How Could We Design Aligned and Provably Safe AI?
Explore AI safety with Dr. Yoshua Bengio, focusing on run-time risk evaluation and Bayesian approaches to mitigate potential harm from advanced AI systems.
Learning Paradigms for Neural Networks: The Locally Backpropagated Forward-Forward Algorithm
Explore innovative neural network training methods combining backpropagation and forward-forward algorithms to address limitations in complex, physics-related AI applications.
Ontologies, Graph Deep Learning, and AI in Materials Science
Explore ontologies, graph deep learning, and AI in materials science, focusing on advanced manufacturing and synchrotron science. Learn about innovative approaches for multimodal analysis and decision-making.
FOCUS Technique: Evolutionary Testing Simulation with Out-of-Distribution Images
Explorez les techniques d'essais évolutifs et de simulation avec des images hors distribution pour améliorer la robustesse des modèles d'apprentissage automatique.
Where Vector Search is Taking Us
Explore vector search options, components, and future prospects with industry expert Dmitry Kan in this keynote address from Haystack EU 2022.
Fine-tuning Methods for Vector Search in Semantic Search and QA Applications
Explore fine-tuning methods for vector search in semantic search and QA applications. Learn when to use different techniques based on data availability and use cases.
Building an Open-Source Online Learn-to-Rank Engine - Haystack EU 2022
Explore Metarank, an open-source personalization service for learn-to-rank tasks. Discover how it simplifies data engineering challenges and improves search relevancy through visitor behavior analysis.
Lowering the Entry Threshold for Neural Vector Search - Applying Similarity Learning
Explore similarity learning for efficient neural search implementation, reducing data requirements and training time while addressing domain-specific challenges.
Unbiased Neural Ranking Model for Product Search
Explore an unbiased neural ranking model for product search, leveraging implicit customer feedback and addressing position bias to improve e-commerce search results.
Testing in Apache Solr - Session 3
Explore Solr's testing capabilities, learn to contribute effectively, and master techniques for writing and managing tests in Apache Solr.
Data Labeling for Search Relevance Evaluation
Explore data labeling techniques for search relevance evaluation, focusing on human-in-the-loop pipelines, ranking metrics, and crowdsourcing best practices.
Building Autosuggest Infrastructure for High-Performance E-commerce
Explore OTTO's journey in building and reinventing autosuggest infrastructure, covering deep technology, architecture, scalability, and team insights for high-performance e-commerce solutions.
Vectorize Your E-commerce Search
Discover how vector search enhances e-commerce, solving misspellings and boosting relevance. Learn about Chorus's new vector capabilities for improved search experiences.
Effective Relevancy Change Management in Search Systems
Explore effective search relevancy change management techniques for continuous improvement in search systems and feature engineering.
Relevance in the Age of Generative Search - Haystack US 2023 Keynote
Explore the integration of generative AI in search, covering strategies, code examples, and the balance between AI capabilities and traditional relevance techniques for accurate results.
Populating and Leveraging Semantic Knowledge Graphs to Supercharge Search
Populate and leverage semantic knowledge graphs to enhance search capabilities, enabling concept-based queries, query expansion, and improved long-tail query matching for reduced zero-result searches.
Exploiting Citation Networks in Large Corpora to Improve Relevance on Broad Queries
Discover how to leverage citation networks in large legal databases to improve search relevance for broad queries, enhancing user experience and document ranking accuracy.
A Cheap Trick for Semantic Question Answering for GPU-Challenged Systems
Explore a cost-effective approach to semantic question answering using LLMs during indexing, combining text and vector matching for efficient search without GPU requirements.
Talking to Non-Searchers about Search Relevance - Haystack US 2023
Learn effective strategies for explaining search relevance to non-technical stakeholders, from CEOs to clients. Gain insights on communicating complex search concepts and their importance.
How Far is the Empire State Building from the Eiffel Tower? Semantic Vectors in Travel Discovery - Haystack US 2023
Explore semantic vector applications in travel marketplaces for improved recommendations, ranking, and ad optimization. Learn about evolving algorithms and practical advice for implementation.
Breaking Search Performance Limits with Domain-Specific Computing
Explore advanced search techniques using domain-specific computing to achieve faster latencies and higher scalability at billion-scale, overcoming limitations of general-purpose CPUs.