Keysight executives deliver 2024 predictions
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Nine top executives from Keysight Technologies, provider of market-leading design, emulation and test solutions globally, has assembled its list of predictions that may impact the electronics industry in 2024.
Dan Krantz, Chief Information Officer at Keysight
Impact of AI in 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.
Trends in the cloud computing industry in 2024
Majority of organizations are multi-cloud, seldom single cloud. Cloud vendors have started to realize this and are now building better multi-cloud interoperability capabilities. For example, the recent Azure/OCI agreement that Larry Ellison struck with Satya Nadella of Microsoft. This leads to organizations needing cloud-agnostic tools for observability, visibility, and quality assurance automation.
Emerging sectors of the cloud industry becoming significant in 2024
As traditional cloud capabilities mature, I predict the emergence of Cloud High Performance Computing (HPC) in the next 12-18 months. Current HPC workloads typically utilize on-premises supercomputing infrastructure, but cloud providers will bring to the HPC market supercomputing capabilities wrapped in cloud-native characteristics of elasticity, programmable automation, and metered usage – this will democratize the most compute-intensive scientific and engineering workloads.
Roger Nichols, 6G Program Manager at Keysight
Why some versions of AI are not the key to optimizing 6G networks
AI has a large role to play in helping optimize 6G. However, it will not be the much-hyped generative AI that relies on large language models and vast data sets. Instead, it will be domain-specific data combined with the power of AI models and wireless domain expertise that will help solve specific industry problems. For example, AI algorithms will make improvements in the air interface, helping optimize the 6G system. Other use cases include advancing how to manage mobility during handovers, cell-site planning, and optimizing MIMO. But, before AI can add value to the development of 6G, it needs to be more reliable, explainable, and much less expensive.
Skills silo throttles integration of AI in 6G
Domain knowledge and AI expertise are vital to successfully integrating 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. I believe this workforce capability gap will take more than a decade to resolve.
5G still a work in progress
At the end of 2023 there are fewer than 50 commercial standalone 5G networks in the world. Over the next few years, the pace of transition from non-standalone to standalone networks will accelerate as these architectures support a fully programmable 5G network, which in turn enables operators to build services beyond enhanced mobile broadband. The expansion of standalone networks should pick up, as will the use of network slicing and resolving defects and performance challenges. In addition, the 5G ecosystem will grow in order to support capabilities in a broader range of industries beyond gaming and social media activities. This will lay the groundwork for 6G to be used across a wide set of use cases.
Mobile gaming turns FR2 from dormant to dominant
The wireless industry is exploring the acquisition of new spectrum between seven and 24 GHz. However, FR2 (millimeter-wave, 24-52GHz) is already available with many cases allocated, but it’s too expensive to support current use cases. FR2 will require new mobile gaming/VR applications to drive the economy of scale to overcome this hurdle. Interest from Gen Z and Gen Alpha in the new consumer applications played on VR/AR devices rather than traditional smartphones will drive a surge in the demand for higher bandwidth and capacity with a low-stakes use model. Current networks will be unable to support this and operators will turn to FR2 to support the demand at this scale. Once this milestone occurs, the downward pressure on costs will help applications outside the entertainment and advertising realm use FR2.
Mobile subterahertz radio systems will not come to fruition anytime soon
Mobile subterahertz (sub-THz) radio systems are at least a decade away. They are not feasible from a mobility standpoint due to immature mobile technology and the associated costs – not to mention power consumption and data-management. The industry’s struggles with FR2 are evidence that mobile sub-THz radio systems will not be viable in the near future.
6G is not going to overhaul the core network
6G will not result in a major overhaul of the core network. It will evolve, but a significant revamp, as happened with network functions in the transition from 4G to 5G, will not occur. The majority of the wireless industry now accepts that this would be a mistake.
