Feature: AI
Over time, these barriers stifle
progress and hinder a more widespread deployment of AI-based systems.
The open-source revolution To overcome the challenges posed by proprietary soſtware, more and more AI solution providers are embracing an open-source culture. Tis is a model for innovation driven by cooperative competition, making soſtware available to many users. One of the main advantages is that,
over time, this model will be more profitable than using algorithms and data protected by copyright. For example, in 2019 Goldman Sachs
released on GitHub some of the code that its traders use to analyse and manage risk, and offered additional funding to engineers who built new applications using the code. Te benefits of making the code available to the public far outweighed those of keeping it secret – not only can users help improve and fine-tune the code, but Goldman Sachs will also own the intellectual property of any application built using it, and will be an early investor in new and promising technology. Other companies have supported the
open-source movement to help democratise access to AI and spur innovation. For example, back in 2015, Google opened up the research of its machine-learning framework, Tensorflow, playing an active role in the development of open-source- powered AI. Since then, the platform has grown in popularity and is now used by some of the world’s largest brands including Airbnb, Uber and eBay. Open source is also making its mark
in electronics. For example, engineers can benefit greatly from circuit-design software enhanced by AI. Efficient proprietary software allows engineers to check and optimise their designs regularly, but the software is often very costly. Free circuit-design soſtware alternatives
are now popular among engineers, some examples being CircuitMaker, Open Circuit Design Soſtware or KiCad EDA. To make these programmes even more efficient, AI can create agile workflows for the rapid development of the next line of products. It combines and collects data from various sources, like sensors attached to the products, customer usage patterns, current market predictions, technician comments and device manuals. Tis helps
generate key insights for companies about product quality, reduces costs and addresses market demands in a more efficient manner.
Reaching jobs Open-source AI is crucial for the eradication of barriers such as high licensing fees or the skills shortage, allowing developers to focus on the job at hand – developing innovative yet secure and easy-to-deploy AI solutions. Open-source soſtware provides a platform where both novices and experienced developers can contribute regardless of their expertise, promoting learning and collaboration. Having a large number of users from different backgrounds also means the coding process is continuously monitored and improved, diminishing the risk of errors and vulnerabilities. In turn, this helps businesses add an extra layer of security, especially during the development stage of emerging AI-based technologies, when they are still being researched. From the IT world to electronics, open
source can make a real difference in the way AI is deployed and developed. Tere’s more about the future of AI in
manufacturing and electronics on the EU Automation’s Knowledge Hub.
www.electronicsworld.co.uk September 2021 37
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