Heartland Forward Launches Bipartisan Heartland AI Caucus
Heartland Forward has launched the Heartland AI Caucus, a bipartisan coalition of state legislators and executive officers focused on advancing responsible AI policy and economic growth across the U.S. heartland, announced in a press release.
The caucus begins with members from Arkansas, Illinois, Louisiana, Ohio, Oklahoma, and Tennessee, with plans to expand to additional states. Arkansas Senate President Pro Tempore Bart Hester will lead the group. The caucus aims to promote collaboration among states, develop model AI legislation, and strengthen the regional workforce and education pipeline.
According to Heartland Forward, recent polling shows that while interest in AI is high, proficiency remains low among workers and students. The organization will support the caucus by providing research and policy insights to help leaders prepare communities and small businesses for AI adoption.
The initiative builds on Heartland Forward’s previous efforts, including the Heartland Health Caucus, and is supported by foundational funding from Google.org to expand access to AI knowledge and skills.
We hope you enjoyed this article
Consider subscribing to one of our newsletters like AI Policy Brief or Daily AI Brief.
Also, consider following us on social media:
More from Regulation
Oct 16 HKMA Introduces ART Framework for AI Use in Banking Oct 15 UK Medicines Regulator Plans AI Safety Tools by 2030 Oct 15 OpenAI Agrees Not to Use Apple Trade Secrets During Lawsuit Oct 15 Financial Stability Board Publishes 12 AI Practices for Financial Firms Oct 15 Singapore Launches Three AI Safety InitiativesAI Policy Brief
Weekly report on AI regulations, safety standards, government policies, and compliance requirements worldwide.
Whitepaper
Tensordyne Napier: What If One Rack Could Do the Work of Nine?
Tensordyne
This Tensordyne whitepaper presents Napier, an inference-focused AI processor and rack-scale system based on the company’s TDN Math logarithmic number system. It examines infrastructure requirements for large mixture-of-experts and agentic models, compares major inference architecture approaches, and details the TDN AIP processor, TDN72 pod, TDN Link fabric, and Napier Ultra configuration. The paper reports simulation-based performance, cost, and accuracy-validation results, including Tensordyne’s projected comparison of one Napier rack with a nine-rack Nvidia Rubin plus Groq deployment; the chip is reported as taped out and in fabrication.
Read moreYou may also like
American Infrastructure Alliance Forms Data Center Standards Coalition
Armor Founder Calls for Governed Enterprise AI at GovWare
HSA Group Launches AI Lab Across Its Businesses
Architect Digital Launches Platform to Track Proposed AI Data Centers
EDGE AI Foundation Forms Three Edge AI Working Groups
Daily AI Brief: the AI news that matters, in your inbox.