At AI Lab, we create smart AI tools that help you streamline your business and improve customer interactions. Our tailor-made solutions free up your time, letting you focus on what you do best – growing your business.
Enhance your customer support with our AI-powered assistant. It uses artificial intelligence to analyze documents, contracts, and previous interactions, reducing response times and providing personalized support. Empower your team, improve customer satisfaction.
Unlock valuable insights and make data-driven decisions with our AI Insights Suite. We index all your documents and data. Get smart decision support with our AI-driven solution. It indexes documents, offers valuable insights, and assists in making informed choices, saving you time and boosting productivity.
Streamline your agile project management with our AI Scrum Bot. This intelligent assistant helps teams by answering questions, facilitating backlog management, and organizing retrospectives. Powered by artificial intelligence, it enhances collaboration, efficiency, and productivity in your scrum process.
AI Sales Bot – your new teammate that never sleeps! It converses with customers in fully natural language across all channels, answers questions round the clock, and learns from your sales materials to keep conversations insightful and engaging. It’s your next step towards simplified, efficient, and enhanced customer interactions and sales processes.
We specialize in crafting unique AI applications to meet your specific needs. Whether it’s machine learning or natural language processing, we’ve got the right AI solution to help you achieve your business goals.
PyTorch 2.5: Enhancing Machine Learning Efficiency Key Improvements The PyTorch community is dedicated to improving machine learning frameworks for researchers and AI engineers. The new PyTorch 2.5 release focuses on: Boosting computational efficiency Reducing startup times Enhancing performance scalability Practical Solutions This release introduces several valuable features: CuDNN backend for Scaled Dot Product Attention (SDPA):…
Overcoming Challenges with Large Language Models Organizations often struggle to implement Large Language Models (LLMs) for complex workflows. Issues such as speed, flexibility, and scalability make it hard to automate processes that need coordination across different systems. Configuring LLMs for smooth collaboration can be cumbersome, impacting operational efficiency. Katanemo’s Solution: Arch-Function Katanemo has open-sourced Arch-Function,…
Understanding Large Language Models (LLMs) and In-Context Learning What are LLMs and ICL? Large Language Models (LLMs) are advanced AI tools that can learn and complete tasks by using a few examples provided in a prompt. This is known as In-Context Learning (ICL). A significant feature of ICL is that LLMs can handle multiple tasks…
Growing Need for Efficient AI Models There is an increasing demand for AI models that provide a good balance of accuracy, efficiency, and versatility. Many existing models face challenges in meeting these needs, especially in both small-scale and large-scale applications. This has led to the development of new, more efficient solutions for high-quality embeddings. Overview…
Flexible and Efficient Adaptation of Large Language Models (LLMs) Challenges with Existing Approaches Current methods like mixture-of-experts (MoE) and model arithmetic face challenges. They require a lot of tuning data, have inflexible models, and make strong assumptions about model usage. This creates a need for a better way to adapt LLMs efficiently, especially when data…
Understanding the Evolving Role of Artificial Intelligence Artificial Intelligence (AI) is rapidly advancing. Large Language Models (LLMs) can understand human text and even generate code. However, assessing the quality of this code can be difficult as complexity increases. This is where CodeJudge comes in, offering a strong framework for code evaluation. Challenges with Traditional Code…
Mobile Vehicle-to-Microgrid (V2M) Services Mobile V2M services allow electric vehicles to provide or store energy for local power grids. This enhances grid stability and flexibility. AI plays a vital role in optimizing energy distribution, predicting demand, and managing real-time interactions between vehicles and the microgrid. Challenges with AI in V2M Services However, AI algorithms can…
Enhancing IoT with AI: The IoT-LLM Framework Growing sectors like Healthcare, Logistics, and Smart Cities rely on interconnected devices that need advanced reasoning capabilities. To address this, researchers are integrating real-time data and context into Large Language Models (LLMs). Traditional LLMs struggle with complex real-world tasks, leading to inaccurate results. The MARS Lab at NTU…
Understanding Meissonic: A Breakthrough in Text-to-Image Synthesis What are Large Language Models and Diffusion Models? Large Language Models (LLMs) have advanced the way we process language, leading researchers to apply similar methods to create images from text. Currently, diffusion models are the leading technology for generating visuals. However, merging these two approaches poses challenges. Challenges…
Challenges in Current Generative AI Models Current generative AI models struggle with issues like reliability, accuracy, efficiency, and cost. There is a clear need for better solutions that can provide precise results for various AI applications. Nvidia’s Nemotron 70B Model Nvidia has launched the Nemotron 70B Model, setting a new standard for large language models…
Our teams are a diverse group of talented individuals working remotely from different corners of the world. With members proficient in seven languages, we value and embrace diversity. However, what truly unites us is our shared passion for the language of modern technology. We come together to collaborate, innovate, and harness the power of cutting-edge technology to create exceptional solutions.