RSS Feed Source: MIT Technology Review

The manufacturing industry is at a crossroads: Geopolitical instability is fracturing supply chains from the Suez to Shenzhen, impacting the flow of materials. Businesses are battling rising costs and inflation, coupled with a shrinking labor force, with more than half a million unfilled manufacturing jobs in the U.S. alone. And climate change is further intensifying the pressure, with more frequent extreme weather events and tightening environmental regulations forcing companies to rethink how they operate. New solutions are imperative.

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Meanwhile, advanced automation, powered by the convergence of emerging and established technologies, including industrial AI, digital twins, the internet of things (IoT), and advanced robotics, promises greater resilience, flexibility, sustainability, and efficiency for industry. Individual success stories have demonstrated the transformative power of these technologies, providing examples of AI-driven predictive maintenance reducing downtime by up to 50%. Digital twin

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RSS Feed Source: MIT Technology Review

Rumors of the ongoing death of software development — that it’s being slain by AI — are greatly exaggerated. In reality, software development is at a fork in the road: embracing the (currently) far-off notion of fully automated software development or acknowledging the work of a software developer is much more than just writing lines of code.

The decision the industry makes could have significant long-term consequences. Increasing complacency around AI-generated code and a shift to what has been termed “vibe coding” — where code is generated through natural language prompts until the results seem to work — will lead to code that’s more error-strewn, more expensive to run and harder to change in the future. And, if the devaluation of software development skills continues, we may even lack a workforce with the skills and knowledge to fix things down the line. 

This

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RSS Feed Source: MIT Technology Review

Amazon Web Services today announced Ocelot, its first-generation quantum computing chip. While the chip has only rudimentary computing capability, the company says it is a proof-of-principle demonstration—a step on the path to creating a larger machine that can deliver on the industry’s promised killer applications, such as fast and accurate simulations of new battery materials.

“This is a first prototype that demonstrates that this architecture is scalable and hardware-efficient,” says Oskar Painter, the head of quantum hardware at AWS, Amazon’s cloud computing unit. In particular, the company says its approach makes it simpler to perform error correction, a key technical challenge in the development of quantum computing.  

Ocelot consists of nine quantum bits, or qubits, on a chip about a centimeter square, which, like some forms of quantum hardware, must be cryogenically cooled to near absolute zero in order to operate. Five of the

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Microsoft announced today that it has made significant progress in its 20-year quest to make topological quantum bits, or qubits—a special approach to building quantum computers that could make them more stable and easier to scale up. 

Researchers and companies have been working for years to build quantum computers, which could unlock dramatic new abilities to simulate complex materials and discover new ones, among many other possible applications. 

To achieve that potential, though, we must build big enough systems that are stable enough to perform computations. Many of the technologies being explored today, such as the superconducting qubits pursued by Google and IBM, are so delicate that the resulting systems need to have many extra qubits to correct errors. 

Microsoft has long been working on an alternative that could cut down on the overhead by using components that are far more stable. These components,

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