If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
We've now tested every version of Apple's M1 processor, from the first M1 chip in the 13-inch Macbook Pro all the way up to the M1 Ultra in the new Mac Studio, and the chip's ability to scale performance is pretty incredible. The M1 Ultra fuses two M1 Max chips together to get you a processor with 20 CPU cores and 64 GPU cores, along with up to 128GB of RAM, and it's one of the fastest processors we've ever tested. We asked what tests you'd like to see run on the M1 Ultra and assembled quite a list, including Adobe Lightroom and Premiere Pro, Davinci Resolve and Fusion, 3D modeling in Blender, machine learning tests like TensorFlow and Pytorch, and even some gaming. Amazingly, the M1 Ultra really does seem to be around twice as fast as the M1 Max in most applications. Whatever overhead is required to shuffle data around such a large chip, it rarely impacts CPU performance.
Never mind reading generic guides or practicing with friends -- Google is betting that algorithms can get you ready for a job interview. The company has launched an Interview Warmup tool that uses AI to help you prepare for interviews across various roles. The site asks typical questions (such as the classic "tell me a bit about yourself") and analyzes your voiced or typed responses for areas of improvement. You'll know when you overuse certain words, for instance, or if you need to spend more time talking about a given subject. Interview Warmup is aimed at Google Career Certificates users hoping to land work, and most of its role-specific questions reflect this.
Figure 1: Summary of our recommendations for when a practitioner should BC and various imitation learning style methods, and when they should use offline RL approaches. Offline reinforcement learning allows learning policies from previously collected data, which has profound implications for applying RL in domains where running trial-and-error learning is impractical or dangerous, such as safety-critical settings like autonomous driving or medical treatment planning. In such scenarios, online exploration is simply too risky, but offline RL methods can learn effective policies from logged data collected by humans or heuristically designed controllers. Prior learning-based control methods have also approached learning from existing data as imitation learning: if the data is generally "good enough," simply copying the behavior in the data can lead to good results, and if it's not good enough, then filtering or reweighting the data and then copying can work well. Several recent works suggest that this is a viable alternative to modern offline RL methods.
This week, host Karen Han talks to voice actor and performer Erika Ishii, whose very long resume includes video games, animated series, and live action projects. In the interview, Erika explains their process of bringing video game characters to life–characters like Valkyrie in the game Apex Legends. Then Erika discusses diversity among both characters and performers in the video game industry and the ability to say no to projects that aren't the right fit. After the interview, Karen and co-host Isaac Butler talk about diversity in entertainment and the progress that has yet to be made. In the exclusive Slate Plus segment, Erika lists some of the voice actors and performances that have inspired them over the years.
Deep reinforcement learning (DRL) is transitioning from a research field focused on game playing to a technology with real-world applications. Notable examples include DeepMind's work on controlling a nuclear reactor or on improving Youtube video compression, or Tesla attempting to use a method inspired by MuZero for autonomous vehicle behavior planning. But the exciting potential for real world applications of RL should also come with a healthy dose of caution – for example RL policies are well known to be vulnerable to exploitation, and methods for safe and robust policy development are an active area of research. At the same time as the emergence of powerful RL systems in the real world, the public and researchers are expressing an increased appetite for fair, aligned, and safe machine learning systems. The focus of these research efforts to date has been to account for shortcomings of datasets or supervised learning practices that can harm individuals.
Six years after its initial release, Stardew Valley has sold more than 20 million copies. Creator Eric Barone shared news of the accomplishment in an update posted to the game's press site and an interview with PC Gamer. "The 20 million copies milestone is really amazing," he told the outlet. But what's even more impressive is the increasing pace of Stardew Valley's sales. It took four years for the game to sell its first 10 million copies.
Tiernan Ray has been covering technology and business for 27 years. He was most recently technology editor for Barron's where he wrote daily market coverage for the Tech Trader blog and wrote the weekly print column of that name. DeepMind's "Gato" neural network excels at numerous tasks including controlling robotic arms that stack blocks, playing Atari 2600 games, and captioning images. The world is used to seeing headlines about the latest breakthrough by deep learning forms of artificial intelligence. The latest achievement of the DeepMind division of Google, however, might be summarized as, "One AI program that does a so-so job at a lot of things."
It's the dream: Find a smoldering someone on a dating app, match with them, and quickly launch into a conversation filled with subtle compliments, definitive date night plans, and witty repartee. According to research conducted by Preply, -- a language learning app and platform, – more than 70 percent of dating app users surveyed said it's possible to engage in meaningful conversation, and even fall in love with someone, before ever meeting in person (having only spoken on an app). The challenge, of course, is getting there, shifting from the notification that "It's A Match!" into dialogue worthy of a Shonda Rhimes production. It's a daunting task, so we brought in the pros: rom-com authors. Mashable spoke with several -- all with books jam-packed with quippy dialogue out this spring and summer -- to get their expert takes on how to write witty banter.
Wondering what everyone's been watching this week? Well, spring is in the air and so is action, action, action! Every week, the popularity of movies across streaming might be determined by promotions, star power, critic raves, social media buzz, good old-fashioned word of mouth, or a new addition to a beloved franchise. While the reasons may vary, you can't argue with the numbers that streaming aggregator Reelgood collected from hundreds of streaming services in the U.S. and UK. As it has for weeks, The Batman continues to reign supreme.
Joe McKendrick is an author and independent analyst who tracks the impact of information technology on management and markets. As an independent analyst, he has authored numerous research reports in partnership with Forbes Insights, IDC, and Unisphere Research, a division of Information Today, Inc. Enterprise architects have been adding a new designation to their titles: digital enterprise architect. That's because their roles have been expanding over the past few years, particularly with data analytics being added to their repertoires. That's the word from Thomas Erl, CEO of Arcitura Education, which provides technology skills training to thousands of professionals across the globe, and co-author of A Field Guide to Digital Transformation. "It's a new era for enterprise architects," he says.