Tags: cost reduction

On a recent earnings call, Pinterest chief executive Bill Ready explained how the company is turning to open‑source artificial‑intelligence models to slash costs while preserving performance across its visual‑AI features, including personalized recommendations, multimodal search, ad targeting and the new AI‑powered Pinterest Assistant. Ready said tests show open‑source models delivering comparable results at a fraction of the price of proprietary alternatives, offering what he described as orders‑of‑magnitude cost reductions. The company plans to expand the use of these models, while also exploring agentic commerce options and AI‑curated boards. The announcement came as Pinterest’s stock fell more than 21% after a revenue forecast miss. Ler mais

Palantir announced a multi-year, multi-million-dollar strategic partnership with Lumen Technologies. The deal pairs Palantir's Foundry and Artificial Intelligence Platform (AIP) with Lumen's edge computing and broadband infrastructure, enabling Lumen to accelerate its transformation from a traditional telecom provider to a modern tech infrastructure player. Lumen reports that using Palantir's technology contributed to significant cost reductions and informs its broader enterprise AI service offering. The collaboration marks one of many partnerships Palantir has formed across diverse sectors this year. Ler mais

DeepSeek announced a new experimental AI model featuring Sparse Attention technology that dramatically lowers inference costs for long‑context tasks. The model, released on Hugging Face and accompanied by a research paper on GitHub, uses a lightning indexer and fine‑grained token selection to focus computational resources on the most relevant excerpts. Preliminary tests suggest API call prices can be cut by as much as 50 percent in long‑context scenarios. The open‑weight release invites third‑party validation and positions DeepSeek as a notable player in the ongoing effort to make transformer‑based AI more cost‑effective. Ler mais

Artificial intelligence tools are being positioned to reshape the healthcare system by shifting care from a reactive model to proactive prevention, early detection, and streamlined operations. AI‑driven image analysis, predictive algorithms, and chat‑based triage can catch diseases earlier, guide patients to the right pathways, and free clinicians to focus on complex cases. Experts emphasize the need for specialist AI agents, hybrid human‑AI workflows, and rigorous safety monitoring to ensure accurate, trustworthy outcomes while reducing overall costs. Ler mais