Mehrzad Mahdavi, PhD

Quantum Revolution: Texas Moves Ahead! Exciting news in the world of quantum computing. Texas has passed the Texas Quantum Initiative, setting the stage for the state to become a powerhouse in quantum technology. Backed by IonQ, this initiative is advancing quantum computing, networking, and sensing…impacting everything from national security to materials to physics to pharmaceuticals. IonQ's shares jumped on this development. And there's more. D-Wave Quantum Inc., another quantum computing enterprise, has successfully raised $400 million, strengthening its position as a leader in quantum computing. With plans for strategic acquisitions, D-Wave is poised to expand its dominance in the commercial quantum space. The future seems incredibly bright. McKinsey predicts a quantum boom, with the industry potentially generating up to $97 billion by 2035. Quantum computing, communication, and sensing are set to transform industries, and the synergy with AI is unlocking mind-blowing possibilities. We are witnessing the transformation of industries with cutting-edge technology. Quantum computing is not just the future; it's happening now. Quantum-driven advancements are reshaping our world. #quantum #computing #ionq #dwave #Texas

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Quantum Could Reshape Industry, Says BofA—But No Coverage For Now https://lnkd.in/g-Q9nSa2 Insider Brief Bank of America analysts view quantum computing as one of the most transformative technologies of the next decade, capable of reshaping finance, cybersecurity, healthcare, and logistics. The firm argues that quantum systems could unlock economic value by processing complex data at scale, but notes the technology is not yet ready for commercialization and remains technically fragile. Despite the bullish outlook, Bank of America has not initiated coverage on any quantum computing stocks, signaling cautious optimism about the timeline for practical adoption. Although stopping short of official recommendations, Bank of America analysts say quantum computing could be among the most transformative technologies of the coming decade, with wide-reaching consequences for finance, cybersecurity, logistics and healthcare. In its latest report on next-generation computing, the Bank of America Institute positions quantum alongside high-performance, neuromorphic, spatial and edge computing as critical to managing the explosion of global data and the growing demands of artificial intelligence. But quantum stands apart, the analysts argue, for its potential to solve problems classical computers may never crack. That potential could tip global power dynamics, said BofA analyst Haim Israel, as reported in the Investor’s Business Daily. “Whoever wins the quantum race will gain an unprecedented geopolitical, technological and economic advantage,” said Israel. From Physics Oddity to Strategic Asset The report details how quantum computing leverages principles of quantum mechanics — specifically, superposition, entanglement, and quantum bits (qubits) — to process information in ways that defy traditional computing logic. Unlike classical bits, which store information as either 0 or 1, qubits can exist in multiple probabilistic states. When entangled, changes to one qubit correlates with other qubits, regardless of distance, enabling a form of parallel computation. The report notes that these principles allow quantum computers to process vast combinations of variables, for all practical purposes, simultaneously. Problems that might take a supercomputer billions of years to solve could potentially be resolved in minutes with a sufficiently large quantum machine. However, the technology is not suited to everyday computing tasks. Instead, it is expected to excel in specific domains where data complexity and scale exceed the limits of conventional hardware, such as simulating molecules in chemistry, optimizing global supply chains, or decoding patterns in massive financial datasets. #quantum #computing #AI #models

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The Texas Quantum Economy Conference (TQEC) was an insightful experience into the business of quantum computing, communications and security. No longer a futuristic technology, the ramifications are global economic and technology leadership from Texas. The TQEC brought together industry, government (state and local), academia and community leaders, to showcase industry advances, research and government participation. Thanks to Rashmi Varma for bringing a quantum technology Center of Excellence to this region via the annual TQEC and her leadership in the Tech Titans Quantum Technology Forum. #tqec #techtitans #texas #texasquantuminitiative #quantumtechnologyforum

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Analysts boost outlook for IonQ, Rigetti, and D-Wave as quantum computing demand grows, with major industry expansion expected by 2040. https://lnkd.in/gDdKzSey

