Four years before Google reportedly paid £400M for DeepMind
Demis Hassabis stood on a conference stage and revealed the idea behind the lab.
His argument sounded almost wrong:
The fastest path to AGI was not copying the human brain
It was stealing its algorithms.
Hassabis rejected both extremes.
Symbolic AI had already consumed an estimated 600 man-years, yet adding one rule could create weeks of contradictions.
Whole-brain emulation was still 50+ years away.
The valuable layer sat in the middle:
representations
learning algorithms
memory
attention
mental simulation
Then he gave the proof.
Engineers invented reinforcement learning with mathematics.
Neuroscientists later found the brain using nearly the same prediction-error mechanism through dopamine.
That was in 2010.
Before DeepMind became Google’s most important AI lab.
This forgotten lecture contains the intellectual blueprint behind a company Google later bought for hundreds of millions.
It is worth more than most $500 AGI courses.
Bookmark it and watch it below ↓
Walter Isaacson, the biographer behind Steve Jobs and Elon Musk, is using a free Google tool to analyze Marie Curie’s journals.
Meanwhile people are paying $240–$600 a year for AI memory apps that mostly remember the last conversation.
NotebookLM works differently.
Bookmark this before another $50 memory app convinces you to subscribe.
You upload the material that shaped how you think:
PDFs
websites
YouTube videos
audio files
Docs and Slides
Then Gemini builds a private research brain around those sources instead of guessing from the open internet. Every answer links back to the exact passage it used.
The system has three moves:
Load - the free version holds up to 50 sources inside one notebook.
Ask - question the entire library and get answers grounded in your own material.
The surprising part comes after the first upload.
A 90-minute podcast, a 40-page PDF, and years of scattered notes stop living in separate tabs.
NotebookLM starts connecting the ideas across the whole pile.
Steven Johnson, Google Labs’ editorial director, calls his version an “everything notebook” and uses project notebooks like another member of the team.
The $50 memory app tries to remember you.
If you want to see how this turns from a second brain into a full work system, start with this breakdown ↓
This developer turned a $150K remote interview into a live AI copilot session.
Before the call, he fed the agent:
1 CV
1 job description
37 pages from the company site
24 likely interview questions
12 fake stories from his past work
Then the interview started.
The recruiter asked one question.
Within seconds, the agent pulled the right project, matched it to the role, and surfaced the strongest answer before he finished thinking.
That is the advantage most people still miss.
They use AI to rewrite a CV after getting rejected.
He used it as a private career team before the offer was even on the table.
The setup can handle:
company research
tailored CV versions
interview prep
salary positioning
follow-up drafts
One strong offer can raise your income by $30K–$80K a year.
A second remote role can change it by another six figures.
It is removing the part where good candidates forget their best examples under pressure.
The full setup takes about 30 minutes to build.
I broke down every file, agent, and workflow below ↓
A founder who generated over $5M from AI businesses
Just uploaded the beginner course most automation agencies would rather sell you.
Liam Ottley spent two years building no-code AI systems and helping NBA teams, adopt them.
He put the entire process into 100 minutes. Free.
Inside:
9:21 - fastest-growing automation opportunities rn
15:48 - the exact tools beginners should learn first
29:00 - build the first sellable automation from 0
1:22:09 - the most advanced build in the course
1:30:36 - why 99% automations fails + how to fix them
At 1:36:55, start Liam teaching you how to sell those automations for high ticket clients
That is where most tutorials stop.
They show you how to connect the tools, then leave you with a workflow nobody has agreed to pay for.
This one covers the products businesses already understand:
Lead qualifiers, voice agents, and proposal generators.
Just the exact course Liam says he wishes existed before he built his first AI company.
The full course is below ↓
Daniel Agrici just open-sourced an SEO department for Claude Code.
claude-seo
25 sub-skills
18 sub-agents
11.1K stars
1.6K forks
Free. Open source. Built for Claude Code and Codex.
→ https://t.co/1iPqvp8qAa
It covers the work most SEO teams split across several specialists:
technical SEO
E-E-A-T
schema
GEO / AEO
backlinks
local SEO
semantic clustering
e-commerce
international SEO
Google APIs
PDF and Excel reporting
The useful part is how the system is structured.
You give Claude the goal, and the right specialist gets pulled into the workflow.
Optional integrations with DataForSEO, Firecrawl, and Banana extend it with live data and deeper research.
Agrici is an AI Marketing Systems Architect and co-founder of Rankenstein.
Now the SEO system he was building for clients is public.
Bookmark it
This is how Claude stops giving generic SEO advice and starts working through the stack like a real team.
One developer just open-sourced an entire AI engineering department.
wshobson/agents packs
192 agents
156 skills
102 commands
84 plugins into one repo.
37.8k stars | MIT
-> https://t.co/0SWSRKRqd7
Covered: Architecture, security, testing, Kubernetes, debugging, data engineering, multi-agent orchestration
The same Markdown source works across Claude Code, Codex, Cursor, Gemini CLI, OpenCode, and GitHub Copilot.
No rebuilding your setup every time you switch tools.
Free. Open source. Ready to install.
This is how one assistant starts operating like a full engineering team ↓
7 GitHub repos that can save you hundreds of dollars every year:
1. https://t.co/zBVSBNgAhw
Download videos from YouTube and hundreds of other sites in multiple formats. Supports audio extraction, playlists, subtitles, and more.
2. https://t.co/tbexdxldAN
OpenAI’s speech recognition model that transcribes audio and video into text with impressive accuracy across 99 languages.
3. https://t.co/mGKQbmO3Di
An open-source alternative to Calendly. Let people book meetings, self-host it if you want, and keep full control of your scheduling data.
4. https://t.co/6jftTSKFic
A free, open-source UI/UX design platform with real-time collaboration. A popular alternative to paid design tools.
5. https://t.co/K2T796Ofgr
A secure, open-source password manager. Store, sync, and manage passwords without being locked into proprietary software.
6. https://t.co/YHBvLakkdU
An open-source AI model trained on billions of financial data points to analyze market trends and price movements.
7. https://t.co/UmEXx1VmQV
Drop your raw footage into a folder, tell Claude Code what you want, and it automatically edits the video, removes filler words, adds subtitles, color grading, and exports a polished final video.