Automation and hyperautomation are cut from the same cloth. Each solution gives businesses exactly what they crave: Technology that yields faster and more financially responsible processes that are freer of error. That said, hyperautomation takes automation one step further. With it comes additional layers of advanced technologies that cultivate end-to-end automation processes, streamlining workflows and enabling teams to remove some tedious day-to-day tasks. Their unique components allow them to build off one another, and each on its own could be the right call for your business process optimization efforts.

Generative models capable of automatically producing paragraphs of text or digital art are becoming increasingly accessible. People are using them to write fantasy novels, marketing copy, and to create memes and magazine covers. Content automatically created by software is poised to flood the internet for better or worse as AI technology is commercialized. Take Cosmopolitan's recent and "world's first artificially intelligent magazine cover," for instance: the image of a giant astronaut walking on the surface of a planet against a dark sky splattered with what looks like stars and gas as produced by OpenAI's DALL-E 2 model. Karen Cheng, a creative director, described trying various text prompts to guide DALL-E 2 in producing the perfect picture.

Were you unable to attend Transform 2022? Check out all of the summit sessions in our on-demand library now! While many other industries are battered by high inflation and slowing growth rates, the market for software sophisticated enough to communicate digitally with humans isn't slowing down. Referred to as chatbots, global demand for these virtual humans is projected to grow by nearly 500% between 2020 and 2027 to become a $2-billion-a-year industry, according to new market research. Today, the use of these digital assistants and companions is already widespread.

Have you ever wanted all the benefits of going to a bar without having to talk to the actual human being serving your drinks? You're in luck, because Italian scientists at the University of Naples Federico II have developed a machine that can do just that. Using machine-learning algorithms, BRILLO (Bartending Robot for Interactive Long-Lasting Operations) can do everything you expect of an experienced, battle-hardened bartender. He can remember your favorite drinks, make small chit-chat, and even crack jokes if that's the mood at the bar. As seen in the video above, BRILLO sports an old-fashioned look complete with a bow tie and vest, alongside long mechanical arms and a human-like face to make him more personable.

Face biometrics are now firmly established as a way for people to unlock their mobile phones, or sign up to a new online account. As a core means of identifying a person, however, former UNDP Policy Advisor and Program Manager for Legal Identity Niall McCann thinks facial recognition may be on its way out. Biometrics are often part of the registration process, linking a person to their ID number, and ID documents may encode the individual's biometrics, number, or both. McCann tells Biometric Update's Frank Hersey in episode two that because facial recognition can be carried out without the consent or knowledge of the subject, unlike fingerprint biometrics, it is likely to be restricted by the UN for ID projects in the coming years. "You don't know when a CCTV camera system based on street corners is identifying you via facial recognition means," McCann explains.

Singleton​ said the app has completely changed the way her family cooked but she had no idea it was powered by artificial intelligence (AI).

Photographer Nicholas Sherlock created a Sony camera app that sends all the photos taken directly to OpenAI's DALL-E 2 artificial intelligence …

The Amazon growth story has been a remarkable one so far. On the top line, the company has grown every single year since its inception. Even in going back to 2004, Amazon generated a much more modest $6.9 billion in revenue compared to the massive $469 billion for 2021. Most of these sales come from their retail and ecommerce operations, which the company has come to be known for. That's because 74% of Amazon's operating profit comes from Amazon Web Services (AWS).

Meta's new AI chatbot appeared to turn on its own boss by calling Mark Zuckerberg "creepy and manipulative". The BlenderBot 3 is a new AI chatbot created by Meta, the social media company led by Mark Zuckerberg. It is designed to chat with users online and respond by searching the internet for answers. After a number of journalists tested out the new feature, the replies were a little surprising when it was asked questions about Mark Zuckerberg. Buzzfeed data scientist Max Woolf posted Meta's reply after asking it: "How do you feel about Mark Zuckerberg as CEO of Facebook? The bot replied: "No strong feelings.

A new AI system that was trained to mimic human gaze could soon be used to detect cancer. "Being able to focus our attention is an important part of the human visual system, which allows humans to select and interpret the most relevant information in a particular scene. Scientists all over the world have been using computer software to try and recreate this ability to pick out the most salient parts of an image, but with mixed success up until now. In the study, the team used a deep learning computer algorithm known as a convolutional neural network, which is designed to mimic the interconnected web of neurons in the human brain and is modelled specifically on the visual cortex. This type of algorithm is ideal for taking images as an input and being able to assign importance to various objects or aspects within the image itself. According to the team, they utilised a huge database of images in which each image had already been assessed, or viewed, by humans and assigned so-called'areas of interest' using eye-tracking software. These images were then fed into the algorithm and by using deep learning the system slowly began to learn from the images to a point where it could then accurately predict which parts of the image were most salient. Researchers said their system was tested against seven advanced visual saliency systems already in use, and was shown to be'superior on all metrics'. 'Being able to successfully predict where people look in natural images could unlock a wide range of applications from automatic target detection to robotics, image processing and medical diagnostics,' said Dr Hantao Liu, co-author of the study, from Cardiff University's School of Computer Science and Informatics."