The model is known for its overly sycophantic nature and its role in several lawsuits involving users' unhealthy relationships with the chatbot.
The Beneish model was designed by M. Daniel Beneish to quantify eight variables that can indicate that a company is misrepresenting its profits. Here’s how it works.
Interstellar Semantics LLC Launches in Frederick, Maryland, Bringing Advanced Semantic and Ontology Expertise to Data Driven Organizations ...
Semantic brand equity ensures LLMs and AI search engines recommend your business. Our guide reveals how AI perceives and ranks your brand.
The latest generation of the universal CAD data converter 3D_Evolution 4.9 has a new function for checking semantic PMI ...
Kyvos Launches Claude Cowork Integration to Enable Governed Agentic Analytics on Enterprise Big Data
Kyvos, the industry-leading semantic layer for AI and BI, today announced the launch of its integration with Claude Cowork, enabling organizations to operationalize agentic analytics reliably on ...
Google Translate's Gemini integration has been exposed to prompt injection attacks that bypass translation to generate ...
Combining MCP, analytics-as-code, and LLMs to automate analytics execution at software speed SAN FRANCISCO, CALIFORNIA ...
Reading an Arabic newspaper, a book, or academic prose fluently, whether digital or in print, remains challenging for many ...
In today’s managerial world, there is a risk as subtle as it is pervasive: mistaking models for reality, representations for ...
In its research, Microsoft detailed three major signs of a poisoned model. Microsoft's research found that the presence of a backdoor changed depending on where a model puts its attention. "Poisoned ...
Kyvos Recognized in Gartner® Report: Reference Architecture Brief: Analytics & Business Intelligence
LOS GATOS, Calif., Jan. 29, 2026 /PRNewswire/ -- Kyvos, the industry-leading semantic layer for AI and BI, has been recognized in the Gartner® Reference Architecture Brief: Analytics & Business ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results