Machine Learning

5 articles

Editorial illustration for A Strategic Guide to AI in Protein Engineering
Product & Engineering

A Strategic Guide to AI in Protein Engineering

Artificial intelligence is transforming protein engineering by enabling faster, more precise design of novel proteins for therapeutics, vaccines, and industrial enzymes, overcoming traditional scale limitations and facilitating de novo design.

Marek Kowalski·October 5, 2026
Explore Battery R&D Data With Wensura AutoML and Time-Series Forecasting
Tech & Innovation

Explore Battery R&D Data With Wensura AutoML and Time-Series Forecasting

Wensura offers a battery-focused research workspace where users can explore R&D data, apply automated machine learning, and investigate time-series changes. It provides tools for exploratory data analysis, correlation matrices, and principal component analysis to understand dataset structure and variable relationships.

Sponsored by Wensura·August 5, 2026
Robotic arms in a futuristic factory assembling machinery, with data visualizations and AI algorithms displayed on background screens.
Product & Engineering

What Is AI Integration in Industrial Machinery and Why Does It Matter?

The U.S. industrial automation market is projected to grow at a staggering 9.8% Compound Annual Growth Rate (CAGR) from 2025 to 2032, according to PS Market Research . This expansion forecasts the mar

Marek Kowalski·July 20, 2026
Futuristic server room with glowing data streams and holographic AI agent network, illustrating the complexities of loop engineering.
Product & Engineering

What is Loop Engineering and Why Does it Matter for AI?

Individual laptop-based AI agent loops can fail with the laptop, manage credentials insecurely, and lead to unmanageable automation sprawl in enterprise environments.

Marek Kowalski·July 7, 2026
Futuristic cityscape with holographic data streams and a glowing AI orb, representing small AI models driving business innovation and efficiency.
Tech & Innovation

Small AI Models Drive Business Efficiency and Innovation in 2026

Qwen3.5-0.8B, an 0.8 billion parameter model, supports native context lengths of up to 262,000 tokens, a capability that defies traditional expectations for small language models and boosts business e

Sofia Reyes·July 6, 2026