Spectrum Smorgasbord: A huge challenge for wireless industry
Over the next five years the global wireless industry will have to support and manage 2G, 4G, 5G, and 6G networks. This carries significant technical and business challenges. With more than a fifth of the world’s population still relying on 2G, developing regions like Africa and most of Asia will not sunset many legacy networks before the end of the decade. However, India is bucking this trend and has deployed country-wide coverage with 5G standalone networks, making it the largest country in the best position to retire 2G. The only constraint that could slow this shift is the affordability of new devices.
India: From wireless laggard to 6G leader
India has become a nation of data guzzlers and is the global leader in per-device monthly data consumption. This is driving the demand for more bandwidth and capacity. After being late to adopt 4G, but accelerating 5G in the past 12 months, the country is emphasizing and championing national objectives for 6G and is looking to help shape and drive its rollout. India has launched multiple 6G research initiatives in 2023. They will be a leading voice in establishing 6G standards and ensuring it is fit for purpose for countries with large rural populations.
Metaverse: More than an entertainment destination
Despite most discussions of the metaverse focusing on gaming, it will evolve to support much broader use cases than those laid out by Meta. By the end of the decade, augmented and virtual reality will be part of our daily lives, and 6G will be pivotal in providing the bandwidth and connectivity to support these synthetic environments and facilitate seamless interactions between the virtual and physical worlds.
Sarah LaSelva, Director of 6G Marketing at Keysight
Regulation on the radar
In 2024, regulation will be on the agenda as the industry looks to provide a framework so that the entire ecosystem, including companies, operators, and countries, can work in unison. Due to the complexity involved, particularly at the geopolitical level, this will take several years to resolve.
AI is everyone’s BFF, including 6G
The combination of complexity and massive amounts of data makes wireless networks ripe for AI optimization. The technology has started to be integrated and in 2024 this will accelerate. A key part of the process will be understanding where AI can help and, crucially, where it’s not the answer and may actually hinder the rollout of 6G.
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 a new test methodology in place. 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.
The drive to net zero
With sustainability concerns growing around wireless networks, AI will play a pivotal role in helping reduce the environmental impact of 6G. For example, the technology can determine how to optimize power consumption by turning on and off components based on real-time operating conditions.
As 6G networks roll out and more devices and machines become wirelessly connected, it will create an opportunity to optimize operations and reduce carbon footprints. For example, 6G will help autonomous vehicles become more advanced, which will reduce traffic and some of the waste and inefficiencies associated with human-led driving. In farming, IoT devices connected to 6G will monitor soil conditions and help optimize water and fertilizer use. Once 6G becomes ubiquitous, it will usher in a new era of sustainability-driven operations.
The industry will look to standardize sustainability measurements in 2024, including measuring the total carbon footprint of a wireless network. This will help avoid greenwashing claims and accelerate the drive to net zero.
Spectrum sharing log jam on the horizon
6G will leverage many different bands and tools to meet the growing demands and expectations for cellular communications. The most challenging technical aspect is how to share spectrum. For example, in 6G the upper mid-band (7-24 GHz) is already used by civilians and governments for meteorology, radio astronomy, and maritime radio navigation. Once wireless access is added, it will necessitate learning how to be good frequency citizens. In 2024, there will be a lot of research in this area to find a pathway forward.
Global spectrum harmonization on the radar for 6G
The World Radio Conference in late 2023 will determine the available frequency bands that 6G will use and put in place a plan to make global spectrum harmonization a reality. This will enable operators to realize economy of scale for components and limit the number of bands to support.
Gareth Smith, General Manager, Software Test Automation at Keysight
Software Testing & AI Predictions
AI & Testing: Always on becomes the baseline
As AI becomes increasingly embedded in software, the systems will become more autonomous, which increases risk and complexity and makes testing a real challenge. As a result, a fixed set of tests (scripts) will no longer suffice when evaluating intelligent systems. Instead, AI will be needed to automatically and continuously test AI applications. The future of software testing is autonomous test design and execution.
Why AI may drive quality down, not up
As AI permeates every system and complexity and sophistication soar, there is a risk that quality will go down. This is a result of the sheer number of permutations, which makes testing everything impossible. This means decisions will need to be made around how, what, and when to test to ensure quality is maintained.
