Large Language Models (LLMs) have transformed artificial intelligence by enabling powerful text-generation capabilities. These models require strong security against critical risks such as prompt injection, model poisoning, data leakage, hallucinations, and jailbreaks. These vulnerabilities expose organizations to potential reputational damage, financial loss, and societal harm. Building a secure environment is essential to ensure the safe…
Neural networks have traditionally operated as static models with fixed structures and parameters once trained, a limitation that hinders their adaptability to new or unforeseen scenarios. Deploying these models in varied environments often requires designing and teaching new configurations, a resource-intensive process. While flexible models and network pruning have been explored to address these challenges,…
Google has introduced a ‘memory’ feature for its Gemini Advanced chatbot, enabling it to remember user preferences and interests for a more personalized interaction experience. This feature is available exclusively to Google One AI Premium Plan subscribers, and it is part of Google’s effort to make its AI tools more responsive and user-centric. Personalized Interactions…
AI-driven solutions are advancing rapidly, yet managing multiple AI agents and ensuring coherent interactions between them remains challenging. Whether for chatbots, voice assistants, or other AI systems, tracking context across multiple agents, routing large language model (LLM) queries, and integrating new agents into existing infrastructures present persistent difficulties. Moreover, many solutions lack the flexibility to…
The machine learning community faces a significant challenge in audio and music applications: the lack of a diverse, open, and large-scale dataset that researchers can freely access for developing foundation models. Despite advances in image and text-based AI research, the audio domain lags due to the absence of comprehensive datasets comparable to those available for…
Natural Language to SQL (NL2SQL) technology has emerged as a transformative aspect of natural language processing (NLP), enabling users to convert human language queries into Structured Query Language (SQL) statements. This development has made it easier for individuals who need more technical expertise to interact with complex databases and retrieve valuable insights. By bridging the…
Planning and decision-making in complex, partially observed environments is a significant challenge in embodied AI. Traditionally, embodied agents rely on physical exploration to gather more information, which can be time-consuming and impractical, especially in large-scale, dynamic environments. For instance, autonomous driving or navigation in urban settings often demands the agent to make quick decisions based…
Using large language models (LLMs) has revolutionized artificial intelligence applications, enabling breakthroughs in natural language processing tasks like conversational AI, content generation, and automated code completion. Often with billions of parameters, these models rely on massive memory resources to store intermediate computation states and large key-value caches during inference. These models’ computational intensity and growing…
Log-based anomaly detection has become essential for improving software system reliability by identifying issues from log data. However, traditional deep learning methods often struggle to interpret the semantic details in log data, typically in natural language. LLMs, like GPT-4 and Llama 3, have shown promise in handling such tasks due to their advanced language comprehension.…
Effective lesson structuring remains a critical challenge in educational settings, particularly when conversations and tutoring sessions need to address predefined topics or worksheet problems. Educators face the complex task of optimally allocating time across different problems while accommodating diverse student learning needs. This challenge is especially pronounced for novice teachers and those managing large student…