AI/SI 6

• Video These 19 Jev-Claude use cases are blowing people's minds (with prompts) — Jay E | RoboNuggets
  AI summary

  This video introduces Jev, a new AI decision model that can be up to 200 times faster and 400 times cheaper than traditional models. The presenter, Jay Enriquez, shares 19 practical use cases for Jev across easy, intermediate, and advanced levels, demonstrating how it can be used for tasks like spreadsheet categorization, customer inquiry triage, and ad analysis. By acting as a fast and cheap decision layer before larger AI models, Jev can streamline workflows and reduce token costs. - Jev functions as a decision model that picks true/false, menu options, or scores rather than generating full sentences, making it lightning-fast and inexpensive. - Practical use cases include automating Google Sheets categorization, triaging customer emails, analyzing competitor ads, clipping long videos, and scoring customer churn risk. - Jev can be used for intermediate tasks like picking the right skill or model in coding environments, routing emails, and building Chrome extensions to filter feeds. - Advanced applications include live fact-checking, building zero-LLM-call chatbots, designing dynamic web pages, and finding personalized use cases via meta-prompts.
• Video What's New with Anthropic: September 2026 Update! — DIY Smart Code
  AI summary

  Anthropic released several updates in September 2026, including the launch of Claude 5.5 models (Opus 5.5 and Sonnet 5.5), integrations like Claude Cowork and Chat, and the Claude Marketplace. The updates also introduced the MCP 2.0 spec, improvements to Claude Code projects, and new security features and threat reports. - Claude 5.5 models (Opus 5.5 and Sonnet 5.5) were released with lower costs and better performance compared to their predecessors. - Claude Cowork and Chat were merged into a single application, along with the launch of Claude Docs and Slides. - Claude Code introduced project rebuilding with coordinators and threads for managing multiple sessions. - The Claude Marketplace launched with over 2,000 connectors, plugins, and agent products. - MCP 2.0 support was added, including MCP Apps for interactive UI in chat and personal connectors in Slack.
• Video Chamath: 3 Things Every Company Needs in the Age of Superintelligence — All-In Podcast
  AI summary

  Chamath Palihapitiya discusses the essential governance framework companies need when adopting superintelligent AI, particularly in light of tech leaders agreeing on self-regulation measures. He argues that practical corporate safeguards are far superior to legislative proposals calling for AI bans or development pauses. Implementing structured internal controls ensures companies remain compliant, transparent, and legally protected. - Companies require end-to-end traceability so leadership and boards have clear visibility into how AI operates. - Organizations must map policies to risks and align AI deployments with standard operating procedures. - Businesses need auditable evidence to prove compliance to regulators, auditors, lawyers, and clients if issues arise. - Internal corporate governance provides a workable solution that avoids stalling technological innovation and economic growth.
• Video Master 96% of Codex in under 35 minutes — Nate Herk | AI Automation
  AI summary

  In this video, a content creator named Nate Herk breaks down 18 core Codex concepts into four parts: Foundation, Environments, Control & Customization, and Tools & Scale. He covers projects, agents.md files, the agent loop, goal prompts, local versus cloud environments, worktrees, .codex settings, different AI models and their pricing, effort levels, permissions, skills, plugins, the browser feature, sites, subagents, scheduled tasks, and voice mode, demonstrating how they work with practical examples to help viewers use Codex effectively. - Part 1 covers Foundations, explaining projects as file/folder collections, agents.md for agent rules, the agentic loop, and /goal prompts for setting objectives. - Part 2 focuses on Environments, discussing local versus cloud setups, workspace worktrees, and user versus project scope in .codex configuration files. - Part 3 addresses Control and Customization, detailing AI model selection, API and subscription pricing, effort levels, user permissions, and reusable agent skills in .agents folders. - Part 4 highlights Tools and Scale, showcasing the built-in browser, hosting sites, delegating work to subagents, scheduled tasks, and voice mode for multimodal control.
• Video Every Ways to Get 32GB VRAM for Local AI at Full Context — Kai
  AI summary

  Running capable local AI models like Qwen 2.5 27B at high context lengths requires 32 GB of VRAM, a tier where standard 24 GB consumer cards fall short. However, evaluating options purely by price-per-gigabyte is misleading due to hidden hardware expenses, dropped driver support, and operating system memory limits. The video analyzes real-world hardware options and software engines to demonstrate which setups provide practical performance versus unexpected friction. - Running 27B models at 6-bit quantization with long context windows pushes memory use to nearly 29 GB, making true 32 GB capacity necessary. - Budget enterprise GPUs like the AMD MI50 and Nvidia Tesla V100 suffer from dropped official software support, painfully slow prompt
• Video ⁠⁠7 Claude Hacks That Feel Illegal (And 3 to Avoid) — Austin Marchese
  AI summary

  This video breaks down the best and worst advice for building with AI tools by ranking ten popular strategies on a