Meta has released BlenderBot 3 chatbot to the public with baked-in "safety recipes" that it claims has reduced offensive responses by up to 90%, but the bot can tell lies and be rude. The BlenderBot 3 demo is accessible online for US-based visitors and should be available in other countries soon. "BlenderBot 3 is capable of searching the internet to chat about virtually any topic, and it's designed to learn how to improve its skills and safety through natural conversations and feedback from people'in the wild'," Meta says in a blogpost. A key part of Meta's research in releasing the chatbot to the public is to help develop safety measures for the chatbot. "We developed new techniques that enable learning from helpful teachers while avoiding learning from people who are trying to trick the model into unhelpful or toxic responses," it says, referring to earlier research in automatically distinguishing between helpful users and trolls. Microsoft's 2016 chatbot mishaps in its public beta for Tay.ai showed exactly what can happen when humans interact with a chatbot which can be trained how say awful and racist comments.

There is an interesting vulnerability in video deepfakes that, to date, has been generally overlooked by the security research community, perhaps because'live', real-time deepfakes in video calls have not been a major cause for concern until very recently. For a number of reasons, which we'll examine in this article, deepfakes are not usually very good at recreating profile views: The above examples are taken* from a session with tech exponent and commenter Bob Doyle, who agreed to run some tests with us, using DeepFaceLive to change his appearance to that of a series of popular celebrities. DeepFaceLive is a live-streaming version of the popular DeepFaceLab software, and is capable of creating alternate video identities in real-time. For these tests, Bob used a mix of models downloaded from deepfake communities, as well as some community-trained models that come bundled with the DeepFaceLive application. From more or less face-on viewpoints, most of the celebrity recreations are quite effective, and some are very convincing even at fairly acute angles – until the facial angle hits a full 90 .

Asia-Pacific has embraced AI and is on track to one single goal -- leadership. The region likely recognizes the benefit of pouring heart, soul, and investment into making world-changing artificial intelligence. The response has been overwhelming. Here is what we're expecting from AI in APAC in the coming years. According to research from IDC, the spending on AI in APAC will almost double by 2025.

In the beginning website, design developers and designers designed websites using HTML. Soon, the internet was formless and empty, darkness was over the surface of the deep web, and the Spirit of Code was hovering over the pinnacle of utmost ignorance. We've come a long way from that time. The internet is still a dark, dreadful place, but it's much more stylish, sophisticated, and amazing now. Website Design has grown exponentially in scale and sophistication over the last few years, thanks to new Artificial Intelligence-based website creation tools that are dominating the digital marketing industry.

Fox News Flash top headlines are here. Check out what's clicking on Foxnews.com. In a recent closed-door meeting with leaders of the agency's counterterrorism center, the CIA's No. 2 official made clear that fighting al-Qaida and other extremist groups would remain a priority -- but that the agency's money and resources would be increasingly shifted to focusing on China. The CIA drone attack that killed al-Qaida's leader showed that fighting terrorism is hardly an afterthought. But it didn't change the message the agency's deputy director, David Cohen, delivered at that meeting weeks earlier: While the U.S. will continue to go after terrorists, the top priority is trying to better understand and counter Beijing.

Never have we ever...remembered exactly what happened last season when a TV series is set to drop a brand new chapter, even if we love it with all our hearts. Yes, we're specifically referring to Mindy Kaling's teen smash Never Have I Ever, which is returning to Netflix for Season 3 on Aug. 12. Who got together with who -- did Devi Vishwakumar pick Ben Gross or Paxton Hall-Yoshida or no one? Why was Kamala pretending to like BLACKPINK and video games at work? What happened at the dance again?

Hosted by Dylan Doyle-Burke and Jessie J Smith, Radical AI is a podcast featuring the voices of the future in the field of artificial intelligence ethics. In this episode Jess and Dylan chat to Shion Guha about the government and AI. How does the government use algorithms? How do algorithms impact social services, policing, and other social services? And where does Silicon Valley fit in?

Eager to learn how to build Deep Learning systems using Tensorflow 2 and Python? Get our'Deep Learning for Programmers' ebook here! This site uses Akismet to reduce spam. Learn how your comment data is processed. From Python and Math basics to Neural Networks and MLOps - Become ML Superhero!

AXREM is the UK trade association representing the interests of suppliers of diagnostic medical imaging, radiotherapy, healthcare IT and care equipment in the UK. The group has formed the AXREM AI SFG (special focus group) to promote the adoption of beneficial AI technology and to identify and seek to overcome hurdles to adoption encountered by suppliers. Most recent AI solutions are based on a process of deep learning in which an artificial neural network is presented with annotated examples of a particular kind of pathology and gradually learns to recognise what that pathology looks like. This process is data dependent, and so the work of data scientists and curators is as important as the AI scientists and software engineers who develop the actual algorithms. A key part of developing safe and reliable AI solutions is the use of a representative dataset while performing the AI training.

K-nearest neighbors (KNN) is a type of supervised learning machine learning algorithm and can be used for both regression and classification tasks. A supervised machine learning algorithm is dependent on labeled input data which the algorithm learns on and uses its learnt knowledge to produce accurate outputs when unlabeled data is inputted. The use of KNN is to make predictions on the test data set based on the characteristics (labeled data) of the training data. The method used to make these predictions is by calculating the distance between the test data and training data, assuming that similar characteristics or attributes of the data points exist within close proximity. It allows us to identify and assign the category of the new data whilst taking into consideration its characteristics based on learned data points from the training data.