My Courses
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Mastering the Art of Mitigating AI Hallucinations
AI hallucinations challenge generative models’ reliability in critical applications. Learn about advanced mitigation techniques, including RLHF, RAG, and real-time fact-checking, to enhance accuracy and trustworthiness.
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Exploring LLMs Reasoning Capability with DeepSeek-R1
DeepSeek-R1 harnesses reinforcement learning to achieve cutting-edge reasoning capabilities, outperforming traditional SFT approaches. Discover its architecture, training methods, and real-world applications in AI advancements.
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Google’s Titans for Redefining Neural Memory with Persistent Learning at Test Time
Titans redefine neural memory by integrating short- and long-term components for efficient retention and retrieval. This article explores its architecture, innovations, and transformative potential across AI applications.
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A Deep Dive into Cache Augmented Generation (CAG)
CAG eliminates retrieval latency and simplifies knowledge workflows by preloading and caching context. Learn how this innovative paradigm improves accuracy and efficiency in language generation tasks.
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A Hands-on Guide to Multilingual Visual Document Retrieval with VDR-2B-Multi-V1
vdr-2b-multi-v1 transforms visual document retrieval with multilingual embeddings, faster inference, and reduced VRAM usage. This article delves into its architecture, training, and groundbreaking applications.
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Knowledge Augmented Generation (KAG) By Combining RAG with Knowledge Graphs
Knowledge Augmented Generation combines knowledge graphs and language models to deliver accurate, logical, and domain-specific AI solutions.
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A Deep Dive into NVIDIA Cosmos and Its Capabilities
NVIDIA Cosmos revolutionizes Physical AI with digital twins and cutting-edge training methodologies. This article explores its architecture, training techniques, and transformative applications across robotics, autonomous driving, and more.
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Interview with Sai Srikanth Gorthy, Chartered Data Scientist – A Data Science Visionary
Sai Srikanth Gorthy shares his journey, achievements, and insights after earning the prestigious CDS credential.
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Understanding FLAME, The Factuality Aware Alignment for LLMs
Large Language Models often struggle with factual inaccuracies, or hallucinations, despite their advanced instruction-following abilities. In this article, we explore how FLAME—a novel alignment method—addresses these challenges using innovative training techniques, ensuring dependable AI-generated responses.
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A Deep Dive into Large Concept Models (LCMs)
Large Concept Models (LCMs) revolutionize NLP with semantic reasoning, hierarchical processing, and cross-modal integration. This article explores their design and applications.