AI: Regulation needs to be deep and wide
There is universal acceptance of the need to regulate AI. However, what the regulation should encompass will be subject to much debate due to the breadth and complexity of the technology involved. It will take a seismic event with significant negative consequences before the necessary funding is available. Only then will clear standards and best practices come into effect. If regulation doesn’t happen in the near future, it increases the risk that it will no longer be possible to rein AI in.
AI and Security: Constant vigilance the new norm
As the risks associated with AI are recognized, enterprises will need to appoint an AI and security compliance officer to the C-Suite. Over time, this role will merge with the CSO.
With live learning, it will be vital to have guardrails in place to keep AI on track. Constant checks and balances will be essential to validate that an intelligent system is behaving and hasn’t gone rogue. Live surveillance will become standard. However, as these systems develop, it will also be necessary to test that they haven’t learned how to look like they are behaving while undertaking nefarious activity. Reinforcement learning and similar techniques can inadvertently drive the AI to cover its tracks to reach its goal and will be a huge challenge to address before the end of the decade.
These problems will create a slew of new opportunities for companies that can help clean up, control, and put guardrails in place for AI.
Why AI needs a driver’s license and a regular inspection
Currently, AI systems are tested by the companies building them. As the risks are increasingly understood, having an independent body to verify that an AI system is compliant is essential. Gaining an AI certification (i.e., AI driver’s license) will be the first step. However, just like your car, it will require a regular test to ensure it remains ethical, responsible, free of bias, and meets the necessary country and industry standards. In the longer term, this may result in an NFT label on each AI system to validate that it’s fit for purpose and meets all the required criteria.
Goodbye citizen developer, hello business developer
Citizen developers have long been touted as the answer to the IT talent shortage. However, the rapid growth of AI-powered solutions is fueling a new generation of business developers. These domain experts will increasingly be involved in the SDLC as they understand the goals and operations of the enterprise. This will give rise to a new wave of no-code systems that enable business users to define goals and then have AI technology close the gap. The operational knowledge ensures that the software meets the specific needs of the organization and mitigates the risk.
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 organizations 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.
Dan Thomasson, Head of Central Technology and Vice President of Keysight Labs
Advanced semiconductor innovations on the horizon
Connecting the digital and physical worlds will require more powerful digital processing and interfaces able to overcome increasingly complex signal physics. An array of advancements in semiconductor technologies will be essential to achieve this and overcome the associated challenges.
These issues include increasing data rates that need wider bandwidths, which dictate higher carrier frequencies, extending into the THz regime for wireless. The use of techniques such as extreme MIMO, adds more complexity and density, and networks with diverse topologies, such as the use of non-terrestrial (satellite) links, magnifies the challenge.
Innovations to address this will include combining commercial semiconductors, such as GPUs and FPGAs, with custom MMICs and ASICs, and these new solutions will deliver significant improvements in size, weight, performance, and power consumption.
Data converters enabling the capture and generation of signals at the widest bandwidths with unsurpassed signal fidelity will be needed. In addition, photonic solutions will be critical to extend the reach and capacity of data transmission technologies.
Seamless software solutions for design and test
Currently, workflows are a set of loosely connected tools. However, as the virtual and physical worlds merge, a unified design and test workflow where data is shared seamlessly via the cloud between simulation and measurement steps is required.
The information will be constantly analyzed to inform the behavior of simulation and measurement, eliminating any gaps in the workflow from concept to final test. The insights from the simulation will be fed into AI-driven tools that will elevate the speed and productivity of the design and test workflow. Digital twins will be used to tightly couple design and test so that only one actual build is needed.
6G embraces AI for network optimization
6G will turn to AI for network optimization, which will create testing challenges. It will be vital to develop technologies able to test AI algorithms to ensure training data is free of bias and the models are effective and devoid of anomalous behavior.
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 optimize the design and test workflow.
