The surge of interest in the overall category of digital twins has led to some confusion, as tends to happen during “hype” cycles. A closer look at the cardiovascular bio-digital twin (one area of focus for my research organization) can help clarify matters. First, the existence of this niche says something. A bio-digital twin does not have to represent an entire person. Just as you can build twins of subsystems such as aircraft wings or landing gears, you can also model physiological systems—something less than an entire human body. Bio-Digital Twin: Getting The Heart Right (forbes.com)

A new processor that uses light, instead of electrons, has the potential to perform its computations up to 100 times more powerfully and efficiently than existing processors inside machine-learning computer systems. That’s according to a new USC and MIT study published in the journal Nature Photonics. Zaijun Chen of USC, Ryan Hamerly of NTT Research, and Dirk Englund are the corresponding authors. Other co-authors who also contributed significantly are Alexander Sludds, Ronald Davis, Ian Christen, Liane Bernstein, and Lamia Ateshian of RLE. The key component of this computing system, VCSEL arrays, is fabricated and provided by Tobias Heuser, Niels Heermeier, James A. Lott, and Stephan Reitzensttein of Technische Universitat Berlin. New Laser-Array Processor Could Vastly Improve AI Computing Efficiency (photonicsonline.com)

Quantum approach: NTT DATA used Quantum Annealing technology with superconducting qubits from D-Wave. NTT Research’s CIM (Coherent Ising Machine) then simulated the technology. The comparison was based on the measurement of computational efficiency, accuracy, and scalability indicators. Quantum News Briefs July 31: OQC and Cogniframe partner to enable users, regardless of their level of expertise, to test drive quantum; Researchers from ORNL use Quantinuum H1-1 quantum computer to identify molecular candidate for development of more efficient solar cells; Why India risks a quantum tech brain drain; Researchers from ORNL use Quantinuum H1-1 quantum computer to identify molecular candidate for development of more efficient solar cells + MORE – Inside Quantum Technology

The impact artificial intelligence will have on society is similar to or greater than that of the discovery of nuclear energy, so robust ethical guidelines need to be put in place. And it’s much easier to access AI than nuclear energy, which makes AI more difficult to control. A lot of thought must go into developing ways to detect AI’s harms and correct them. We don’t currently have many effective measures for this. – Kazuhiro Gomi, NTT Research 16 Current And Potential Ethical Crises In Technology (forbes.com)

The impact artificial intelligence will have on society is similar to or greater than that of the discovery of nuclear energy, so robust ethical guidelines need to be put in place. And it’s much easier to access AI than nuclear energy, which makes AI more difficult to control. A lot of thought must go into developing ways to detect AI’s harms and correct them. We don’t currently have many effective measures for this. 16 Current And Potential Ethical Crises In Technology (forbes.com)

NTT Research’s CIM (Coherent Ising Machine) then simulated the technology. The comparison was based on the measurement of computational efficiency, accuracy and scalability indicators. The same dataset was used as a reference for the concept proof and the comparison. Specifically, the bacteriophage phiX174 genome’s sequencing was synthetically generated, allowing the simulation of different test scenarios and comparison of the reference indicators. First-of-its-kind research project stress tests quantum computing for optimised genome assembly | Manufacturing & Logistics IT Magazine

 NTT Research’s CIM (Coherent Ising Machine) then simulated the technology. The comparison was based on the measurement of computational efficiency, accuracy, and scalability indicators. The same dataset was used as a reference for the concept proof and the comparison. Specifically, the bacteriophage phiX174 genome’s sequencing was synthetically generated, allowing the simulation of different test scenarios and comparison of the reference indicators. NTT DATA Demonstrates Quantum Computing’s Potential in Genome Assembly and Disease Treatment (hpcwire.com)