ibl.ai
ibl.ai is a generative AI education platform based in NYC. This podcast, curated by its CTO, Miguel Amigot, focuses on high-impact trends and reports about AI.
Episodes
Summary of https://arxiv.org/pdf/2504.16902
Explores the critical need for secure communication protocols as AI systems evolve into complex networks of interacting agents. It focuses on Google's Agent-to-Agent (A2A) protocol, designed to enable secure and structured communication between autonomous agents.
The authors analyze A2A's security through the MAESTRO threat modeling framework, identifying potential vulnerabilities like ag...
Summary of https://arxiv.org/pdf/2412.15473
Investigates whether student log data from educational technology, specifically from the first few hours of use, can predict long-term student outcomes like end-of-year external assessments.
Using data from a literacy game in Uganda and two math tutoring systems in the US, the researchers explore if machine learning models trained on this short-term data can effectively predict performanc...
This is a Policy Research Working Paper from the World Bank's Education Global Department, published in May 2025. Titled "From Chalkboards to Chatbots: Evaluating the Impact of Generative AI on Learning Outcomes in Nigeria," it details a study on the effectiveness of using large language models, specifically Mi...
Introduces a multi-agent system built using the OpenAI Agents SDK for complex investment research. It outlines an "agent as a tool" pattern where a central Portfolio Manager agent orchestrates specialized agents (Fundamental, Macro, Quantitative) and various tools to analyze market data and generate inv...
Summary of https://www.bondcap.com/report/pdf/Trends_Artificial_Intelligence.pdf
Extensively examines the rapid evolution of Artificial Intelligence, highlighting its unprecedented growth in user adoption, usage, and capital expenditure.
It details the competitive landscape, noting the rise of open-source models and the significant presence of China alongside the USA in AI development.
The text also explores AI's increasing integra...
Presents an overview of AI agents, defined as autonomous systems capable of complex tasks without constant human supervision, highlighting their rapid progression from research to real-world application.
It identifies three major risks: catastrophic misuse through malicious applications, gradual human disempowerment ...
Summary of https://conference.pixel-online.net/files/foe/ed0015/FP/8250-ESOC7276-FP-FOE15.pdf
This conceptual paper explores the potential of AI-driven conversations, such as those from ChatGPT, to function as dynamic Open Educational Resources (OER) that support self-directed learning (SDL).
Unlike traditional, static resources, AI-powered dialogues offer personalized, interactive, and adaptive experiences that align with learners...
Summary of https://www.kaggle.com/whitepaper-agent-companion
This technical document, the Agents Companion, explores the advancements in generative AI agents, highlighting their architecture composed of models, tools, and an orchestration layer, moving beyond traditional language models.
It emphasizes Agent Ops as crucial for operationalizing these agents, drawing parallels with DevOps and MLOps while addressing agent-specific need...
Summary of https://arxiv.org/pdf/2503.23674
Researchers Cameron R. Jones and Benjamin K. Bergen investigated whether advanced large language models (LLMs) can pass the standard three-party Turing test. Their study involved human interrogators conversing with both a human and an AI, then judging which was human.
The findings indicate that GPT-4.5, when prompted to adopt a persona, was identified as human significantly more often tha...
Summary of https://imaginingthedigitalfuture.org/wp-content/uploads/2025/03/Being-Human-in-2035-ITDF-report.pdf
This Elon University Imagining the Digital Future Center report compiles insights from a non-scientific canvassing of technology pioneers, builders, and analysts regarding the potential shifts in human capacities and behaviors by 2035 due to advanced AI. Experts anticipate blurred boundaries between reality and fiction, h...
Nvidia's GTC 2025 highlighted a significant shift in AI, moving from experimental phases to becoming core enterprise infrastructure. The event showcased how data remains crucial, but AI itself is now a data generator, leading to new insights and efficiencies.
Furthermore, smaller, specialized AI model...
Summary of https://transformer-circuits.pub/2025/attribution-graphs/methods.html
Introduces a novel methodology called "circuit tracing" to understand the inner workings of language models. The authors developed a technique using "replacement models" with interpretable components to map the computational steps of a language model as "attribution graphs." These graphs visually represent how different computational units, or "feature...
Summary of https://www.rand.org/content/dam/rand/pubs/research_reports/RRA100/RRA134-25/RAND_RRA134-25.pdf
A RAND Corporation report, utilizing surveys from the 2023-2024 school year, investigates the adoption and use of artificial intelligence tools by K-12 public school teachers and principals. The research highlights that roughly one-quarter of teachers reported using AI for instructional planning or teaching, with higher usage ...
Stanford HAI highlights a growing disparity between academia and industry in frontier AI research. Industry's access to vast resources like data and computing power allows them to outpace universities in developing advanced AI systems.
The authors argue that this imbalance risks hindering public-interest AI innovation ...
Summary of https://arxiv.org/pdf/2502.12447
Explores the rapidly evolving influence of Generative AI on human cognition, examining its effects on how we think, learn, reason, and engage with information. Synthesizing existing research, the authors analyze these impacts through the lens of educational frameworks like Bloom's Taxonomy and Dewey's reflective thought theory.
The work identifies potential benefits and significant concer...
Summary of https://arxiv.org/pdf/2406.02061
Introduces the "Alice in Wonderland" (AIW) problem, a seemingly simple common-sense reasoning task, to evaluate the capabilities of state-of-the-art Large Language Models (LLMs). The authors demonstrate that even advanced models like GPT-4 and Claude 3 Opus exhibit a dramatic breakdown in generalization and basic reasoning when faced with minor variations of the AIW problem that do not al...
Summary of https://nvlpubs.nist.gov/nistpubs/ai/NIST.AI.100-2e2025.pdf
This NIST report explores the landscape of adversarial machine learning (AML), categorizing attacks and corresponding defenses for both traditional (predictive) and modern generative AI systems.
It establishes a taxonomy and terminology to create a common understanding of threats like data poisoning, evasion, privacy breaches, and prompt injection. The document ...
Summary of https://journals.sagepub.com/doi/10.1177/20539517241299732
Explores the emerging field of artificial intelligence ethics auditing, examining its rapid growth and current state through interviews with 34 professionals. It finds that while AI ethics audits often mirror financial auditing processes, they currently lack robust stakeholder involvement, clear success metrics, and external reporting.
The study highlights a pred...
Summary of https://www.nature.com/articles/s41599-024-04018-w
Investigates how the increasing use of artificial intelligence in organizations affects employee mental health, specifically job stress and burnout. The study of South Korean professionals revealed that AI adoption indirectly increases burnout by first elevating job stress.
Importantly, the research found that employees with higher self-efficacy in learning AI experience...
Summary of https://www.eciia.eu/wp-content/uploads/2025/01/The-AI-Act-Road-to-Compliance-Final-1.pdf
"The AI Act: Road to Compliance," serves as a practical guide for internal auditors navigating the European Union's Artificial Intelligence Act, which entered into force in August 2024. It outlines the key aspects of the AI Act, including its risk-based approach that categorizes AI systems and imposes varying obligations based on ri...
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