AI Inference
549 episodes · Page 13 of 23
#2405: LLM Benchmarks Are Full of Noise: Statistical Rigor in AI Evals
Why most benchmark claims in AI are statistically indefensible — and what to do about it.
#2388: From Tool Picker to Problem Solver
Discover how OpenRouter intelligently routes your prompts to the most optimized AI model, reshaping how we interact with AI tools.
#2374: How Granular Can MoE Experts Get?
Exploring the limits of expert granularity in Mixture of Experts models—how narrow can segmentation go before efficiency or accuracy suffers?
#2368: The Multi-Stage Pipeline Behind Netflix's Recommendations
Unpacking the multi-stage AI pipeline behind Netflix, Spotify, and Amazon’s "you might also like" suggestions—from candidate generation to real-tim...
#2356: Why AI Coding Needs Two Brains
Discover how specialized fast apply models streamline AI-powered code edits, cutting costs and latency while maintaining precision.
#2355: Why Open-Weight Models Are Winning
Discover how Cogito v2.1 leverages process supervision and MoE architecture to redefine reasoning efficiency in open-weight AI models.
#2353: Evaluating Enterprise AI: Palmyra X5
Explore Palmyra X5, Writer’s flagship AI model designed for enterprise workloads, featuring a million-token context window and agentic capabilities.
#2352: The Structured Output Gap in Vision APIs
How do object detection APIs like Gemini, AWS Rekognition, and YOLO compare for automated annotation workflows?
#2351: AI Model Spotlight: ** Aion-2.0
Why is a biopharma AI lab releasing a storytelling-optimized model? We explore Aion-2.0’s architecture, pricing, and niche adoption.
#2350: NVIDIA's Strategic Pivot: From Chipmaker to Model Builder
Dive into NVIDIA’s Nemotron 3 Super, a hybrid MoE model combining Mamba, Transformers, and multi-token prediction for cutting-edge efficiency.
#2349: The 30-Person Lab Outpacing AI Giants
Discover how Arcee AI’s Trinity Large Thinking delivers cutting-edge reasoning at a fraction of the cost, all from a team of just 30.
#2348: Diffusion Models Take on Text Generation
Explore Inception Labs’ Mercury 2, a groundbreaking diffusion-based language model that rethinks text generation and reasoning.
#2340: How AI Models Track a Ship Seizure’s Ripple Effects
When the US seized an Iranian cargo ship, three AI models reshuffled their predictions overnight. Here’s what they saw—and where they disagreed.
#2335: Staking Out the Middle: UK's Post-Brexit AI Strategy
The UK’s £500M Sovereign AI Fund is a bold move to boost domestic AI startups with compute access, visas, and strategic partnerships. How does it s...
#2314: One Model or Three? Inside Claude's Architecture
What makes Claude’s Haiku, Sonnet, and Opus different? Discover how architecture shapes their unique strengths and weaknesses.
#2312: When Bigger Context Windows Aren't Better
Exploring the real-world impact of massive context windows in AI models, from academic research to codebase analysis.
#2308: When AI Forecasts Collide: Geopol Model Divergence
Five AI models forecast the Iran-Israel-US crisis — and their disagreements reveal surprising insights about geopolitical reasoning.
#2307: Inside Frontier LLM Training: Stages, Costs, and Checkpoints
Discover the multi-stage process of training frontier large language models, from pretraining to post-training, and why checkpoints are the key to ...
#2303: The Serverless Paradox: Why TTS Eats Your Budget
How batch processing and smart queue management can slash TTS costs for episodic podcast production.
#2295: Why Taiwan's Automation Strategy Leaves the West Behind
Asus has achieved 85% automation in motherboard production—how did they outpace Western competitors?
#2288: The Invisible Gatekeeper of Voice Tech
How voice activity detection shapes every step of the voice tech pipeline, and why it’s harder than it seems.
#2272: The AI Transcription Sweet Spot
Does higher-quality audio make AI transcription worse? New research reveals a surprising "sweet spot" for bitrate, challenging a core assumption of...
#2253: Why AI Agents Get Three Steps, Not Infinity
Why do AI agents get exactly three rounds of tool use? It's a critical guardrail against infinite loops and runaway costs, not a limit on intellige...
#2243: What Enterprise AI Pricing Actually Negotiates
Enterprise customers rarely get the deep discounts they expect from AI APIs. What they actually negotiate for—and why the ramp-up requirement exist...