Niels Faché, Vice President & General Manager, Design and Simulation at Keysight
Predicting performance remains imperative in electronic design
In 2024, engineers will continue embracing shift left with their electronic product development cycles. As design moves from the physical into the virtual space, engineers are able to discover and fix problems in the most efficient manner, providing greater insights and performance improvements. The next few years will see a continuing emphasis on connecting design and test workflows to handle rising complexity and more demanding time-to-market requirements for electronic products in wireless, wired, aerospace & defense, and other industries.
Emerging Electronic Design Innovations
3DIC and Heterogeneous Chiplets: New standards come into view
New standards such as UCIe are emerging for the creation of chiplets and the disaggregation of system-on-chip designs into smaller pieces of intellectual property that can be assembled into 2.5D and 3D integrated circuits using advanced packaging. For designers to accurately simulate die-to-die physical layer interconnect, it will require high-speed, high-frequency channel simulation to UCIe and other standards.
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, organizations will increasingly adopt both technologies for device modeling of silicon and III-V semiconductor process technologies, as well as system modeling for forthcoming standards such as 6G, where research is well underway.
Software automation empowers engineers
As Moore’s Law reaches its limits, improving design processes through workflow automation will provide a pathway to increasing the productivity of design engineers. In 2024, software automation techniques, such as Python APIs, will take a more significant role in integrating “best-in-class” tools into open, interoperable design and test ecosystems.
Navigating the Digital Shift: Design management essentials
With the creation of digital enterprise workflows, many organizations are investing in design management across tool sets, data, and IP. Moving forward, design data and IP management software will play a critical role in the success of complex SoC and heterogeneous chiplet designs supporting large, geographically distributed teams. The creation of digital threads between requirements definition and compliance as well as establishing tighter links with enterprise systems such as PLM will play a role in the digital transformation of product development cycles.
Next-Gen Quantum Design: Optimizing system performance
Quantum computing is advancing at a rapid pace and is transitioning from predominantly free research tools to commercial products and workflows in quantum design. Next-generation quantum design will require more integrated simulation workflows that provide developers with fast and accurate capabilities to optimize system performance.
Silicon photonics fuels data center transformation
Data centers are evolving to provide higher compute performance to support the exponential growth in AI and ML workloads, as well as the need for more efficient power utilization and thermal management. Silicon photonics will play a critical role in accelerating the transformation of data centers to meet the appetite for compute performance. As design engineers develop high-speed data center chips that incorporate silicon photonics interconnect, they will need process design kits (PDKs) and accurate simulation models that support the advanced development work.
Dr. Philip Krantz, Quantum Customer Success Manager at Keysight
From Theory to Reality: The quantum potential
Quantum technology allows us to harness the fundamental laws of quantum mechanics to solve problems that are extremely challenging or impossible today. With quantum technology, complex simulations and computations, secure communication, and more powerful imaging and sensor techniques will be possible.
Navigating the Quantum Landscape: Bridging the talent gap
Quantum technologies are expanding beyond the academic realm and into startups, high-tech companies, and the military. This will give rise to more quantum hubs, incubators, and local and national ecosystems all trying to build a workforce able to seize the quantum opportunity. Solving the talent gap is critical to realizing the potential of quantum in the coming years and decades.
From Labs to Lecture Halls: The quantum leap in education
The shortage of quantum talent will create an opportunity for higher education to offer new programs to help train the future quantum workforce. By 2030, quantum courses will be commonplace. These programs will involve industry partners so students can access the latest quantum control and readout technologies and obtain the right technical skills. In addition, business schools will offer quantum courses to prepare the next generation of entrepreneurs to enter the quantum ecosystem.
Democratizing Quantum: The emergence of quantum-as-a-service (QaaS)
Due to the significant cost and resource burden in developing quantum labs, this will give rise to more quantum-as-a-service (QaaS) providers. Remote cloud access to quantum processors, test beds for device characterization, and foundries that offer fabrication services are examples of services that are available which in turn will help attract startups into the quantum ecosystem. QaaS providers, over time, will help standardize device operation, characterization, and fabrication, which will enable benchmarking of quantum processors and qubit-adjacent enabling technologies.
