No, your favourite influencer hasn't got a dozen dachshund dogs. When scrolling through social media recently, you might have noticed posts which seem a bit off. It's all AI generated and due to its low quality and its inauthenticity, it's being branded AI slop. Both social media users and content creators say they're worried that AI slop flooding feeds is leading to a less authentic online experience - and is drowning out real posts. But a new trend, which sees people adding AI-generated animals to original photographs, has encouraged some content creators to embrace AI.

With the withdrawal of the U.K. from the European Union, MHRA as part of its new Brexit freedoms is moving to update the country's regulations for software and AI as a medical device without the burden of accommodating the regulatory approaches of EU members. "These measures demonstrate the U.K.'s commitment, following our exit from the European Union, to drive innovation in healthcare and improve patient outcomes," states MHRA's announcement. "Regulatory measures will be updated to further protect patient safety and take account of these technological advances." AI and SaMD technologies have the potential for better diagnosing and treating a wide variety of diseases, but FDA has yet to finalize a regulatory framework for machine learning-based software as a medical device. The agency is considering a total product lifecycle-based regulatory framework for adaptive or continuously learning algorithms.

Natural Language Processing (NLP), the ability of a software program to understand human language as it is spoken, has seen major breakthroughs, thanks to Artificial Intelligence (AI) and improved access to fast processors and cloud computing. With the introduction of more personal assistants, better smartphone functionality, and the evolution of Big Data to automate even more regular human jobs, NLP adoption is projected to gain up steam in the future years. SoundHound creates AI and conversational intelligence systems that are voice-enabled. It offers a Speech-to-Meaning engine as well as Deep Meaning Understanding technology, which may be integrated into other services and devices. It also creates music recognition apps and voice search assistants.

AI and machine learning in particular have grown over the past decade to become key tools for processing and making sense of large and complex …

FreshLime is building a next-generation customer engagement platform for locally-focused businesses. It is a multi-channel platform that gathers data from marketing, point of sale, and customer data, enabling merchants to develop and implement targeted marketing campaigns to increase customer spend and frequency. Rasa Technologies provides the standard infrastructure layer for developers to build, improve, and deploy better AI assistants. The Company offers an open-source machine learning tools for developers to create contextual text and voice-based chatbots and assistants. Rasa Technologies serves customers in the United States and Germany.

Just AI, a сonversational AI technologies developer and solutions provider, received from two strategic investors: MTS PJSC and Sovcombank PJSC . The new investors' total share in the capital of Just AI was 22.5%, with a total market valuation of $40 million. Just AI, a сonversational AI technologies developer and solutions provider, received funding from two strategic investors. The first one is MTS PJSC – one of the leading mobile network operators in Russia, Ukraine, Armenia and Belarus with over 106.5 million subscribers. The second investor is Sovcombank PJSC – one of Russia's top-15 commercial banks.

Amazon, like many other tech companies investing heavily in artificial intelligence, has always been forthright about its Alexa assistant being a work in progress. "The more data we use to train these systems, the better Alexa works, and training Alexa with voice recordings from a diverse range of customers helps ensure Alexa works well for everyone," reads the company's Alexa FAQ. What the company doesn't tell you explicitly, as highlighted by an in-depth investigation from Bloomberg published this evening, is that one of the only, and often the best, ways Alexa improves over time is by having human beings listen to recordings of your voice requests. Of course, this is all buried in product and service terms few consumers will ever read, and Amazon has often downplayed the privacy implications of having cameras and microphones in millions of homes around the globe. But concerns about how AI is trained as it becomes an ever more pervasive force in our daily lives will only continue to raise alarms, especially as most of how this technology works remains beyond closed doors and improves using methods Amazon is loathe to ever disclose. In this case, the process is known as data annotation, and it's quietly become a bedrock of the machine learning revolution that's churned out advances in natural language processing, machine translation, and image and object recognition.

For many people, the first name that comes to mind when you say "Artificial intelligence" still isn't Siri, Alexa or Google. They all talk like us, or look like us. We just can't resist defining AI, an abstract and potentially revolutionary concept, in terms of ourselves. All we can see and hear is the interface -- the way we interact with AI is what makes it intelligent to us. Not what it knows, what it can do or the choices it makes.