A mother of two says she was left penniless after giving her savings to Tinder predator Christopher Harkins in a fake investment scam. The pair matched on the dating app in London in 2020. Caitlyn - not her real name - told how the fraudster and rapist initially tried to talk her into going on holiday with him - a regular ruse of Harkins, now 38. When she said she couldn't afford a holiday, he offered to help by doubling what money she had via his foreign currency exchange business. She's one of four women the BBC is aware of who were targeted by Harkins in the capital - where he fled to after his crimes were exposed in Scotland.

The saying goes that'mother knows best', and now struggling singletons can enlist their mum's help finding love online. Dating app, Badoo, now lets you add video clips from your family members to your dating profile. The unusual tool is part of Badoo's new'Family-Approved' feature, which allows users to show that they've called on their family to help them land a date. Remy Le Fèvre, Global Head of Brand Engagement and Influence at Badoo, said: 'Here at Badoo, we're all about making sure singles feel confident putting their best foot forward when dating, and for many of us, that means getting a little help from the people that love them most. 'Family-Approved is here to help singles feel good right from the start of their dating journey, whilst also showing potential matches when profiles have had the trusted green light from their loved ones - which could be a fun icebreaker when starting a conversation!'

Natural language processing (NLP) has come a long way in recent years, and the development of advanced AI models like MUM (Multitask Unified Model) is making the field even more exciting. While BERT (Bidirectional Encoder Representations from Transformers) has been a powerful tool in NLP, MUM is expected to surpass it in terms of functionality and versatility. BERT (Bidirectional Encoder Representations from Transformers) is a natural language processing model that was introduced by Google in October 2018. The model was developed by a team of researchers at Google led by Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. BERT was designed to improve the accuracy of NLP tasks such as sentiment analysis, question answering, and language translation.

When many of us think of algorithms and machine learning models, we think of Google. And really, who can blame us? But there is a lot going on in and out of the Googleplex right now, and it's becoming increasingly important that we keep up. We'll cover some of the current uses where applicable, then move on to discuss where I see the technology going in the near-to-mid future and how it'll impact marketers. So let's dive in – starting with arguably my favorite "new release."

Google is one of the pioneers in the use of artificial intelligence. The company recently announced that it could use AI techniques to analyze users' searches and detect whether they are in a crisis. To do this, Google has developed machine learning models. The company's latest model is called MUM, which was introduced at the IO conference last year. Google has now integrated the MUM machine learning model with its search engine to provide a higher level of analysis.

Every day, the company fields searches on topics like suicide, sexual assault, and domestic abuse. But Google wants to do more to direct people to the information they need, and says new AI techniques that better parse the complexities of language are helping. Specifically, Google is integrating its latest machine learning model, MUM, into its search engine to "more accurately detect a wider range of personal crisis searches." The company unveiled MUM at its IO conference last year, and has since used it to augment search with features that try to answer questions connected to the original search. In this case, MUM will be able to spot search queries related to difficult personal situations that earlier search tools could not, says Anne Merritt, a Google product manager for health and information quality.

Google plans to use artificial intelligence in more ways to make using search safer. In the coming weeks, it will roll out some updates for its AI model, MUM. The upgrades should help it detect a wider variety of personal crisis searches about sexual assault, substance abuse, domestic violence and suicide. The company says people search for information about these topics in a broad range of ways. By employing MUM's machine learning capabilities, Google says it can better understand the intent behind queries to recognize when someone is in need. As such, it'll be able to provide them with more actionable, reliable information at the appropriate time.

We've seen an explosion of AI language models in recent years. The ultimate goal of these systems is to be able to extract, communicate, and interpret human-level language. Do you ever wonder how Google interprets your search queries? There's a lot that goes into providing relevant search results, and one of the most critical skills is language interpretation. Search systems are comprehending human language better than ever before because of advancements in AI and machine learning. Google describes how its artificial intelligence (AI) systems interpret human language and deliver appropriate search results.

Roughly a year ago, VentureBeat wrote about progress in the AI and machine learning field toward developing multimodal models, or models that can understand the meaning of text, videos, audio, and images together in context. Back then, the work was in its infancy and faced formidable challenges, not least of which concerned biases amplified in training datasets. But breakthroughs have been made. This year, OpenAI released DALL-E and CLIP, two multimodal models that the research labs claims are a "a step toward systems with [a] deeper understanding of the world." DALL-E, inspired by the surrealist artist Salvador Dalí, was trained to generate images from simple text descriptions.

In May, Google executives unveiled experimental new artificial intelligence trained with text and images they said would make internet searches more intuitive. Wednesday, Google offered a glimpse into how the tech will change the way people search the web. Starting next year, the Multitask Unified Model, or MUM, will enable Google users to combine text and image searches using Lens, a smartphone app that's also incorporated into Google search and other products. So you could, for example, take a picture of a shirt with Lens, then search for "socks with this pattern." Searching "how to fix" on an image of a bike part will surface instructional videos or blog posts.