Emerging Technologies Beyond Quantum Computing

C-suite leaders need to be aware of trends in the present that are likely to become our future reality. #WEF neatly describes the future as “both a realm of study and a landscape to shape”; as we study it in detail, and WEF notes the advancements across 10 emerging technologies for 2024, three in particular caught my eye. Not only am I following these closely myself for HotTopics, but they each have burning questions that may impact their potency for genuine change. 1. AI for scientific discovery  Deep Mind’s #AlphaFold is accurately predicting 3D models of protein structures, and researchers are discovering a new family of antibiotics, as well as materials for more efficient batteries. We are seeing similar advances in the diagnosis, treatment and prevention of diseases, and in how the human mind is understood. More research is needed to manage AIs impact. Beyond energy usage and ethics, tackling inherent biases in data sets and improving the reliability of model-generated content is crucial to scientific integrity. Look out for: intellectual property rights, particularly ownership and copyright of model-generated content, are still largely unaddressed. 2. Privacy-enhancing technologies Access to increasingly large datasets powers genAI, and transforms research, discovery and innovation. However, appropriate concerns around privacy, security and data sovereignty limit the degree to which high-value data can be shared and used. CISOs and CROs are renewing interest in homomorphic encryption, which allows encoded data to be analysed without the raw data being directly accessible. It does, however, require significantly more energy and time to achieve a secure result. I’m also hearing a lot about synthetic data. Powered by AI, synthetic data “removes many of the restrictions to working with sensitive data and opens new possibilities in global data sharing.” Look out for: Regulation on synthetic data is a grey area, and certain data sets (like, national health) are too vulnerable to be considered in this context—yet. 3. Reconfigurable intelligent surfaces Global demand for higher data rates, lower latency and energy-efficient connectivity is skyrocketing; the launch of 6G by 2030 will compound this demand. Enter: reconfigurable intelligent surfaces (#RIS). RIS platforms use meta-materials, smart algorithms and advanced signal processing to turn ordinary walls and surfaces into “intelligent components for wireless communication.” The growth of RIS is likely to impact several industrial sectors: tailored radio wave propagation in smart factories can ensure reliable communication in a highly complex environment; or, to improve coverage in farming, RIS has low energy consumption and high-cost efficiency. Look out for: Hardware costs need reducing immediately, as is the need for clearer standards and regulations on the secure and ethical use of  the technology. https://lnkd.in/gZ94_MUM

The Next 24 Months Will Reshape Everything We Know About “Technology” Remember when “emerging tech” meant AI, blockchain, and IoT? That era is over. We’re entering a new convergence age — where technologies no longer evolve in silos, but in collision. Here’s what’s quietly transforming under the surface 1. AI is becoming multi-modal Not just text or images — but understanding across senses. Imagine AI that watches a factory line, listens to operator feedback, reads the instruction manual, and learns how to optimize production in real-time. This isn’t science fiction — it’s enterprise reality in 2026. 2. Synthetic Biology meets Machine Learning Bio-engineering is being automated. Startups are training models to design proteins like we design code. The implications for healthcare, agriculture, and energy? Staggering. 3. Edge Computing + Generative AI = Intelligent Infrastructure Your data won’t need to “go to the cloud.” The cloud will come to you. Think smart grids, hospitals, and cars making instant local decisions without sending terabytes to a central server. Latency dies. Efficiency explodes. Privacy improves. 4. The Trust Layer: Quantum & Blockchain’s Unexpected Reunion Quantum-safe encryption and decentralized identity systems are merging into what many call “the next internet of value.” Your identity, credentials, and assets — all portable, provable, and private. The Leadership Imperative Technology isn’t just transforming tools. It’s reshaping decision-making itself. In the next 24 months, the leaders who thrive will be those who: 1. Build cross-disciplinary teams (AI + biology + policy). 2. Prioritize ethical foresight — not just compliance. 3. Treat learning velocity as a KPI. Last year, I thought we were at the peak of digital acceleration. Now it feels like we’re just leaving base camp. What emerging tech are you most bullish (or cautious) about right now? #EmergingTech #AI #Leadership#Futurework#

