Process bottlenecks and related issues often require complex and dynamic solutions. Discover how FlexSim recommends process improvements from live data, and see how the FlexSim OptQuest optimization engine solves multidimensional problems. OptQuest uses machine learning to evaluate multiparameter input groups in order to strategically determine optimal outcomes across various performance objectives. This method provides faster and more intelligent solutions to intricate problems than manual techniques do. In scenarios with constantly evolving operational inputs, FlexSim can be configured as a live Digital Workplace, continuously operating at set intervals, and using live data streams based on system feedback and artificial intelligence (AI) predictions. This approach necessitates specific model programming, which we will explore. By implementing these advanced techniques, businesses can significantly improve their process optimization capabilities, addressing complex challenges more effectively than traditional methods allow.

SAMSUNG C&T uses digital twins to optimize building operations. We have developed a digital twin with BIM and AI in an office building with a total floor area of 100,000 square meters, and we are utilizing it to operate the building. The basic functions are the Energy/Asset/Space Management, and Virtual Tours. In particular, the energy management function monitors building energy usage in real time. And we have developed 10 solutions for energy management that can save energy while maintaining the comfort of occupants in the building. These solutions are derived through AI-based machine learning models and optimization algorithms to provide real-time notifications to building operators for sustainable and optimized building energy management. Therefore, SAMSUNG C&T aims to provide efficient building operation and management services by simultaneously implementing digital spaces, going beyond the role of a construction company that constructs physical spaces.

This session will explore how language learning models (LLMs) can be integrated with Autodesk Platform Services APIs for optimization of hyperparameters like structural design, reduction of material usage, and embodied carbon. We'll demonstrate this using Autodesk Platform Services to extract building information modeling (BIM) data from Revit models to train LLMs, generating intelligent-design suggestions. The optimized designs are later visualized in Autodesk Platform Services Autodesk Viewer, clearly identifying improvements. Using sample Revit models, we'll showcase how this approach has led to substantial reductions in material consumption and carbon emissions, such as a 25% reduction in steel usage and a 30% decrease in embodied carbon. Discover how using AI and Autodesk Platform Services can create more-sustainable, more-efficient, and more-innovative structural designs, driving the industry toward a greener future.

Explore the forefront of MEP modeling efficiency with AI-driven automation techniques. This session provides a deep dive into the use of Avant Leaps tools within Revit software for sophisticated MEP design and conflict resolution. Attendees will learn how to harness automated pattern-based modeling to standardize and expedite the creation of MEP systems. The workshop will cover strategic applications of AI to detect and resolve clashes early in the design process, significantly enhancing coordination and reducing rework. By integrating these AI-nurtured solutions, participants will achieve more-streamlined project execution and improved team collaboration.

Artificial intelligence (AI) has the potential to significantly affect our industry. How can we use AI to improve our programming skills and make us more efficient? In this session, we'll go over the creation of a program using LISP to copy files from one location to another. Once created, we will use AI to convert a portion of that code into a visual basic script (VBS) so that the user can continue to work while files copy in the background.

The Autodesk Research Residency Program is open to external groups in academia, the startup ecosystem, and industries focused on novel project work. The program provides Autodesk with industry insights and offers resident teams access to a global network of innovators, events, and the Autodesk Technology Centers. Resident teams often work alongside Autodesk researchers and peers, fostering a conducive environment for problem-solving, ideation, and development with rapidly advancing technology like artificial intelligence (AI). As leaders in AI research and a trusted partner to industry, Autodesk Research and the Autodesk Residency Program are natural fits for Design and Make teams developing high-impact industry solutions with AI. This session will provide multiple case studies of the AI work taking place within the Autodesk Research Residency Program. We will feature specific teams using AI, and highlight how their participation in the Residency Program is accelerating their work and use of AI.

For several years, KLH Engineers has led efforts to bridge the gap between AutoCAD and Revit software through machine learning, enhancing our deliverable by building intelligent models from CAD plans. Expanding on our foundational work from 2019, our tool now automatically generates Revit wall elements with precise thickness from AutoCAD drawings, eliminating the problem of thin wall creation and significantly saving time. In this session, we'll demonstrate how machine learning is integral to our process. We have incorporated advanced algorithms that accurately place door and window families within Revit models, using AutoCAD data to inform our workflow and put the "I" back in building information modeling (BIM). Join us to see these advancements in action and learn how they can enhance your design process, making it faster, smarter, and more precise.

