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THE DAILY INDEX

Technology, AI, software, security, crypto and business

HEADLINES & LAUNCHES

TLDR AI

OPENAI ANNOUNCES NEW GUARANTEED CAPACITY OFFERING FOR CUSTOMERS TO SECURE COMPUTE

OpenAI's new Guaranteed Capacity offering allows customers to secure long-term access to compute to power AI products, agents, and workflows. Customers can choose between one-, two-, and three-year-long commitments, with discounts based on how long the commitment is. The company will offer Guaranteed Capacity until it sells out of its current allocation. It plans to offer it again in the future.

USING CLAUDE CODE: THE UNREASONABLE EFFECTIVENESS OF HTML

HTML's richness allows it to convey complex information more effectively than Markdown, including layouts, data tables, and interactive elements. It enhances readability by organizing specs into well-structured, easily navigable documents and offers better sharing and interaction capabilities. Claude Code uses HTML to efficiently ingest context from various sources, aiding in specs, design prototyping, and creating custom editing interfaces with improved engagement and clarity.

OLMOEARTH V1.1: A MORE EFFICIENT FAMILY OF MODELS

OlmoEarth v1.1, a new model family, reduces compute costs by up to 3X while maintaining performance, making planet-scale mapping more affordable. The models efficiently process remote sensing data by optimizing token sequence lengths, crucial for reducing computational costs. Methodological improvements allow similar performance to the original version with significantly less compute, benefiting developers and enhancing scientific research in remote sensing.

INTRODUCING THE ETTIN RERANKER FAMILY

Six new state-of-the-art CrossEncoder Ettin rerankers built on Ettin ModernBERT encoders have been released, offering models from 17M to 1B parameters. These models, trained with pointwise MSE distillation from a strong 1.54B parameter teacher, provide significant accuracy improvements over legacy models while enhancing speed, especially with Flash Attention 2. The models are particularly notable for their efficiency in retrieve-then-rerank systems and outperform models like ms-marco-MiniLM-L12-v2 on MTEB and NanoBEIR benchmarks.

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