Last week, #NVIDIA CEO Jensen Huang's keynote speech took the AI / ML community by storm. To me, he's just selling 𝐛𝐞𝐭𝐭𝐞𝐫 𝐩𝐢𝐜𝐤𝐚𝐱𝐞𝐬 𝐝𝐮𝐫𝐢𝐧𝐠 𝐚 𝐠𝐨𝐥𝐝 𝐫𝐮𝐬𝐡! If this sounds crazy to you, allow me to explain why... 🥞 Don't get me wrong, outpacing Moore's law by a staggering 12 years while reducing electric consumption is indeed remarkable, and Huang's vision, leadership, and charisma are unparalleled in the tech industry. That being said, NVIDIA's achievements and vision are all happening within traditional computing, where digital silicon transistor-based chip designs have reigned supreme for almost seven decades. And 𝐆𝐏𝐔𝐬 𝐚𝐫𝐞 𝐬𝐞𝐥𝐥𝐢𝐧𝐠 𝐥𝐢𝐤𝐞 𝐡𝐨𝐭𝐜𝐚𝐤𝐞𝐬 because we have fossil fuels and a computation-hungry data economy. The real question is whether our relentless pursuit of smaller, more powerful silicon chips diverts attention and investment from alternative paths. And, no, I'm not talking about Quantum computing! 💡 Consider computing at the speed of light. Imagine computations between 𝟏,𝟎𝟎𝟎 𝐚𝐧𝐝 𝟏𝟎,𝟎𝟎𝟎 𝐭𝐢𝐦𝐞𝐬 𝐟𝐚𝐬𝐭𝐞𝐫 and 400 times more energy efficient than currently possible! In the past few months, there have been several breakthroughs with #PhotonicComputing chips designed for vector-matrix multiplication, which are crucial for #AI neural network training. These chips are made out of lithium niobate, known for its transparency to visible and infrared light. Links to papers and articles about these advancements are in the comments. 🔥 I wonder if so much 𝐛𝐮𝐳𝐳 𝐚𝐛𝐨𝐮𝐭 𝐆𝐏𝐔𝐬 𝐚𝐧𝐝 𝐋𝐋𝐌𝐬, and the abundance of resources and the growing investment in the semiconductor economy that made them possible have overshadowed potentially better alternatives, both on the hardware and software end. I've made this argument before: historically, necessity has spurred invention. Foundational technologies like MapReduce, LZW Compression, Fast Fourier Transform, and even neural architectures like Transformers emerged not out of abundance but from the need to do more with less. Today, as we grapple with the environmental and economic costs of our computing infrastructure, perhaps it's time to broaden our horizons and consider these emerging technologies not just as alternatives but as the next evolution in computing. 🚧 If we don't take a fork in the road, GPUs will undoubtedly hit the physical limits of Moore's law and train #LLMs with every text ever publicly written and uttered, and then what? In essence, this is why I wish we had more constraints. Without resource constraints in place to slow us down and pay attention to alternatives, we will continue going down a 𝐭𝐞𝐜𝐡𝐧𝐨𝐥𝐨𝐠𝐢𝐜𝐚𝐥 𝐝𝐞𝐚𝐝-𝐞𝐧𝐝 — when measured on a larger timescale. What do you think?

𝐓𝐡𝐞 𝐅𝐮𝐭𝐮𝐫𝐞 𝐨𝐟 𝐓𝐞𝐜𝐡𝐧𝐨𝐥𝐨𝐠𝐲 𝐈𝐬 𝐍𝐨𝐰 The future isn’t waiting to arrive—it’s already running beneath our feet. Artificial Intelligence has become the interpreter of everything digital and physical, uniting data from millions of sensory nodes into a living network of awareness. Across agriculture, defense, transportation, and energy, advanced sensors form the new sensory cortex of civilization. They feel vibration, temperature, stress, magnetism, radiation, and even chemical signatures at scales smaller than the eye can perceive. From LIDAR and hyperspectral imaging to bio-electronic skin, these systems are feeding the cognition of robotics, drones, and autonomous infrastructure. Edge AI now processes sensory input on-site, turning perception into action in microseconds. Quantum sensors measure the imperceptible—gravitational waves, quantum spin, and atomic drift—creating precision that surpasses GPS. Quantum computers are solving simulations that redefine material science, while photonic processors convert light itself into logic. Robotics have evolved beyond automation; they now see, hear, and reason. Biotechnology fuses with computation—synthetic tissues, neural implants, and AI-guided cellular programming redefining medicine and biology itself. Energy systems are being reborn through hydrogen, graphene, and zero-loss superconductors. Augmented and extended reality have become operational environments. And across it all, data—encrypted, authenticated, and autonomously maintained—has become the connective tissue of the planet. The infrastructure of intelligence is here. The question isn’t when we’ll reach the future. It’s whether we’ll have the wisdom to lead it.

