Meta AI setting new standards in AI innovation Meta has introduced the Llama 3 series, a significant advancement in language models featuring configurations of 8 billion and 70 billion parameters, and plans for a robust 400 billion parameter model in

Meet Atlas: the world’s most dynamic humanoid robot, designed by Boston Dynamics for real-world applications The latest generation of Atlas builds on decades of research, delivering highly capable and practical mobile robots. With an advanced control system and state-of-the-art hardware,

Envisioning a World Where AI Understands Our Reality Meta’s Bold Move: Empowering AI to Decode Our World and Elevate Its Intelligence. This Thursday, the tech giant unveiled OpenEQA, a groundbreaking initiative aiming to equip AI with a deeper understanding of

AI has been a game-changer in many industries, and call centers are no exception Things are moving QUICKLY! Bland AI, a platform that uses AI technology, focuses on making and receiving phone calls through the most realistic-sounding AI phone agents.

YOLO v9: The Latest Evolution in Object Detection YOLO v9, developed by Chien-Yao Wang, I-Hau Yeh, and Hong-Yuan Mark Liao, is the latest iteration in the YOLO series, known for its real-time object detection capabilities. This version introduces significant innovations,

A Closer Look at System Prompt Design Recently, users have noticed that ChatGPT, referring to it as as lazy ChatGPT seems to exhibit lazier behavior. This might initially seem like it stems from a lack of effort or intelligence. However,

Researchers from Meta, Google, and Stability AI are making significant strides in 3D reconstruction. SceneScript from Meta uses natural language descriptions to represent 3D spaces, while MELON by Google tackles reconstructing objects from few unposed images.

Harnessing Multimodal Large Language Models for Instruction-Based Image Editing Recently, advancements in artificial intelligence have paved the way for innovative applications in image editing. One such breakthrough is the utilization of Multimodal Large Language Models (MLLMs). These models guide instruction-based

Features, Getting Started and Gradio Playground A new player in the text-to-speech and voice cloning arena, MetaVoice, has unveiled its innovative technology, MetaVoice 1B. Distinguished by its open-source status under the Apache license, this technology invites widespread tinkering and enhancements.

Getting Started With Open-Source Latte The ability to create high-quality videos using artificial intelligence is rapidly evolving. Recently, models like OpenAI’s SORA, along with the newly released open-source model Latte, have showcased the potential of transformer-based architectures for generating realistic

Bard’s new skills include creating images and understanding over 40 languages Google’s Bard, an AI tool, has some new tricks. It can now understand and chat in more than 40 different languages and create pictures from text descriptions. Let’s dive

Video Synthesis and Super-Resolution Techniques of Decoder-Only Transformer Architectures Developed by Google Research, VideoPoet skillfully blends images, videos, text, and audio. It employs a decoder-only transformer architecture. This setup adheres to LLM training protocols for achieving multimodal objectives. Moreover, VideoPoet

Multimodal Learning through Ego and Exocentric Perspectives Meta’s Ego-Exo4D dataset uniquely captures human skills. It offers egocentric and exocentric views to understand intricate activities. Picture a chef icing a cake. The egocentric view shows every hand movement, grip, and gaze

Navigating Complex Data Landscapes with TaskWeaver’s Innovative Framework Microsoft introduces TaskWeaver, a revolutionary code-first agent framework designed to revolutionize data analytics and domain adaptation. Moreover, this new tool integrates user requests into executable code, leveraging the capabilities of Large Language

Can state-of-the-art safety training techniques detect and remove deceptive strategies in AI systems? Today’s AI landscape significantly focuses on the reliability of Large Language Models (LLMs). Anthropic’s recent research tackles this by focusing on the hidden deceptive strategies in these