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Product updates, research, customer stories, and perspectives from the team building AI at S&P Global.
NewsArchive
Inside Kensho’s LLM-ready API: How engineers enable secure natural language access to S&P Global data
Three engineers share how Kensho — S&P Global's AI innovation engine — built and scaled the Kensho LLM-ready API to deliver financial intelligence wherever customers work.
Kensho LLM-Ready API adds Private Company Financials, S&P Capital IQ Estimates datasets, and enhanced auditability for public company financials
Kensho LLM-Ready API now features access to S&P Global Private Company Financials and S&P Capital IQ Estimates data, along with in-line source document links for existing S&P Global public financials data. These enhancements unlock new possibilities for AI-driven financial analysis workflows to enable deeper insights, transparency, and confidence in data-driven decision-making.
S&P Global launches Kensho LLM-ready API (beta), making its structured data accessible for generative AI
New solution enables customers to seamlessly integrate complex, high-priority S&P Global datasets into Generative AI models.
We’re expanding S&P AI Benchmarks to cover long-document QA
New benchmark assesses how well AI systems analyze complex financial documents hundreds of pages long.
Unlocking precision and speed: Discover the latest enhancements to Kensho Scribe
We are excited to introduce the latest update to Kensho Scribe AI, our speech-to-text transcription tool. From meeting note documentation to earnings call transcription, our enhanced model offers cutting-edge technology to streamline your workflow and deliver precise results. This new model delivers a 30% reduction in errors compared to our previous model while significantly increasing output quality. These latest advancements can transform your transcription experience and drive greater efficiency in your operations.
Enhanced document extraction for generative AI use cases
Introducing Kenverters, a set of open source Python developer tools for fast and easy use of Kensho Extract in pipelines for Retrieval Augmented Generation (RAG), Large Language Models (LLMs), table extraction, and more!
4 key takeaways from our workshop at HCII2024
During our recent workshop at the Human-Computer Interaction International Conference (HCII2024), we delved into the intersection of the evolving landscape of AI models, human-centric design, and the growing field of financial AI. Here are four key takeaways from our workshop, offering insights into how these areas shape designing AI applications.
An Introduction to mitigating toxicity in LLMs - Pt. 2
In our last post, we introduced toxicity as a challenge when building LLMs and various methodologies to mitigate it. In this post, we’re going to focus on utilizing one of those methodologies — auxiliary tools — and assessing some tools that are available to the public.
An introduction to mitigating toxicity in LLMs
A vital aspect of “productionalizing” Large Language Models (LLMs) is to ensure a safe user experience and promote alignment with societal standards. LLMs excel at generating language and answering user-input questions, even some of the hardest ones. However, when given a malicious prompt, LLMs may also try to answer that with an unsafe response.
What is the future of generative AI beyond chat interfaces?
While chat-based AI models have dominated the landscape, the future of GenAI appears to extend beyond casual conversation. By acknowledging the limitations of chat for extended and diverse tasks and recognizing the suitability of both small and large models in specific scenarios, the trajectory of AI points towards integrated systems.
Learnings from the lab: Querying S&P Global’s tabular data using LLMs
Understanding complex data structures is a major challenge for Generative AI use cases. Kensho is designing specialized LLM-Ready APIs to tackle this problem.
Launched: S&P AI Benchmarks, a solution that evaluates LLMs for finance and business
Today we launched S&P AI Benchmarks by Kensho (Beta), a solution that assesses the abilities of Large Language Models (LLMs) to understand and leverage text that concerns finance and business. This exciting project, which combines S&P Global’s finance expertise with Kensho’s cutting-edge research and engineering, has witnessed substantial growth in the past year. It originated as an R&D initiative to fairly evaluate models, culminated in an academic research paper, and has now blossomed into a full-fledged resource for the industry at large.
Beyond innovation: Leveraging the power of machine learning for business growth
Discover the transformative role of GenAI and Machine Learning for business growth as it reshapes business operations and drives innovation in the era of AI.
Introducing S&P Global Marketplace generative AI search
Announcing enhanced natural language search functionality utilizing large language models (LLMs). The initial release of Marketplace Generative AI search enables users to ask an array of questions — from simple data questions, such as a dataset’s geographic coverage or history, to more complex questions where answers are pulled from dataset user guides.
Databricks Data + AI Summit (DAIS) 2023 top themes
In June, I had the chance to attend Databricks’ annual Data + AI Summit (DAIS) in San Francisco along with a team of my colleagues from S&P Global. In addition to showcasing our product and data offerings, we hosted a speaking session, Using Databricks to Power Insights and Visualizations on the S&P Global Marketplace.
Catch the replay — Kensho webinar on the past, present and future of NLP and LLM technologies for business
The webinar featured Kensho’s Chief Strategy Officer, Peter Licursi, and our Head of R&D, Chris Tanner, discussing topics including the evolution of NLP research over the past decade and how it’s led us to where we are today with technologies like ChatGPT.
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