Potatoes, Yorkshire puds, gravy, meat and veggies - the Sunday Roast is a meal integral to British identity. It is believed to have its origins in medieval times, around the 12th century, when village serfs were rewarded with roasted ox by their masters after church. At first glance, these plates show golden roast potatoes, billowing Yorkshire puddings, a perfectly juicy joint and lashings of gorgeous gravy. But take a closer look and the traditional dish appears more and more suspicious. Artificial intelligence has generated several photos of the traditional dinner, including all the trimmings. A user on Reddit shared the images, however it was unclear how the AI created the pictures or what software was used.

AI girls, or AI-powered virtual assistants, do not have physical appearance or emotions like human girls. However, here are some things that are considered "beautiful" or advantageous about AI girls in a virtual or technological context: Efficiency: AI girls can perform tasks quickly and accurately, without getting tired or making mistakes. Customization: AI girls can be programmed to respond to specific commands or perform specific functions, making them highly customizable to meet different needs. Availability: AI girls are available 24/7, without breaks or time off, making them highly convenient for users who need assistance at any time. Language abilities: AI girls can understand and respond to multiple languages, making them accessible to a wide range of users. Cost-effectiveness: In many cases, AI girls are more cost-effective than hiring human workers, as they do not require salaries, benefits, or time off.

Are you in the middle of creating a new machine-learning model and unsure of what activation function you should be using? But wait, what is an activation function? Activation functions allow machine learning models to understand and solve nonlinear problems. Using an activation function in neural networks specifically helps with the passing of the most important information from each neuron to the next. Today, the ReLU Activation Function is generally used in the architecture of Neural Networks, however, that does not necessarily mean it is always the best choice.

I recently started an AI-focused educational newsletter, that already has over 150,000 subscribers. TheSequence is a no-BS (meaning no hype, no news etc) ML-oriented newsletter that takes 5 minutes to read. The goal is to keep you up to date with machine learning projects, research papers and concepts. When it comes to the space of generative AI and foundational models, OpenAI seems to have hit escape velocity with the recent release of technologies such as ChatGPT. Given the computational requirements of these systems, it seems logical that the core competition of OpenAI will come from incumbent AI labs such as Google-DeepMind and Meta AI.

Do you have a digital wealth management application for your investment portfolio that recommends investing in specific funds? You are likely using artificial intelligence (AI) to manage your money. From automating and optimizing processes to using conversational AI for enhanced customer engagement and fraud detection, AI and machine learning (ML) are leaving an indelible mark on banks and financial institution performance, completely disrupting the financial industry. In fact, the global market for AI in banking is expected to reach $64.03 billion by 2030. Today, 80% of banks are very aware of the potential benefits of implementing AI, and a majority are looking to deploy AI-enabled solutions.

In a nutshell, Federated Learning (FL) is a way to train AI models without anyone seeing or touching your data, offering a way to unlock information to feed new AI applications. Generally, federated learning operates in a decentralized machine learning method (ML) where instead of training a model on a central server with all data, the model is trained on many devices such as smartphones, laptops, or IoT devices. Each device trains the model locally on its own data and sends the updates to a central server, where the updates are aggregated to improve the overall model. This process continues until a satisfactory model is reached. The key idea behind FL is to allow the devices to learn from their own data while keeping the data on the devices themselves. This approach has several benefits, including improved privacy, reduced data transfer costs, and improved model performance due to the diverse data sources.

A new'outside-the-box' method of teaching artificial intelligence (AI) models to make decisions could provide hope for finding new therapeutic methods for cancer, according to a new study from the University of Surrey. Computer scientists from Surrey have demonstrated that an open ended - or model-free - deep reinforcement learning method is able to stabilize large datasets (of up to 200 nodes) used in AI models. The approach holds open the prospect of uncovering ways to arrest the development of cancer by predicting the response of cancerous cells to perturbations including drug treatment. There are a heart-breaking number of aggressive cancers out there with little to no information on where they come from, let alone how to categorize their behavior. This is where machine learning can Dr Sotiris Moschoyiannis, corresponding author of the study from the University of Surreyprovide real hope for us all.

The AI startup culture in China has expanded quickly in recent years due to vast amounts of data and an abundance of people with technical skills. A wide spectrum of technology, including computer vision, natural language processing, and self-driving automobiles, has been developed by Chinese firms in the AI domain. Many of these firms have also successfully obtained sizable funding from investors, domestically and abroad. Let's check out a few of the most cutting-edge AI startups based in China. Horizon Robotics is focused on developing energy-efficient solutions for the Internet of Things (IoT) and smart vehicles.

The cybersecurity industry is expanding rapidly, and there is a growing demand for advanced solutions that can detect and respond to bot-based attacks. The AI-powered Threat Response platform allows a startup to enter the market with a cutting-edge solution that leverages the most recent advances in AI technology. Organizations have faced increasing challenges in defending against bot-based attacks in recent years. Traditional threat detection and response methods are manual, time-consuming, and prone to human error. To address these challenges, the ChatGPT-powered AI-powered Threat Response platform is gaining traction as a solution to improve organizations' cybersecurity posture. The ChatGPT technology will be used by the AI-powered Threat Response platform to provide organizations with real-time threat detection and response capabilities.

If you have an Amazon Echo device in your home, you most likely use it for everyday uses, such as listening to music or checking the news. However, there are a range of interesting things Alexa can also do. Once you know what to ask, you can put your Alexa to the test and ask her to supply you with hilarious jokes, pop culture references, trivia, and much more. These hidden features will certainly not leave users disappointed and are worth giving a go. Here is a list of 15 questions you can ask Alexa to lighten the mood or to tackle your boredom.