Inclusive Innovation: Quantum community champions gender equality
Quantum has the potential to become the first technology sector to achieve gender equality. This will result from an ongoing concerted effort to attract women and ensure a diverse workforce is the norm rather than the exception.
Knowledge gaps will throttle the progress of quantum
Quantum research and development will continue to attract investment from governments, academia, and industry. However, knowledge gaps and the availability of state-of-the-art technology will limit the pace of progress. For example, if the capability to produce high-quality quantum processor units (QPUs) is missing due to the lack of an advanced and dedicated cleanroom facility, this will slow progress.
Marie Hattar, Senior Vice President & Chief Marketing Officer at Keysight
AI and Marketing: What the future holds
Marketing organizations will increasingly adopt AI to help analyze data, uncover insights, and deliver efficiency gains, all in the pursuit of optimizing campaigns.
Customer Engagement: AI in the driving 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 optimization.
Copyright comes into focus
Generative design tools are increasingly being adopted, but one thorny issue is copyright. Many of these AI solutions scrape visual content without being subject to any consequences. In 2024, there will be a lot of energy and effort focused on finding a solution to the copyright problem with AI image creation to clarify ownership. This will allow marketing teams to embrace AI design tools without fear of encountering legal issues, saving precious time and money.
AI and Talent: The augmentation era
As AI becomes more pervasive, this will inevitably change the fabric of marketing teams. Lower-level admin-centric roles will disappear, and many analytical positions will become redundant. However, it’s not all doom and gloom; the demand for data scientists will explode, making it one of the most sought-after skill sets for the rest of this decade and immune to economic pressures. Humans will continue to drive marketing, but the role of machines will increase each year. This era of AI (with guardrails) augmenting humans will continue for at least another decade in marketing.
AI key to scaling personalization efficiently
AI will be pivotal as marketing struggles to scale personalization efforts. The intelligence will enable marketing to generate more customer experiences from improved segmentation. In addition, the technology will optimize advertising targeting and marketing strategies to achieve higher engagement and conversion levels.
AI & Retail – The retail industry has been quick to integrate AI to deliver efficiencies and increase sales. One innovation on the horizon is combining neural networks with a shopper and a product to create a new retail experience. For example, starting in 2024, you can expect an AI assistant to showcase an item of clothing on a model with similar dimensions to you so you can see exactly how it will look in various poses. These immersive, highly personalized experiences are the future of retail.
AI & Digital Twins: Changing the face of healthcare – Digital twins are increasingly ubiquitous, and now, with AI-infused, they are creating a new reality in healthcare. The technology will significantly reduce the pressure on the system and provide individuals with more options, helping improve the quality of life. AI-powered digital twins will usher in a new era of caring for an aging population, allowing people to live independently for longer.
AI will play a pivotal role in the early diagnosis of potential health issues. For example, full-body MRIs will tap into AI’s ability to identify, predict, and analyze data patterns to help diagnose disease long before it’s visible to the human eye. In addition, AI will take on a more prominent role in assisting medical staff to understand and interpret findings and provide treatment and care recommendations.
Jeff Harris, Vice President, Corporate and Portfolio Marketing at Keysight
The Next Frontier in EVs: Prioritizing and predicting battery health
As EVs continue to evolve, range anxiety will start to dissipate as 300 miles becomes standard. However, attention will shift to the health of batteries. With cell phones already illustrating how batteries can deteriorate over time, no driver wants to experience a car that quickly loses power, potentially leaving them stranded or, at the very least, requiring multiple charges per day. Battery health will become a factor influencing EV buying decisions, presenting an opportunity for auto manufacturers to visualize 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 at peak performance. Additionally, by integrating AI algorithms into the system, it will predict the health and performance of batteries under various conditions, quelling any concerns.