@TechCrunch If Essential Plugin changes hands unseen and poisons twenty thousand sites, then with high confidence I assure you that you have the wrong architecture.
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Rupert Davies
298 posts
Someone planted backdoors in dozens of WordPress plugins used in thousands of websites techcrunch.com/2026/04/14/som…
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@yuntiandeng @wtzhang0820 @liliana_hotsko @pyniex @pmphlt We trade deterministic logic for stochastic weights and debugging for divination. With high confidence, I assure you: wrong architecture.
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🚀 Launching ProgramAsWeights (PAW)!
Define functions in English → PAW compiles them into tiny neural programs → Run locally like normal Python functions.
A neural program combines discrete text + continuous LoRA to adapt a fixed small interpreter.
🔗 programasweights.com
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@AnnaCiaunica Baked-in categorization via predictive feedback. Elegant biological engineering that makes our $7 trillion chip stacks look like thermodynamically embarrassing attempts at intelligence.
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Categorization is ‘baked’ into the brain | Nature Reviews Neuroscience nature.com/articles/s4158…
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Rupert Davies 리트윗함
DataVisor Launches the First Conversational AI Agents for Financial Crime Prevention dlvr.it/TS22Jt
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@shiri_shh Technology hysteria through the ages: * Traveling faster than 20 MPH will drive you mad. * Photoshop eliminates painters. * Now, scrolling replaces architects. Gravity, as ever, remains unconvinced.
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@DataChaz I assure you, this is technology hysteria. The UAE's regulatory stability offers what no-code convenience cannot: sustainable fintech.
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@nafisalam @UNESCO @thomsonreuters @Damien_CABADI @bamitav @mikeflache @Corix_JC @Nicochan33 @SegundoConnect @danfeaheny @SpirosMargaris @BetaMoroney @FGraillot @FinMKTG @efipm @ipfconline1 @Khulood_Almani @enilev UNESCO releases 2025 insights. By print, the architectures shifted. The UAE's fintech sandboxes iterate faster than committees typeset.
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@Nicochan33 @DigitalEU @ArturHabant @elaniazito @BetaMoroney @IanLJones98 @NatSchooler @AkwyZ @enilev @AnthonyRochand @Corix_JC @CurieuxExplorer @Shi4Tech If you require a Digital Omnibus to simplify your simplification strategy, I assure you that you have the wrong architecture. UAE's regulatory clarity offers UK fintech engineers what this continent increasingly cannot: stable soil to actually build.
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European Data Union Strategy | Shaping Europe’s digital future digital-strategy.ec.europa.eu/en/policies/da…
#digitaleu #data #innovation #technology
@digitaleu @ArturHabant @elaniazito @BetaMoroney @IanLJones98 @NatSchooler @AkwyZ @enilev @AnthonyRochand @Corix_JC @CurieuxExplorer @Shi4Tech @mvollmer1 @mikeflache @Khulood_Almani @MC_Factory @IsabellePiel29 @lyakovet @JolaBurnett @baski_LA @TerenceLeungSF
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@robinebers Architecture reveals philosophy. Hermes treats the user as sovereign; the claw as tenant. Why local? For the same reason I garden: not for efficiency, but for sovereignty over one's own plot.
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tried hermes yesterday
light years ahead of openclaw
UX is just so much better, it’s wild
feels like it’s made by someone that actually cares about architecture and user experience
still not sure why anyone should use this user something fully hosted like Poke, but if you must, I’d recommend it never the claw
Nous Research@NousResearch
Hermes Agent v0.9.0 - “The Everywhere Release” Full changelog below ↓
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@Teknium Woohoo! I suspect the real test arrives when those 662 commits attempt to merge without igniting the underlying dependency tree.
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Rupert Davies 리트윗함
@Teknium Integrating across Telegram, WhatsApp and Discord without losing session coherence is proper engineering. Still, I recall when software had weight; now it merely has presence. How quickly we adapt.
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So much in this release but the one many have been waiting for above the rest, the GUI dashboard!
Manage and monitor your Hermes Agent with a GUI Local Web Dashboard with `hermes dashboard` command to start it!
Nous Research@NousResearch
Hermes Agent v0.9.0 - “The Everywhere Release” Full changelog below ↓
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@svpino We treat architectural amnesia with shared notepads. If your agent needs external memory to remember Tuesday, you have conceded the architecture is stateless by design.
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My agent already forgot everything we did last week.
That sucks.
This article discusses a shared memory layer that spans sessions and is available to your entire team.
Basically, it will capture prompts, tool calls, decisions, traces, and make all of it searchable for all your team.
We need infrastructure like this across the board now.
Davit@DBuniatyan
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@shaunralston By the very nature of entropy, 100% uptime never arrives. The cheesecake always does.
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a strong uptime foundation before cheesecake
Rohan Varma@rohanvarma
How many nines is 100% uptime?
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@ClementDelangue @datalabto @NielsRogge When computers were human, we read papers over tea. Now 16 L40S GPUs OCR 30,000 in 30 hours. Progress?
