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In this profound and thought-provoking clip from the Quantum Convergence documentary, tech pioneer and physicist Federico Faggin delves into his transformative experience of consciousness — the moment he felt himself as the universe observing itself. Faggin, best known for his work in developing the first microprocessor, explores the fundamental nature of consciousness, its relationship with matter, and the deeper purpose of the universe.

🌐 About Quantum Convergence:
Quantum Convergence is a groundbreaking documentary that explores the intersection of science, technology, and consciousness. Featuring leading thinkers and visionaries, the film examines how our understanding of reality is evolving in the age of AI and quantum physics.

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👍 Like, share, and comment if you believe in the power of consciousness.

#QuantumConvergence #Consciousness #FedericoFaggin #AI #Philosophy #Science #QuantumPhysics.

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A joint research team from Seoul National University and Harvard University has developed a next-generation swarm robot system inspired by nature—capable of movement, exploration, transport, and cooperation, all without the need for precise sensors or centralized control.

The study was led by Professor Ho-Young Kim, Dr. Kyungmin Son, and master’s student Kwanwoo Kim at SNU’s Department of Mechanical Engineering, and Professor L. Mahadevan and Dr. Kimberly Bowal at Harvard.

Their approach connects simple, active particles into chain-like structures that can carry out complex tasks without any advanced programming or artificial intelligence. The research is published in Science Advances.

Infrared optoelectronic functional materials are essential for applications in lasers, photodetectors, and infrared imaging, forming the technological backbone of modern optoelectronics. Traditionally, the development of new infrared materials has relied heavily on trial-and-error experimental methods. However, these approaches can be inefficient within the extensive chemical landscape, as only a limited number of compounds can achieve a balance of several critical properties simultaneously.

To tackle this challenge, researchers from the Xinjiang Technical Institute of Physics and Chemistry of the Chinese Academy of Sciences have made significant strides in the (ML)-assisted discovery of infrared functional materials (IRFMs). The research team has developed a cohesive framework that integrates interpretable ML techniques to facilitate the targeted synthesis of these materials.

The paper is published in the journal Advanced Science.

China’s Origin Quantum has launched its fourth-generation quantum control system, a move signaling the country’s increasing push to industrialize and scale quantum computing capabilities.

The new system, dubbed Origin Tianji 4.0, supports over 500 qubits and serves as the central control for superconducting quantum computers, according to The Global Times, a media outlet under the Chinese Communist Party (CCP). The system, unveiled this week in Hefei, is positioned as a critical enabler for mass-producing quantum computers with more than 100 qubits.

The control system is considered the “neural center” of a quantum computer. It generates, acquires and controls the precise signals that manage quantum chips, which are the computational heart of a quantum system. With the Tianji 4.0 upgrade, Origin Quantum claims major improvements in integration, automation and scalability compared to its previous version, which powered the country’s third-generation superconducting quantum computer, Origin Wukong.

Please see my latest Security & Tech Insights newsletter. Thanks and have a great weekend!

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Dear Friends & Colleagues, please refer to the latest issue of the Security & Tech Insights newsletter. In this issue, several articles highlight emerging tech trends for 2025. Some of these topics were also selected by Forrester’s research on emerging technologies in 2025, which highlights tech that will help drive AI-led innovation while enabling long-term resilience. Thanks for reading and stay safe! Chuck Brooks.

#artificialintelligence #quantum #robotics #emergingtech #tech #trends #space #security | on LinkedIn.

In an experiment reminiscent of the Transformers movie franchise, engineers at Princeton University have created a type of material that can expand, assume new shapes, move and follow electromagnetic commands like a remotely controlled robot even though it lacks any motor or internal gears.

“You can transform between a material and a robot, and it is controllable with an external magnetic field,” said researcher Glaucio Paulino, the Margareta Engman Augustine Professor of Engineering at Princeton.

In an article published April 23 in the journal Nature, the researchers describe how they drew inspiration from the folding art of origami to create a structure that blurs the lines between robotics and materials. The invention is a metamaterial, which is a material engineered to feature new and unusual properties that depend on the material’s physical structure rather than its chemical composition. In this case, the researchers built their metamaterial using a combination of simple plastics and custom-made magnetic composites. Using a magnetic field, the researchers changed the metamaterial’s structure, causing it to expand, move and deform in different directions, all remotely without touching the metamaterial.

Introduction One thing newcomers to machine learning (ML) and many experienced practitioners often don’t realize is that ML doesn’t extrapolate. After training an ML model on compounds with µM potency, people frequently ask why none of the molecules they designed were predicted to have nM potency. If you’re new to drug discovery, 1nM = 0.001µM. A lower potency value is usually better. It’s important to remember that a model can only predict values within the range of the training set. If we’ve trained a model on compounds with IC50s between 5 and 100 µM, the model won’t be able to predict an IC50 of 0.1 µM. I’d like to illustrate this with a simple example. As always, all the code that accompanies this post is available on GitHub.

Tesla is preparing to launch an innovative robo-taxi network in Austin next month, supported by a new affordable Model Y and favorable federal regulations for self-driving vehicles ## ## Questions to inspire discussion ## Tesla’s Robo Taxi Network.

🚗 Q: When and where is Tesla launching its robo taxi network? A: Tesla’s robo taxi network is set to launch in Austin, Texas in June, marking a significant milestone for the company’s self-driving technology.

🤖 Q: How will the robo taxi network impact Tesla’s valuation? A: The successful launch could potentially double Tesla’s stock valuation to over **$1 trillion, validating its unique approach to self-driving vehicles. Cost and Production Advantages.

💰 Q: How does Tesla’s self-driving system compare to competitors in terms of cost? A: Tesla’s AI-based self-driving system is significantly cheaper, with a per-mile cost of $0.10 compared to **$0.50-$1.00 for human-driven rides offered by competitors like Whim and Uber.

🏭 Q: What production advantage does Tesla have over competitors? A: Tesla’s mass production capability of 2 million cars per year gives it a significant advantage over competitors like Whim, which operates with a limited fleet of 1,500 cars. Marketing and Revenue Generation.

📈 Q: How will the robo taxi network benefit Tesla’s marketing efforts? A: The network will serve as a unique marketing channel, allowing customers to experience self-driving rides firsthand, making it easier for Tesla to sell its cars and reach scale.