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With the development in cognitive science and Large Language Models (LLMs), increasing connections have come to light between these two distinct fields. Building upon these connections, we propose a conjecture suggesting the existence of a duality between LLMs and Tulving’s…
Millions of new job opportunities appear online every day. For candidates, it’s usually the main way to find new career opportunities. For companies, job posting platforms offer a convenient way to find qualified professionals. However, some businesses find a different…
It’s easy to accuse algorithms of stifling creativity, but designers of every stripe should be embracing their multidisciplinary abilities. Source link
Back in July, we released the public preview of the new Databricks Assistant, a context-aware AI assistant available in Databricks Notebooks, SQL editor and the file editor that makes you more productive within Databricks, including: Generate SQL or Python code…
In May 2022, the global supercomputer rankings were shaken up by the launch of Frontier. Now the fastest supercomputer in the world, it can perform more than 1 quintillion (1018) floating-point operations per second. That’s a 1 followed by 18…
In this continuing regular feature, we give all our valued readers a monthly heads-up for the top 10 most viewed articles appearing on insideBIGDATA. We’ve heard from many of our followers that this feature will enable them to catch up…
McAfee has revealed a pioneering AI-powered deepfake audio detection technology, Project Mockingbird, during CES 2024. This proprietary technology aims to defend consumers against the rising menace of cybercriminals employing fabricated, AI-generated audio for scams, cyberbullying, and manipulation of public figures’…
The problem of structured matrix estimation has been studied mostly under strong noise dependence assumptions. This paper considers a general framework of noisy low-rank-plus-sparse matrix recovery, where the noise matrix may come from any joint distribution with arbitrary dependence across…
Researchers from multiple universities have addressed the challenge of designing large-scale DNN chiplet accelerators, focusing on optimizing monetary cost (MC), performance, and energy efficiency. The complexity arises from the interplay of various parameters, including network-on-chip (NoC) communication, core positions, and…