AI model memory problems

Tensormesh Inc. has hit upon a way to make artificial intelligence inference more efficient by eliminating the need for redundant computations, and its technology is so convincing that several of AI ...
marktechpost

MEMO: A Modular Framework for Training a Dedicated Memory Model on New Knowledge Without Modifying LLM Parameters

Large language models become static after pretraining. Their knowledge does not update as the world changes. Retraining a full LLM is too expensive at modern scales. Fine-tuning risks degrading ...
Semiconductor Engineering

Four-Tier Memory Hierarchy for LLM Reasoning (USC, UW)

A new technical paper, “Not All Thoughts Need HBM: Semantics-Aware Memory Hierarchy for LLM Reasoning,” was published by researchers at USC and University of Wisconsin-Madison. “Reasoning LLMs produce ...
Microsoft

Human-Inspired Memory Architecture for LLM Agents

Current LLM agents lack principled mechanisms for managing persistent memory across long interaction horizons. We present a biologically-grounded memory architecture comprising six cognitive ...