Hanan Tabak’s Post

Exciting News! PyGraft, the powerful tool for generating synthetic Knowledge Graphs, is here to supercharge your data-driven projects. Discover how it empowers your research, enables precise benchmarking, and opens doors to new possibilities. Read the full story now! #PyGraft #KnowledgeGraphs #DataScience #AI #SemanticWeb #Research #Innovation" Link: https://lnkd.in/emj3yYRF

Unstructured Data to Knowledge Graph Construction - LLMs are helpful in extracting the the Entities, relationships from Text to develop a Knowledge Graph. However the it is a costly procedure and often gives us Shallow relationships leading to poor performance. Sciphi released a custom LLM trained on creating Graph Knowledge data from text. Read more on https://lnkd.in/gYeKgkup #graphrag #llms #ai

Getting AI to understand and utilise your private organisational data is one of the most important things you can get right in 2024 to accelerate your business’ journey to reinventing itself with AI. If you’re building AI apps which don’t draw on your business’ unique knowhow or data, you’re likely competing with someone with a massive budget and their entire business focused on the solving exactly the same problem. You’d be better just buying their software when they’re done! The companies who make the most headway will be the ones focused on unlocking the value in their unique datasets. Not only will that drive huge value in the immediate use cases, it’ll also massively accelerate their entire AI transformation as they build an AI platform which can be utilised across the organisation. If you want you get this right, check out this article by my Tomoro co-founder Rishabh on when to choose Knowledge graphs or other RAG techniques, or his previous blog outlining how to get these techniques working for organisational data. Choosing the correct RAG approach - https://lnkd.in/eBYv_5nP Using Knowledge Graphs to access organisational data - https://lnkd.in/eSee5n4U Or follow Tomoro for regular LLM insights #genai #ai #aiadoption #autonomousagents

knowledge graphs in RAG, These systems are basically solving the "I know a lot, but I don't know what I know" problem for AI. Think of it like giving the AI a super-organized mental map. It helps the AI connect the dots between different pieces of info, which is huge for answering complex questions or understanding context. Plus, it's a game-changer for fact-checking – the AI can actually verify its own output against a structured knowledge base. This setup also helps with the hallucination issue that plagues a lot of LLMs. By grounding responses in a knowledge graph, we're reducing those wild, made-up answers. And here's a cool bit: it allows for more transparent AI. You can actually trace back how the AI came to its conclusions by looking at the graph pathways it used. Key takeaways: Improves context understanding Enables complex reasoning Reduces hallucinations Enhances fact-checking capabilities Increases transparency and explainability https://lnkd.in/eKdwfy9n

The emergence of generative AI has made data even more valuable to organizations looking to develop large language models. Discover how vector databases power #LLMs and their intriguing connection to #AI. https://hubs.la/Q02bqR8B0

As we introduced TigerGraph CoPilot to a few customers, we discovered a common theme: many had not previously utilized #generative #AI in conjunction with their #knowledgegraphs. Integrating generative AI requires the AI, through a large language model (#LLM), to "understand" your knowledge graph. Read this blog and explore how the CoPilot is setting new standards in leveraging AI to enhance knowledge graph interactions. #AI #GenerativeAI #KnowledgeGraph #TechInnovation

As we introduced TigerGraph CoPilot to a few customers, we discovered a common theme: many had not previously utilized #generative #AI in conjunction with their #knowledgegraphs. Integrating generative AI requires the AI, through a large language model (#LLM), to "understand" your knowledge graph. Read this blog and explore how the CoPilot is setting new standards in leveraging AI to enhance knowledge graph interactions. #AI #GenerativeAI #KnowledgeGraph #TechInnovation

While advancements in technology, automation, and artificial intelligence continue to shape various industries, the role of data engineers remains crucial. The human element in data engineering involves critical thinking, problem-solving, and decision-making skills that are challenging to replicate with full automation. Equitus KGNN enables and empowers data experts within the enterprise by making it easier to uncover and visualize the goldmine of data residing within your own proprietary technology stack.  THE KGNN system, using machine learning and AI, automates entity extraction and link generation into the knowledge graphs that exist within the data fabric, organizing and priming that data for optimal smart querying. Data experts report more accurately and confidently based on enhanced decision making capabilities within the #KGNN system. #EquitusAI. #KGNN #OpenFabric #NovusPointAI #AI #nextgenai

RAG is an important technique, but there are many questions it simply can’t answer. How LlamaIndex is helping provide those answers. #AI #ArtificialIntelligence #GenerativeAI

🔍 Unlock the true potential of data analytics with Jeda.ai's Generative AI DataGPT!  📈 Seamlessly process and analyze up to 100 MB of CSV, Excel, and big data. 👉 Try at https://lnkd.in/gYU2Jxpy #JedaAI #GenerativeAI #AI #DataGPT #Data #Analysis #DataScience