ENERGY REDUCTION
2026 Fiber Connect Keynote: “The Future of Fiber Optics: AI and the Quantum”
Dr. Michio Kaku’s 2026 Fiber Connect keynote, “The Future of Fiber Optics: AI and the Quantum,” kicked off the inaugural AI & Emerging Technology Infrastructure Summit on Wednesday, May 20,2026.
As a theoretical physicist and futurist, Dr. Kaku delivered a high-altitude roadmap framing fiber optic networks not merely as faster telecom pipes, but as the mandatory foundation for a world defined by concurrent, multi-cloud AI infrastructure and quantum mechanics.
Kaku described the convergence of AI, quantum computing, and fiber infrastructure as a critical shift toward an AI-native, quantum-enabled internet essential for national competitiveness. Kaku emphasized that fiber optics are necessary to facilitate “quantum AI” by handling high-density, low-latency data movement, moving beyond traditional networking to support exponential computing advancements.
Key Takeaways:
- Fiber as the Foundation for AI: Dr. Kaku explained that massive data sets and hyperscale AI computations cannot run efficiently over wireless or legacy networks. Fiber’s near-limitless bandwidth and sub-millisecond latency are required to process these workloads in real-time.
- The Quantum Computing Leap: He detailed how quantum networks—which compute at the atomic level—will redefine security and processing power. He emphasized that quantum data requires the stability, security, and bandwidth that only fiber optics can provide.
- National Competitiveness: Dr. Kaku framed fiber broadband as a strategic national asset. He argued that a region’s ability to evolve into an AI-native economy depends directly on robust fiber infrastructure to secure future healthcare, financial, and climate innovations.
- The “Thinking Economy”: He projected that networks are evolving to do more than just transport data. They will increasingly support “thinking economies” where intelligence moves instantly between edge computing centers, end-points, and the cloud.
The presentation and subsequent fireside chat with quantum computing firm IonQ offered several critical technological dimensions and actionable industry analysis:
The Physics of the “AI Triad” (Compute, Quantum, & Photonics):
Kaku mapped out how classical silicon-based computing is approaching its physical limits (thermodynamics and transistor gating). He explained that the future relies on a three-pronged convergence:
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- AI Models: The brain processing the logic.
- Quantum Computing: The hyper-accelerator solving atomic, chemical, and multi-variable optimization issues.
- Optical Fiber: The unified nervous system. Quantum and distributed AI workloads cannot scale on traditional copper networks because they require absolute determinism, zero-jitter latency, and near-limitless bandwidth.
Upgrading to a Quantum-Ready Internet:
Drawing from themes in his book Quantum Supremacy, Kaku noted that the move toward a quantum-enabled web alters the physical network topology. Operators must plan for physical security layers (like Quantum Key Distribution) and data transmission methods that preserve quantum entanglement across distances.
–>Fiber is the only media capable of transporting light photons over vast geographies without disrupting these states.
The Power and Cooling Crisis:
A significant focus of the analysis was the staggering energy footprint of next-generation AI factories and hyper-scale data centers. Kaku noted that moving data electronically creates heat resistance. Shifting toward all-optical (photonic) networks and in-rack fiber interconnects removes electronic bottlenecks, drastically reducing the power required to pass massive datasets between distributed data centers
Strategic Implications for Network Operators:
During the fireside chat, the discussion moved from theoretical physics to immediate business strategy and tactics:
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- National Competitiveness: Bandwidth, latency, and optical infrastructure are the new benchmarks for a country’s economic power.
- Capacity Planning: Network planners must shift from estimating consumer download speeds to calculating the throughput required for real-time, stateful AI agents and machine learning inference workloads operating at the network edge.
FBA Panel and Summit Sessions:
Following Kaku’s opening address, the Fiber Broadband Association (FBA) hosted deep-dive industry panels that put these physics concepts into operator terms:
- The Open Compute Project (OCP): Discussed open-source hardware standards for in-rack photonics to support massive AI clustering.
- Multi-Data-Center Architectures: Network engineers mapped out how dense dark fiber rings are being laid to link secondary edge facilities, allowing enterprises to run heavy inference closer to end-users without overwhelming backbone networks.
- AI data center speed and power requirements are transitioning towards 800 Gbps–1.6 Tbps node-to-node networking and gigawatt-scale power to handle distributed generative AI workloads.
- High rack densities up to 240 kW require advanced liquid or immersion cooling, with optical technologies being introduced to reduce heat generation.
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References:
https://fiberconnect.fiberbroadband.org/about/whats-new/
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China vs U.S.: Race to Generate Power for AI Data Centers as Electricity Demand Soars
The International Energy Agency (IEA) forecasts that in the next five years, the global demand for power (electricity) is set to grow roughly 50% faster than it did during the previous decade – and more than twice as fast as energy demand overall. That tremendous increase in demand is due to power hungry AI data centers. There’s also electric cars and buses, electric-powered industrial machines, and electric heating of homes.
Global AI growth will be contingent on generating more power for data centers:
- Global data center power demand is now expected to rise to a record 1,596 terawatt-hours by 2035 – +255% increase from 2025 levels.
- The U.S. is set to remain the leader in energy consumption with a +144% surge in demand over this period, to 430 terawatt-hours.
