GenAI Level UP

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 of modern AI, a...

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 fundamental barrier that has...

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 obscures the real gap...

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 especially apparent...

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 Transformer networks...

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 to superior...

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 be concise to a...

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 fiction; it's the...

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 the hype and...

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 unpacks a groundbreaking...

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 trial, error, and...

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 science fiction; this...

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 episode gives you the...

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 prompt bloat and...

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 procedure, where...