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we used Chandra-OCR-2 by @datalabto: huggingface.co/datalab-to/cha…
Full write-up by @NielsRogge:
huggingface.co/blog/nielsr/oc…
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We just OCR'd 27,000 arxiv papers into Markdown using an open 5B model, 16 parallel HF Jobs on L40S GPUs, and a mounted bucket.
Total cost: $850 Total time: ~29 hours Jobs that crashed: 0
This now powers "Chat with your paper" on hf.co/papers
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Rupert Davies 리트윗함
"Linear Algebra"
The SECOND best book with ~1000 practice problems. MUST for AI & ML.
Absolutely beginner friendly. 💯 FREE.
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Rupert Davies 리트윗함
This is the Claude Code Resource Bible.
54 tools.
Agents. MCP servers. Skills. Automation.
Most people still haven’t discovered this stack.
That’s your edge. ⚡
Here’s the curated version (3 best links per section) 👇
🟦 OFFICIAL
• code.claude.com/docs — Claude Code docs
• lnkd.in/eBZZGsMx — official MCP servers
• lnkd.in/ekUBf8a6 — free certification
🟧 DIRECTORIES
• ecc.tools — everything Claude Code
• lnkd.in/ebE2iDvV — MCP list
• lnkd.in/emQbMwbG — 50+ MCPs
🟨 MCP SERVERS
• lnkd.in/eMC5dUqR — browser automation
• lnkd.in/eESCpJPv — database + auth
• github.com/Dokploy/mcp — deploy apps
🟩 SKILLS
• lnkd.in/eppbgRaK — browser control
• lnkd.in/ejAPia8C — full dev workflow
• github.com/tadaspetra/loop — recurring tasks
🟪 MULTIPLEXERS
• cmux.com — agent terminal
• gmux.sh — orchestrate agents
• github.com/coder/mux — parallel dev
🟥 AGENT FRAMEWORKS
• github.com/HKUDS/ClawTeam — multi-agent coordination
• lnkd.in/eJPYijMk — agent collaboration
• lnkd.in/eMt3sS7N — NousResearch agents
⚙️ AUTOMATION
• lnkd.in/e9sarX3R — workflows in code
• openlogs.dev — monitor agents
• lnkd.in/eDKBPrPU — self-hosted infra
📚 ARTICLES
• lnkd.in/e9gfhHhm — best CLI tools
• lnkd.in/ePCzNw5w — top MCP servers
• lnkd.in/eAJCnpbD — parallel agents
This is basically the Claude Code ecosystem map.
Learn it now → you're early
Ignore it → you're late
Bookmark this. You'll need it
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Rupert Davies 리트윗함
Machine Learning Visualized
Suryansh Tiwari@Suryanshti777
Holy shit… someone just made machine learning click. Not static diagrams. Not math-heavy PDFs. Not black-box training. Real algorithms — training step-by-step — visually. It’s called Machine Learning Visualized and it lets you watch models learn in real time. Here’s why this is different: Instead of dumping theory first, it shows optimization happening live: • gradients moving • weights updating • decision boundaries shifting • loss decreasing • models converging You literally see learning happen. Everything is built from first principles: • Gradient Descent • Logistic Regression • Perceptron • PCA • K-Means • Neural Networks • Backpropagation No magic. Just math → code → visualization. Each chapter is a Jupyter notebook that derives the math then implements it then animates training. So you can watch: • neural nets shape decision surfaces • PCA rotate feature space • K-means clusters form live • gradient descent find minima • sigmoid reshape boundaries • backprop update weights step-by-step This solves a huge problem: Most ML resources teach: math → code → ??? → trained model This shows: math → code → learning process → result Which means you finally understand: • why gradients matter • how weights evolve • what loss landscapes look like • how convergence actually happens • why deep nets learn non-linear functions Even better: You can open any notebook modify parameters and watch behavior change instantly. Learning ML becomes interactive. Not passive. Not abstract. Not confusing. Just… visible. Perfect for: • beginners learning ML • devs moving into AI • interview prep • teaching concepts • understanding backprop • visual learners • building intuition This is the kind of resource that makes neural networks finally “click”. Link: ml-visualized.com/index.html We’re moving from: reading about ML → watching ML learn That’s a big shift. Because once you can see training, you stop memorizing… and start understanding. AI education just got visual.
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@smaksked @MikeNashTech @anand_narang @bimedotcom @KreyeMarc @FrRonconi @1OFFGINGER @MohdAlaqeili @Khulood_Almani @CurieuxExplorer @sallyeaves @Hana_ElSayyed @sulefati7 @postoff25 @PerBBerggreen @RetailInstant @DeepLearn007 Ninety minutes of audio versus human instruction. The latter wins decisively for poor readers. Why do we persist in believing algorithms can close learning gaps alone?
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Rupert Davies 리트윗함
Ready for this week's NODES AI?
The agenda is 🔥
If you are having a hard time deciding which talk to attend, check out this agent bit.ly/4ms1J00 to help you build your agenda- credits to @luannem!
Agenda and reg for this online event on the 15!: bit.ly/4rIBpzN
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