In addition to his role at Meta, LeCun is Silver Professor at New York University (NYU) affiliated with the Courant Institute and the Center for Data Science, where he's a founding director. Considered one of the godfathers of deep learning, LeCun has worked since the mid-1980s to advance deep learning methods, particularly the convolutional neural network model, which is the basis of many products and services deployed by numerous companies including Meta, Google, Microsoft, and many others for image and video understanding and speech recognition. The character recognition technology he developed at Bell Labs is used by several banks around the world to read checks while his image compression technology, called DjVu, is used by hundreds of websites and publishers and millions of people to access scanned documents online. In 2018, LeCun was awarded the ACM A.M. Turing Award along with Geffrey Hinton and Yoshua Bengio for "conceptual and engineering breakthroughs that have made deep neural networks a critical component of computing." More recently, his contributions to the advancement of AI were recognized with the Princess of Asturias Award for Technical & Scientific Research (bestowed by the King of Spain).

The Artificial Intelligence (AI) is the capability of a machine to perform tasks which normally require human intellect such as visual perception, …

WBUR's On Point brings you Smarter health, a four-part series exploring how artificial intelligence and machine learning may revolutionize the …

A recent Washington Post article about artificial intelligence (AI) briefly caught the publics' attention. A former engineer working for Google's Responsible AI organization went public with his belief that the company's chatbot was sentient. It should be stated bluntly: this AI is not a conscious entity. It is a large language model trained indiscriminately from Internet text that uses statistical patterns to predict the most probable sequence of words. While the tone of the Washington Post piece conjured all the usual Hollywood tropes related to humanity's fear of sentient technology (e.g., storylines from Ex Machina, Terminator, or 2001: A Space Odyssey), it also inadvertently highlighted an uncomfortable truth: As AI capabilities continue to improve, they will become increasingly effective tools for manipulating and fooling humans.

Bowers & Wilkins might be a name many associate with high-end home audio gear, but the company has been steadily chugging along with headphones too. Its latest model, the Px7 S2 ($399), is a completely overhauled version of the PX that debuted in 2019. At every turn, this new model is a worthy upgrade over its predecessor, and you won't have to pay more for the improvements either. For the Px7 S2, Bowers & Wilkins borrowed elements of both the original PX and the Px7 that contribute to the refined look. The company also slimmed down the overall shape and opted for more cushion in the earpads – all while trimming the overall weight.

In August 2020, I wrote about the stunning storytelling prowess of another LLM, GPT3 (bit.ly/3RbHfbB). The Generative Pre-trained Transformer Version 3, I wrote, was being heralded as the first step towards the holy grail of AGI (Artificial General Intelligence), where a machine has the capacity to understand or learn any intellectual task that a human being can. GPT has been trained on a massive body of text, mined for statistical regularities or parameters or connections between different nodes in its neural network. The scale is gargantuan, with 175 billion parameters; all of Wikipedia comprises just 0.6% of its training data! GPT-3 was developed by OpenAI too, and with DALL-E, it took this to another level.

On 6 July, the organisers of the AI Song Contest revealed the winner of this year's competition. What makes this song stand out is that it uses Thai tuning. Most AI models are rooted in Western definitions of melody, harmony and tuning. This means that models can only output notes on the 12-note Western scale, making it very difficult to apply machine learning to music from many musical cultures around the world. In his submission, Lamtharn aimed to demonstrate "how advancements in realtime audio machine learning enable unprecedented audio synthesis with respect to a culture's native tuning".

The Monitor is a weekly column devoted to everything happening in the WIRED world of culture, from movies to memes, TV to Twitter. When it premiered six years ago, Westworld epitomized prestige sci-fi at its peak. An expensive HBO series with an old-school Michael Crichton pedigree, it featured a stellar cast and a mind-trippy premise: What if all the sentient robots, or "hosts," at a Western theme park decided they'd had enough of being kicked and dragged around? Subsequent seasons revealed the influence of artificial intelligence and reached far beyond the borders of the Westworld attraction, a global mess of money, corruption, and consciousness-tampering that was nightmare fuel for viewers watching at home while scrolling through Twitter. It was a hit--even if a modest one.

Bengaluru: Researchers at Indian Institute of Technology (IIT)-Madras have developed a machine learning (ML) algorithm to identify personalised …

Within Machine Learning this is known as Model-performance Measures, in addition to measuring efficiency, it can also be used to compare the …