Deep Netts on foojay.io - Friends of OpenJDK

How to Create a Spring Boot Fraud Scoring Service

Fri, 31 Jul 2026 08:45:43 +0000

Most Java teams who want a machine learning model in production end up standing up a Python service and calling it over HTTP. That works, but it buys you, as a Java developer, a second runtime, a second deployment pipeline, a network hop on every prediction, and a team boundary that turns retraining into someone else’s ticket.

Deep Netts removes that split: it’s a pure-Java deep learning library, so the model trains in Java, serializes to a file, and loads back into your Spring Boot application as an ordinary bean. Predictions become in-process method calls measured in microseconds, with nothing extra to deploy, secure, or monitor.

How Deep Netts and Java AI Transformed Particle Physics

Mon, 19 May 2025 10:58:34 +0000

At the intersection of nuclear physics and artificial intelligence, Jefferson Lab is leveraging Java-based AI to overcome one of the most computationally intense challenges in modern science: reconstructing particle trajectories from high-frequency electron scattering experiments.

Each second, over 16,000 interactions are recorded as particles pass through a complex array of drift chambers. Traditional reconstruction methods—based on mathematical likelihood calculations—must sift through thousands of signal combinations to identify valid particle tracks. The result? Up to 300 milliseconds of processing per event on a single core, leading to massive compute demands.

Foojay Podcast #29: How will AI and ML Influence the Role of Developers?

Mon, 25 Sep 2023 07:24:33 +0000

Artificial Intelligence and ChatGPT are the talk of the town.

Every conference has several talks about these technologies, and on Foojay, you can find multiple posts about it.

In this podcast, we want to take a look at it from the Java point of view.

How can we use AI in Java programs or our job as a developer?

Podcast Apps

You can listen and subscribe to the Foojay Podcast on:

Foojay Podcast #12: State and Future of the IDEs

Mon, 23 Jan 2023 10:14:45 +0000

In this podcast, we are talking to some of the key people working on different IDEs, Integrated Development Environments.

Those are applications that provide tools to computer programmers for software development.

An IDE typically consists of at least a source code editor, build automation tools, and a debugger.

Let’s learn how these tools evolved, and the challenges they face to stay up-to-date with the many evolutions in Java and all other programming languages.

Deep Learning in Java Using Deep Netts (Part 2)

Wed, 03 Aug 2022 09:48:18 +0000

Deep Netts is a deep learning development toolkit that enables Java developers to easily add modern AI to their apps. It provides a deep learning IDE and a Java-native deep learning library for embedding AI models into Java apps.

In part 1 , we looked at the Deep Netts Community Edition, which is capable of solving basic machine learning problems, and provides a standard set of features.

If you have more complex challenges, more data, and need better performance or just want friendly tools to quickly try and learn AI, you should take a look at Deep Netts Professional Edition.

Getting Started with Deep Learning in Java using Deep Netts

Tue, 05 Jul 2022 07:22:18 +0000

Deep Netts is pure Java deep learning library with a friendly, Java centric API.

It makes it easy for Java developers to quickly start using deep learning and it is easy to integrate with existing Java applications.

It supports commonly used neural network architectures (feed forward networks, convolutional networks) for classification, regression and image recogniton tasks.

Adding Deep Netts to your Project

To be able to use Deep Netts in Maven based Java project, add the following dependency into dependencies section of your pom.xml file:

Deep Learning in Java for Nuclear Physics using Deep Netts

Thu, 16 Jun 2022 09:01:44 +0000

Background

The CLAS12 detector at Jefferson Lab conducts nuclear physics experiments to study the structure of nucleons and new particle states.

At the core of detector setup are drift chambers that measure charged particles resulting from the interaction of an electron beam with a liquid hydrogen target.

The charged particles are reconstructed by combining segments of the track measured in 6 separate drift chambers along the particle trajectory.

In high-intensity experiments, detector systems produce noise segments increasing the combinatorics of track candidates to be analyzed by the conventional algorithm, which leads to decreased track reconstruction efficiency.

Visual Recognition for Chess with Deep Learning in Java on Android

Thu, 11 Nov 2021 20:07:51 +0000

Find out how can you use AI in Java to build applications that can see and understand the world. This article describes an Android chessboard position scanner built with pure Java deep learning engine Deep Netts .

Over the last few decades, the technological advancement in the Artificial Intelligence (AI) field has greatly assisted many chess grand masters’ preparation as well as understanding chess theory. There are programs called chess engines, like Bagatur, Stockfish, and Komodo, which play extremely strong chess. These engines make deep and beautiful moves, but sometimes these moves are difficult to understand even by chess experts. Clearly, AI/ML has allowed chess engines to become quite advanced, but they are only one aspect of the story. There are more applications of AI/ML in playing the game of chess.

Deep Learning in Java for Drug Discovery

Fri, 20 Aug 2021 09:28:10 +0000

In the age of big-data, rising pharmaceutical costs, and an ever-increasing market demand, it is becoming apparent that drug design strategies need to adapt in order to meet patients’ therapeutic needs for a host of medical conditions.

Costly and time-intensive experimental work is one of the main bottlenecks in the drug discovery pipeline, which can take up to a decade, while experiencing a failure profile of up to 95% before a molecular candidate can be approved for patient use.

Open Source Tools as an Opportunity for SMEs to Use AI?

Wed, 02 Jun 2021 14:36:04 +0000

Time-traveling cyborgs and robots that are able to love. These interesting and romantic ideas emerged from the imagination of Hollywood film directors. Nevertheless, many people are afraid of Artificial Intelligence (AI). This also can be seen in the economic world. Small and medium-sized enterprises (SMEs) in particular see AI as a threat to their own business. Surprisingly however, all different-sized companies are able to see the potential of AI when it comes to penetrating the national and global market. ^[1]^

Quick Start with Machine Learning for Java

Wed, 07 Oct 2020 01:21:00 +0000

So you’re a Java developer and you want to do some machine learning. Some of the questions that you might be wondering about are—what can machine learning do for me anyway, which library to use, which algorithms, and is there a common standard API?

Since recently there is a standard API that was created to address exactly these questions. Meet JSR 381 , a standard Java API for Visual Recognition using machine learning.