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Elevate your simulation modeling journey with ChatGPT integration for data analysis. Explore how OpenAI's technology enhances insights, facilitating seamless communication between decision-makers and models.

Companies increasingly use advanced machine learning models, requiring management throughout their lifecycles. ModelOps focuses on scaling and deploying models in production environments, ensuring accuracy and reliability, and optimizing performance. It involves continuous monitoring, evaluation, and redeployment. In this blog post, read more about ModelOps and how PwC has developed a simulation to effectively manage their portfolio of models.

ChatGPT is a dynamic tool that can be used to make simulation modeling simpler and faster. Check out the blog post on this exciting new development, and then watch the video to explore some use cases in more detail. Whether you are a beginner or an advanced modeler, this latest webinar from the AnyLogic team has something for you.

When packing a container, every square inch of empty space is a money loss – either for you or your company. In warehousing and logistics, filling a container with items as tight to each other as possible to reduce the number of containers is a big deal. Decision Lab took it upon themselves to identify what techniques would help make packing quicker and more efficient. Read to learn more about the project and its results.

There are many cases where it’s desirable to incorporate trained machine learning (ML) models into a simulation model. Now, thanks to a new AnyLogic library, using ONNX ML models is easier and more efficient.

By incorporating this add-on library into your AnyLogic environment, your models can access its functionalities, just like with any other built-in library. It’s simply a matter of adding the helper object to your model and configuring it. Read on to find out more.

Automated systems have reached their limits and companies wanting to further enhance business processes are turning to artificial intelligence (AI) technologies like machine learning (ML). In an AnyLogic workshop, Microsoft Autonomous Systems Principal Program Manager Kence Anderson explored the advanced decision-making possibilities of ML and showed how Microsoft’s machine teaching concept is achieving faster training times.

The easily accessible workshop session provides a high-level overview of AI’s state of the art with examples from Microsoft and DeepMind research, as well as illustrative Karate Kid analogies.

Accenture partnered with San Francisco based AI company Pathmind to investigate the potential of new reinforcement learning (RL) opportunities in simulation.

The results obtained were extremely good. The method produced a waiting time more than 4x shorter than the Nearest Agent heuristic.

In this blog post, Agustin Albinati summarizes the model, introduces the three key considerations when defining the neural net, and presents the results of his team's investigations. Linked at the end of the blog post is a step by step how-to with Pathmind. Read on!

As COVID-19 vaccines have become available, many challenges have needed resolving. Not least, ensuring sufficient supply and effective distribution.

At our webinar, March 2021, guest presenter Dr. Ali Asgary of York University, Canada, gave insight into the development and use of a drive-through mass COVID-19 vaccination simulation. He provided details of its machine learning model and online application, including how public authorities are using the results in their vaccination rollouts. Here are the webinar details, recording, and Q&A answers.

The intersection of simulation and artificial intelligence (AI) was the subject of AnyLogic’s AI workshop at the 2020 Winter Simulation Conference. This intersection is benefiting the technologies themselves and providing businesses with new insights and decision support.

Read the summary and watch the workshop recording to learn more about the technology and concepts involved in combining simulation and AI.

In this article, we introduce the broad field of predictive analytics, its connection with machine learning, and how simulation works as a predictive analytics technology.

Why use predictive analytics? Good question. Predictive analytics is about making forecasts based on historical data. Practitioners analyze past events with statistical algorithms and machine learning techniques to produce probabilities and predictions for systems in the future. Almost everyone is subject to and may benefit from predictive analytics. Learn more...