- China’s demand is projected to rise +255%, to 397 terawatt-hours.
- European demand is expected to surge +303%, to 274 terawatt-hours.
- New data centers coming online between now and 2030 will need more than 600 terawatt-hours of electricity. This is enough to power ~60 million homes.
Power for AI Data Centers: China vs U.S.:
China is currently ahead of the United States in generating and building out power infrastructure to support AI data centers, a phenomenon sometimes described by industry observers as an “electron gap.”
China’s rapid, centralized expansion of electricity generation—including both massive renewable projects and traditional, dispatchable power—has created a significant capacity advantage in the race to support AI workloads, which are increasingly limited by energy availability rather than just chip access.
Key factors in China’s power advantage for AI include:
Massive Generation Growth: Between 2010 and 2024, China’s power production increased by more than the rest of the world combined. In 2024 alone, China added 543 gigawatts of power capacity—more than the total capacity added by the U.S. in its entire history.
Significant Surplus Capacity: By 2030, China is projected to have roughly 400 gigawatts of spare power capacity, which is triple the expected power demand of the global data center fleet at that time.
“Eastern Data, Western Computing” Initiative: China is actively shifting energy-intensive data centers to its resource-rich western regions (like Inner Mongolia) while powering them with surplus renewable energy, such as wind and solar.
Lower Costs and Faster Buildouts: Data centers in China can pay less than half the rates for electricity that American data centers do. Furthermore, projects in China can move from planning to operation in months, compared to years in the U.S. due to faster permitting and fewer regulatory hurdles.
Conclusions:
While the U.S. currently leads in advanced AI chips and model development, it is facing a severe “energy bottleneck” for new data centers, with some requiring over a gigawatt of power. U.S. power demand has remained relatively flat for 20 years, resulting in a lag in building new capacity, whereas China has traditionally built power infrastructure in anticipation of high demand. Morgan Stanley has forecast that U.S. data centers could face a 44-gigawatt electricity shortfall in the next three years.
Despite China’s advantage in energy, U.S. export controls on high-end AI chips (such as Nvidia’s GPUs) have acted as a significant constraint on China’s actual AI compute power. This has led to a situation where the U.S. has the best “brains” (chips) but limited power to run them, while China has the “muscle” (energy) but limited access to top-tier AI brains.
However, the rapid improvements in Chinese AI models (such as DeepSeek), which are more energy-efficient and optimized for lower-tier hardware, may help mitigate this constraint.
References:
https://www.iea.org/reports/electricity-2026
https://x.com/KobeissiLetter/status/2023437717888250284
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Beyon partners with Ericsson to build energy-efficient wireless networks in Bahrain
Bahrain based Beyon announced it has renewed its sustainability Memorandum of Understanding (MoU) with Ericsson to expand their joint sustainability initiatives and circular economy practices for building energy-efficient networks in Bahrain.
The MoU renewal was signed by Beyon Chief Communications & Sustainability Officer Shaikh Bader bin Rashid Al Khalifa and Vice President and Head of Gulf Council Countries at Ericsson Middle East and Africa, Nicolas Blixell.
The companies also announced the successful outcomes of their sustainability collaboration, signed in early 2024, for accelerating the journey to a Net Zero future for both companies and managing Waste from Electronic and Electrical Equipment (WEEE).
Key achievements during the year include the initiation of ‘Ericsson Product Take-Back Programme’, which addresses the issue of e-waste and enables recycling of end-of-life electronic and electrical equipment in a responsible and sustainable way.
Software such as Cell Sleep Mode and Artificial Intelligence (AI)-powered MIMO Sleep Mode were also implemented on pilot sites, leading to a 22% average reduction in energy consumption where the features were activated.
Another 18% percent energy reduction was apparently achieved through the deployment of the single-antenna footprint Interleaved AIR 3218, compared to AIR 3227, to provide “5G Massive MIMO while addressing space constraints on rooftops and towers.”
“Our partnership with Ericsson demonstrates the substantial progress that can be made through focused sustainability initiatives,” said Shaikh Bader bin Rashid Al Khalifa, Beyon Chief Communications & Sustainability Officer. “The outcomes reflect our commitment to energy efficiency and our goal to reduce our environmental footprint through innovative technologies and circular economy practices. Ultimately these efforts fall in line with the Kingdom of Bahrain’s vision to achieve its sustainable development goals of 2030.”
Nicolas Blixell, Vice President and Head of Gulf Council Countries at Ericsson Middle East and Africa added: “The results of our collaboration with Beyon highlight the role of technologies in achieving sustainability goals. By leveraging our expertise and technologies, we have been able to deliver measurable energy savings and support Beyon in their journey towards Net Zero.”
Earlier this year, Three and Ericsson claimed to have improved energy efficiency by up to 70% at selected sites through AI, data analytics and a ‘Micro Sleep’ feature. The deployment of ‘next-generation AI-powered hardware and software solutions’ from Ericsson is part of a network modernisation initiative Three had been engaged in over the previous 18 months, we were told at the time.
Ericsson and Beyon share a longstanding relationship, through its telecom arm Batelco, with this sustainability collaboration marking another milestone in their efforts to enhance network efficiency and environmental performance across Beyon’s operations.
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