Covering Disruptive Technology Powering Business in The Digital Age

Written By: Ee Huei Sin, President, Electronic Industrial Solutions Group, Keysight Technologies

With the introduction of ChatGPT, Dall-e, and many other tools to the public, Artificial Intelligence (AI) has become a hotly debated topic that will continue to dominate headlines throughout the decade. Engineers are integrating AI into technologies and reaping the benefits to enhance operations, extract and leverage intelligence, and drive organisation-wide benefits across industries. Given the foregoing, here are 10 AI predictions from Keysight on how the technology will influence and strengthen technologies across industries in 2024.

AI Prediction 1: Bridging the Simulation Gap with AI

Moving forward, AI technologies will underpin simulation models, ushering in a new era of more accurate, capable, and informative models. In addition, the intelligence will provide enhanced insights into measurement data, reduce errors, and help optimise the design and test workflow.

AI Prediction 2: AI and the Sustainability Quandary

There has been significant hype around how AI systems will transform our lives, but little attention has focused on the compute power required. In 2024, AI’s impact on sustainability will enter the spotlight, and organisations will start to monitor the carbon footprint of their entire technology infrastructure as they strive to meet net-zero targets. As a result, companies will need to decide where and how to judiciously use AI rather than thinking it can be deployed everywhere. And when it comes to testing software and applications, businesses will also have to pivot from testing everything to predicting the tests that matter most to reduce the environmental impact.

AI Prediction 3: Cybersecurity in the AI Era: Good and Bad

AI is impacting every aspect of our lives, including cybersecurity. Adversarial AI will increasingly be a problem. For example, generative AI can collect information from social media, corporate email, blogs, and other sources to generate specific and realistic phishing emails that can be personalised and mass-produced with almost no human input. As a result, companies must deploy more advanced phishing detection systems, including those optimised to detect AI-generated content and improve employee training.

AI Prediction 4: Skills Silo Throttles Integration of AI in 6G

Domain knowledge and AI expertise are vital to successfully integrate AI into 6G networks. Today, we have either wireless experts or AI specialists, but too few heads that share expertise in both domains. Until these skill sets are blended, it will be tough to find the right resources to deploy AI effectively in support of 6G goals. This workforce capability gap will take over a decade to resolve.

AI Prediction 5: EDA Turns to AI: From Complexity to Clarity

The application of AI and ML techniques in EDA is still in the early adopter phase, with design engineers exploring use cases to simplify complex problems. The intelligence is particularly valuable in model development and validation for simulation, where it assists in processing large volumes of data. In 2024, organisations will increasingly adopt both technologies for device modelling of silicon and III-V semiconductor process technologies, as well as system modelling for forthcoming standards such as 6G, where research is well underway.

“With the introduction of ChatGPT, Dall-e, and many other tools to the public, Artificial Intelligence has become a hotly debated topic that will continue to dominate headlines throughout the decade.”

AI Prediction 6: Customer Engagement: AI in the Driver’s Seat

By the end of 2024, most customer emails will be AI-generated. Brands will increasingly use generative AI engines to produce first drafts of copy for humans to review and approve. However, marketing teams must train large language models (LLMs) to fully automate customer content and differentiate their brand. By 2026, this will be commonplace, enabling teams to shift focus to campaign management and optimisation.

AI Prediction 7: AI and the Next Frontier in EV’s: Prioritising and Predicting Battery Health

Battery health will become a factor influencing EV buying decisions, presenting an opportunity for auto manufacturers to visualise a car’s health status to reassure and inform drivers. The information will be more granular and incorporate gamification interfaces so drivers can see how their actions influence keeping the battery management system (BMS) at peak performance. Additionally, by integrating AI algorithms into the system, it will predict the health can performance of batteries under various conditions, quelling any concerns.

AI Prediction 8: AI + 6G: A Measured Approach

Unlike other sectors, the wireless industry will take a more measured approach to integrating AI. Operators will focus on thoroughly training the machine learning models on diverse data sets, quantifying the impact, and putting in place a new test methodology. As AI adoption matures, it will transform the wireless industry over the next decade, unleashing new capabilities such as improved beam management and smart spectrum sharing.

AI Prediction 9: Surge in AI Reshaping the Cloud Computing Market

AI workloads require GPU and memory intensive capacity. In the past, we thought of Cloud Computing as having 3 primary competitors: AWS, Azure, GCP. Generation 2 of the Oracle Cloud Infrastructure (OCI) with its significant price and performance advantage in GenAI training has created a 4-horse race in the cloud computing space now.

AI Prediction 10: AI Unmasked: From Hype to Reality

Despite all the hype around AI and generative AI, the technology is far away from being able to automate and optimise every aspect of our lives anytime soon. AI is making progress; however, automating a chatbot or creating a digital assistant are constrained problems that are much easier to automate. When it comes to helping manage real-world processes such as optimizing call quality on a 5G network or managing energy consumption, these are incredibly complex operations, with a wide array of variables requiring vast unbiased data sets before AI can be effective. While intelligence will undoubtedly help us in 2024, realistically, AI will not be ready to direct physical-world activities until the end of the decade.

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