Soham Nandi

Computer Science Engineering, specializing in Artificial Intelligence and Machine learning

Soham Nandi is a technical writer based in Memari, India. His academic background is in Computer Science Engineering, specializing in Artificial Intelligence and Machine learning. He has extensive experience in Data Analytics, Machine Learning, and Python. He has worked on group projects that required the implementation of Computer Vision, Image Classification, and App Development.

Soham's passion for AI and Machine Learning propels him toward his goal of becoming a distinguished Machine Learning Engineer and leveraging his knowledge to help the less fortunate. His projects include the Rice grain classifier and Handwriting-based Personality Detector, and he is certified in Data Analytics and Data Science.

Drawing inspiration from writers ranging from Satyajit Ray to Mark Manson, he has his own science fiction stories and blog. He also creates content on personal development and mental health through his Instagram handle. Beyond the screen and code, Soham's world is filled with music. With the ability to play the guitar, ukulele, and drums, he rocks to the tunes of the metal and rock genres, using music as a creative outlet, planning to start a band of his own.

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Articles from Soham

Meta GenAI Boosts AI Learning with CGPO, Tackling Reward Hacking and Improving Multi-Task Performance

Researchers at Meta GenAI introduced CGPO, a new post-training method for reinforcement learning that outperforms existing techniques by addressing reward hacking and optimizing multi-task learning. CGPO showed superior performance across benchmarks in chat, coding, and STEM tasks.

7 Oct 2024

Lotus Model Advances Dense Prediction with State-of-the-Art Efficiency and Precision

Researchers introduce Lotus, a novel diffusion-based model that revolutionizes dense prediction tasks by boosting accuracy and efficiency through single-step diffusion and advanced parameterization strategies.

3 Oct 2024

AI Outperforms Humans in Creative Tasks But Still Needs Human Input to Excel

Research reveals that AI can outperform humans in certain creative tasks, but human input is still crucial to fully harness AI's creative potential, especially in originality-focused challenges.

3 Oct 2024

Machine Learning Model Enhances Drone Formation Stability and Accuracy

Researchers developed a machine learning model using CatBoost to predict disturbances in drone formations with an R² of 83.3%, significantly improving from the previous baseline of 54%. The SHAP method was applied for better model explainability, aiding UAV operators in minimizing disruptions.

2 Oct 2024

Vision-Language Models Bring Comic Panels to Life, Enhancing Accessibility for Visually Impaired Readers

Researchers developed a vision-language model pipeline that generates dense, grounded captions for comic panels, improving accessibility and understanding for visually impaired individuals. Their approach annotated over 2 million comic panels, advancing computational comic analysis.

30 Sep 2024

Scaling Large Language Models Makes Them Less Reliable, Producing Confident but Incorrect Answers

Researchers found that as large language models (LLMs) scale, they become less reliable, making errors even on simple tasks, and producing plausible but incorrect answers to complex questions. The study emphasizes the need for better strategies in AI development, especially for high-stakes applications.

29 Sep 2024