8 billion tokens a day forced AT&T to rethink AI orchestration — and cut costs by 90%

AT&T's chief data officer shares how rearchitecting around small language models and multi-agent stacks cut AI costs by 90% at 8 billion tokens a day.

When Hackers Leverage AI: Defending What You Don’t Know Is Exposed

These days, defending what you don’t know is exposed could define the difference between resilience and regret.
InfoWorld

Three web security blind spots in mobile DevSecOps pipelines

Mobile platforms operate under fundamentally different trust assumptions than we relied on for web security. Your mobile ...
Communications of the ACM

Managing and Securing Google’s Fleet of Multi-Node Servers

Server hardware and software co-design for a secure, efficient cloud.
Security Info Watch

From Detection to Disruption: The Rise of Unified Intelligence in Financial Crime

Today’s attackers move from account takeover to mule networks in hours, exploiting the gaps between fraud and AML functions.
AZoLifeSciences on MSN

Proteomics approaches to overcome undruggable targets in disease

This proteomics-driven approach to drug discovery improves target validation and uncovers insights into undruggable proteins, advancing precision medicine.
XDA Developers on MSN

I found an open-source Canva alternative, and it handles everything I actually need

For creators who want more control ...
eLife

Cytoplasmatic polyadenylation of mRNA by TENT5A is critical for enamel mineralization

This study reports an important and novel finding that TENT5A, an enzyme involved in fine-tuning poly(A) tail length on selected mRNAs, is required for proper enamel mineralization in mice. The ...
IEEE

State-Attracted Functions-Based Trajectory Planning and Tracking Control for Uncertain Robotic Systems Based on a Human-Inspired Vector Field

Abstract: This article proposes a state-attracted function-based trajectory planning and tracking control (SAF-TPATC) method for robotic systems that achieves simultaneous trajectory planning, ...
Open Heart

Enhanced cardiovascular disease risk prediction using integrated machine learning models: a study from the UK Biobank cohort

Objective Cardiovascular diseases (CVD) remain the leading cause of mortality globally, necessitating early risk identification to improve prevention and management strategies. Traditional risk ...