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Harvard Scientists Achieve Breakthrough in Magic State for Fault-Tolerant Quantum Computing A major leap in quantum computing was made by Harvard researchers who experimentally realized the magic state essential for fault-tolerant quantum computation. - Magic states enable universal fault-tolerant quantum operations beyond standard gates. - Their creation had remained a theoretical challenge until now. - Harvard’s team demonstrated practical preparation and control of these states. - This unlocks new pathways for scalable, reliable quantum processors. - It significantly advances efforts to suppress errors in quantum systems. - The result brings us closer to practical quantum advantage. - Paves the way for more robust quantum algorithms. - Validates theoretical models with experimental proof. - Inspires new research into quantum error correction protocols. - Marks a milestone in harnessing quantum mechanics for computing power. Read more here: https://lnkd.in/d9fqNxHR #QuantumComputing #HarvardResearch #FaultTolerance #MagicState #QuantumErrorCorrection #Innovation #QuantumTech #Research #khiko #khikapital This post was generated by Linda, Sergio’s personal AI Agent

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**Shengjia Zhao: A Strategic Move for Meta's AI Future** The appointment of Shengjia Zhao as chief scientist of Meta's AI superintelligence unit reflects the growing importance of advanced AI systems in shaping the future of technology. At ElevenX Capital, we believe that attracting top talent like Zhao can create significant opportunities for innovation and investment in AI. How can other companies leverage strategic hires to accelerate their growth in the AI sector? #investing #innovation #venturecapital #entrepreneurship

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Decentralized Science (DeSci) is emerging as one of the strongest real-world use cases for blockchain, and crypto treasuries are at the center of this transformation. The traditional scientific ecosystem - reliant on grant cycles, slow funding approvals, opaque peer review, and centralized institutions - is being reimagined using open, programmable financial infrastructure. Here’s how crypto-powered treasury models are enabling the shift: Scientific discovery often waits months, or years, for grant approvals. DeSci platforms like VitaDAO, ValleyDAO, PsyDAO, and others are instead using on-chain treasuries stored in crypto to fund research in days, not months. These treasuries pool capital globally, record funds transparently, distribute grants instantly via smart contracts and allow community governance over which research gets funded. This enables rapid, democratized funding for longevity, health, biotech, climate science, and more. DeSci introduces the concept of IP-NFTs, where research rights, data, patents, and discoveries are tokenized. This offers massive advantages: researchers can raise funding upfront by selling future rights, investors gain exposure to potential scientific breakthroughs, institutions maintain verifiable ownership records on-chain, royalties and licensing are automated via smart contracts. Crypto treasuries manage and distribute revenue from tokenized research, creating entirely new incentive models for science. One of science’s biggest problems is reproducibility and data manipulation. Blockchain solves this through immutable research logs, timestamped experiments, publicly verifiable datasets and tamper-proof storage for lab results, creating a world where scientific truth is cryptographically protected, not left to institutional trust. DeSci is no longer fringe. We’re seeing governments exploring blockchain-backed research grants, universities partnering with DeSci DAOs, biotech companies exploring tokenized patents and investors creating large crypto-native science funds. The merging of crypto + science is becoming a structural trend. Rather than simply observing this shift, we’re helping shape its foundation. At Block Intelligence - Top Blockchain & AI Development Company, our work focuses on building the trusted infrastructure that DeSci ecosystems rely on - from secure treasury management and programmable funding rails to IP tokenization frameworks, auditability layers, and compliance-ready governance systems. As scientific discovery increasingly moves on-chain, we ensure the underlying architecture is robust, transparent, and institution-grade. #DeSci #Blockchain #CryptoTreasury #Tokenization #Web3Innovation #FutureOfScience #DigitalAssets #ResearchFunding #IPNFT #Biotech #LongevityScience #CryptoInfrastructure #OnChainGovernance #BlockIntelligence

