Tim's AI and data science podcast

T McClean
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  • TECHNOLOGIES

Podcasts on interesting AI, data science and LLM papers. Created using Notebook LLM. Papers you want to read, but don't have the time.

  1. 30 MARS

    Gemini 2.5 Pro: A New State-of-the-Art Model

    **Zvi Mowshowitz's blog post announces Gemini 2.5 Pro Experimental as a new state-of-the-art large language model, highlighting its strong reasoning capabilities and impressive performance on benchmarks.** Despite its technical prowess, the author points out Google's lack of transparency regarding its documentation and system cards, contrasting it with the practices of OpenAI and Anthropic. **Positive user feedback emphasizes Gemini 2.5 Pro's ability to solve complex problems and excel in coding, often surpassing previous top models.** The post also includes various benchmarks and user anecdotes showcasing its strengths in areas like reasoning, coding, and long context understanding. **While acknowledging minor shortcomings and the need for improved rate limits, the overall sentiment suggests that Gemini 2.5 Pro represents a significant advancement in AI and could shift the competitive landscape.**

    25 min

  2. 24 MARS

    Open Source: IBM's Granite model

    This technical report from IBM Research introduces the **Granite series of enterprise-ready foundation models** for generative AI tasks. The authors detail the **architecture, training data, governance processes, and evaluation** of these decoder-only large language models, including specific variants like `granite.13b.instruct` and `granite.13b.chat`. The report also covers the **compute infrastructure, energy consumption, and efforts to mitigate socio-technical harms and biases**. Furthermore, it provides **usage policies and documentation** for these models, which are available through IBM's watsonx platform, and discusses ongoing developments including multilingual and multimodal versions.

    21 min

  3. 9 MARS

    Model Context Protocol by Anthropic

    https://modelcontextprotocol.io/llms-full.txt **This compilation of texts introduces the Model Context Protocol (MCP), a standardized framework facilitating communication between language models and external data sources or tools.** It provides client developers with instructions on building a chatbot that connects to MCP servers and also offers instructions to server developers on how to build a server to test out an existing host. **It outlines MCP's architecture, core components, and implementation details, including the roles of resources, prompts, tools, and transports.** The resources emphasize how MCP empowers LLMs to access real-time data, execute actions, and create dynamic workflows while focusing on best practices for security and debugging. **A curated list of example servers demonstrates the versatility of the protocol.**

    1 h 13 min

  4. 2 MARS

    Anthropic's Model Context Protocol (MCP): AI, Agents, and Tooling

    https://www.youtube.com/watch?v=kQmXtrmQ5Zg **This presentation introduces Anthropic's Model Context Protocol (MCP), an open protocol designed to standardize how AI applications and agents interact with external systems.** **MCP aims to solve fragmentation in AI development by providing a unified interface for accessing tools, data, and resources.** **The protocol utilizes prompts, tools, and resources as key interfaces.** **MCP enables developers to build context-rich AI applications that can seamlessly integrate with various data sources.** **The ultimate vision includes agents capable of dynamically discovering new capabilities through a centralized registry, evolving their functionality without requiring pre-programmed knowledge.** **Furthermore, forthcoming features such as remote servers, OAuth support, and a registry API promise enhanced security, discoverability, and extensibility for AI applications.**

    17 min

  5. 28 FÉVR.

    Andrej Karpathy: How I use LLMs

    https://www.youtube.com/watch?v=EWvNQjAaOHw&t=6305s **The YouTube video by Andrej Karpathy is a guide to using Large Language Models (LLMs) like ChatGPT in practical ways.** It offers examples for various settings and applications, and it shows different LLM options, highlighting the differences between the original ChatGPT and its competitors such as Google's Gemini and Anthropic's Claude. **Karpathy explains how these LLMs work, including their pre-training and post-training stages, and discusses the concept of a "thinking model,"** which uses reinforcement learning to improve accuracy in complex tasks. **The video also explores tool use, such as enabling internet search and using a Python interpreter, alongside multi-modal interaction through audio and images.** Karpathy further examines quality of life features, like custom GPTs and memory settings, to demonstrate how users can personalize their experiences.

    20 min

  6. 28 FÉVR.

    TabPFN v2: Analysis, Evaluation, and Scalability Extensions

    https://arxiv.org/html/2502.17361 **The paper comprehensively evaluates TabPFN v2, a novel tabular foundation model, confirming its strong generalization capabilities on small to medium-sized datasets.** It identifies randomized feature tokens as a key mechanism enabling TabPFN v2 to handle diverse data. To better understand TabPFN v2, the authors introduce a leave-one-fold-out strategy, transforming the model into a feature extractor to reveal its data simplification capabilities. The research addresses TabPFN v2's limitations on large, high-dimensional, and many-category tasks by implementing divide-and-conquer methods. **Ultimately, the study provides insights into TabPFN v2's strengths, limitations, and extensions, suggesting future research directions for tabular foundation models.**

    20 min

  7. 26 FÉVR.

    Claude 3.7 Sonnet System Card: Model Evaluations and Safeguards

    **The document introduces Claude 3.7 Sonnet, a hybrid reasoning model, and details its system card with a focus on safety and harm reduction.** **It covers training data, the model's "extended thinking" mode, and the decision to share Claude's reasoning process.** **Evaluations related to child safety, bias, computer use risks like prompt injection, and the faithfulness of extended thinking are presented.** **The document also outlines the Responsible Scaling Policy (RSP) evaluations, including CBRN, autonomy, and cyber assessments, leading to the determination of ASL-2 safeguards.** **Finally, it discusses monitoring for concerning thought processes and methods to address excessive focus on passing tests, highlighting ongoing safety commitments and third-party assessments.**

    14 min

  8. 26 FÉVR.

    Time to Welcome Claude 3.7 by Zvi Mowshowitz

    **Zvi Mowshowitz's blog post introduces Anthropic's Claude 3.7, highlighting its capabilities and safety measures.** The new model features an upgraded underlying architecture with optional reasoning capabilities and a command-line coding tool called Claude Code. **The post emphasizes the model's strength in coding tasks and analyzing long texts.** Anthropic has focused on safety, releasing a system card outlining extensive safety considerations and testing, which suggests that we are rapidly approaching the danger zone. **Despite improvements, the model remains within the ASL-2 safety level, though ASL-3, which would significantly increase the risk of misuse, may be coming soon.** The post also mentions the model's easter egg, and the system prompt that guides Claude's behavior.

    15 min
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À propos

Podcasts on interesting AI, data science and LLM papers. Created using Notebook LLM. Papers you want to read, but don't have the time.

Informations

  • Création
    T McClean
  • Années d’activité
    2024 - 2025
  • Épisodes
    53

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