Large Language Models, StructBERT — Incorporating Language Structures into Pretraining

Large Language Models, StructBERT — Incorporating Language Structures into Pretraining AI News, AI, AI tools, Innovation, itinai.com, LLM, t.me/itinai, Towards Data Science - Medium, Vyacheslav Efimov 🚀 **Introducing StructBERT: Enhancing Language Understanding with AI** Since the success of BERT, a language model that has revolutionized natural language processing (NLP), researchers have been striving to improve its performance. Enter StructBERT, a new model that surpasses BERT in top benchmarks by incorporating better learning objectives. 🔍 **Modifying BERT's Pretraining Objective** StructBERT focuses on enhancing BERT's pretraining objective to make the model smarter. It introduces two new objectives: word sentence objective and sentence structural objective. 1️⃣ **Word Sentence Objective** BERT struggles with reconstructing sentences with shuffled words. StructBERT addresses this by partially shuffling input tokens during the masked language modeling task. This helps the model learn to predict the original order of words. 2️⃣ **Sentence Structural Objective** StructBERT enhances BERT's next sentence prediction task by making the model predict the correct sentence order. By training with pairs of sequential sentences, StructBERT learns to identify the correct order of sentences. 🔀 **Combining Objectives** StructBERT combines the word sentence objective and the sentence structural objective into a final objective. This combination improves the model's performance in understanding word order and inter-sentence relations. 💼 **Practical Applications and Value** StructBERT outperforms BERT in various NLP tasks, making it a valuable tool for companies looking to leverage AI. By incorporating language structures into pretraining, StructBERT enhances your company's language understanding capabilities. 🌟 **How to Get Started with AI** 1️⃣ Identify Automation Opportunities: Find key customer interaction points that can benefit from AI. 2️⃣ Define KPIs: Ensure your AI endeavors have measurable impacts on business outcomes. 3️⃣ Select an AI Solution: Choose tools that align with your needs and provide customization. 4️⃣ Implement Gradually: Start with a pilot, gather data, and expand AI usage judiciously. 📚 **Useful Links** - AI Lab in Telegram: @aiscrumbot (free consultation) - Large Language Models, StructBERT - Incorporating Language Structures into Pretraining - Towards Data Science - Medium - Twitter: @itinaicom 🤖 **Spotlight on a Practical AI Solution: The AI Sales Bot** Discover how AI can redefine your sales processes and customer engagement with the AI Sales Bot from itinai.com/aisalesbot. This solution automates customer engagement 24/7 and manages interactions across all customer journey stages. For AI KPI management advice and continuous insights into leveraging AI, connect with us at hello@itinai.com or stay tuned on our Telegram channel t.me/itinainews and Twitter @itinaicom.