Meet LEAP: Revolutionizing Few-Shot Learning in Large Language Models by Learning from Mistakes

Retrieval Augmented Generation (RAG) has revolutionized open-domain question answering by using a retrieval module to find relevant context passages and a generative module to provide answers. However, vector search, one of the critical components, has limitations…

Graph Attention Inference for Network Topology Discovery in Multi-Agent Systems (MAS) Practical Solutions and Value The study presents a unique Machine Learning (ML) strategy to understand and manage multi-agent systems (MAS) by identifying their underlying graph…

Revolutionizing Creativity with Generative AI Introduction to Generative AI Models Generative AI models, including Large Language Models (LLMs) and diffusion techniques, are changing creative fields such as art and entertainment. These models can create a wide…

Researchers from Zhipu AI and Tsinghua University have introduced CogVLM, an open-source visual language model that aims to enhance the integration between language and visual information. This model achieves state-of-the-art or near-best performance on various cross-modal…

As an analyst, to make impactful product changes, follow best practices and insights shared in the detailed guide available on the “Towards Data Science” platform.

Deep Learning models have transformed data processing but struggle with binary data. Researchers introduce bGPT, a model that efficiently processes bytes, offering vast potential in areas like malware detection and music conversion. Its accurate digital system…

Bing Chat, Microsoft’s AI-driven search tool, has vulnerabilities that allow for the integration of malicious ads, potentially leading users to phishing sites and malware downloads. Malwarebytes has alerted Microsoft, but no action has been taken. Actions…

Perplexity AI, a revolutionary search engine, raised $73.6 million in funding, increasing its valuation to $520 million. The investment, led by IVP and involving influential tech leaders like Jeff Bezos, signifies strong endorsement. With an innovative…

The Importance of Theory of Mind in AI Theory of Mind (ToM) is the ability to understand others’ mental states and predict their behaviors. This capability is becoming essential as Large Language Models (LLMs) are increasingly…

Building an Interactive Multimodal Image-Captioning Application In this tutorial, we will guide you on creating an interactive multimodal image-captioning application using Google’s Colab platform, Salesforce’s BLIP model, and Streamlit for a user-friendly web interface. Multimodal models,…

Practical AI Solutions in Language Modeling Efficient Language Modeling Language modeling in machine learning predicts word sequences, enhancing applications like text summarization, translation, and auto-completion. Large models face challenges with computational and memory overhead, hindering scalability…

The GovAI Summit 2023, on December 5-6 in Arlington, VA, will explore AI’s public sector impact, featuring keynotes by AI experts and industry leaders. Lane Dilg from OpenAI and others will discuss AI’s role in government,…

AI relies on data, but its legal and ethical origins are often unclear. Large language models like LLM require substantial amounts of text data, which can be found on platforms like Kaggle, GitHub, and Hugging Face.…

Microsoft AI Releases Phi 3.5 Mini, MoE, and Vision Phi 3.5 Mini Instruct: Balancing Power and Efficiency Phi 3.5 Mini Instruct is a compact model with 3.8 billion parameters, supporting 128K context length for handling long…

Large Language Models (LLMs) have expanded into multimodal tasks, particularly in video grounding (VG). The precision of temporal boundary localization in VG presents a core challenge for LLMs. Traditional VG methods are limited by specialized training…

Advancing AI Research with PEER Architecture Addressing Computational Challenges in Transformer Models In transformer architectures, the computational costs and activation memory grow linearly with the increase in the hidden layer width of feedforward (FFW) layers. This…

Understanding Vision-Language Models (VLMs) Vision-language models (VLMs) are becoming essential in AI because they combine visual and textual information. They are useful in areas like video analysis, human-computer interaction, and multimedia, enabling tasks such as answering…

AI’s effectiveness heavily relies on data availability for training purposes. However, a study by University of Toronto Engineering researchers suggests that deep learning models may not always require a lot of training data. The researchers found…