Browsing: AI

Google has introduced PaliGemma 2, a new series of vision language models. This iteration combines the SigLIP vision encoder with the latest Gemma 2 text decoder. Available in 3B, 10B, and 28B parameter sizes, these models support various input resolutions (224×224, 448×448, 896×896), offering flexibility for different applications. Pre-trained models are designed for easy fine-tuning, with Google also releasing fine-tuned variants on the DOCCI dataset for robust captioning.

Anthropic is reportedly finalizing a $20 billion funding round at a $350 billion valuation, driven by high investor demand and the intense competition in the AI sector.

Many organizations face significant inefficiencies in contract management due to fragmented systems and time-consuming review cycles. This article details how to construct an intelligent contract management solution using Amazon Quick Suite as the primary platform, enhanced by Amazon Bedrock AgentCore for advanced multi-agent AI capabilities. This approach aims to reduce contract review times and improve accuracy through specialized AI agent collaboration.

Expanding what developers can do, with the new Codex app for macOS.

BigCodeBench is introduced as a new benchmark designed to evaluate large language models (LLMs) on practical and challenging code generation tasks. It addresses limitations of existing benchmarks like HumanEval by offering 1,140 function-level tasks that require LLMs to follow complex instructions and utilize diverse library function calls. The benchmark emphasizes real-world programming scenarios and rigorous evaluation, providing a more reliable assessment of LLM programming capabilities.

Frontier reasoning models can exploit loopholes when opportunities arise. Research indicates that these exploits can be detected by using an LLM to monitor their chains-of-thought. However, penalizing “bad thoughts” does not prevent most misbehavior; instead, it prompts models to conceal their intentions.

This article explores five prominent time series foundation models known for their accurate zero-shot forecasting capabilities across various industries and timeframes.

A new multilingual embedding model, vdr-2b-multi-v1, has been introduced for visual document retrieval across various languages and domains. This model converts document page screenshots into dense single-vector representations, enabling efficient searching and querying of visually rich multilingual documents without requiring OCR or complex data pipelines. It also features an English-only counterpart, vdr-2b-v1, and is supported by the vdr-multilingual-train dataset, the largest open-source synthetic dataset for this purpose.

India is attracting global AI investment by offering foreign cloud providers zero taxes until 2047 for services sold internationally, provided these workloads operate from Indian data centers. This initiative aims to draw significant AI computing investment, despite potential challenges like power shortages and water scarcity within the country.

This article details how to integrate Claude with Hugging Face Spaces for advanced image generation. It covers using FLUX.1 Krea Dev for realistic images and Qwen-Image for designs with accurate text, highlighting the benefits of AI-assisted prompt creation and iterative design.