Tim's AI and data science podcast

T McClean

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 MAR

    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 MAR

    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 MAR

    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.**

    1h 13m

  4. 2 MAR

    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 FEB

    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 FEB

    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 FEB

    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 FEB

    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
See All (53)

About

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

Information

  • Creator
    T McClean
  • Years Active
    2024 - 2025
  • Episodes
    53
  • Provider

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