Nigerian fintech startup, Kredete, has officially launched its lending platform to deepen accessibility to formal credit, financial education, and innovative financial solutions. The launch event, which took place on the 16th of April 2023, at the Civic Centre, Victoria Island, hosted tech specialists and entrepreneurs, who convened to discuss the future of lending in Africa and Kredete's commitment to bridging the significant credit gap and financial exclusion faced by Nigerians who lack access to formal credit through traditional means. Kredete aims to revolutionize the sphere of lending in Nigeria and beyond by leveraging AI-driven technology and strategic partnerships with financial institutions to create a complete lending infrastructure that enables lenders to be more efficient and cost-effective while empowering users to access credit products suited to their needs. With AI, the pre-approval odds for users enhance by providing tailored loan options based on their credit history and financial profile, while for lenders, it becomes easier to assess risks, reduce non-performing loans, and make informed lending decisions. Kredete is also passionate about strengthening financial literacy in Nigeria and will achieve this by offering free credit scores, reports, and monitoring tools to help users understand their credit standing and make informed financial decisions.

As AI continues to evolve, chatbots are becoming increasingly sophisticated and human-like in their ability to respond to natural language inputs. One of the most impressive models in this space is OpenAI's chatGPT, which has set new standards for language understanding and generation. But what if you could have your own chatbot that could answer your questions, provide information, and even make jokes, just like chatGPT? With recent advancements in fine-tuning techniques, it is now possible to create your own high-quality chatbot by fine-tuning a pre-trained model. In this article, we'll take a look at how to create your own chatbot using a fine-tuning technique called LoRA (Low Rank Adaptation) and the pre-trained model flan-T5 XXL.

SAN FRANCISCO, April 17 (Reuters) - Billionaire Elon Musk said on Monday he will launch an artificial intelligence (AI) platform that he calls "TruthGPT" to challenge the offerings from Microsoft (MSFT.O) and Google (GOOGL.O). He criticised Microsoft-backed OpenAI, the firm behind chatbot sensation ChatGPT, of "training the AI to lie" and said OpenAI has now become a "closed source", "for-profit" organisation "closely allied with Microsoft". He also accused Larry Page, co-founder of Google, of not taking AI safety seriously. "I'm going to start something which I call'TruthGPT', or a maximum truth-seeking AI that tries to understand the nature of the universe," Musk said in an interview with Fox News Channel's Tucker Carlson aired on Monday. He said TruthGPT "might be the best path to safety" that would be "unlikely to annihilate humans".

Artificial Intelligence (AI) is a rapidly evolving technology that can revolutionize the way we use and interact with software. In recent years, the integration of AI in Windows software has transformed the computing experience, making it more personalized, efficient, and effective. AI is vital in enhancing the accessibility of Windows software. For example, Windows uses Natural Language Processing (NLP) and machine learning algorithms to learn from user behavior and respond to voice commands. As a result, it can adapt to user needs, making it easier to use and more intuitive.

Human Activity Recognition has been researched in thousands of papers so far, with mobile / environmental sensors in ubiquitous / pervasive domains, and with cameras in vision domains. As well, Human Behavior Analysis is also explored for long-term health care, rehabilitation, emotion recognition, human interaction, and so on. However, many research challenges remain for realistic settings, such as complex and ambiguous activities / behavior, optimal sensor combinations, (deep) machine learning, data collection, platform systems, and killer applications. In this conference, we comprehend such research domains as ABC: Activity and Behavior Computing, and provide an open and a confluent place for discussing various aspects and the future of the ABC. The submitted papers are peer reviewed by expert researchers, and accepted based on the research quality.

Abstract: Electron, optical, and scanning probe microscopy methods are generating ever increasing volume of image data containing information on atomic and mesoscale structures and functionalities. Variational autoencoders (VAEs) are emerging as a powerful paradigm for the unsupervised data analysis, allowing to disentangle the factors of variability and discover optimal parsimonious representation. Here, we summarize recent developments in VAEs, covering the basic principles and intuition behind the VAEs. The invariant VAEs are introduced as an approach to accommodate scale and translation invariances present in imaging data and separate known factors of variations from the ones to be discovered. We further describe the opportunities enabled by the control over VAE architecture, including conditional, semi-supervised, and joint VAEs.

The insurance industry has undergone significant changes over the years. The integration of advanced technologies such as artificial intelligence (AI) has paved the way for further evolution, offering improved efficiency, reduced costs and enhanced customer experience. Various AI applications are currently in use in the insurance industry, ranging from underwriting to claims processing. AI can help insurers evaluate risk more accurately by analyzing large amounts of data such as historical claims data, credit scores and social media activity--thereby enabling insurers to offer personalized coverage to customers and price policies more accurately. It can also aid in detecting and preventing fraud by analyzing data patterns and identifying suspicious activity, which can help insurers save money by reducing the number of fraudulent claims they pay out.

A song featuring the voices of Drake and The Weeknd called "Heart on My Sleeve" has amassed over 250,000 Spotify streams and 10 million views on TikTok. But the two renowned musicians had nothing to do with the song -- an artist going by the name "Ghostwriter" generated the song using AI. Drake and The Weeknd have not yet responded to the song, but Drake recently commented on AI-generated music that rips off his voice. When Drake noticed an AI model of himself singing "Munch" by Ice Spice, he wrote on his Instagram story, "This is the final straw AI." It's possible he was messing around, but he would be far from the first major artist to take issue with the rising count of deepfake songs. Ghostwriter and Spotify did not immediately respond to TechCrunch's requests for comment.

Welcome to my tutorial for installing and setting up Tensorflow 2 Object Detection! This tutorial goes over how to install Tensorflow 2 and get object detection up and running. I try to cover as many possible errors you may find when trying to do this yourself so that you can skip the headaches and get right to object detecting! Common Tensorflow 2 fixes: "protoc not found" - make sure you add protoc to path and also do "conda install protobuf" "numpy not found" - make sure to do "conda install numpy"

Artificial intelligence imaging can be used to create art, try on clothes in virtual fitting rooms or help design advertising campaigns. But experts fear the darker side of the easily accessible tools could worsen something that primarily harms women: nonconsensual deepfake pornography. Deepfakes are videos and images that have been digitally created or altered with artificial intelligence or machine learning. Porn created using the technology first began spreading across the internet several years ago when a Reddit user shared clips that placed the faces of female celebrities on the shoulders of porn actors. Since then, deepfake creators have disseminated similar videos and images targeting online influencers, journalists and others with a public profile.