RSS Feed Source: MIT Technology Review

Tech companies have been funneling billions of dollars into quantum computers for years. The hope is that they’ll be a game changer for fields as diverse as finance, drug discovery, and logistics.

Those expectations have been especially high in physics and chemistry, where the weird effects of quantum mechanics come into play. In theory, this is where quantum computers could have a huge advantage over conventional machines.

But while the field struggles with the realities of tricky quantum hardware, another challenger is making headway in some of these most promising use cases. AI is now being applied to fundamental physics, chemistry, and materials science in a way that suggests quantum computing’s purported home turf might not be so safe after all.

The scale and complexity of quantum systems that can be simulated using AI is advancing rapidly, says Giuseppe Carleo, a professor of computational

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RSS Feed Source: MIT Technology Review

It turns out that you don’t need to be a scientist to encode data in DNA. Researchers have been working on DNA-based data storage for decades, but a new template-based method inspired by our cells’ chemical processes is easy enough for even nonscientists to practice. The technique could pave the way for an unusual but ultra-stable way to store information. 

The idea of storing data in DNA was first proposed in the 1950s by the physicist Richard Feynman. Genetic material has exceptional storage density and durability; a single gram of DNA can store a trillion gigabytes of data and retain the information for thousands of years. Decades later, a team led by George Church at Harvard University put the idea into practice, encoding a 53,400-word book.

This early approach relied on DNA synthesis—stringing genetic sequences together piece by piece, like beads on a

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Lab scientists spend much of their time doing laborious and repetitive tasks, be it pipetting liquid samples or running the same analyses over and over again. But what if they could simply tell a robot to do the experiments, analyze the data, and generate a report? 

Enter Organa, a benchtop robotic system devised by researchers at the University of Toronto that can perform chemistry experiments. In a paper posted on the arXiv preprint server, the team reported that the system could automate some chemistry lab tasks using a combination of computer vision and a large language model (LLM) that translates scientists’ verbal cues into an experimental pipeline. 

Imagine having a robot that can collaborate with a human scientist on a chemistry experiment, says Alán Aspuru-Guzik, a chemist, computer scientist, and materials scientist at the University of Toronto, who is one of the project’s leaders.

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In an age where customer experience can make or break a business, Cathay Pacific is embracing cloud transformation to enhance service delivery and revolutionize operations from the inside out. It’s not just technology companies that are facing pressure to deliver better customer service, do more with data, and improve agility. An almost 80-year-old airline, Cathay Pacific embarked on its digital transformation journey in 2014, spurred by a critical IT disruption that became the catalyst for revamping their technology.

By embracing the cloud, the airline has not only streamlined operations but also paved the way for innovative solutions like DevSecOps and AI integration. This shift has enabled Cathay to deliver faster, more reliable services to both passengers and staff, while maintaining a robust security framework in an increasingly digital world. 

According to Rajeev Nair, general manager of IT infrastructure and security at Cathay Pacific, becoming

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