We're so back! ??
We’re excited to announce that Latitude is live on Product Hunt! ?? Latitude is the open-source prompt engineering platform to build, evaluate, and refine your prompts with AI. Proud to be building this alongside Gerard Clos and the amazing team. We’d greatly appreciate your support! ???https://lnkd.in/egitH3-4
We’re pumped to unveil Arpeely’s Engineering Blog! ? arpeely.com/blog Arpeely runs on pretty wild tech - TBs of daily traffic, Billions of real-time predictions, and of course 400 Tons of AI??? To get there, we made a lot of mistakes, learned lessons, and gained insights - we want to share these with our fellow R&D community. To kick it off, read about some tools we use for Go Optimization(Yoav Jacobson) and some tricks for better BigQuery collaboration (Or Yarnitzky). Stay updated here or on our DailyDev squad >> https://lnkd.in/dggF8Zej
Spotted: FLUX.1 ?? Our developers are constantly on the look-out for new, state-of-the-art technology releases and yesterday, the original Stable Diffusion creators launched a new company, Black Forest Labs, and their first open-source image generation model, FLUX.1. Our first impressions: → Very high-quality image generation → Insanely good at generating written words (including our tagline) → Flux is able to understand and generate complex compositions → Hands that look like hands! Good news for the open-source image generation community. We're looking forward to testing this new model further. ???? #flux1 #blackforestlabs #generativeAI
?? New Video Content!??? Milo? ?vaňa's latest video, "MLflow: Serving LLMs and Prompt Engineering", is now live! If you're working with large language models (LLMs), this is a must-watch! In this video, Milo? dives into the MLflow features designed specifically for LLMs. You'll take a closer look at the LLM deployment server and MLflow's prompt engineering interface. Plus, Milo? includes a hands-on experiment demo to help you grasp these concepts in practice. Don't miss out – watch the video now and stay ahead in the AI game!?? https://lnkd.in/e3EDkjp2 ???Note:?For a complete understanding, make sure to watch our previous video on evaluating LLMs with MLflow first.
Exciting news! ?? This marks my first granted patent with Iterate.ai and the sixth overall for the company. It’s an honor to be part of a team that truly encourages innovation and supports groundbreaking ideas. Here’s to many more milestones ahead! ??? #Innovation #Patent #Grateful #TechInnovation #ArtificialIntelligence #TechPatents #InnovationInTech
Co-founder, CEO @ Iterate.ai (est 2013) + eBags.com (est 1998, $1.65 bn sold pre-acquisition)
Iterate.ai just received its 6th patent grant from the US Patent Office. Coincidentally, this patent was granted on the same day?Fast Company?recognized us as one of the world's #BestWorkplaces for #Innovators. A few other patents granted to Iterate.ai include: ? Container Architecture for Modular Machine Learning* ? Developer Independent Resource Based Multithreading Module ? Data Pipeline and Access Across Multiple Machine Learned Models * Internally, we call this one Drag-n-Drop AI. We have many more pending patents. They are "AI and generative AI" applications: ?? Language Independent Textual Extraction ?? Generation of Entity Plans Comprising Goals and Nodes ?? Large Language Modules In Modular Programming ?? Dynamic Polygon Systems For Deep Object Detection ?? Fusion Between Computer Vision Object Detection and Radar Object Detection Our Iterate team is excited by "Dreaming and then Doing." A big thank you to our patent attorneys Gina Cornelio, Amy Mapes, and their team. #FCBestWorkplaces #FastCompany Niharika Shukla . Mike Frazzini . Brian Sathianathan
Software Engineer | Ex-Google & Oracle | Integrating Cutting-Edge ML Solutions with Microservices & Cloud Technology
?? Exciting News! I’ve just launched an open-source Flowable Docs LLaMA model to help developers explore and build Flowable-based solutions. ?? With our model fine-tuned on Flowable documentation, it’s designed to answer questions and offer insights into Flowable’s capabilities. ?? Model on Hugging Face Hub: https://lnkd.in/g-CBhp4P ?? GitHub Repository: https://lnkd.in/gvS_GZ6g ?? Docker Image: Run a web UI to interact with the model right from your desktop. https://lnkd.in/gNWTjmYx Get Started: To launch the model locally: 1. Pull and Start: docker run -p 7860:7860 zzzmahesh/flowable-docs-llama-3.2-1b 2. Access the Interface: Open your browser and go to https://localhost:7860 to start exploring Flowable’s features! This resource is perfect for developers and teams looking to learn more about Flowable or experiment with its documentation in an interactive way. Happy experimenting! ??? ?? Note: We also have a larger model for those interested in more complex tasks! Check out the 3B parameter version here: https://lnkd.in/gZct2pdm #OpenSource #MachineLearning #Flowable #AI #LLaMA #HuggingFace #Docker #DevOps #Innovation #bpmn #conversationalKnowledge #conversationalbpmn #mlbpmn #aibpmn
Just finished "Prompt Engineering: How to Talk to the AIs" by Xavier Amatriain! Check it out: https://lnkd.in/e5XAwhXd #generativeai, #largelanguagemodels, #promptengineering. My
This week on Florida Tech & Growth, presented by Tiro Partners, we discuss the Impact of AI on Software Engineering. This is not one to be missed. Check out the promo video here. Follow Florida Tech & Growth and Paul Church so you don't miss it! #ai #florida #softwareengineering
We are big fans of YOLO11 ? Its best features include: ??. ???????????????? ????????????????????????: Ultralytics YOLO11 introduces a refined architecture that includes new components like the C3k2 block and C2PSA (Channel-wise and Spatial Attention), which improve feature extraction and attention to critical image areas. This design allows for better detection of smaller or occluded objects compared to its predecessors. ??. ??????????-???????? ????????????????????????: Unlike earlier versions, YOLO11 supports multiple computer vision tasks, including: ?? Object Detection ??Instance Segmentation ??Image Classification ??Pose Estimation ??Oriented Object Detection (OBB) This versatility makes it a robust choice for various applications! ??. ?????????? ?????? ????????????????????: YOLO11 is touted as the fastest and lightest model in the YOLO series, with improvements in inference speed (around 2% faster than YOLOv10) while maintaining high accuracy. This efficiency is crucial for real-time applications. ??. ?????????????????? ??????????????????????: In comparative tests, YOLO11 demonstrates superior performance in terms of Mean Average Precision (mAP) while using fewer parameters than previous models, making it both computationally lighter and more effective. We recently took up the challenge of experimenting with ?????????????????? ?????????????????? ?????????? ????????????. And the results were fantastic. Check out our tutorial, the link for which we’ve added in the comments. Happy coding! #yolo11 #yolo #signaturedetection?#ArtificialIntelligence #AI #objectdetection
The MIT Technology Review covered a startup named Exa taking a novel approach to Gen AI search based web searches with the goal of using the web like a database. Charles Araujo and Hyoun Park discuss the scale and results for this approach. Will Bryk Jeffrey Wang https://lnkd.in/gAc8hAmT
Check out the short video from our CEO on Generative AI! ??
Hey friends! ?? Have you ever wondered what makes Generative AI tick? I released a video where I break it all down in a simple and engaging way—no heavy jargon, just clear explanations. ??? From understanding the motivation behind it to diving into the magic of Transformer Architecture, encoders, decoders, and even how to train a transformer model—it’s all packed into 15 minutes. Perfect if you’re curious but short on time! ?? Take a look and let me know what you think. Would love to hear your thoughts or answer any questions—drop them in the comments! ??
