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Images generated by artificial intelligence of public figures such as Pope Francis and President Trump have taken the internet by storm in recent days, and the results make clear that passing off such creations as genuine photos is no longer the stuff of science fiction or hyperbole.

Over the weekend, an image of his holiness repping a white Balenciaga puffer coat lit the internet on fire, with Twitter users quipping over the name of a papal lifestyle brand and sharing other famous images of his holiness.

The photo, though, was a fake. It was generated by the latest version of the AI Midjourney, which can now be used by anyone to generate photorealistic images.

Some users have replicated the viral image, or created similar images, with their own prompts, often ordering the AI to recreate images in the style of an Associated Press photo or dictating the sort of camera settings for the AI to replicate.

Last week, with the country awaiting a potential presidential indictment, there was an eruption of AI-generated images of Mr. Trump being arrested and wrestled to the ground by New York City police officers. While all of these images were known to be fake from the outset, social media facilitated their rapid sharing, not always including the context that they were fakes.

The creator of some of these artificially generated images, the founder of the outlet Bellingcat, Eliot Higgins, was later locked out of the Midjourney server where the images are generated.

The Trump arrest image was really just casually showing both how good and bad Midjourney was at rendering real scenes, Mr. Higgins told the Associated Press. The images started to form a sort of narrative as I plugged in prompts to Midjourney, so I strung them along into a narrative, and decided to finish off the story.

The rise of AI has made it possible for anyone with access to the technology to create convincing fakes of what would be newsworthy events.

One of these instances came early last month, when videos from an outlet called Wolf News that featured AI-generated anchors, voices, captions, and images were circulated online.

The fictitious anchors were delivering pro-China messaging that was spread by pro-China bot accounts on various social media platforms. It was one of the first times that apparently fully AI-generated fake news was circulated widely.

A professor of information sciences at RMIT University, Lisa Given, addressing the issue in the Conversation, said she doesnt have a simple solution to the problem, but did offer a few strategies consumers can deploy to prevent confusion over the authenticity of a photo or a piece of audio.

In the article, she recommended that people cross-reference suspicious material with independent sources and look for imperfections in images as a sign that they might be AI-generated.

Where spelling errors once alerted us to email scams, or extra fingers flagged AI-generated images, system enhancements make it harder to tell fact from fiction, Ms. Given wrote. Creating fake photos and deep-fake videos no longer requires specialist skills and equipment.

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Fake Images Created by Artificial Intelligence Beginning To ... - The New York Sun

Microsoft Trying to Block Other Artificial Intelligence Chatbots

Microsoft, which has achieved great success with the Bing artificial intelligence it has recently introduced, is determined to block other search engines. Details are here!

OpenAI, which is currently one of the most talked about companies in the industry on artificial intelligence, has signed a long-term partnership with Microsoft with an agreement worth more than 10 billion dollars. After this situation, many people accused Microsoft of trying to have a monopoly in the field of artificial intelligence. Microsofts steps in this direction began to come gradually.

Microsoft has warned search engines powered by Bing data not to develop their own AI chatbots. Engines that use Bing include sites like You.com and DuckDuckGo.

Although the commercialization of OpenAI, which initially emerged as a non-profit organization to conduct artificial intelligence research, has garnered reactions from the technology world, its partner Microsoft is not afraid to launch a new artificial intelligence tool almost every week.

Allegedly, Microsoft, which transferred $10 billion and Azure server support to the OpenAI team, also started to set up a giant supercomputer complex for GPT-4 to work. All these events have led the industry, especially its arch-rival Google, to fear that Microsoft is trying to monopolize it.

The fact that the Bing chat bot, which uses the GPT-4 language model, is currently only available in the Microsoft Edge browser, seems to be one of the important examples of this situation. According to Bloombergs report, Microsoft, which threatens other search engines using Bing, wants to seize power in the field of artificial intelligence.

You.com currently has its own chatbot. However, Microsoft may have wanted to take action to prevent this situation from progressing any further. The company has not yet received a response to the allegations.

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Microsoft Trying to Block Other Artificial Intelligence Chatbots - Expat Guide Turkey

AI-powered automation for healthcare operations liberates clinicians and others from tedious, manual activities and helps them to focus on patient care.

FREMONT, CA: Artificial Intelligence (AI) is evolving to address the ever-evolving needs of patients. It truly understands a patient's long-term health needsnot just their transactional care needs requires assessing an unimaginably enormous collection of data, including genome, demographic data, medical history, environmental factors, and symptoms. It is physically challenging for providers to manually undertake this analysis. AI is evolving to produce solutions that can automatically undertake this massive data processing and analysis, with the ultimate goal of assisting clinicians in establishing safe, individualized treatment pathways. The obstacles and modifications required to progress AI transcend technological issues.

