LLM 技术 - Transformer 与 Mixture of Experts (MoE) 在 LLMs 中的对比分析 [1] - 行业关注 DS (数据科学), ML (机器学习), LLMs (大型语言模型), 和 RAGs (检索增强生成) 的教程和见解 [1] 社交媒体互动 - 鼓励用户分享信息 [1] - 行业专家 Avi Chawla 在社交媒体上分享相关内容 [1]

Technology & Software Deployment - Containerized versions of 450+ MCP servers are available in a single repository [1] - The solution offers an easy and safe way to use MCP servers with Agents [1] - No manual setup is required; users can simply pull the image [1] - The solution is safe to run in isolated containers, unlike scripts [1] - The solution is auto-updated daily [1]

If you found it insightful, reshare it with your network.Find me → @_avichawlaEvery day, I share tutorials and insights on DS, ML, LLMs, and RAGs.Avi Chawla (@_avichawla):A great tool to estimate how much VRAM your LLMs actually need.Alter the hardware config, quantization, etc., and get to know about:- Generation speed (tokens/sec)- Precise memory allocation- System throughput, etc.No more VRAM guessing! https://t.co/lZbIink12f ...

A great tool to estimate how much VRAM your LLMs actually need.Alter the hardware config, quantization, etc., and get to know about:- Generation speed (tokens/sec)- Precise memory allocation- System throughput, etc.No more VRAM guessing! https://t.co/lZbIink12f ...

AI and Automation in Unstructured Data Processing - AI is expected to significantly drive automation, potentially replacing Robotic Process Automation (RPA) [2][56] - The industry is moving towards decentralized, federated AI execution for automation [2][55][56] - Enterprises are exploring AI-driven automation for end-to-end workflows, potentially replacing RPA [62] Challenges and Solutions for Unstructured Data - Unstructured data is defined as anything that cannot be put into a nice database table for SQL queries, such as PDF documents or images [3][4] - Traditional techniques for processing unstructured data, like templates and rule-based systems, are brittle and unreliable [7][8] - A key challenge is ensuring reliability, completeness, and accuracy when using Large Language Models (LLMs) for unstructured data processing, especially in critical decision-making processes [18][19][24][25] - The industry emphasizes the need for complex, explainable, and auditable workflows to guarantee accuracy when using LLMs with unstructured data [24] Enterprise Adoption and Requirements - Enterprises prioritize data safety, security, auditability, and predictability when adopting AI solutions [42][43] - Predictability of errors is more important than achieving 100% accuracy; enterprises need to know which cases require human review [28][30][31] - Enterprises are adapting their acceptance criteria for AI, focusing on improvements over human performance rather than absolute perfection [27] The Role of AI Agents - AI agents can assist during the build or compile time by generating initial drafts of workflows, but runtime execution should remain deterministic and auditable [48][49][50][65][66] - The industry views autonomous agents as a compile-time phenomenon, where they aid in creating artifacts for deterministic runtime execution [49] Transforming Customer Experience - AI is enabling new, conversational customer interactions, such as lending over WhatsApp [36] - AI can transform processes like insurance claims and account openings, making them more interactive and user-friendly [37][38][39]

If you found it insightful, reshare it with your network.Find me → @_avichawlaEvery day, I share tutorials and insights on DS, ML, LLMs, and RAGs.Avi Chawla (@_avichawla):9 MCP projects for AI engineers (with code): ...

If you found it insightful, reshare it with your network.Find me → @_avichawlaEvery day, I share tutorials and insights on DS, ML, LLMs, and RAGs.Avi Chawla (@_avichawla):OpenAI meets MCP!Now you can add tools from any MCP server to your OpenAI LLM calls.Below, I integrated the @MindsDB MCP server, which lets you query 200+ data sources in plain English or SQL.Takes just 3-5 lines of code! https://t.co/uzbBEq61AD ...

If you found it insightful, reshare it with your network.Find me → @_avichawlaEvery day, I share tutorials and insights on DS, ML, LLMs, and RAGs.Avi Chawla (@_avichawla):Train AI models on data that does not even exist!SDV is an open-source framework that uses ML to learn patterns from your real data and generate tabular synthetic data at scale.Supports built-in anonymization, validation, and more. https://t.co/KyTZsaILvh ...