GenAI News Jun 6 25: Nothing Essential but Mind Blowing Chemistry Model for the Intellectually Curious
The folks at Future House are building a chemistry first model: the implications for science and organization are profound...
Happy Sunday , GAI Insights Community!
Two things struck me about Friday’s news — first was the amazing new chemistry first model which at times “forgot” how to speak in English because it was so busy “speaking” chemistry. Science based businesses take note and the video with the Future House folks is worth a listen.
If you missed us Friday, watch tomorrow’s show on YouTube. Join the fun! Watch and comment on our Live feed on Linkedin or YouTube. We post articles for the daily briefing here so you can follow along and comment. Today there were 3 Important, and 3 Optional articles.
BenchmarkQED: Automated benchmarking of RAG systems
Rating: Important
Rationale: Microsoft has introduced BenchmarkQED, a tool that automates evaluation of RAG systems using qualitative metrics such as comprehensiveness, diversity, empowerment, and relevance, with LLM acting as a judge. Our analysts emphasized its growing relevance for enterprise AI workflows and praised its open, framework-based approach to measuring the effectiveness of graph, vector, and relational RAG configurations across environments.
Enhanced diagnostics flow with LLM and Amazon Bedrock agent integration
Rating: Important
Rationale: This AWS case study details how Noodoe used LLMs via Amazon Bedrock to optimize pricing for EV charging stations, claiming a 15% revenue increase and 10% implementation time reduction. While some of our analysts questioned whether GenAI was necessary for the task versus traditional ML, they acknowledged its cross-industry applicability and clear architectural insights.
ether0: a scientific reasoning model for chemistry
Rating: Important
Rationale: FutureHouse’s ether0 is a fine-tuned version of Mistral optimized for scientific reasoning in chemistry, demonstrating high performance in molecule generation but lower performance in language tasks. Our analysts viewed it as a compelling case of AI in science, highlighting the efficiency of small, domain-specific models and the implications for future AI-driven scientific discovery.
Coding Agents with Multimodal Browsing are Generalist Problem Solvers
Rating: Optional
Rationale: This research presents a model that uses a minimal toolset (web search, file access, code editing, browsing) to outperform specialist models on certain tasks using Claude Sonnet. However, our analysts considered it an academic benchmark exercise with limited immediate relevance for enterprise AI leaders.
How Morgan Stanley Tackled One of Coding’s Toughest Problems
Rating: Optional
Rationale: Morgan Stanley developed a custom model to convert COBOL code to English summaries to help refactor legacy systems, claiming a savings of 280,000 developer hours. Despite the financial scale, our analysts noted the approach lags behind current GenAI capabilities, and viewed the article as light on technical details and better suited for awareness than actionable insight.
BNP Paribas provides its businesses with an LLM as a Service platform to accelerate the industrialization of generative AI use cases
Rating: Optional
Rationale: BNP Paribas launched an internal platform offering LLM-as-a-Service to accelerate AI use cases across departments. The announcement lacked specific implementation outcomes or economic impact, leading our analysts to treat it as a basic product reveal rather than a strategic milestone.
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Enjoy,
John Sviokla, and our AI Analysts Paul Baier , Adam Rappaport and our Guest Reviewer today, Kevin Petrie. Thank you for joining, Kevin!