The Future Auto: A Software Bundle
on Wheels

Other than the use of Self-Aware™ and AdaptiveAI™ technologies as for AI training and inference for every imaginable application, or the direct application of these technologies to improve performance on hyperscale AI data centers and the chips that run them, no other application space is more perfect for inclusion of these capabilities than those in the Automotive Industry.

In the early days, hardware was easy to configure. Then software “ate” hardware. Now, AI has eaten the world and everything is being disrupted.

There are few industries where so much complexity and active disruption exists as companies are forced to respond to so many unexpected market forces and technology changes. 

Dynamic Workloads Need to Be Controlled

Every complex interface needs to be efficiently configured to be performative and robust. Bugs, recalls and configuration conflicts increase risk, raise the costs of development and strain capital budgets, contributing little in return. Configuration is hard and complexity relentlessly increasing.

Every automotive developer and system integrator should be trained to use Self-Aware™ and AdaptiveAI™ as a normal part of their coding expertise, whether for hardware, o/s, integration of software packages or for optimizing run-time physical devices. 

Next generation configuration practices need goal-oriented strategies to be controllable and performative, to better meet changing dynamic requirements. Consider, there are so many complex opportunities to exploit everywhere, including in the factory, in the vehicles and in the hardware and software that manages them and the user experiences. Complexity abounds, whether in EV’s, autonomous vehicles, robotics, energy management systems, ui/ux interfaces, version control, or in the pieces and parts that make all this work.

Any System Can Be Self-Aware

The idea is simple to get started; simply use conventional practices and standards to build. Then, identify areas in the hardware, software or inference modules that are in conflict or results uncertain, are mission critical, just difficult to configure or may need to be managed to bridge to future versions. 

Identify every interface of complexity that needs to be managed, where goals can be inserted to monitor the workload and optimize configuration parameters continually. Use different goals as needed to set constraints, meet performance objectives, improve feedback loops, protect against unpredictable events, or just collect data. Change goals as needed. The Sequitur™ Platform has all of the foundational computational methods to be additive to conventional practices.

Config is not an automotive system developer nor integrator. We just make complex systems perform better by adapting them to meet their goals.