Machine learning inference has thoroughly penetrated embedded applications, especially with visual and spatial data like images and radar/lidar. Texas Instruments has a scalable processor portfolio for vision inference at the edge. From inexpensive Arm®-only solutions to computationally-efficient ha...

The buzzword soup of Machine Learning, AI, edge computing, and IoT can be overwhelming (and intimidating) for many developers. In this talk, we will start from a beginner's view of these concepts and evolve to see how we can merge the worlds of ML with the Internet of Things to create a few silly, i...

When it comes to AI, there are inherent dangers one must consider at the board/system level, or when moving over to the edge. Malicious attacks are growing more sophisticated, and hackers are finding new ways to cause disruption to critical systems. With sensor data vulnerable to modification, the v...

The percentage of systems that incorporate AI continues to grow. Hence, it’s now clearly on the radar for most developers/engineers, in applications ranging from consumer to industrial to medical healthcare. With the compute performance available today, the technology has migrated to the Edge of...

Did you know more than 1 billion tons of food is wasted every year? What if we could reduce that? What if optimized AI was the key? Building AI applications to solve real-world problems is our common challenge as developers. To solve a challenge like food waste, optimization is important. In t...

AI at the Edge is no longer “something down the road” or even “bleeding-edge technology.” Some consider it to be mainstream technology. But that doesn’t make it any less complex. In this session, we will look at the hardware and software components that are required to implement AI at the Edge, and...

Many AI applications are based on vision, and most of those applications contain multiple imaging sensors. The pattern/image-recognition software has improved to the point where accuracy is in the high 90%s. But the real trick is making sure that the software is tuned for your application. In this s...

AI is rapidly expanding from the cloud to the everyday objects around us; unlocking a myriad of new use cases from smart shoes to smart cities. As we embed intelligence into more of the everyday objects around us, this raises a number of important questions, such as how should that change our intera...

Today, the state-of-the-art solution to enable high performance imaging radar is to increase the antenna count and processing capabilities of the system. Fundamentally, this approach is not an optimal solution for automotive and robotics applications as the imaging radar available on the market use...

In this session we will work with ModusToolbox and our ModusToolbox & Friends partners and how we can combine multiple capabilities from connectivity, audio and machine learning through the example of Audio classification. You will learn how ModusToolbox is extending to external tools that make it e...

In the recent past, the Edge computer would collect and process data from the sensors/endpoints, then either take an action directly or send a signal back to the endpoint for the action to occur. Today, the intelligence that’s built into the endpoints is more than adequate to process the data and ta...

While many (most?) of the uses of AI in automotive are for autonomous-drive-related features, there is a growing need for AI to be used in software development and testing. Analysis of the relationships and dependencies between software functions, and of their behavior in run-time will generate acti...

Deep learning models are advancing at a fast pace, creating difficult dilemmas for system developers. When you begin developing an edge AI system, you select the best available model for your needs. But by the time you’re ready to deploy your product, your original model is obsolete. You’d like to u...

AI technology is the focus of many organizations. This discussion will explore the common themes around adoption to understand what AI technology is being used and why.

Algorithms for processing graphical objects such as raster images and 3D point clouds can quickly become very compute-intensive. Many of these algorithms are excellent choices for parallel processing optimizations. Developing custom general-purpose GPU code in C++ is easier than you might think, and...

Bringing security into the automated pipeline for continuous integration is a proven approach to creating more mature and robust secured systems - those which are more resilient to cybersecurity incidents, hence significantly reducing the mitigation costs. This concept is often referred to as DevSec...

Voice control is now common in consumer products and can offer unique advantages to medical devices – operating convenience, improved workplace hygiene over touchscreens or keyboards, and less distraction from important tasks. OEMs will want to learn about Digi ConnectCore® Voice Control, an easy-to...

Whether you know it or not, advanced driver assistance systems appear in every vehicle. Some might be obvious to the driver, while some might only appear in an emergency. As ADAS technologies become a requirement, OEMs must ensure that they maintain compliance with evolving regulatory standards as c...

The breadth and specifics involved in driving successful cloud-connected product and services initiatives can be overwhelming. All product development phases from hardware design to cloud engineering require an ecosystem of technology providers. Choosing the best fit solution in a complex supplier l...

What if you could improve device security by using simple software and on-chip storage to create your very own root of trust (RoT)? Well, now you can. Join this Embedded Toolbox Live interactive webcast where engineers from embedded system security IP leader Intrinsic ID will demonstrate the comp...

The voltages deployed in modern vehicles seems to be a moving target. Each OEM has his own ideas of what’s best for future vehicles. And even after standards are put in place, there is still lots of indecisiveness. In this session, we will look not just at the varying voltages, but the power compone...

In-Vehicle Infotainment (IVI) combines the various subsystems within the automobile, delivering information to and from the driver and passengers from the sensors and ECU. With the wealth of information that’s moving around the vehicle, both wired and wireless, it’s important that critical data gets...

Produced by Embedded Computing Design, the Automotive Technologies virtual conference will cover five key areas related to the design of today’s and tomorrow’s automobiles. It will look at these topics in great technical detail, cover the hardware, software, and everything in between. In-Vehicle...

Advanced driver assistance systems (ADAS) like automatic emergency braking, lane and highway assistance, and driver monitoring have become so commonplace that consumers/drivers take them for granted. What use to be a “feature” is now standard equipment. However, that doesn’t make their design and/or...

Data, analytics, and automation can help your organization reach higher levels of production and performance. However, making the best use of the information at hand can be a daunting task, particularly in a world like automotive where quality and safety must be top priorities. In this Keynote Addre...