News & Updates

Fighting Back Against Attacks in Federated Learning

Testing EE-Trimmed Mean defenses against malicious node poisoning inside our simulator tray.

Edge AI: A Comprehensive Guide to Real-Time AI

A complete primer on running AI on local edge devices for low-latency, private, real-time inference.

Federated Learning: Train AI Without Moving Data

An introduction to the decentralised approach that trains models across distributed data without centralising it.

Scalable Federated Learning with FEDn

A comprehensive overview of FEDn's three-tier architecture for production-grade, geographically distributed FL.

From Satellites to Fleets: Research Initiatives

Overview of four live research tracks across orbital telemetry and autonomous vehicular networks.

Federated Learning with 10,000 Asynchronous Clients

Benchmarking core engine scalability across intermittently connected network infrastructures.

Data Selection on the Edge for Adaptive ML

Filtering optimal training frames on device without dispatching raw intelligence feeds.

Collaborative AI for Lung Cancer Detection

Cross-hospital algorithmic training case study meeting clinical privacy regulations.

Fleet Intelligence with Mixture-of-Experts FL

Architecting resource-efficient routing architectures for deep connected network systems.

Vertical Federated Learning with FEDn

Cooperative modeling mechanics across complementary feature parameters with zero data sharing.

Exploring Python vs. C++ Runtime Performance

A framework optimization deep dive checking computational and memory latency variables.

Scaleout Secures 35 MSEK Investment Round

Accelerating secure edge development with expanded support from Fairpoint Capital.

Distributed Continuous Machine Learning

Analyzing systemic architectural transitions as global parameters process natively on devices.

Machine Learning in the Cloud-Edge Continuum

Balancing remote aggregation steps against central analytics to scale storage constraints.

Scaleout Joins NATO's DIANA Programme

Deploying the FEDAIR node system framework to support contested electronic warfare positions.

Federated Learning Made Easy with FEDn

Implementing unified compute bundle processes directly over standard PyTorch graph networks.

Guaranteeing Data Privacy for Clients in FML

Injecting adaptive Gaussian noise matrices to guarantee node protections on tracking devices.

Federated Learning for Object Detection Using YOLO

Running decentralised computer vision training weights over remote field cameras.

Hyperparameter Tuning with Optuna and FEDn API

Automating server-side optimizer updates inside distributed production environments.

Enhancing Semiconductor Pick-and-Place via FML

Collaborative training with Mycronic hardware assets using proprietary customer datasets.

Federated Multi-task Learning Structures

Isolating localized validation sequences across non-identical, heterogeneous end-devices.

Enhancing Data Security with Intel SGX and AMD SEV

Comparing hardware enclave performance criteria during distributed parameter aggregation blocks.

Email Spam Detection with FEDn and Hugging Face

Fine-tuning deep BERT-tiny language configurations across edge nodes with total data privacy.

Federated Self-Supervised Learning in Autonomy

Training vehicle fleet models on unlabelled sensor data directly within localized loops.

Leveraging JWT Authentication in FEDn Studio

Securing core administrative API access pathways against untrusted perimeter interactions.

Project Management via ArgoCD in FEDn Studio

Deploying structured Helm charts to automate federated systems directly over Kubernetes.

The Impact of Backdoor Attacks on MNIST Graphs

Tracking vector manipulation traits when isolated nodes introduce poison samples to the pool.

Federated Learning: Self-Managed On-Premise or SaaS?

A full compliance trade-off audit between bare-metal deployments and hosted clouds.

Scaleout and Flower Partner on FL Solutions

Strategic integration connecting frontend Flower nodes with backend FEDn tracking engines.