TJS Articles & News

Enabling small language models to solve complex reasoning tasksMIT News – Machine learning The “self-steering” DisCIPL system directs small models to work together on tasks with constraints, like itinerary planning and budgeting.

 The “self-steering” DisCIPL system directs small models to work together on tasks with constraints, like itinerary planning and budgeting. Read More  

How to Design a Fully Local Agentic Storytelling Pipeline Using Griptape Workflows, Hugging Face Models, and Modular Creative Task OrchestrationMarkTechPost In this tutorial, we build a fully local, API-free agentic storytelling system using Griptape and a lightweight Hugging Face model. We walk through creating an agent with tool-use abilities, generating a fictional world, designing characters, and orchestrating a multi-stage workflow that produces a coherent short story. By dividing the implementation into modular snippets, we can
The post How to Design a Fully Local Agentic Storytelling Pipeline Using Griptape Workflows, Hugging Face Models, and Modular Creative Task Orchestration appeared first on MarkTechPost.

 In this tutorial, we build a fully local, API-free agentic storytelling system using Griptape and a lightweight Hugging Face model. We walk through creating an agent with tool-use abilities, generating a fictional world, designing characters, and orchestrating a multi-stage workflow that produces a coherent short story. By dividing the implementation into modular snippets, we can
The post How to Design a Fully Local Agentic Storytelling Pipeline Using Griptape Workflows, Hugging Face Models, and Modular Creative Task Orchestration appeared first on MarkTechPost. Read More  

Fuzzy Hierarchical Multiplexcs.AI updates on arXiv.org arXiv:2512.09976v1 Announce Type: new
Abstract: A new fuzzy optimization framework that extends FCM causality is proposed. This model utilizes the dynamics to map data into metrics and create a framework that examines logical implication and hierarchy of concepts using a multiplex. Moreover, this is a white-theoretical paper introducing the framework and analyzing the logic and math behind it. Upon this extension the main objectives and the orientation of this framework is expounded and exemplified; this framework is meant for service optimization of information transmission in service process design. Lastly, a thorough analysis of the FHM is included which is done following the logical steps in a simple and elegant manner.

 arXiv:2512.09976v1 Announce Type: new
Abstract: A new fuzzy optimization framework that extends FCM causality is proposed. This model utilizes the dynamics to map data into metrics and create a framework that examines logical implication and hierarchy of concepts using a multiplex. Moreover, this is a white-theoretical paper introducing the framework and analyzing the logic and math behind it. Upon this extension the main objectives and the orientation of this framework is expounded and exemplified; this framework is meant for service optimization of information transmission in service process design. Lastly, a thorough analysis of the FHM is included which is done following the logical steps in a simple and elegant manner. Read More  

Towards Foundation Models with Native Multi-Agent Intelligencecs.AI updates on arXiv.org arXiv:2512.08743v2 Announce Type: replace
Abstract: Foundation models (FMs) are increasingly assuming the role of the “brain” of AI agents. While recent efforts have begun to equip FMs with native single-agent abilities — such as GUI interaction or integrated tool use — we argue that the next frontier is endowing FMs with native multi-agent intelligence. We identify four core capabilities of FMs in multi-agent contexts: understanding, planning, efficient communication, and adaptation. Contrary to assumptions about the spontaneous emergence of such abilities, we provide extensive empirical evidence across 41 large language models showing that strong single-agent performance alone does not automatically yield robust multi-agent intelligence. To address this gap, we outline key research directions — spanning dataset construction, evaluation, training paradigms, and safety considerations — for building FMs with native multi-agent intelligence.

 arXiv:2512.08743v2 Announce Type: replace
Abstract: Foundation models (FMs) are increasingly assuming the role of the “brain” of AI agents. While recent efforts have begun to equip FMs with native single-agent abilities — such as GUI interaction or integrated tool use — we argue that the next frontier is endowing FMs with native multi-agent intelligence. We identify four core capabilities of FMs in multi-agent contexts: understanding, planning, efficient communication, and adaptation. Contrary to assumptions about the spontaneous emergence of such abilities, we provide extensive empirical evidence across 41 large language models showing that strong single-agent performance alone does not automatically yield robust multi-agent intelligence. To address this gap, we outline key research directions — spanning dataset construction, evaluation, training paradigms, and safety considerations — for building FMs with native multi-agent intelligence. Read More  

Spectral Community Detection in Clinical Knowledge GraphsTowards Data Science Introduction How do we identify latent groups of patients in a large cohort? How can we find similarities among patients that go beyond the well-known comorbidity clusters associated with specific diseases? And more importantly, how can we extract quantitative signals that can be analyzed, compared, and reused across different clinical scenarios? The information associated to
The post Spectral Community Detection in Clinical Knowledge Graphs appeared first on Towards Data Science.

 Introduction How do we identify latent groups of patients in a large cohort? How can we find similarities among patients that go beyond the well-known comorbidity clusters associated with specific diseases? And more importantly, how can we extract quantitative signals that can be analyzed, compared, and reused across different clinical scenarios? The information associated to
The post Spectral Community Detection in Clinical Knowledge Graphs appeared first on Towards Data Science. Read More  

BBVA embeds AI into banking workflows using ChatGPT EnterpriseAI News BBVA is embedding AI into core banking workflows using ChatGPT Enterprise to overhaul risk and service in the sector. For the banking industry, the challenge of generative AI is rarely about adoption; it is about value extraction. BBVA has addressed this by integrating OpenAI’s platform directly into its operational backbone, a decision that will see
The post BBVA embeds AI into banking workflows using ChatGPT Enterprise appeared first on AI News.

 BBVA is embedding AI into core banking workflows using ChatGPT Enterprise to overhaul risk and service in the sector. For the banking industry, the challenge of generative AI is rarely about adoption; it is about value extraction. BBVA has addressed this by integrating OpenAI’s platform directly into its operational backbone, a decision that will see
The post BBVA embeds AI into banking workflows using ChatGPT Enterprise appeared first on AI News. Read More