The SAG Deal Sends a Clear Message About AI and Workers
The agreement between Hollywood actors, studios, and streamers isn’t perfect. But it could set the tone for how future labor movements confront changes brought about by artificial intelligence.
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The agreement between Hollywood actors, studios, and streamers isn’t perfect. But it could set the tone for how future labor movements confront changes brought about by artificial intelligence.
From ChatGPT to DALL-E, deep learning artificial intelligence (AI) algorithms are being applied to an ever-growing range of fields. A new study from University of Toronto Engineering researchers, published in Nature Communications, suggests that one of the fundamental assumptions of deep learning models—that they require enormous amounts of training data—may not be as solid as …
Read more “New study finds bigger datasets might not always be better for AI models”
Give your favorite adventurer a gift that lets everybody know their happy place is the Great Outdoors.
Engineers developed a technique to quickly identify a range of potential failures in a system before they are deployed in the real world.
The short story presents a fresh take on the idea of an AI uprising.
When engineers have the right mix of time, support, information and tools, they’re capable of doing more than a team 10 times the size.Read More
Deep neural networks (DNNs) have proved to be highly promising tools for analyzing large amounts of data, which could speed up research in various scientific fields. For instance, over the past few years, some computer scientists have trained models based on these networks to analyze chemical data and identify promising chemicals for various applications.
For individuals and organizations interested in building their own GPTs, here’s a brief overview on getting started.Read More
Top senate officials are planning to save the Section 702 surveillance program by attaching it to a crucial piece of legislation. Critics worry a chance to pass privacy reforms will be missed.
Large language models (LLMs) can utilize ‘encoded reasoning,’ a form of steganography, to subtly embed reasoning steps within their responses, enhancing performance but potentially reducing transparency and complicating AI monitoring.Read More