What’s your experience working with model serving and model inference? Do you know what are the potential ways to improve for it?
When moving model from training to production. There are things to be concerned, for instances, SLA, model management, compute, data, cost and security. This session Mia is going to share how to optimize the model inference from software, hardware and network perspectives. Tips about model inference optimization.
In many cases, a data scientists just needs a Jupyter notebook on a powerful virtual machine to be productive. However, there are some cases where more powerful cloud services can be helpful. We will give overview of Azure Machine Learning, a platform ML service on Microsoft Azure cloud, and consider some best practices of using it for repeated experimentation, hyperparameter optimization and running parallel sweep jobs. We will focus our specific examples around CORD-19 dataset of scientific papers on COVID-19.
At Accenture Industry X, we understand the importance of including machine learning techniques in the services offered to our clients in order to improve efficiency,help with quality control and predictive maintenance. We aim to show how an alarm status for a motor can be predicted with 10 days in advance , by using as input historical daily sensor readings and data derived from such readings.
By doing so, we can optimize maintenance actions and prevent downtimes.
Most papers and conference talks focus on model architecture and how it improves on the state-of-the-art.
Not this one. In this talk, we focus on system design. How do we design systems for low-latency, high-throughput serving for recommendations and search? In this talk, I’ll share a 2×2 framework of online vs. offline and retrieval vs. ranking. We’ll also go through examples of how companies like Alibaba, Facebook, and DoorDash serve their recommendation and search.
The session focuses on the generative aspects of Natural Language Processing. Barbara will introduce how AI new advancements are being used for text generation. This will be followed by the review of existing systems and available tools that could be used for creating their own solutions.
The audience will get three key takeaways:
– NLP techniques for text generation.
– Tools that can be used to generate text.
– How text generation is and can be used in the real world applications.
Machine translation has come a long way over the past 70+ years.
Today’s state-of-the-art Neural Machine Translation (NMT) has created a paradigm shift. This radically different approach to the challenge of language translation uses deep neural networks and artificial intelligence to train models for different language combinations and content types.
In this talk we’ll cover challenges and solutions on building and improving upon these advances and turning them into powerful real-world products.
Using machine learning techniques such as neural networks and evolutionary computation, it is possible to build models to predict not only how the pandemic spreads, but also how it could be mitigated. I will review Cognizant’s Evolutionary Surrogate-Assisted Prescription (ESP) technology, its application to this task, the XPRIZE competition that Cognizant sponsored based on it, and lessons learned from the competition, as well as opportunities for using this technology on other decision-making tasks in healthcare, design, and business. – AI support for decision making requires not only predictive models, but prescriptive models as well – ESP is a powerful new technology for discovering prescriptive models – Evolutionary AI can be used to bring together insights from a community of human experts – AI can play a significant role in coping with COVID-19 and future similar challenges
Meet Mambu: the only true SaaS banking platform leading the change in the world of banking. Some call us “experts at collaborating globally”, others know us as a close-knit team capable of solving big problems. One thing is for sure, what brings us together is drive, confidence and a collaborative spirit. We are a dedicated team of +500 professionals spanning 6 continents, building the core part of a major shift in the future and evolution of banking. Our leading cloud native solution is the driving force behind our customers as they grow, scale and transform to meet evolving digital demands. Our mission? Make modern financial services accessible to everyone.
Cognizant Romania is one of Eastern Europe’s largest Software Product Engineering delivery networks. We serve global clients in several industries, including Banking & Financial Services, Insurance, Healthcare & Life Sciences, Communication Media & Technology, and Retail & MLEU (manufacturing, logistics, energy & utilities).
Our product thinking mindset defines, builds, and launches new, experience-centered software products that reinvent business.
To learn more about Cognizant Romania and explore career opportunities visit our website (https://www.cognizant.com/ro/en)!
Bosch Service Solutions is a leading provider for Business Process Outsourcing. We are solution designers offering complex technical and software services to the Bosch Group and to external customers in the areas of automotive/ mobility, sensor technology and Internet of Things. We design and provide best-in-class services, such as: software-based solutions, AI and automation, project management, customer experience. Join a team with more than 17 years of experience providing exceptional services as our newest AI Consultant, DevOps engineer, software developer or business process modeler.
Work #LikeABosch
Microsoft enables digital transformation for the era of an intelligent cloud and an intelligent edge. Its mission is to empower every person and every organization on the planet to achieve more.
Take global content and ideas further. Create meaningful connections with customers through global content and idea management.
Accenture Industry X is helping clients reimagine the products they make, and how they make them. Working across multiple industries, we offer the broadest suite of services for digitizing engineering and R&D functions, factory floors and plant operations. Using data and technologies such as AR/VR/XR, cloud, AI, 5G, robotics and digital twins, you’ll work with our clients to design, engineer and manufacture products and services in ways that are more connected, more efficient and more sustainable.
