New agentic memory framework uses 118K tokens per query. LangMem burns through 3.26M.

NUS researchers' MRAgent framework reduces LLM agent memory retrieval to 118K tokens per query — vs. 3.26M for LangMem — using step-by-step reasoning.

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.
Digi Times

DeepSeek cuts API prices 90%, sets new global low for LLM services

DeepSeek's 90% cut to fees for input cache hit, which occurs when the model reuses previously computed results for identical or similar inputs instead of recomputing them, across its API lineup could ...
ZDNet

How indirect prompt injection attacks on AI work - and 6 ways to shut them down

Malicious web prompts can weaponize AI without your input. Indirect prompt injection is now a top LLM security risk. Don't treat AI chatbots as fully secure or all-knowing. Artificial intelligence (AI ...
PC Magazine

The Best Speech-to-Text Apps and Tools for 2026

With speech-to-text software, you don't need to use your fingers to create digital text. The top dictation software is fast, accessible, and helpful for anyone who struggles with typing. Justin has ...
BBC

Relational databases and structured query language (SQL) - AQA

Databases are used in many different settings, for different purposes. For example, libraries use databases to keep track of which books are available and which are out on loan. Schools may use ...