AI isn’t just a software revolution, it’s a hardware revolution, maybe the biggest since the dawn of computing. I’m with Jensen Huang on this: this is the first true reinvention of computing architecture in 60 years. What’s thrilling? Technologies we once shelved as “too early” or “too exotic” are roaring back because AI demands it: ̇ᐧ Optical computing → Celestial AI, Lightmatter, LightOn, and others reviving light-based processors to break energy barriers. ᐧ Neuromorphic computing → Intel’s Loihi and IBM’s TrueNorth mimic brain-like networks for ultra-efficient learning. ᐧ Quantum computing → IBM, Google, and Rigetti are chasing quantum acceleration — once niche research, now seen as a potential leap for AI optimization, quantum ML, and beyond. ᐧ Silicon photonics & new materials → Ayar Labs and others push past electronic limits using light-speed interconnects. ᐧ Advanced packaging → Intel, TSMC, and Samsung race to stack and stitch chips together to feed insatiable AI workloads. AI isn’t just pushing hardware, it’s forcing us to open the vault and reimagine what a computer even is. This is the biggest hardware shift in decades. Are you ready to build for it? #AIHardware #Neuromorphic #JensenHuang #FutureOfComputing #EngineeringInnovation #NextGenChips

The WEF 2025 top 10 Emerging Technologies are not just scientific milestones. They represent choices that will either accelerate a sustainable and equitable future or widen the gaps we are already struggling to close. 1. Structural Battery Composites Vehicles and aircraft that store energy in their body panels could reduce emissions. Yet carbon fiber is energy heavy and recycling is limited. Without a closed loop strategy this may solve one problem while creating another. 2. Osmotic Power Systems Saltwater gradients can generate clean and steady power. This could bring resilience to coastal communities. The challenge is cost and ensuring installations do not harm fragile marine ecosystems. 3. Advanced Nuclear Technologies Small modular reactors and new cooling systems promise low carbon power. Yet the social license for nuclear is fragile. Communities need transparency, trust building, and waste strategies or progress will stall. 4. Engineered Living Therapeutics Microbes that produce medicines inside the body could transform care. Safety, patient consent, and equitable access must guide development or this may deepen inequalities. 5. GLP 1s for Neurodegenerative Disease Repurposed diabetes drugs may slow Alzheimer’s and Parkinson’s. But if affordability is not solved this will widen divides in access to years of quality life. 6. Autonomous Biochemical Sensing Continuous monitoring of health and environment could create early warnings for food safety and pollution. But constant data capture raises risks for privacy and governance. 7. Green Nitrogen Fixation Reimagining ammonia with renewable energy could eliminate one of the most carbon intensive processes in agriculture. Yet lithium dependency and toxicity concerns must be addressed to ensure true sustainability. 8. Nanozymes Synthetic enzymes can support medicine, water purification, and food safety at lower cost. The opportunity is vast, but ethical guidelines and biocompatibility will determine trust. 9. Collaborative Sensing Connected networks of sensors could create responsive cities and factories. The risk is surveillance and misuse of data. Without trust, adoption will falter. 10. Generative Watermarking Invisible markers to authenticate digital content may help combat misinformation. Crucial for protecting democracy, but technology alone cannot solve the social dynamics of disinformation. ⚡ Technology is not inherently good or bad? Its value lies in how we design the systems, supply chains, and governance that shape its impact. 👉 Which of these ten will most shape our world by 2030, and what blind spots do you see? Please 👍🏽 like, comment or reshare ♻️ to spread the message

The Evolution of AI: From Generative to Beyond Physical Intelligence AI isn’t standing still—it’s accelerating through distinct phases that are reshaping industries and redefining what’s possible: 🔵 Generative AI From text and image generation to multimodal creativity, tools like ChatGPT, Gemini, and Runway Gen-3 are enabling real-time content creation and synthetic data generation. Next 5–10 years: Expect fully interactive, editable media and enterprise-grade governance for AI-driven creativity. 🟢 Agentic AI Autonomous agents like Cognition Labs’ Devin and frameworks such as Microsoft AutoGen are moving beyond chat—they plan, reason, and execute tasks across ecosystems. Future trend: Multi-agent collaboration, perceptual assistants (think Google’s Project Astra), and dynamic adaptability for complex workflows. 🟠 Physical AI Robotics powered by AI is leaving the lab. Boston Dynamics Atlas, Figure AI, and Agility Robotics Digit are piloting humanoids in factories and warehouses, while Waymo and Zipline scale autonomous mobility and logistics. What’s next: Scaled fleets, general-purpose manipulators, and integrated AI-robotics stacks with digital twins. 🟣 Beyond Physical AI The frontier: AI fused with biology and quantum computing. - Neuralink’s brain-computer interfaces - AlphaFold 3 accelerating drug discovery - Organoid Intelligence exploring bio-hybrid computing - IBM Quantum System Two pushing toward quantum utility Future vision: Assistive neurotech becomes augmentation, bio-hybrid processors emerge, and quantum systems deliver verified advantage for chemistry and optimization. Why it matters: Each layer builds on the last—moving from creativity to autonomy, embodiment, and ultimately integration with the fundamental fabric of life and computation. 👉 Which layer do you think will have the biggest impact on your industry in the next decade? Let’s discuss. #AI #GenerativeAI #AgenticAI #Robotics #QuantumComputing #Innovation

