And as has become customary in the last few years, major tech companies are taking this week as a chance to share their latest accessibility-minded products. From Apple and Google to Webex and Adobe, the industry's biggest players have launched new features to make their products easier to use. The company actually had a huge set of updates to share, which makes sense since it typically releases most of its accessibility-centric news at this time each year. For 2023, Apple is introducing Assistive Access, which is an accessibility setting that, when turned on, changes the home screen for iPhone and iPad to a layout with fewer distractions and icons. You can choose from a row-based or grid-based layout, and the latter would result in a 2x3 arrangement of large icons.

Ever since the release of ChatGPT last year, new generative AI tools and services have captured people's attention. Now, Meta is warning that bad actors have taken notice of interest in AI chatbots. The Facebook parent said scammers are creating malware that poses at ChatGPT and similar tools. In a security report released Wednesday, Meta said it discovered 10 malware families posing as ChatGPT or related tools since March. Some of the malicious software, which can steal your personal information and compromise accounts, came in the form of browser extensions and links.

Amazon Lookout for Vision provides a machine learning (ML)-based anomaly detection service to identify normal images (i.e., images of objects without defects) vs anomalous images (i.e., images of objects with defects), types of anomalies (e.g., missing piece), and the location of these anomalies. Therefore, Lookout for Vision is popular among customers that look for automated […]

Software enables completely new inspiration in the creative process By keeping AI software development entirely in-house, Audi demonstrates competence in a crucial emerging field Leveraging artificial intelligence (AI) in all departments: this is the goal Audi has set itself on its way to becoming a data-driven company. With FelGAN, the company now employs software that uses artificial intelligence to open up new sources of inspiration for designers. Creative people are always on the lookout for inspiration. The same is true of the designers who create new wheels at the Audi Design Studio in Ingolstadt. But where to find untapped sources of inspiration?

Artificial Intelligence has made life easier than ever.

One of the challenges encountered by teams using Amazon Lookout for Metrics is quickly and efficiently connecting it to data visualization. The anomalies are presented individually on the Lookout for Metrics console, each with their own graph, making it difficult to view the set as a whole. An automated, integrated solution is needed for deeper analysis. In this post, we use a Lookout for Metrics live detector built following the Getting Started section from the AWS Samples, Amazon Lookout for Metrics GitHub repo. After the detector is active and anomalies are generated from the dataset, we connect Lookout for Metrics to Amazon QuickSight.

Yes, once upon a time, it was a Steven Spielberg movie (and an underrated masterpiece on top of that). But today "AI" is a buzz phrase that pops up with more and more frequency in all kinds of social, political and especially technological contexts. AI stands, of course, for "artificial intelligence," also often referred to as "machine learning." Ask most folks to define AI, however, and it's much like asking people how a toilet works: You think you know, until you have to explain it to someone else. Artificial intelligence is a moving target, which makes it a challenge for even professionals in tech to fully understand it.

Predictive maintenance can be an effective way to prevent industrial machinery failures and expensive downtime by proactively monitoring the condition of your equipment, so you can be alerted to any anomalies before equipment failures occur. Installing sensors and the necessary infrastructure for data connectivity, storage, analytics, and alerting are the foundational elements for enabling predictive maintenance solutions. However, even after installing the ad hoc infrastructure, many companies use basic data analytics and simple modeling approaches that are often ineffective at detecting issues early enough to avoid downtime. Also, implementing a machine learning (ML) solution for your equipment can be difficult and time-consuming. With Amazon Lookout for Equipment, you can automatically analyze sensor data for your industrial equipment to detect abnormal machine behavior--with no ML experience required.

The past few years have seen the rise of deepfake technology. These often take the form of convincing fake images and videos made generated through the use of artificial intelligence software. Moving on from how the technology was manifest a couple of years ago, the images displayed have become increasingly realistic. One example of deepfake technology ("deep learning" and "fake") convincing many people, and as an example of the technology entering the mainstream (in terms of wider public awareness), was when a graphic designer created a "Tom Cruise" deepfake video. In January 2022, this video went viral on TikTok.

You will support real-time analysis in the Lookout Security Cloud, as well as ad hoc analysis by researchers and analysts hunting for new mobile threats. Your datasets will directly support product features such as data dashboards and threat detection. We're looking for engineers who understand both data and infrastructure, and are enthusiastic about working on both. Do you have good software development skills with Python and Java or Scala? Do you have experience with frameworks such as Apache Spark or Kafka?