DeepSeek open sources DSpark, a new framework to speed up LLM inference by up to 85%

DSpark can make decoding faster, but acceptance quality still determines how much speed the system actually realizes.
Computerworld

Z.ai pitches GLM-5.2 for long-running software engineering tasks

The open-source model combines a one-million-token context window with architectural updates aimed at lowering the cost of repository-scale AI coding. Z.ai has released GLM-5.2, an MIT-licensed ...
InfoWorld

Z.ai pitches GLM-5.2 for long-running software engineering tasks

The open-source model combines a one million-token context window with architectural updates aimed at lowering the cost of repository-scale AI coding. Z.ai has released GLM-5.2, an MIT-licensed ...

Z.ai’s open-weights GLM-5.2 beats GPT-5.5 on multiple long-horizon coding benchmarks for 1/6th the cost

It allows engineering teams to host frontier-level AI on their own sovereign infrastructure, entirely eliminating vendor lock ...
Tech Times

NVIDIA Diffusion LLM Hits 2.42x Throughput Without Retraining: Nemotron TwoTower Released

NVIDIA diffusion language model Nemotron TwoTower achieves 2.42x LLM inference throughput without a full retraining run, ...
MUO on MSN

Your GPU is probably making VLC stutter during 4K playback — here's the fix

My 4K videos stuttered in VLC until I turned off one setting.

What is GLM-5.2: China’s AI model challenging Anthropic’s Claude Fable 5 in coding and long-context reasoning

In recent days, a new large language model from China has started circulating through technical circles with an unusual mix ...
Tech Times

Compile Once, Run Offline: New AI Method Matches 32B Models With a 23MB File

Local AI inference at 32B-parameter quality, no cloud API required: University of Waterloo researchers released PAW on July 2 ...
CSOonline

As AI speeds coding, CVE Lite CLI keeps security deliberately AI-free

The OWASP-backed tool scans JavaScript and TypeScript lockfiles locally, aiming to help developers catch and remediate dependency risks before CI failures. As AI coding assistants accelerate software ...

Waterloo's PAW compiles task specs into 23MB LoRA adapters a 600M-parameter model runs entirely offline.

Local AI inference at 32B-parameter quality, no cloud API required: University of Waterloo researchers released PAW on July 2, 2026, a system that compiles any natural-language task spec into a 23MB ...