Emerging Technologies of 2025: #Innovation and Societal Impact . The World Economic Forum report spotlights breakthrough innovations poised to transition from scientific discovery to real-world application, aiming to catalyze dialogue and shape technology agendas. It details ten specific technologies, ranging from structural battery composites and osmotic power systems to #AI watermarking and engineered living therapeutics, explaining their novelty, development progress, and transformative potential across various sectors like #energy , #healthcare , and urban systems. •Key Themes of Emerging Technologies: The 2025 technologies reveal exciting patterns, often representing a convergence of fields: ◦Combining Energy Systems with Advanced Materials: This includes innovations like structural battery composites, which integrate energy storage within load-bearing structures, improving functionality and efficiency in transport. ◦Using Biological Approaches to Improve Human Health: Examples are engineered living therapeutics (genetically engineered microbes producing medicines in the body) and GLP-1s for neurodegenerative disease (repurposing drugs for Alzheimer's and Parkinson's). ◦Reimagining Industrial Processes for Sustainability: This involves technologies such as green nitrogen fixation for low-carbon ammonia production and nanozymes (laboratory-produced nanomaterials with enzyme-like catalytic properties). ◦Creating New Foundations for Trust in Connected Systems: This includes collaborative sensing (distributed sensors connected to AI systems for context-aware decisions) and generative watermarking (invisible markers in AI-generated content to verify authenticity) Each technology's overview includes its strategic outlook, ecosystem readiness, and the challenges to its widespread adoption, emphasizing their capacity to address complex global challenges and foster resilient, sustainable societies.

The Next Computing Revolution: Thermodynamic Chips That Embrace Chaos Introduction: A Radical Rethink of Computation In a discreet office near Boston, Guillaume Verdon unveils a silicon chip that could redefine the future of computation. Unlike classical or even quantum computers, this chip is built on a bold, emerging concept: thermodynamic computing. Rather than suppressing randomness as a flaw, this paradigm embraces thermal fluctuations as a computational asset—potentially unlocking entirely new approaches to AI, optimization, and physics-based problem-solving. Key Details: How Thermodynamic Computing Differs • Beyond Binary: • Traditional computing relies on deterministic 1s and 0s; quantum computing leverages superposition and entanglement. • Thermodynamic computing uses stochastic (random) energy fluctuations as the core logic mechanism, simulating how real-world physical systems evolve over time. • Contrasting with Quantum: • Quantum chips require extreme cooling to suppress noise. • Thermodynamic chips embrace thermal noise, modeling it as a source of usable energy and information, rather than something to be eliminated. • The Physical Chip: • Verdon’s chip contains novel components unlike standard transistors or qubits, and sits on a circuit board no bigger than a burger box. • It was recently fabricated and could soon demonstrate new modes of computational learning and inference. • The Visionary Behind It: • Guillaume Verdon is already well-known in quantum computing circles (notably at Alphabet’s SandboxAQ). • His thermodynamic chip is the foundation for what he claims could be a new era in machine intelligence, particularly in mimicking natural, physics-based decision-making processes. Why It Matters: A New Model for AI and Optimization Thermodynamic computing could dramatically improve how machines tackle probabilistic reasoning, inference under uncertainty, and nonlinear optimization—tasks that stump conventional and even quantum systems. This architecture could lead to machines that reason more like living systems, blurring the line between computation and physical reality. Conclusion While still early-stage, thermodynamic computing could become a third path beyond classical and quantum paradigms—redefining how we solve complex problems, simulate nature, and perhaps even understand consciousness itself. If Verdon’s chip delivers on its promise, it won’t just be a new processor—it’ll be a new philosophy of computing. Keith King https://lnkd.in/gHPvUttw