Label Your Data

💡 Elon Musk calls Grok 3 the "Smartest AI on Earth." With the launch coming up, will it push AI boundaries or is the competition still ahead? Let’s discuss! ⬇️

Here’s what’s new in AI/ML: 📌 AI Action Summit in Paris Recap: Leaders from over 100 countries discussed global AI regulations, focusing on collaboration, innovation, and building a trustworthy AI ecosystem (https://lnkd.in/d5sSGVVF). 📌 Sam Altman Unveils GPT-5 Roadmap: OpenAI scraps o3 release for a unified GPT-5 system with tiered intelligence access for free, Plus, and Pro users. Expect GPT-4.5 (Orion) in weeks (https://lnkd.in/dcE2ug2E). 📌 Apptronik Raises $350M for Humanoid Robots: Partnering with Google DeepMind, Apptronik focuses on embodied AI for bipedal robots, targeting industrial scaling in 2026 (https://lnkd.in/d3m_fTu6). There’s more in our ML Digest newsletter: 🔬 Research overview 📊 Trending dataset 📝 New blog articles Link in the comments!

🧪 New Machine Learning Research: Implicit Learning in LLMs Lisa Alazraki from Imperial College London and Cohere researchers (Maximilian Mozes, Jon Ander Campos, Yi Chern T., Marek Rei, and Max Bartolo found that LLMs can improve their reasoning by just observing incorrect answers alongside correct ones. No detailed explanations needed. - Goal: Test if LLMs can infer patterns and improve from mistakes without corrective rationales. - Method: Compared implicit learning (no explanations) to chain-of-thought prompting and explicit feedback. - Results: Implicit learning outperformed in 88% of tests, with a 4.4% accuracy boost in editing tasks and over 90% success on GSM8K and ASDiv datasets. - Why It Matters: Simplifies LLM training, cuts the need for curated feedback, and delivers rationales nearly as good as explicit feedback (0.98 vs. 1.01). Could this change how we train LLMs? What do you think? ➡️ Read the full paper here: https://lnkd.in/dxU4HUhQ #MachineLearning #LLMs #AIResearch #NaturalLanguageProcessing #DataScience #ImplicitLearning #MathReasoning #AIModels

Updates in AI research, competition, and copyright law: 📌 Hugging Face launches Open Deep Research – A new initiative for open-source AI transparency: (https://lnkd.in/dSNQ45Ju). 📌 Google CEO criticizes DeepSeek – Pichai claims DeepSeek models are less efficient than Gemini: (https://lnkd.in/dyZ7ri-H). 📌 US Copyright Office rules on AI creations – AI-generated works can’t be copyrighted: (https://lnkd.in/d69jg4QZ). There’s more in our ML Digest newsletter: - research overview - trending dataset - new blog articles Link in the comments!

Which matters more for LLM success? 🔮

🧪 New Machine Learning Research: Exploring Innovations in Bioacoustic Monitoring Aude Vuilliomenet and Santiago Martinez Balvanera from UCL have introduced acoupi, an open-source Python framework for deploying bioacoustic AI models on edge devices. - Research goal: Simplify biodiversity monitoring by integrating AI models into edge devices to improve efficiency and reduce data transfer challenges. - Research methodology: Designed a modular framework combining AI-based analysis and wireless data transfer. Tested with BirdNET (birds) and BatDetect2 (UK bats) classifiers on Raspberry Pi devices. - Key findings: The system maintained 100% data transmission reliability under stable network conditions. Processed over 129,900 recordings in a month-long deployment with a failure rate of just 0.003%. - Practical implications: This framework enables cost-effective, real-time biodiversity monitoring with flexible configurations for specific ecological needs. #LabelYourData# #MachineLearning #Innovation #AIResearch #MLResearch #Bioacoustics #EdgeDevices #DataScience #BiodiversityMonitoring

💳 AI is revolutionizing how we manage and interact with finances. For instance, JPMorganChase has implemented AI to enhance their fraud detection systems, resulting in a significant reduction in fraudulent activities. At Label Your Data, we specialize in providing high-quality data annotation services tailored for the fintech sector. Our expertise includes: - Named entity recognition (NER): Identifying and classifying entities such as names, dates, and financial terms in documents. - Sentiment analysis: Assessing customer feedback to gauge satisfaction and improve services. - Document classification: Organizing financial documents for efficient processing and retrieval. 💡 With our solutions, financial you can: ✅ 🔒 Detect fraudulent transactions with high accuracy, enhancing security. ✅ 🎯 Personalize customer experiences by understanding individual needs and preferences. ✅ ⚙️ Streamline document processing, reducing manual effort and errors. Let's bring AI-driven efficiency to finance together! 🚀#Fintech #AI #DataAnnotation #Finance #Innovation

🚗🔬 Improving LiDAR Accuracy for smarter automation Ouster, a leader in 3D sensing, partnered with us to scale and enhance their LiDAR annotation process. With precise 2D bounding boxes and 3D cuboids, our team improved model accuracy and tracking capabilities across dynamic and static environments 📊✨ 🚀 Key results: ✅ 20% boost in product performance ✅ 15% improvement in multi-object tracking ✅ Scaled annotation team from 2 → 10 members We’re proud to support David Pike and the Ouster team in enhancing the precision of AI-driven LiDAR systems 🤖🌍 #LiDAR #AI #Automation #DataAnnotation #MachineLearning

Can active learning ⚡ outperform random sampling for edge case detection?

1️⃣ DeepSeek-R1: OpenAI’s Rival Emerges DeepSeek's new model challenges OpenAI’s reasoning tech, using pure reinforcement learning without human supervision. Researchers are working to replicate its training pipeline for transparency. 🔗 Read more: https://lnkd.in/dCufrQpK 2️⃣ OpenAI’s ChatGPT Gov for U.S. Agencies OpenAI introduces ChatGPT Gov, a version tailored for federal and state agencies, supporting cybersecurity compliance and AI-powered productivity enhancements. 🔗 Continue reading: https://lnkd.in/dW3D4G-D 3️⃣ DeepSeek Unveils Janus-Pro DeepSeek launches Janus-Pro, a multimodal AI model that outperforms OpenAI’s DALL-E 3 in image generation. Available under an MIT license for commercial use. 🔗 The details: https://lnkd.in/dsySHHYm There’s more in our ML Digest newsletter: - research overview - trending dataset - new blog articles Link in the comments!