Our universe has been developing for about 14 billion years, but human-level intelligence, at least on Earth, has emerged in a remarkably short period of time, measured in tens or hundreds of thousands of years. What then is the future of intelligence? With the exponential growth of computing, will non-biological intelligence dominate?
Presenting its findings as “Unlocking the future of computing” Microsoft is edging ever closer to photon computing technology with the Analog Iterative Machine (AIM). Right now, the light-based machine is being licensed for use in financial institutions, to help navigate the endlessly complex data flowing through them.
According to the Microsoft Research Blog, “Microsoft researchers have been developing a new kind of analog optical computer that uses photons and electrons to process continuous value data, unlike today’s digital computers that use transistors to crunch through binary data” (via Hardware Info).
The product itself is an interesting one, and seems built to hit a sweet price/performance ratio for anyone that plans on using a discrete GPU solution. Of course, the absence of an integrated GPU does limit the users’ flexibility — I can’t count the number of times I used an integrated GPU to try and pinpoint issues with my systems (and graphics cards). But the fact remains that more consumer choice is best: users can make their own decision on whether that’s worth the extra $10 or not.
Most of this information comes courtesy of Harukaze (via Twitter), as well as a benchmark on PugetBench, where the Ryzen 5 7500F was paired with an X670E motherboard and 32 GB of DDR5-4800 memory.
A new online platform to explore computationally calculated chemical reaction pathways has been released, allowing for in-depth understanding and design of chemical reactions.
Advances in computational chemistry have lead to the discovery of new reaction pathways for the synthesis of high-value compounds. Computational chemistry generates much data, and the process of organizing and visualizing this data is vital to be able to utilize it for future research.
A team of researchers from Hokkaido University, led by Professor Keisuke Takahashi at the Faculty of Chemistry and Professor Satoshi Maeda at the Institute for Chemical Reaction Design and Discovery (WPI-ICReDD), have developed a centralized, interactive, and user-friendly platform, Searching Chemical Action and Network (SCAN), to explore reaction pathways generated by computational chemistry. Their research was published in the journal Digital Discovery.
Whether it’s baking a cake, constructing a building, or creating a quantum device, the caliber of the finished product is greatly influenced by the components or fundamental materials used. In their pursuit to enhance the performance of superconducting qubits, which form the bedrock of quantum computers, scientists have been probing different foundational materials aiming to extend the coherent lifetimes of these qubits.
Coherence time serves as a metric to determine the duration a qubit can preserve quantum data, making it a key performance indicator. A recent revelation by researchers showed that the use of tantalum in superconducting qubits enhances their functionality. However, the underlying reasons remained unknown – until now.
Scientists from the Center for Functional Nanomaterials (CFN), the National Synchrotron Light Source II (NSLS-II), the Co-design Center for Quantum Advantage (C2QA), and Princeton University investigated the fundamental reasons that these qubits perform better by decoding the chemical profile of tantalum.
The concept of a computational consciousness and the potential impact it may have on humanity is a topic of ongoing debate and speculation. While Artificial Intelligence (AI) has made significant advancements in recent years, we have not yet achieved a true computational consciousness that can replicate the complexities of the human mind.
It is true that AI technologies are becoming more sophisticated and capable of performing tasks that were previously exclusive to human intelligence. However, there are fundamental differences between Artificial Intelligence and human consciousness. Human consciousness is not solely based on computation; it encompasses emotions, subjective experiences, self-awareness, and other aspects that are not yet fully understood or replicated in machines.
The arrival of advanced AI systems could certainly have transformative effects on society and our understanding of humanity. It may reshape various aspects of our lives, from how we work and communicate to how we approach healthcare and scientific discoveries. AI can enhance our capabilities and provide valuable tools for solving complex problems.
However, it is important to consider the ethical implications and potential risks associated with the development of AI. Ensuring that AI systems are developed and deployed responsibly, with a focus on fairness, transparency, and accountability, is crucial.
However, traditional atomic clocks are bulky, exhibit frequent instabilities due to various environmental factors, and require calibration. Due to these limitations, technological advancements and the miniaturization of atomic clocks are ongoing to make them more accessible and practical for various applications.
A system using photonics-based synthetic dimensions could be used to help explain complex natural phenomena.
Researchers at the University of Rochester have developed a chip-scale optical quantum simulation system using controlled photon.
A photon is a particle of light. It is the basic unit of light and other electromagnetic radiation, and is responsible for the electromagnetic force, one of the four fundamental forces of nature. Photons have no mass, but they do have energy and momentum. They travel at the speed of light in a vacuum, and can have different wavelengths, which correspond to different colors of light. Photons can also have different energies, which correspond to different frequencies of light.
Computers are built around logic: performing mathematical operations using circuits. Logic is built around things such as Adders—not the snake; the basic circuit that adds together two numbers. This is as true of today’s microprocessors as all those going back to the very beginning of computing history. You could go back to an abacus and find that, at some fundamental level, it does the same thing as your shiny gaming PC. It’s just much, much less capable.
Nowadays, processors can do a lot of mathematical calculations using any number of complex circuits in a single clock. And a lot more than just add two numbers together, too. But to get to your shiny new gaming CPU, there has been a process of iterating on the classical computers that came before, going back centuries.
