UNSW Sydney nano-tech startup Diraq has shown its quantum chips aren’t just lab-perfect prototypes – they also hold up in real-world production, maintaining the 99% accuracy needed to make quantum computers viable. Diraq, a pioneer of silicon-based quantum computing, achieved this feat by teaming up with European nanoelectronics institute InteruniversityContinue Reading
UNSW engineers have made a significant advance in quantum computing: they created ‘quantum entangled states’ – where two separate particles become so deeply linked they no longer behave independently – using the spins of two atomic nuclei. Such states of entanglement are the key resource that gives quantum computers theirContinue Reading
Dr. Dong-Soo Han’s research team at the Korea Institute of Science and Technology (KIST) Semiconductor Technology Research Center, in collaboration with the research teams of Prof. Jung-Il Hong at DGIST and Prof. Kyung-Hwan Kim at Yonsei University, has developed a device principle that can utilize “spin loss,” which was previouslyContinue Reading
At Amazon, our team builds Rufus, a generative AI-powered shopping assistant that serves millions of customers at immense scale. However, deploying Rufus at scale introduces significant challenges that must be carefully navigated. Rufus is powered by a custom-built large language model (LLM). As the model’s complexity increased, we prioritized developingContinue Reading
Sandia National Laboratories has joined a new partnership aimed at helping the United States regain its leadership in semiconductor manufacturing. While the U.S. was considered a powerhouse in chip production in the 1990s, fabricating more than 35% of the world’s semiconductors, that share has since dropped to 12%. Today, theContinue Reading
One of the current hot research topics is the combination of two of the most recent technological breakthroughs: machine learning and quantum computing. An experimental study shows that already small-scale quantum computers can boost the performance of machine learning algorithms. This was demonstrated on a photonic quantum processor by anContinue Reading
The exponential miniaturization of electronic chips over time, described by Moore’s law, has played a key role in our digital age. However, the operating power of small electronic devices is significantly limited by the lack of advanced cooling technologies available. Aiming to tackle this problem, a study published in CellContinue Reading
Plasma — the electrically charged fourth state of matter — is at the heart of many important industrial processes, including those used to make computer chips and coat materials. Simulating those plasmas can be challenging, however, because millions of math operations must be performed for thousands of points in theContinue Reading
Large language models (LLMs) have revolutionized the way we interact with technology, but their widespread adoption has been blocked by high inference latency, limited throughput, and high costs associated with text generation. These inefficiencies are particularly pronounced during high-demand events like Amazon Prime Day, where systems like Rufus—the Amazon AI-poweredContinue Reading
The Qwen 2.5 multilingual large language models (LLMs) are a collection of pre-trained and instruction tuned generative models in 0.5B, 1.5B, 3B, 7B, 14B, 32B, and 72B (text in/text out and code out). The Qwen 2.5 fine tuned text-only models are optimized for multilingual dialogue use cases and outperform both previousContinue Reading