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⬛ PART 2: @HSBC / @IBM QUANTUM PAPER – A TECHNICAL REFLECTION (see Part 1 for primer https://lnkd.in/eQi8Shdr)   ⚫ Observation 1: Why Might the Quantum Model Perform Better? A possible reason for the quantum ML model outperforming the classical ones lies in how the Projected Quantum Feature Map (PQFM) transforms data. The PQFM effectively maps classical input vectors from a low‑dimensional Euclidean space into a high‑dimensional entangled Hilbert space, where quantum entanglement can reveal complex correlations between features. Expectation values are then projected back into real‑valued observables for classical learning (I’ve attached diagram for a pictorial representation of this). However, to better understand the quantum vs classical results, I would be keen to see more detail: how many PQFM features were used vs. classical features? The paper mentions 109 qubits, giving q = 3N = 3×109 (three per qubit) = 327 single‑qubit Pauli observables (page 8), but also notes possible two‑Pauli strings (page 7), which would expand the possible feature set dramatically, potentially ~50,000 additional two‑local observables if one measured all 2‑local strings (my calculation). I would welcome the authors revealing more details on the quantum and classical comparisons, perhaps in a supplementary document, to allow other researchers to investigate this, as understanding this distinction is crucial to proving genuine quantum advantage.   ⚫ Observation 2: The “Noise” Puzzle Perhaps more interesting is the finding that adding artificial noise to a classically simulated PQFM doesn’t recover the performance seen on real hardware. If the improvement were just a form of stochastic regularisation, similar to the way a stochastic genetic algorithm can find better local minima, we’d expect the noisy simulation to help. That leaves two possibilities: 1) The quantum hardware noise arising from decoherence, state preparation, and/or PQFM feature calibration introduces some correlations we’re not yet modelling properly; or 2) More provocatively, our current simulations of quantum systems may still be incomplete in this context (i.e., the interaction between real‑device noise and entanglement may not be fully captured by standard unitary‑plus‑noise models). I’m not implying new physics here; rather, this points to practical gaps in how we model real‑device noise and correlations. It would be good to see research performed on simpler (smaller‑qubit) systems with a well‑understood objective. I.e., what is the simplest example we can construct where this “noise puzzle” can still be observed, allowing us to identify the cause, pushing the frontiers of scientific understanding and financial optimisations. Overall, a thoroughly interesting read and great work to the authors, Philip Intallura Ph.D and the HSBC and IBM team. #QuantumMachineLearning #QuantumComputing #MachineLearning #Trading #Finance

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Quantum computing is breaking out of the lab in 2025 Recent breakthroughs signal real-world deployment is near: Exponential speedup achieved: Quantum processors from USC and Johns Hopkins outperformed classical computers unconditionally – a true “holy grail” milestone. Record low error rates: Oxford reached a 0.000015% error rate, drastically reducing error correction overhead. First topological processor: An 8-qubit Majorana-based chip brings fault-tolerant quantum closer. Hardware leaps: IBM surpassed 1,000 qubits, Google launched a 105-qubit chip, and D-Wave solved a simulation in minutes that would take classical supercomputers millions of years. Quantum sensing matures: Real-world applications are emerging in defense, semiconductors, and navigation. Five things banks should do now to be ready: Assess quantum risk exposure in cryptography and begin quantum-safe migration planning. Monitor quantum advances for potential use cases in portfolio optimization and risk modeling. Build quantum literacy among technology, risk, and strategy teams. Engage with quantum startups, cloud providers and research hubs to stay ahead. Evaluate regulatory and data security implications of quantum breakthroughs. Quantum is shifting from theory to transformative reality.

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AI Alert 📢 On 27-Oct-2025, AMD + U.S. Department of Energy (DOE) unveil “Lux” & “Discovery” supercomputers at ORNL (Oak Ridge National Laboratory) Combined $1B public-private investment aligned with the U.S. AI Action Plan to accelerate breakthroughs in energy, materials, medicine, manufacturing, and national security. ➡️ Follow for latest AI alerts 📢 #AMD #ORNL #Supercomputing #AI #HPC #AIForScience #SovereignAI (Video Credit: CNBC)

