logo
episode-header-image
May 10
24m 41s

Memory Management for AI Agents (The Age...

SoundCloud Feeds
About this episode
Context windows are powerful — but finite, and surprisingly easy to overwhelm. When an AI agent is tackling a long, complex task, the information it needs has to fit inside that limited real estate, and research shows that anything buried in the middle tends to quietly disappear. So how do you design a system that actually *remembers* what matters? This epis ... Show More
Up next
May 4
Lost in the Middle (The Agents Season, Episode 3)
Just like a memorable talk lives or dies by its opening and closing, LLMs have a surprisingly similar quirk: they pay close attention to what's at the beginning and end of their context window — and kind of zone out in the middle. This "lost in the middle" phenomenon has real con ... Show More
19m 44s
Apr 27
ReAct and Tool Usage (The Agents Season, Episode 2)
Before 2022, there was a wall between AI and the real world — models could reason impressively, but couldn't look anything up, run code, or check whether anything they said was actually true. This episode traces the moment that wall came down, through two landmark papers: ReAct, ... Show More
23m 41s
Apr 20
What's an AI Agent? And Why's That Hard to Define? (The Agents Season, Episode 1)
AI agents are having a moment — and unpacking them properly takes more than a single conversation. This episode kicks off a dedicated multi-part season exploring AI agents from every angle, building up a complete picture piece by piece rather than skimming the surface. Think of i ... Show More
19m 3s
Recommended Episodes
Feb 2022
AI Today Podcast: Overview of Synthetic Data
Machine learning algorithms need examples of data from which they can learn, especially supervised machine learning algorithms. However, one big challenge for those looking to put machine learning into practice is the lack of a sufficient quantity of good quality data examples fr ... Show More
47m 14s
Feb 2017
MLG 004 Algorithms - Intuition
<div> <p>Machine learning consists of three steps: prediction, error evaluation, and learning, implemented by training algorithms on large datasets to build models that can make decisions or classifications. The primary categories of machine learning algorithms are supervised, un ... Show More
23m 27s
Jun 2020
Rust and machine learning #4: practical tools (Ep. 110)
<p>In this episode I make a non exhaustive list of machine learning tools and frameworks, written in Rust. Not all of them are mature enough for production environments. I believe that community effort can change this very quickly.</p> <p>To make a comparison with the Python ecos ... Show More
24m 18s
Feb 2017
MLG 001 Introduction
<p>Show notes: <a href= "https://ocdevel.com/mlg/1?utm_source=podcast&utm_medium=mlg&utm_campaign=mlg1" target="_blank" rel="noopener">ocdevel.com/mlg/1</a>. MLG teaches the fundamentals of machine learning and artificial intelligence. It covers intuition, models, math, languages ... Show More
8m 11s
Nov 2024
SE Radio 641: Catherine Nelson on Machine Learning in Data Science
<p><strong>Catherine Nelson</strong>, author of the new O'Reilly book, <em data-renderer-mark="true">Software Engineering for Data Scientists</em>, discusses the collaboration between data scientists and software engineers -- an increasingly common pairing on machine learning and ... Show More
48m 19s
Jul 2023
AI Today Podcast: AI Glossary Series – Automated Machine Learning (AutoML)
In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the term Automated Machine Learning (AutoML), explain how this term relate to AI and why it’s important to know about them. Show Notes: FREE Intro to CPMAI mini course CPMAI Training and Certifi ... Show More
9m 11s
Mar 2017
MLG 009 Deep Learning
tail spinning
51m 28s
Apr 2021
464: A.I. vs Machine Learning vs Deep Learning
In this episode, I tackle three often conflated terms - AI, machine learning, and deep learning - to shine some light on what exactly they are. Additional materials: www.superdatascience.com/464 
7m 14s
Feb 2017
MLG 002 Difference Between Artificial Intelligence, Machine Learning, Data Science
<div> <div> <p>Artificial intelligence is the automation of tasks that require human intelligence, encompassing fields like natural language processing, perception, planning, and robotics, with machine learning emerging as the primary method to recognize patterns in data and make ... Show More
1h 5m