InTDS ArchivebyDr. Leon EversbergHow to Improve LLM Responses With Better Sampling ParametersA deep dive into stochastic decoding with temperature, top_p, top_k, and min_pSep 2, 20245097Sep 2, 20245097
InTDS ArchivebyHans Christian EkneExploring the Strategic Capabilities of LLMs in a Risk Game SettingIn a simulated Risk environment, large language models from Anthropic, OpenAI, and Meta showcase distinct strategic behaviors, with Claude…Aug 27, 20246098Aug 27, 20246098
InTDS ArchivebyKatherine MunroNo Baseline? No Benchmarks? No Biggie! An Experimental Approach to Agile Chatbot DevelopmentLessons learned bringing LLM-based products to productionAug 26, 2024147Aug 26, 2024147
InTDS ArchivebyLina FaikFrom Text to Networks: The Revolutionary Impact of LLMs on Knowledge GraphsA Step-by-Step Guide to Building and Leveraging Knowledge Graphs with LLMsAug 29, 20243802Aug 29, 20243802
InTDS ArchivebyOzgur GulerTackle Complex LLM Decision-Making with Language Agent Tree Search (LATS) & GPT-4oEnhancing LLM Decision-Making: Integrating Language Agent Tree Search with GPT-4o for Superior Problem SolvingAug 26, 2024121Aug 26, 2024121
InTDS ArchivebyAparna DhinakaranNavigating the New Types of LLM Agents and ArchitecturesThe failure of ReAct agents gives way to a new generation of agents — and possibilitiesAug 30, 20241.6K9Aug 30, 20241.6K9
Vipra SinghLLM Architectures Explained: Word Embeddings (Part 2)Deep Dive into the architecture & building real-world applications leveraging NLP Models starting from RNN to Transformer.Aug 18, 20247499Aug 18, 20247499
InTDS ArchivebyAlmog BakuThe LLM Triangle Principles to Architect Reliable AI AppsSoftware design principles for thoughtfully designing reliable, high-performing LLM applicationsJul 16, 20245.6K14Jul 16, 20245.6K14
InTDS ArchivebyDr. Leon EversbergHow to Use Hybrid Search for Better LLM RAG RetrievalBuilding an advanced local LLM RAG pipeline by combining dense embeddings with BM25Aug 11, 20241K5Aug 11, 20241K5
Vipra SinghLLM Architectures Explained: NLP Fundamentals (Part 1)Deep Dive into the architecture & building of real-world applications leveraging NLP Models starting from RNN to the Transformers.Aug 15, 20242.6K25Aug 15, 20242.6K25
InArtificial Intelligence in Plain EnglishbyAndrew BestWhy OpenAI’s “Strawberry” is a GAME CHANGER!This is a big step closer to AGI.Aug 9, 20241.6K34Aug 9, 20241.6K34
InData Science CollectivebyAhmed BesbesWhat Nobody Tells You About RAGsA deep dive into why RAG doesn’t always work as expected: an overview of the business value, the data, and the technology behind it.Aug 23, 20241.93K29Aug 23, 20241.93K29
InTowards AIbyMandar Karhade, MD. PhD.Why RAG Applications Fail in ProductionIt worked as a prototype; then all went down!Mar 19, 20242.5K30Mar 19, 20242.5K30
InTowards AIbyChristopher TaoDo Not Use LLM or Generative AI For These Use CasesChoose correct AI techniques for the right use case familiesAug 10, 20244.3K46Aug 10, 20244.3K46
InTDS ArchivebyTarik DzekmanWhat Do Large Language Models “Understand”?A deep dive on the meaning of understanding and how it applies to LLMsAug 21, 20247268Aug 21, 20247268