Much has been made of the existential threat AI poses to many professions. However, due to the complex nature of architectural projects, we need not fear losing our design agency (or employment) to an AI architect. While there's work over which architects want and need to maintain control, there's also plenty of work that architects would gladly hand over to an AI bot. Using AI allows architects to focus on meaningful design work, rather than tedious minutiae. Also, by passing off more-menial tasks to AI, junior staff can be empowered to get more-meaningful experience. This will be demonstrated through practical examples of how AI is integrated into multiple workflows and processes at ZGF Architects, including project benchmarking, Revit automation/standardization, and semantic search of code documents.

The evolution of design and drafting has increasingly given us tools that inform and expedite our processes. But what can we learn from the implementation of CAD, building information modeling (BIM), and now AI to prepare teams for the future of design tools? Working at a multidisciplinary design firm encompassing planning, landscape, architecture, and interiors has shown me that technology adoption and digital maturity happen at different rates. But regardless of the tools used and efficiency in practice, projects are completed. Focusing on the finished work, lessons learned can become the quantitative outcomes we bring to the beginning of projects in this era of outcome-focused process. By distilling 50+ years of digital asset creation and the analysis of completed projects, we can uncover the potential embedded within our digital archives.

This session will explore the innovative integration of building information modeling (BIM) and artificial intelligence (AI) in advancing sustainable design, focusing on achieving LEED certification through an AI-powered BIM Process. The merging of AI with BIM marks a significant leap in design precision, efficiency, and sustainability, setting new industry benchmarks. This integration transforms the approach to LEED certification, using AI-driven analytics within BIM tools to make sustainable design accessible and effective. Through practical examples and case studies, attendees will gain insights into the practical application of different technologies—such as chatbots and dynamic dashboards—in real-world projects. This session aims to equip professionals with the knowledge and tools to use the synergy between BIM and AI, pushing the boundaries of what's possible in sustainable design.

In this session, we'll explain what machine learning (ML) is, what it's used for, and how it falls into the discipline of artificial intelligence (AI), data science, and computer science. We'll also provide an overview of how ChatGPT works, and what other kinds of ML applications and models you can use to solve problems using data from Autodesk Construction Cloud, building information modeling (BIM), or any of our Autodesk services and APIs. This session will benefit everyone who would like to enable their teams to quickly gain insight from historical data, speed up learning, and create a more agile collaboration environment.

This presentation will dive into a groundbreaking case study of BRK Ambiental, Brazil's second-largest water utility, which implemented advanced automation techniques in the design of water and wastewater treatment facilities. We will explore how the use of generative design software not only streamlined the utility's infrastructure design processes, but also significantly reduced project timelines and costs, while enhancing compliance with stringent environmental regulations. Attendees will learn about the specific challenges BRK Ambiental faced, including the need for rapid design of wastewater infrastructure to meet increasing demand and compliance pressures. The session will highlight how automated design tools facilitated innovative solutions and accelerated project delivery, setting a new standard for efficiency in the water utility sector.

Believing that perfect BIM models are essential for project success is a common misconception. This session debunks that myth, highlighting that the quest for perfect models is not only unrealistic but also uneconomical, especially for standard projects. We will discuss how stakeholder expectations differ, making a universally "perfect" BIM-model virtually impossible. Crucially, I will introduce strategies to manage imperfect BIM models effectively, using tools and technology like AI that help contractors work with imperfections as they do in 2D. Learn how embracing imperfect models can cut costs, save time, and provide a competitive advantage.

Explore the industry trends and macro-economic conditions shaping the future of AEC technology. Learn from product and strategy leaders what Autodesk is doing to support AEC excellence and innovation, while evolving the portfolio of software your design and construction teams trust to get the job done. From desktop to cloud, from product to platform, and from CAD and BIM and into the era of AI: go in-depth in this session to see how Autodesk is transforming design, construction, and project delivery tools to better support the people, teams, and technologies that allow you to transform your businesses, and give shape to our world.

