HumanSignal

Data labeling is still crucial for building high-quality models. However, we recognize that manual labeling is often time-consuming and very expensive. Label Studio offers several methods to automate and streamline the labeling process, ensuring that your models receive high-quality labeled data more efficiently, while still keeping a human in the loop for more difficult or tricky items. We recently published a post delving into three effective methods to automate your labeling using Label Studio: bootstrapping labels, semi-automated labeling, and active learning. Each method is discussed in detail, followed by links to technical resources for implementation. Check it out! https://lnkd.in/dFhNYetq #datalabeling #labelingautomation #mlops #ml #ai #machinelearning

Our very own Jo Booth is speaking at the #AGIBuildersMeetup next week! He'll be presenting on "Fine-Tuning Enterprise Knowledge Bases with Label Studio and ChatGPT." This promises to be an awesome event, so if you're around NYC, make sure to check it out - you won't want to miss it! Signup link is below ⬇️

🚀 Exciting News! We just launched fully-automated labeling using LLMs in our new Prompts interface! While automated labeling offers time and cost savings, accuracy has been a challenge—until now. Our new Prompts tool lets you create, test, and refine prompts to label large datasets accurately using real-time quality metrics. You can prototype quickly, set up human reviews, and streamline your workflow without switching tools. To get a sense for how much of a difference this can make, our client, Geberit, achieved 5x faster labeling, 95% annotation accuracy, and 4-5x cost savings using our Prompts interface to auto-label. Curious about how this can boost your labeling efficiency? Schedule a demo today! 🚀 https://lnkd.in/dV3tGsHs #datalabeling #ai #mlops #labeling #ml #machinelearning

🎉 Today we're celebrating the release of 'Evals' as part of the new HumanSignal Platform, previously known as Label Studio Enterprise! Changing the platform name to HumanSignal reflects the expanded functionality—beyond data labeling to model evaluation, prompt engineering, and fine-tuning, all aligned with our mission to help data science teams ship the highest quality AI models and applications. 🚀 What's unique about our approach is the ability to configure the level of automation and human supervision in a tightly integrated workflow, based on the requirements of your use case. 🤖 + 👩🔧 Check out 5 ways you can use the new HumanSignal Platform to evaluate and ship AI applications you can trust! https://humansignal.com/

🎉 Today we're celebrating the release of 'Evals' as part of the new HumanSignal Platform, previously known as Label Studio Enterprise! Changing the platform name to HumanSignal reflects the expanded functionality—beyond data labeling to model evaluation, prompt engineering, and fine-tuning, all aligned with our mission to help data science teams ship the highest quality AI models and applications. 🚀 What's unique about our approach is the ability to configure the level of automation and human supervision in a tightly integrated workflow, based on the requirements of your use case. 🤖 + 👩🔧 Check out 5 ways you can use the new HumanSignal Platform to evaluate and ship AI applications you can trust! https://humansignal.com/

It's almost here! This is your last chance to register for our AI Evaluation: Ensuring Mission-Critical Trust & Safety event. We'll explain why evaluations are the key to safely using Generative AI in production, show off some first looks at some brand-new functionality, and share some walkthroughs to help you start evaluating your own #GenAI models. The event is tomorrow, June 26, 2024 at 9 PDT / Noon EDT / 6 CET. We’ll see you there! https://lnkd.in/dSzHF85y #machinelearning #mlops #ai #aievaluations

😊 Excited to see you this Wednesday to demo some of the latest work we've been focusing on at HumanSignal. With Label Studio at the core, enabling efficient and advanced workflows to create ground truth data, we will be showcasing new functionality that leverages human signal. "Proximity to ground truth" turns out to be a critical factor in enhancing the accuracy and reliability of AI systems. By maintaining close alignment with verified data, we can significantly improve the performance and trustworthiness of our models. This approach not only streamlines workflows but also ensures that AI outputs are more aligned, unbiased, and accurate. If you: – 🤖 Need more reliability in LLM output – ✅ Want to ensure LLM output alignment – 🔍 Are testing multiple prompts to find the best-performing one – 🧠 Are evaluating multiple LLMs to find the best fit for a prompt – 🏷️ Need to auto-label large datasets You will find this event useful.

Most businesses struggle to evaluate their AI models. Did you know few companies can accurately assess the performance of their AI systems? This skill, known as LLM evaluation, is crucial for better decision-making and improving the results from your genAI systems. Evaluation Metrics These are tools that help measure the effectiveness of AI models. They teach us to pinpoint strengths and weaknesses, boosting our AI strategy. Here are a few specific techniques you can use to improve your LLM evaluation: 1. Regular Benchmarks: Set aside time each month to run standardized tests. This helps track performance over time. 2. Error Analysis: Analyze where your model makes mistakes. This can help you understand its limitations and areas for improvement. 3. Use Evaluation Tools: Try tools like Hugging Face Evaluate (https://lnkd.in/eiT-kqkF) or OpenAI's evals (https://lnkd.in/eND8b4AP) to assess your models. These platforms offer various metrics and insights. 4. Learn from Data: Engage with real-world data. Testing your model with diverse datasets can broaden its applicability and reliability. My first client at Peripety Labs was HumanSignal my buddy Nate Kartchner and I got to work together on content marketing. I also got to work with my other dear friend, Lauren Sell, their VP of Marketing on projects. They gave me my first job in AI and I will always be grateful. Anyhow they are presenting a webinar on LLM Evaluation on Wednesday and while we are no longer working together formally, I am a big fan of them both and HumanSignal. So if you want to learn more about LLM evaluation. I suggest you take a look. If you want more of this type of commentary on AI then: ☑️ Like👍 and share♻️ this post ☑️ Follow Mark Hinkle ☑️ Subscribe to my newsletter The Artificially Intelligent Enterprise and get insights for AI and Business in your inbox every Friday. https://lnkd.in/eGKQeMHE

Our CTO Nikolai Liubimov is speaking at #AIDev Europe, taking place 19-20 June in Paris, France! Check out his session, Choosing The Best Open Source LLM For Your Application. 💥 Join us for THE #OpenSource event delving into #GenAI and #MachineLearning! Register today: https://hubs.la/Q02kgLCn0.

Have you signed up for our AI Evaluation event yet? Next Wednesday, June 26, we're holding a one-hour virtual event to show how model evaluation plays a critical role at every step of the AI development lifecycle. And we just announced the agenda! Check it out: 🔭 Vision Learn why the combination of automation plus human-in-the-loop workflows is essential for building reliable and trustworthy GenAI applications, and how leading enterprises are de-risking and unlocking the value of GenAI.   🚀 Launch Get a first look at new functionality! We'll show off some exciting new features to make evaluating and ensuring correct LLM outputs reliable and more efficient.   ⚡ Lightning talks & demos Our experts and engineers will guide you through practical demonstrations to show you how to make the most of Label Studio Enterprise core functionality and new features including: * Prompt evaluation and general “proximity to ground truth” * Auto-labeling datasets for training and fine-tuning * Creating custom evaluation metrics * Utilizing new SDK methods for efficiency and scale * Optimizing RAG pipelines * And more! We'll see you there! https://lnkd.in/dSzHF85y #mlops #machinelearning #ai #machinelearning #evaluation #aievaluation #promptengineering