Storing tree data structures as lists simplifies node location. Converting full-list to condensed index trees requires explicit child indexes.
May loses her job to humanoid robots, undergoes experimental facial injection to evade them. Family copes with polluted environment, device addiction in a dystopian world.
Multimodal embeddings merge text and image data into a single model, enabling cross-modal applications like image captioning and content moderation. CLIP aligns text and image representations for 0-shot image classification, showcasing the power of shared embedding spaces.
Open Food Facts uses Machine Learning to enhance its food database by reducing unrecognized ingredients, improving data accuracy. The project showcases the success of creating a custom model, outperforming existing solutions by 11%.
Whitehall departments lack transparency in AI use. Concerns arise as AI affects millions of lives, with examples in DWP and Home Office.
Agentic AI combines specialized agents for enhanced capabilities. Major players like Microsoft and Google are investing heavily in agentic AI research.
LLMs.txt is a new web standard optimized for reasoning engines, gaining rapid adoption thanks to Mintlify's support. Co-founder Jeremy Howard proposed LLMs.txt to help AI systems understand website content more efficiently.
Dogs prefer to poop facing North-South. Learn how to measure this at home using a compass app and Bayesian statistics. Researcher replicates study with own dog, capturing over 150 "alignment sessions."
Senate recommends standalone AI legislation & protections for creative workers. Amazon, Google, Meta criticized for vagueness on Australian data use in AI training.
Optimizing LLM-based applications with a serverless read-through caching blueprint for efficient AI solutions. Utilizing Amazon OpenSearch Serverless and Amazon Bedrock to enhance response times with semantic cache for personalized prompts and reducing cache collisions.
Spines startup faces backlash for using AI to edit and distribute books for $1,200-$5,000. Critics question quality and impact on traditional publishing.
Quantization limits are being pushed with ft-Quantization, a new approach to address current algorithm limitations. This memory-saving technique compresses models and vectors for retrieval, popular in LLMs and vector databases.
Salesforce centralizes customer data for insights. Amazon Q Business AI empowers employees with data-driven decisions and productivity.
Rad AI's flagship product, Rad AI Impressions, uses LLMs to automate radiology reports, saving time and reducing errors. Their AI models generate impressions for millions of studies monthly, benefiting thousands of radiologists nationwide.
Hallucinations in large language models (LLMs) pose risks in production applications, but strategies like RAG and Amazon Bedrock Guardrails can enhance factual accuracy and reliability. Amazon Bedrock Agents offer dynamic hallucination detection for customizable, adaptable workflows without restructuring the entire process.