Greater patient centricity: Stakeholders now have a greater awareness of what patients genuinely want, but they also feel more suited to provide those requirements. More intelligent capacity utilization, as provider and hospital capacity, is limited and will come under growing demand as the elderly population seeks care. While some AI-based products can forecast events, the most effective ones are integrated into workflows to fix difficulties and motivate frontline people to take action. It is essential that the capacitywhether provider or facilities such as OR rooms utilizes to the fullest extent. Using AI and ML to improve demand forecasting and maximize resource usage is gaining popularity across the board. And more and faster care is superior care that saves lives.

Possibilities for increasing revenues: AI-powered care automation helps healthcare facilities maximize surgical income by maximizing the utilization of operating rooms through more innovative scheduling. By automating aspects of the discharge procedure, hospitals can reduce the average length of patient stays. Hospitals are experiencing a personnel crisis compounded by the Covid-19 outbreak. They no longer have the workforce to devote to procedural chores, so they must release their suppliers to focus on the most critical jobs. Automation of care enabled by AI makes this possible.

More productive study: Major pharma and research organizations are altering the landscape of R&D. There are many ways to reduce the number of promising medication candidates, sometimes utilizing quantum. The quest for more efficient drug development builds excitement around reexamined methods, new data sources, and value-added use cases that address patient and practitioner pain points. Many firms are implementing acculturation strategies to improve their resources' data and AI literacy in appealing formats. AI transcends mere technological considerations.

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Key Healthcare Applications of Artificial Intelligence - Healthcare Tech Outlook

The automotive industry continues to be a hotbed of innovation, with activity driven by demand for intelligent and connected cars that are safer and offer enhanced driving experience, as well as the growing importance of technologies such as electric, connected and autonomous vehicles. Adaptive control systems, backed by artificial intelligence, assist driver in real-time scenario. The technology studies driver behaviour patterns, preferred temperature settings, songs, and destinations, to make the commuting experience convenient and comfortable. Almost all major automotive original equipment manufacturers (OEMs) are working towards the development of software to create an ideal in-car experience for drivers. In the last three years alone, there have been over 1.2 million patents filed and granted in the automotive industry, according to GlobalDatas report on Artificial intelligence in Automotive: AI-assisted adaptive control systems.

However, not all innovations are equal and nor do they follow a constant upward trend. Instead, their evolution takes the form of an S-shaped curve that reflects their typical lifecycle from early emergence to accelerating adoption, before finally stabilising and reaching maturity.

Identifying where a particular innovation is on this journey, especially those that are in the emerging and accelerating stages, is essential for understanding their current level of adoption and the likely future trajectory and impact they will have.

290+ innovations will shape the automotive industry

According to GlobalDatas Technology Foresights, which plots the S-curve for the automotive industry using innovation intensity models built on over 619,000 patents, there are 290+ innovation areas that will shape the future of the industry.

Within the emerging innovation stage, manufacturability analysis, autonomous parking, and lidar for vehicle anti-collision are disruptive technologies that are in the early stages of application and should be tracked closely. Speed profile estimation, smart light dimmers, and driver drowsiness detection are some of the accelerating innovation areas, where adoption has been steadily increasing. Among maturing innovation areas are road slope estimation and adaptive cruise control, which are now well established in the industry.

Innovation S-curve for artificial intelligence in the automotive industry

AI-assisted adaptive control systems is a key innovation area in artificial intelligence

Artificial intelligence-based adaptive control systems provide real-time monitoring and tracking of data with sensors to adjust the controlled parameters to adapt to the changing conditions.

GlobalDatas analysis also uncovers the companies at the forefront of each innovation area and assesses the potential reach and impact of their patenting activity across different applications and geographies. According to GlobalData, there are 60+ companies, spanning technology vendors, established automotive companies, and up-and-coming start-ups engaged in the development and application of AI-assisted adaptive control systems.

Key players in AI-assisted adaptive control systems a disruptive innovation in the automotive industry

Application diversity measures the number of different applications identified for each relevant patent and broadly splits companies into either niche or diversified innovators.

Geographic reach refers to the number of different countries each relevant patent is registered in and reflects the breadth of geographic application intended, ranging from global to local.

Source: GlobalData Patent Analytics

Toyota is one of the leading innovators in adaptive control systems. In a recent development, Toyota collaborated with Google to build Toyota Drivers Companion AI named Joya, designed to answer any questions a driver has about their vehicle. The AI-based product highlights how cloud computing can support interactive, engaging consumer experiences in a natural, accessible format, that is, voice commands. Other companies in this technology domain are Fanuc, Strong Force, Siemens, and Bosch. To further understand how artificial intelligence is disrupting the automotive industry, access GlobalDatas latest thematic research report on Artificial Intelligence (AI) in Automotive.

