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S3E20 Master the New Physics of AI with Context Graphs & GraphRAG
Stop trying to find the "magic words" to hack your LLM. The era of the Prompt Engineer—tweaking adjectives and hoping for the best—is officially over. We are entering the age of the Context Engineer,…
S3E19 Context Graph
Stop feeding your AI static facts in a dynamic world.Most RAG systems and Knowledge Graphs rely on a fundamental unit called the "Triple" (Subject, Verb, Object). It’s efficient, but it’s brittle. It…
S3E18 Nested Learning: The Illusion of Deep Learning Architectures
Why do today's most powerful Large Language Models feel... frozen in time? Despite their vast knowledge, they suffer from a fundamental flaw: a form of digital amnesia that prevents them from truly…
S3E17 Memento: Fine-tuning LLM Agents without Fine-tuning LLMs
What if you could build AI agents that get smarter with every task, learning from successes and failures in real-time—without the astronomical cost and complexity of constant fine-tuning? This isn't…
S3E16 MemGPT: Towards LLMs as Operating Systems
Have you ever felt the frustration of an LLM losing the plot mid-conversation, its brilliant insights vanishing like a dream? This "goldfish memory"—the limited context window—is the Achilles' heel…
S3E15 DeepSeek-OCR: Contexts Optical Compression
The single biggest bottleneck for Large Language Models isn't intelligence—it's cost. The quadratic scaling of self-attention makes processing truly long documents prohibitively expensive, a…
S3E14 A Definition of AGI
For decades, Artificial General Intelligence has been a moving target, a nebulous concept that shifts every time a new AI masters a complex task. This ambiguity fuels unproductive debates and…
S3E13 Teaching LLMs to Plan: Logical CoT Instruction Tuning for Symbolic Planning
Large Language Models (LLMs) like GPT and LLaMA have shown remarkable general capabilities, yet they consistently hit a critical wall when faced with structured symbolic planning. This struggle is…
S3E12 Five Orders of Magnitude: Analog Gain Cells Slash Energy and Latency for Ultra-Fast LLMs
In this episode, we explore an innovative approach to overcoming the notorious energy and latency bottlenecks plaguing modern Large Language Models (LLMs).The core of generative LLMs, powered by…
S3E11 The Great Undertraining: How a 70B Model Called Chinchilla Exposed the AI Industry's Billion-Dollar Mistake
For years, a simple mantra has cost the AI industry billions: bigger is always better. The race to scale models to hundreds of billions of parameters—from GPT-3 to Gopher—seemed like a straight line…
S3E10 RewardAnything: Generalizable Principle-Following Reward Models
What if the biggest barrier to truly aligned AI wasn't a lack of data, but a failure of language? We spend millions on retraining LLMs for every new preference—from a customer service bot that must…
S3E9 AI That Evolves: Inside the Darwin Gödel Machine
What if an AI could do more than just learn from data? What if it could fundamentally improve its own intelligence, rewriting its source code to become endlessly better at its job? This isn't science…
S3E8 The AI Reasoning Illusion: Why 'Thinking' Models Break Down
The latest AI models promise a revolutionary leap: the ability to "think" through complex problems step-by-step. But is this genuine reasoning, or an incredibly sophisticated illusion? We move beyond…
S3E7 When AI Rewrites Its Own Code to Win: Agent of Change
Large Language Models have a notorious blind spot: long-term strategic planning. They can write a brilliant sentence, but can they execute a brilliant 10-turn game-winning strategy?This episode…
S3E6 Eureka: How AI Learned to Write Better Reward Functions Than Human Experts
Reward engineering is one of the most brutal, time-consuming challenges in AI—a "black art" that forms the very foundation of how intelligent agents learn. For decades, it's been a manual process of…
S3E5 AlphaEvolve: How Google's AI Now Evolves Code to Solve Decades-Old Puzzles & Optimize Our World
Imagine an AI that doesn't just write code, but evolves it—learning, adapting, and iteratively improving to conquer challenges that have stumped human ingenuity for over half a century. This isn't…
S4E1 LLM Evaluation - How We Really Know If AI Is Getting Smarter
AI leaps forward every week, but how do we cut through the noise and truly measure progress? This isn't just academic; it's fundamental to trusting and advancing AI. Forget marketing claims – this…
S2E10 RAG-MCP: Mitigating Prompt Bloat and Enhancing Tool Selection for LLM
Large Language Models (LLMs) face significant challenges in effectively using a growing number of external tools, such as those defined by the Model Context Protocol (MCP). These challenges include…
S2E9 DeepSeek Prover V2 - AI's New Frontier in Formal Mathematics
In this episode, we dissect DeepSeek Prover V2, an open-source large language model pushing the boundaries of AI in formal theorem proving using Lean 4. We unpack its innovative "cold start" training…
S3E4 From QA to AI Improvement Engineer: Navigating the Shift in the AI Era
Quality Engineering (QE) professionals are well-positioned to transition into AI Improvement Engineering roles due to their deep knowledge of testing, quality assurance, and processes. This…
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GenAI Level UP has published 44 episodes since November 2024, covering topics in Technology.
GenAI Level UP is currently dormant with new episodes weekly. Average episode length is 17m.
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