Today, much of the mechanical design has been completed before electrical design has barely started, practically eliminating any possibility of effective mechanical-electrical co-design. We propose an integrated MCAD-ECAD flow, harnessing generative AI to make mechanical electrical co-design a reality—to achieve optimal design and reduce turnaround time, design churn, and cost. We'll show how integration between Autodesk Fusion software and OrCAD X combined with Cadence's generative-AI printed circuit board (PCB) design solution, can transform mechanical-electrical co-design. The flow helps users achieve two seemingly contradictory goals: shift-left for mechanical and electrical engineers and shift-right for layout designers. In hours, mechanical/electrical engineers can get information like fully placed boards and thermal profiles early in design cycle, while PCB designers can start their work when the design is stable. This flow can help users reduce design cost and turnaround time, and create much more optimal designs.

Through this conversation, you'll see the journey of five different architecture, engineering, construction, and operations (AECO) professionals from different countries and backgrounds. They'll talk about their experiences maneuvering through the AEC industry and the unique situations they've faced. Learn how they adapted to the new environments, cultures, and practices while working to provide excellence in their respective fields. This conversation will provide insight into how diversity, equity, and inclusion can positively impact your company, its culture, the way it's perceived in the industry—and its bottom line.

While professional artists use high-fidelity animation techniques—pioneered and refined by Autodesk's animation products MotionBuilder, 3ds Max, and Maya—in games, film, and design production pipelines, we ask the questions: What if the user is not as skilled? What if their requirements for control are not as stringent Could we leverage new input modalities to allow untrained creators to record and edit 3D motion in just a few minutes? We'll discuss the speed and utility afforded by animating in a completely new paradigm: One that allows you to express intent with your body, fingers, face, gaze, and speech while enhancing presence, storytelling, and collaboration in real-time immersive experiences, and engaging your spatial understanding, reasoning, and memory to author 3D animations. Come and hear what our panel of experts from Meta Platforms, Workshop XR, Entertainment and Media Solutions as well as Autodesk Research have to say.

Change is happening at breakneck speed. Getting blindsided by unexpected forces can be disastrous. How do foresight experts prepare their organizations to get ready for the future, seize opportunity, and mitigate risks? In this roundtable, Autodesk's Strategic Foresight team will help participants prepare to confront industry uncertainty. Participants will learn about key industry forces, and will discuss the drivers they're tracking in their sectors (e.g., next steps for machine learning, impacts of our aging populations, and knock-on effects of supply chain disruption). The moderator will share implications linked to each of these forces using a "suitcase of futures” containing fictional props that make possible circumstances feel vivid. Using these compounding forces, participants will learn to reverse-engineer preferred futures into concrete actions. Participants will leave the session with new foresight skills and information about forces that will help improve their future readiness.

To meet global demand for affordable and sustainable housing, the architecture, engineering, and construction (AEC) industry must streamline the design-to-construction process. Modular builders—like Factory_OS—are doing just that by productizing their building systems to generate customizable buildings from a catalog of construction-ready unit types. With Factory_OS, Autodesk Research has developed new design methods that connect their building unit catalog with AI-powered generative design to create multiple design options. This case study demonstrates how new procedural design systems enabled rapid, no-code design exploration while balancing trade-offs between cost, carbon, and habitability. The study also showcases how the prototype made it onto Autodesk Forma using the developer extension model to deliver customized novel design functionality and metrics. Going beyond existing capabilities, Autodesk Research and Autodesk Forma enabled Factory_OS to rapidly and intuitively evaluate new development projects in a data-informed manner.

Learn how high-resolution imagery products like True Ortho imagery, 3D textured mesh, 3D point clouds, and DSM/DTM can set the stage for designing the built environment, provide site-wide content at any scale, and help jumpstart any project. AI and machine learning help identify and extract raster and vector features that give context to the design. These AI features can include building footprints, impervious surfaces, vegetation levels, infrastructure locations, pavement markings, and more. These powerful datasets can be used as the source data for your design or can be further leveraged to create additional content like linear feature extraction, surfaces, contours, and 2D/3D project visualizations.