MLG 013 Shallow Algos 2

The aggregate job market held, the entry-level door narrowed, and software postings sit a quarter below pre-pandemic. Why cheap implementation made specification, verification and domain scarce, how M...

26 Helmi 36min

OpenClaw as the worked example of the always-on personal agent: gateway, markdown memory, heartbeats, skills, coding agents from your phone, hosted vs local models, and the 2026 security record (expos...

22 Helmi 36min

What an AI agent actually is, why coding agents got good first, how memory really works, what MCP and A2A standardize, which SDKs are alive, how to evaluate on trajectories, and where the products sta...

22 Helmi 33min

How to automate AI media end to end: clone your own voice on open TTS, pick music that's actually licensed, run ComfyUI graphs headless, design around fal, Replicate and provider queues, finish with f...

14 Heinä 202535min

Sora is shut down, Google runs two video models, Kling 3 does lip-synced dialogue, and open-weight MiniMax H3 is what you can actually fine-tune. What a usable clip costs, which models do native audio...

12 Heinä 202532min

Editing replaced generation as the core task. How GPT Image 2.5, Google's Nano Banana line, Midjourney V8.2 and Flux 2 differ, what open weights and LoRAs buy you, ControlNet vs instruction editing, a...

9 Heinä 202530min

Auto encoders are neural networks that compress data into a smaller "code," enabling dimensionality reduction, data cleaning, and lossy compression by reconstructing original inputs from this code. Ad...

30 Touko 20251h 5min

At inference, large language models use in-context learning with zero-, one-, or few-shot examples to perform new tasks without weight updates, and can be grounded with Retrieval Augmented Generation ...

8 Touko 202545min