Architects often describe their work in diagrams and other visual artifacts, but how can they test to see if the implementation is aligned with the architecture? Architects are expected to not only design new systems, but continuously govern what they’ve already built and ensure that their architecture is aligned with the technical and business environment. This session uncovers a new way to think about architecture—as code. Architecture as Code is a new concept that allows you to describe an architecture through executable source code, therefore allowing you to govern the architecture as well. In this session we discuss numerous intersections of software architecture with all the tendrils of the organization, including implementation, infrastructure, engineering practices, team topologies, data topologies, systems integration, the enterprise, the business environment, and generative AI, defining each intersection using architecture-as-code to verify that the architecture is properly aligned.
A common saying by software architects is “that’s an implementation detail”. All too often we treat software architecture and implementation as two separate things, where implementation is something that happens once a software architecture is defined. In fact, it’s the other way around: software architecture should be viewed as a first draft, where implementation reveals more details and refinements. In this session Mark Richards discusses the intersection of architecture and implementation and how the two must be in constant alignment to achieve success, demonstrating along the way why architecture is a critical element of any system. Through real-world examples, he shows how implementation can easily get out of alignment with the architecture, causing the system to fail to achieve its desired goals. He then shows some techniques and tools to help ensure the alignment between architecture and implementation.
Production agentic AI needs more than agents.
It needs structure. It needs boring stuff: observability, modularity, data profiling, and monitoring.
Otherwise, it becomes chaos with a personality, fancy demos that fail silently in production.
In this talk, we’ll show you how old-school software and MLOps principles are the secret weapon for building real, scalable, and reliable agentic systems.
No hype. No buzzword bingo.
Just field-tested thinking and hard-learned lessons from production AI deployments.
What you’ll take home:
* A framework to cut through the noise and think clearly about agentic architecture
* How to debug, observe, and monitor agents like real software systems
* How to avoid the trap of shiny tools and focus on system design that actually works
* A checklist for building agentic AI that doesn’t crash after your first user touches it
In today’s fast-paced, global market, companies must be agile, responsive, and interconnected. A connected Product Lifecycle Management (PLM) environment is no longer a luxury but a necessity. This transformation is powered by advanced technologies such as cloud computing, the Internet of Things (IoT), Artificial Intelligence/Machine Learning (AI/ML), digital twins, and digital threads.
These technologies offer unprecedented opportunities to enhance efficiency, collaboration, and innovation across the entire product lifecycle. However, they also present significant challenges, particularly in terms of system integration and data management. Properly managed, these tools can revolutionize your operations, breaking down data silos and streamlining processes from product conception to retirement.
By integrating these digital tools, experts can transform their PLM systems into robust, dynamic platforms that not only meet but exceed the demands of the digital age.
Join us in exploring how these technologies can revolutionize your PLM strategy and drive a company’s success.
When teams adopt Microservices with an understanding of the structure of the architecture, but not of how to get all the pieces to communicate, it is all too easy to accidentally create a distributed Big Ball of Mud. Neal introduces a new measure, the architecture quantum, to help analyze and identify communication boundaries and define static and dynamic coupling. Then, the session provides tools – integrators and disintegrators – to help architects iterate towards the correct granularity for their Microservices for static coupling. Next, for dynamic coupling, architects must understand when to choose synchronous versus asynchronous communication between services, consistency, and coordination to ultimately analyze transactional sagas; this talk describes eight possible sagas and when each is applicable.
Leadership Coach and author Andrei Postolache talks about the attitudes, behaviours and skills that high performance Individual Contributors and Leaders need to succeed in today’s world. Based on his work with hundreds of teams and individuals, he narrows down the essential organizational, communicational and inter-relational skills that truly make the difference.
During this session, you’ll discover how GenAI is transforming Quality Engineering efficiently and cost-effectively. From summarizing specifications to designing manual test cases, GenAI streamlines early QA activities. It also revolutionizes automation code and test framework architecture.
Join us to see how GenAI makes Quality Engineering faster and easier!
Coding has always been more than just writing lines of code; it’s about solving puzzles, creating solutions, and adapting to challenges. But what happens when AI begins to tackle those puzzles as well? How will your role evolve in this new landscape?
As AI integrates deeper into our toolsets and workflows, the real revolution isn’t about simply learning new technologies. It’s about fundamentally changing the way we think, how we architect solutions, and our entire approach to software development. This talk cuts through the AI hype and zeroes in on your growth as a developer.
Discover practical strategies to leverage AI beyond mere automation, unlock untapped creativity, strategic thinking, and problem-solving. It’s time to not just write code, but to reforge it, leveraging AI as a powerful ally in your journey towards mastery.
As our industry has evolved through various paradigm shifts, certain fundamental patterns continually emerge despite changing technologies and methodologies. In this keynote, Michael Feathers examines why we repeatedly rediscover similar solutions across decades and propose that there may be one deeper universal principle governing effective software design. Though this singular principle might appear to be an over-generalization, it provides surprisingly good guidance across contexts. Drawing connections between biological scaling laws, human cognitive limitations, and software architecture patterns, I challenge you to look beyond surface-level best practices to understand the underlying forces that shape successful systems. This perspective—discovering the fundamental principle that underlies all principles—could transform how we approach software design challenges at any scale, helping us make more intentional design decisions that withstand the test of time.