phospho (YC W24)’s Post

🙌 Presenting MEGAnno+, a cost-efficient way to label data using LLMs! LLM-human collaboration on data annotation can alleviate the headache and time consumption of data annotation. Try the MEGAnno+ demo 👉 https://meganno.github.io/ #MEGAnno #LLMs #annotation #phd #nlproc #ai #MachineLearning #datascience #phdlife #data

I'm thrilled to announce an innovative integration between Langtrace, our cutting-edge open-source observability platform, and Pinecone, the premier vector database! This collaboration brings effortless observability to Pinecone-based applications, offering developers a suite of tools to supercharge performance, reliability, and user experience. Here’s what you can achieve with Langtrace and Pinecone: - Deep Insights: Visualize query execution times, uncover latency hotspots, and monitor resource utilization effortlessly. - Enhanced Analysis: Leverage OpenTelemetry to analyze traces, evals, metrics, and logs. - Community Power: Join a vibrant, community-driven project and play a key role in shaping the future of observability for vector databases. More info on how to get started in comments. https://lnkd.in/dFJg3F2U

MEGAnno, our human-LLM collaborative annotation framework. To read more https://lnkd.in/gAs7CcUr. Note that we have a demo notebook so you can try it out. Instructions and access request form at the bottom of page. #llm #annotation

LangChain with LangGraph is a cutting edge research in action for agentic workflows. Agentic Memory, persistence, human in the loop feedback, in addition to tools is what makes multi-agent workflows actually work and be production-ready. https://lnkd.in/eRdZc9Hb

I prepared a paragraph on how to use YOLOv10, one of the biggest of the non-stop artificial intelligence developments, effectively with OpenVINO! Thank you for your interest. #OpenVINO #YOLO #YOLOv10 #CPU #AI #ObjectDetection

What Are The Three Levels Of Computer Vision? "Uncover the three levels of computer vision and their transformative impact on technology." #ComputerVision #ArtificialIntelligence #AI #MachineLearning #TechExplained #DataScience #DeepLearning #TechInnovation #SmartTech #TechTrends #FutureTech #ImageRecognition #AIApplied #DigitalTransformation #Innovation https://lnkd.in/ee5FADHC

Artjom Shestajev and I attended last week’s LLM Slush Side event hosted by Valohai and Root Signals in Helsinki 🇫🇮, and we came back with a few takeaways: 1) While LLMs are becoming increasingly popular, the panelists haven’t seen any real production use cases in enterprises beyond the POC level. Those that are emerging are mostly internal-facing scenarios. Tools like LlamaIndex make it easy to prototype and this is how everyone is trying to ride the wave. 2) Exploration mostly happens around prompt-engineering with some companies looking into RAG. Very few advances towards fine-tuning or deep-train so far. 3) Having control over your own data, cost, performance, and service may be worthwhile if you want to lower your risks and dependency on external companies. This would require extensive knowledge and investment, i.e. typical “buy vs build” problem. 4) The field is evolving very quickly. A paper you read last week may be obsolete this week. The service you used yesterday may be gone tomorrow. This results in a pressure towards product and development teams and requires a careful assessment of ML tech being adopted If you want to take your LLM POCs to the next level, check out Clarifai - we would love to help you put that into production using our full stack production-grade AI platform 🚀 #clarifai #developers #generativeAI #llms

#Day22 of #100DaysOfGenAI Today, I delved into the concept of LLMOps, which focuses on the operational management of large language models, and explored Vext, a platform designed to simplify the LLM pipeline. Vext provides a suite of tools that make deploying, maintaining, and scaling LLMs more efficient. By streamlining the complexities of LLM workflows, Vext ensures smoother integration of these models into real-world applications. Understanding platforms like Vext is becoming increasingly important as the role of LLMs expands across various industries. This knowledge enhances my ability to work effectively with advanced AI systems, ensuring they operate at peak efficiency in production environments. Vext: https://vextapp.com #LLMOps #MachineLearning #AI #DeepLearning #LLM #Vext #100DaysOfCode

Fine-tuning LLMs is tasking and complicated. If you don't have an in-depth knowledge about LLMs, you will find it difficult. However, there's a framework that makes this easy with just a few lines of code. It doesn't just fine-tune LLMs but helps: ▫️Generate data ▫️Estimate costs for fine-tuning and ▫️Evaluate the model. It's absolutely beautiful to see how this works. The framework is #scalexi built by Dr. Anis Koubaa and his profound team. You can check his profile for more about this framework. #llms #artificialintelligence #aiwithtee #generativeai #finetuning

Welcome back, fellow futurists, to our final episode in this enlightening AI generated series! Today, we're delving into Conflict-Free Replicated Data Types, or CRDTs, a cornerstone in managing data within distributed systems where concurrent user interactions are the norm. CRDTs are ingeniously designed to handle multiple simultaneous updates by different nodes, without the need for immediate coordination, ensuring data remains consistent and conflict-free across the board. This functionality is pivotal in applications requiring real-time collaboration and high concurrency, such as collaborative text editors and dynamic e-commerce platforms. We will explore how CRDTs seamlessly integrate changes from various users, maintaining data integrity and continuity even under complex operating conditions. Their role in modern distributed systems is not just beneficial but essential, transforming the landscape of real-time, collaborative data interactions. So, let’s uncover the mechanics of CRDTs and their profound impact on digital ecosystems. What challenges do you think CRDTs can solve in your current projects? Join the conversation and share your insights as we wrap up this series!