tcworld’s Post

An educational piece with multilayered perspective on the future of AI based on interviews with Boston College CS professors and a student. William Griffin kicks off the discussion stating "We should look at AI from many ethical perspectives, such as justice, responsibility, duty, and so on. My sense is that is the way to think about most of the challenges that confront us, not only technologically but socially and environmentally." What's on your mind beyond concerns of plagiarism? Can you see positive outcomes? I'm hopeful.

This announcement from Anthropic about Claude AI's new API-based capabilities is world-changing. "With tool use, Claude can agentically: - Retrieve documents from your internal knowledge base and internal APIs - Access and take action via public and vendor APIs - Better handle tasks that require real-time data or complex computations - Orchestrate a set of small and fast Claude subagents to perform more granular tasks like checking different calendars of coworkers to find the best time to meet" I mean, you can basically create computer functionality across multiple different services through natural language.

Wolters Kluwer introduces a new AI-enhanced search feature in UpToDate Enterprise Edition, designed to transform how you find answers to medical questions. This cutting-edge technology understands both simple and complex queries using natural language, delivering rapid and reliable answers directly from #UpToDate. Learn more: https://gag.gl/jAUdOk #UpToDateEnterpriseEdition #ClinicalDecisionSupport #HealthcareAI #HealthcareInnovation

Discover how CometLLM enhances the explainability of large language models with prompt logging, tracking, and visualization. This hands-on guide dives into experiment tracking, RAG analysis, prompt management, and more, offering practical insights for transparency and optimization in LLMs. Perfect for those looking to understand and optimize LLM behaviour with ease and efficiency. Read the full article here: https://lnkd.in/gdwzCBwR #generativeai #artificialintelligence #largelanguagemodels #llmexplainability

“Some anticipate human immortality; others predict humanity’s colonization of the stars. The common tenet is that an all-powerful technology—AGI or superintelligence, choose your team—is not only within reach but inevitable. “ Maybe instead of debating on what AI is we can first debate on what HI is, since what pertains into thinking, reasoning, creating in the human mind is not known either, but in my humble opinion it resembles to what ChatGPTs reasoning is. Maybe we can approach the LLMs with symbolic logic and knowledge structures instead of metrics?

Knowledge graphs can help capture complex relationships between entities, providing meaningful context for large language models (LLMs) and their downstream data sets. This article https://lnkd.in/dabxWb6s by my colleagues Jorge Machado , Kayvaun Rowshankish and others is a great read for a playbook on the how.

𝗔𝗿𝘁𝗶𝗳𝗶𝗰𝗶𝗮𝗹 𝗜𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝗰𝗲 𝗮𝗻𝗱 𝗛𝘂𝗺𝗮𝗻 𝗥𝗶𝗴𝗵𝘁𝘀 The HELP course on Artificial Intelligence and Human Rights aims to enhance understanding of AI technologies and their human rights implications. Its objective is to assist professionals in navigating the relevant legal and regulatory landscape while fostering ethical decision-making. The course provides information about the most important instruments at the international and European levels and their practical implementation across Europe and beyond, with a focus on the Council of Europe and the European Union frameworks. Developed using the HELP methodology, the topics are explored practically through presentations, interactive screens, knowledge tests, and reflective exercises, enabling users to apply their gained knowledge and skills. @councilofeurope To register for the course ⬇️ https://lnkd.in/dB9Cybqh

Our own Hanna Barakat, OLY has been featured in Tech Policy Press, recapping our recently published report, ‘Selective Perspectives: A Content Analysis of The New York Times’ Reporting on Artificial Intelligence.’ Hanna explores how mainstream reporting on artificial intelligence often perpetuates reductive narratives, primarily by prioritizing voices from the commercial tech industry while sidelining diverse perspectives from civil society and academia. This imbalance can distort public understanding of AI's capabilities and risks, ultimately influencing policy and societal perceptions. Using The New York Times as a case study, we reveal the implications of this trend and call for more inclusive journalism that reflects the complexities of AI technology. Check out the TPP piece here summarising findings → https://lnkd.in/e7U8K62H Link to the full report below 👇

Wolters Kluwer introduces a new AI-enhanced search feature in UpToDate Enterprise Edition, designed to transform how you find answers to medical questions. This cutting-edge technology understands both simple and complex queries using natural language, delivering rapid and reliable answers directly from #UpToDate. Learn more: https://gag.gl/jAUdOk #UpToDateEnterpriseEdition #ClinicalDecisionSupport #HealthcareAI #HealthcareInnovation

Revolutionizing Knowledge Graph Completion with AI-Powered Frameworks In artificial intelligence, knowledge graph completion (KGC) plays a vital role in various applications, including intelligent question-answering, recommendation systems, and dialogue systems. However, traditional KGE methods have limitations when it comes to handling unstructured data and complex reasoning capabilities. The rapid development of large language models (LLMs) has opened new prospects for KGC tasks, but their integration with traditional KGE methods raises new challenges. #quantum #quantumcomputing #technology https://lnkd.in/eEYv-JEP