Popular devices

Latest News

Latest Reviews

iPhone XS Max review
Jan 16, 2020
Moto G7 Power review
Jan 16, 2020

Apple engages in talks with leading News outlets for AI advancements: Report

Dec 25, 2023 News Source livemint 9 hits

Apple engages in talks with leading News outlets for AI advancements: Report

In the past few weeks, Apple has initiated talks with prominent news and publishing entities, aiming to secure approval for utilizing their content in the company's advancement of generative artificial intelligence systems, as reported by the New York Times on Friday. The has proposed multiyear agreements, valued at a minimum of $50 million, to obtain licenses for the archives of news articles, as indicated by sources familiar with the negotiations, as reported in the article. Apple has reached out to news entities such as Condé Nast, the publisher of Vogue and the New Yorker, along with NBC News and IAC, the owner of People, the Daily Beast, and Better Homes and Gardens, as reported by the New York Times. According to the report, certain publishers approached by Apple showed a tepid response to the outreach. Meanwhile, Apple has also reportedly developed an internal service akin to ChatGPT, intended to assist employees in testing new features, summarizing text, and answering questions based on accumulated knowledge. In July, suggested that Apple was in the process of creating its own AI model, with the central focus on a new framework named Ajax. The framework has the potential to offer various capabilities, with a ChatGPT-like application, unofficially dubbed "Apple GPT," being just one of the many possibilities. Recent indications from an Apple research paper suggest that Large Language Models (LLMs) may run on Apple devices, including iPhones and iPads. This research paper, initially discovered by VentureBeat, is titled "LLM in a flash: Efficient Large Language Model Inference with Limited Memory." It addresses a critical issue related to on-device deployment of Large Language Models (LLMs), particularly on devices with constrained DRAM capacity. Keivan Alizadeh, a Machine Learning Engineer at and the primary author of the paper, explained, "Our approach entails developing an inference cost model that aligns with the characteristics of flash memory, directing us to enhance optimization in two crucial aspects: minimizing the amount of data transferred from flash and reading data in larger, more cohesive segments." (With inputs from Reuters) Livemint tops charts as the fastest growing news website in the world to know more. Unlock a world of Benefits! From insightful newsletters to real-time stock tracking, breaking news and a personalized newsfeed – it's all here, just a click away!


Rate this article:

Share this article:

Leave a comment:

Related articles