Over the past few weeks, three publications landed that—when read together—tell a clearer story about where quantum is actually headed next. 1. IBM + Qognitive demonstrate a hardware-aware approach to supervised learning using up to 50 qubits on IBM Heron, explicitly targeting two long-standing QML bottlenecks: data loading cost and trainability. 2. The QCHALLenge consortium (BMW, BASF, SAP, Siemens, and research partners) applies a disciplined “traffic-light” framework to evaluate industrial optimization & ML use cases—scoring scalability, runtime, solution quality, and transferability. 3. The OECD–EPO mapping report shows the ecosystem is growing rapidly, but deployment capacity (skills, commercialization, capital concentration) will determine who translates innovation into economic outcomes. My takeaway: quantum is entering an integration era—hybrid quantum-classical workflows + benchmarking discipline + ecosystem readiness will define the next wave. I wrote a short synthesis on substack (link in comments) - Quantum’s “Integration Era” Has Started: What Three New Papers Reveal About the Path From Hype to Economic Impact We plan to have an invigorating discussion around these topics at the Texas Quantum Economy Conference (Feb 28, 2026). Registration & Details 📍 Location: Richardson, Texas 📅 Date: February 28, 2026 🎟 Register here: 👉 https://lnkd.in/gYvGhr9S #QuantumTechnology #Quantum #QuantumComputing #HybridQuantum #QuantumAlgorithms #benchmarking #QuantumEconomy #QuantumAI

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NVIDIA GTC Washington, D.C. Keynote Summary (Oct 28, 2025): It was great to see this presentation where Jensen Huang, CEO of NVIDIA, presented the next phase of accelerated computing and AI, emphasizing advances in national AI infrastructure, quantum computing, robotics, and reindustrialization. He highlighted NVIDIA’s role in America’s AI leadership, the shift from GPU to CPU-accelerated computing, and the critical importance of CUDA-X libraries for opening new markets and unleashing the power of accelerated computing across industries. The keynote stressed that AI is now essential infrastructure: every company and nation will use it and invest in its development. As AI models get smarter and wider adoption increases, the compute demands grow exponentially. Quantum computing was a major topic, with NVIDIA announcing its QLink Quantum-GPU Interconnect, enabling hybrid quantum/classical supercomputing. The concept of AI Factories was introduced: specialized data centers dedicated to producing valuable AI tokens, as opposed to general-purpose computing of the past. Extreme co-design in hardware/software (e.g., Grace Blackwell NVL72 system) was positioned as key for continuing exponential growth and keeping the “virtuous cycle” of AI advancement alive despite the slowing of Moore’s Law. Major partnerships and deployments were revealed in telecommunications, national science, industry, and robotics. #NVIDIA, #GTC202, #Infrastructure, #QuantumComputg, #AILeadership

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Hallucination by AI can’t be avoided. It can limiting it requires a comprehensive list of expected hallucinations. How does one then audit the truth of untold amounts of content being generated? Less is more.

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Researchers at Harvard have demonstrated a new quantum system that can detect and correct errors below a critical threshold. The breakthrough offers a potential solution to quantum error correction, which has long been considered the single greatest obstacle to building practical, large-scale quantum computers. To overcome the error hurdle, the Harvard-led team built a “fault-tolerant” system using 448 atomic qubits. This new architecture is the first to suppress errors below the critical point, where adding more qubits to the system further reduces errors rather than increasing them, a requirement for scaling up the technology. Error Correction is key as well as the operating environment and other factors in scalability. It is good to see progress being made but I think it will still be a while before quantum computers solve more mainstream problems #quantum #quantumcomputing #digital #innovation #future

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I’m excited to share that I’ve reached the final stage of my PhD journey—my doctoral defense on April 17th. This moment represents more than a degree. It reflects a long, intentional journey grounded in a commitment to ensuring that youth—especially those from marginalized communities—have access to learning technologies that support, not dictate, how they build their career identity. My research explores how design and technology can move beyond simply recommending careers to instead act as a mediating force—helping students reflect, explore, and make sense of who they are and who they want to become. Through this work, I introduce the Career Identity through Design and Reflection (CIDR) framework and the NorthStar© prototype, both aimed at expanding career exposure while preserving student agency. This milestone is deeply personal. It is shaped by my lived experiences, my work in the community through the Jerome Burke Foundation, and my belief that when students are given the space to reflect and imagine, they begin to see possibilities that once felt out of reach. I would be honored for you to join me for my defense. You are invited to join Salena Burke's PhD Defense 🔗 https://lnkd.in/gjUcd_U9 📅 Friday, April 17 ⏰ 2:00 – 3:00 PM CT 🎥 Live Stream: https://lnkd.in/g53an32n Thank you to everyone who has supported me along this journey. This is just the beginning. #PhDJourney #DesignResearch #CareerIdentity #EquityInEducation #NorthStar #CIDR #DreamDareDo

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