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GlobalData, the leading provider of industry intelligence, provided the underlying data, research, and analysis used to produce this article.

GlobalDatas Patent Analytics tracks patent filings and grants from official offices around the world. Textual analysis and official patent classifications are used to group patents into key thematic areas and link them to specific companies across the worlds largest industries.

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Who are the leading innovators in AI-assisted adaptive control ... - just-auto.com

At the special session chaired by His Majesty the King Unity and diversity of Spanish. Tradition and the challenge of artificial intelligence, Telefnica, together with Microsoft, Google, Amazon and Meta, have unveiled the progress made in the LEIA initiative whose aim is to help machines speak correct Spanish and ensure that the rules, drawn up by the Royal Spanish Academy (RAE, by its acronym in Spanish), are respected by the AI tools in support of the generation and understanding of the language.

ngel Vil, Chief Operating Officer at Telefnica, gave an overview at the event of all the advances made by Telefnica to promote the proper use of Spanish in home products and services, such as the RAE Living App on Movistar Plus+ to consult definitions or learn more about the language, and the RAE game available on the Movistar Home device. As a novelty, he presented the prototype LEIA-X, a extension for Chrome browsers that uses artificial intelligence to improve the understanding of Spanish. This tool highlights the most appropriate meaning of a selected word according to the context. It uses an AI model that has been trained with more than 70,000examples from various RAE dictionaries.

This functionality is especially useful for the more than 100million non-native Spanish speakers. In addition, using automatic translation APIs, it is capable of providing a response in any language, always aimed at improving the users understanding of Spanish.

LEIA-X responds to the need of improving reading comprehension in a web browser on a laptop, an e-book or simply a mobile phone. Today, all readers have access to a look up or define feature that allows them to select a word and automatically open a dictionary window with its corresponding entry. From there, as readers, we have to navigate through all the meanings to find the one that fits best; a task that distracts from reading, especially on small screens or devices that are not particularly fast. LEIA-X uses AI to provide an exact definition of a word according to its context, making it much easier to read.

The extension is based on an AI model trained specifically with Spanish text (namely the BETO model[1], trained by the University of Chile) to solve a problem that does not require huge large language models (LLMs) such as GPT3 or 4: the disambiguation of the meaning of a word.

The original model (BETO) is trained, by the University of Chile, on a task known as fill the mask, which consists of, given a phrase, masking a word and asking the model to try to predict which word is the best fit. This method of machine learning is called self-supervised. By doing this a sufficient number of times, the model is able to extrapolate which words are related to the context in the phrase or what is, for example, the sentiment of the phrase, or when a verb or noun is required. In short, the AI model learns to extract knowledge or correlations between the words that make up a phrase.

To disambiguate a word in Spanish, you have to use the context where the word appears. To give an example, the Spanish word banco (bank or bench in English) takes on different meanings depending on the context:

I have gone to the bank to make a deposit

Or if we say:

Im sitting on a bench reading a book

While people do this process automatically and almost unconsciously, it is really complex for an algorithm to know which of the definitions of the word banco is being referred to in each case. The only way to know this is to understand each of the words and how they relate to each other in a given context.

Based on the BETO model, LEIA-X has been trained with a corpus of positive and negative examples of words with their meanings in the following way: given a word and a phrase, e.g. the word banco (bank or bench in English) and the sentence:

I have gone to the bank to make a deposit

The model, during the automatic learning process, takes as input the different definitions of the word banco; including, according to the RAE dictionary:

In order to build the LEIA-X training corpus, each sentence and target word has been automatically labelled by its correct meaning and positive examples, or an incorrect one and negative use examples.

The examples in the corpus will eventually take the following form:

In this way, a corpus of more than 70,000examples has been constructed based on various dictionaries provided by the RAE. In the Students Dictionary, each meaning or definition of an entry has a positive example, the correct meaning. To complement this corpus, we have also taken advantage of the Spanish Language Dictionary (DLE, by its acronym in Spanish), in which approximately 15% of its meanings have examples of use. Thanks to the corpus generated, the BETO model has been adapted by incorporating disambiguation capabilities.

Once trained, the LEIA-X model is able to assign to each of the word-sentence pairs the confidence or probability that a particular meaning is the correct one. In the case of the example with the Spanish word banco, for the first sentence, the model would assign a level of probability close to 0% and for the second sentence a level of confidence close to 100%, showing the latter as the most likely meaning. It has therefore succeeded in disambiguating the word.

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Telefnica presents Leia-X, a new extension to improve reading comprehension based on artificial intelligence - Telefnica