Collaborating Authors

AI Research Helps Businesses Make Better Decisions - Australian Cyber Security Magazine


The University of Adelaide and MTX Group have entered into a research collaboration to develop new insights in machine learning (ML) and artificial intelligence (AI). Bringing together their academic research and commercial expertise and experience, the two organisations will undertake specific, outcomes-focussed research. They will use AI to model uncertainty with a view to avoiding failure within systems that may be used in defence and business environments. The University and MTX Group have jointly been awarded $100,000 under the Artificial Intelligence for Decision Making Initiative which is a collaborative project between the Australian Government's Office of National Intelligence (ONI) and the Defence Science and Technology Group (DST). Dr Duong Nguyen and Dr George Stamatescu from the University's School of Computer Science will work alongside Dr Ammar Mohemmed from MTX Group.

PyTorch vs TensorFlow: What Will be the Best Option for Data Scientists?


If you want to be a successful data scientist or AI engineer, you must master the various deep learning frameworks that are currently available. In this article, we'll enlighten you about the best option for data scientists. TensorFlow and PyTorch both provide valuable abstractions that make model creation easier by minimizing boilerplate code. They vary in that PyTorch takes a more "pythonic" approach and is object-oriented, whereas TensorFlow provides a wide range of possibilities. PyTorch is used for many deep learning projects today, and its popularity among AI researchers is growing, despite being the least popular of the three main frameworks.

How Do Those AI Face Generator things work?


Just by browsing the internet, you may have heard or seen of fascinating apps and websites that can generate a seemingly random face of a person within a span of seconds. You may even have tried some out to see what types of faces can be generated. Are the faces faces of real people? A lot of these platforms develop a GAN (General Adversarial Network) machine learning model and train it on a dataset made of real human faces so this GAN can then learn these differing human features to generate new human faces. Therefore, most of the times, the generated faces you see on the internet or on an app are not real, meaning you won't be able to trace any photo back to someone in this world.

UK, Italy and Japan team up for mind-reading jet

BBC News

Work on developing it is already under way - with the aim to create a combat aircraft that will provide speed stealth, use advanced sensors and even artificial intelligence to assist the human pilot when they are overwhelmed, or under extreme stress.

Amazon Games will bring Bandai Namco's 'Blue Protocol' to the west


At the Game Awards, Amazon Games announced it will be publishing Bandai Namco's forthcoming free-to-play online RPG, Blue Protocol in the west. It's an action RPG, with the ability to play both solo and cooperatively. You'll apparently be able to participate in raids with up to 30 other players. While the game will be coming to PC, Xbox Series X/S and PlayStation 5, Blue Protocol is designed to be played on controllers, with aim-assist support for people not using a mouse and keyboard. In fact, each class will have different sliders to adjust controls for smoother playstyles. Talking of style, you'll apparently be able to customize your character deeply, across hairstyles, clothing accessories and even mounts – yes you'll have your own fantasy steed a little like Pokemon Legends Arceus.

iot bigdata, Twitter, 11/23/2022 2:01:51 PM, 284854


The graph represents a network of 1,719 Twitter users whose tweets in the requested range contained "iot bigdata", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Wednesday, 23 November 2022 at 12:43 UTC. The requested start date was Wednesday, 23 November 2022 at 01:01 UTC and the maximum number of tweets (going backward in time) was 7,500. The tweets in the network were tweeted over the 19-day, 11-hour, 51-minute period from Thursday, 03 November 2022 at 13:08 UTC to Wednesday, 23 November 2022 at 00:59 UTC. Additional tweets that were mentioned in this data set were also collected from prior time periods.

Meet ChatGPT: The Artificial Intelligence (AI) Chatbot That Knows Everything - MarkTechPost


If you still haven't heard about the latest development in the field of conversational AI, let us introduce you to ChatGPT, the newest release from OpenAI. This large language model is available for everyone to use for a limited time. It has been creating a buzz on social media for its engaging, sometimes humorous, and occasionally dark responses to user queries. People all over the globe are having fun interacting with ChatGPT and trying to push its boundaries. So what is ChatGPT, and what makes it different from other conversational AI systems?

How Artificial Intelligence is a Game Changer - Joel Comm


I've been fascinated by new technologies my entire life. First entranced by computers in 1980 when I purchased a TRS-80 model I with 4K of RAM, I am always watching for the next big thing. All those years ago, I recall playing with a program called "Eliza". Designed to be an interactive computer therapist, this was my first encounter with artificial intelligence. I thought it was pretty cool.

What is Data Annotation and What are its Advantages?


AI and machine learning is one the fastest growing technology brining unbelievable innovations providing the advantages to different fields globally. And to create such automated applications or machines, huge amount of training data sets is required. And to create such data sets, image annotation technique is used to make the objects recognizable to computer vision for machine learning. And this annotation process is benefiting not only the AI filed but also providing advantages to other stakeholders. Here we will discuss about the advantages of data annotation in various fields.

Artificial Intelligence Security Competition (AISC)


Preliminary competition: This phase examines the generalization of the semi-supervised Deepfake method identification algorithms, including their generalization to different source images and post-processing methods. The provided training dataset consists of two parts: the labelled dataset Dtrland the unlabelled dataset Dtru. To represent data with informed Deepfake synthesis methods, each sample in the labelled dataset Dtrlprovides information of its source images and deepfake synthesis method. The unlabelled dataset Dtru does not provide any relevant information, which represents forged data that are collected in the wild (e.g., from social media, websites) with uninformed deepake synthesis methods and source images. The Deepfake synthesis methods used in the labelled dataset are clearly defined, and we denote the set of these methods as Yl.