Aetheris_consulting

Agentic data engineering harness for dbt and cloud warehouses github.com/AltimateAI/alt…

145 tokens per second. Add speculative decoding. 424 tokens per second. Same model. Same H100. Zero change in output quality. If you're serving LLMs in production and not using speculative decoding, here's what you're leaving on the table... A 🧵:

This is the most hilarious thing I saw and did today Ran gemma-4-12B-coder-fable5-composer2.5-v1-GGUF locally with 8 GB VRAM at 20+ tok/sec Anthropic's Claude Fable 5 launched June 9. By June 12 it was banned. I can't access it. You can't either. But here's the twist: I'm running a model trained on its chain of thought at 20 tok/s on my RTX 4060 8GB. Locally. Offline. No cloud. No export control. Enter: Gemma4-12B-Coder GGUF (Q4_K_M) Base: Google's gemma-4-12B-it Fine-tuned on verifiable Python CoT data: - Primary: Composer 2.5 real reasoning traces (only passing solutions kept) - Auxiliary: Fable 5 used to redo the hard cases Composer missed. Every training example's reasoning led to code that actually ran. No hallucinated logic. Llama.cpp flags: -m gemma4-coding-Q4_K_M.gguf -cnv -ngl 44 -c 64000 -v (huggingface model link in comments) Flag breakdown: -ngl 44 → offload 44 layers to GPU (tune this for your VRAM) -c 64000 → 64K context window -cnv → conversation/chat mode -v → verbose output The irony writes itself. Anthropic spent weeks telling the world Fable 5 (mythos) is too powerful to release. Then released it. Then got banned from serving it, including their own researchers. Meanwhile: a Gemma 4 12B fine tune, trained on Fable 5's reasoning, runs fully offline on my mid range consumer GPU No API. No cloud. Just me and llama.cpp. This is why local AI matters. Check out the model's link in the comments. How's your experience been with this model?

@TaskandPurpose Anyone who ever wore goggles in the box and was sweating could tell you goggles are not the go to for every day.

10,000 Army IVAS headsets worth $2 billion will never be used Story here: taskandpurpose.com/news/ivas-head…

@SciTechera @NVIDIAAI make chips with this

THIS NANOENGINEERED WOOD COULD MAKE POWER GRIDS FAR MORE RELIABLE 👀! Researchers just developed OIDWV, a nanoengineered wood material designed for power transformer insulation. The material achieved record electrical insulation performance, along with 384 MPa mechanical strength and 0.33 W/m·K thermal conductivity, helping transformers withstand higher voltages and dissipate heat more effectively. Since transformer failures are a major cause of grid disruptions, This breakthrough could help build safer, longer-lasting power grids for the growing demands of AI, EVs and renewable energy.

Curated patterns and templates for AI agent harnesses github.com/ai-boost/aweso…

Google quietly open-sourced a time-series AI that predicts anything. Sales trends. Market prices. User traffic. Energy demand. Crypto volatility. It's called TimesFM. Pre-trained on 100B real-world data points. Zero-shot forecasting with no fine-tuning.

The military implications of frontier general-purpose models built by top American and Chinese labs are becoming unavoidable, writes Jake Steckler. foreignpolicy.com/2026/06/10/mil…

The University of Michigan put their entire robotics degree on GitHub. Not one course. The whole curriculum. ROB 101 — Computational Linear Algebra for Robotics ROB 311 — How to Build Robots and Make Them Move ROB 501 — Mathematics for Robotics ROB 530 — Mobile Robotics Every lecture video on YouTube. Every textbook on GitHub. Every problem set, every exam, every line of code. Professor Jessy Grizzle said it best when they launched it: "Linear algebra has become the language of computer vision, machine learning, robotics, and autonomy." So instead of making students wait four semesters of calculus before touching a robot... they built a curriculum that starts with the math that actually matters, applied to real robotics problems from day one. This is what open education looks like when a top-10 engineering school decides to mean it. Free. GitHub. YouTube. 📌 [github.com/michiganroboti…] Follow for more robotics resources! —— Weekly robotics and AI insights. Subscribe free: 22astronauts.com

@satyanadella The answer is a modular harness ecosystem that allows for increased ; access to specific data, substrate translation, increased agency, and a ton of other things. This doesn’t stop but allows companies and individuals to still have their own llm slm.

@satyanadella Pls check out my business forward AI implementation model that defines organization into Industry groupings and their ai implementation ( why how they want to work with ai) as 5 tracks x.com/aetheris2099/s…

No way someone actually made a Claude episode of The Office 😭

251 years of defending America's freedom, and we're just getting started. From the first musket shots in 1775 to the high-tech, multi-domain force of today, our Soldiers have always been, and always will be, ready to answer the call.

@codyschneider Cody do you have this as a guide?

your team has 100+ questions they wish they could get answered to do their job better but they don't have data analytics resources to do this so they're just sitting there in the dark moving papers to look like their working but what's crazy is claude code and codex can do this analysis for them now all you have to do is set up a data pipeline, a data warehouse and then give the coding agent access to the data warehouse and then they can do conversational analytics for whatever they want open source solutions for this: data pipeline - airbyte data warehouse - clickhouse MCP connecting claude code to clickhouse but if you want to do this in the next 1.5 hours you can just use graphed .com lmk below and i'll onboard you and 10 team member today

@spwfeijen AFF

I’m pulling $48K/month from affiliate commissions using a method that requires: - No team - No filming - No editing Just AI avatars reviewing e-com products & dropping 100+ videos/day on autopilot. If you're ready to roll up your sleeves and actually build something, you're in the right place. I put together a complete guide with everything inside so you don't have to search all over the internet for answers. Follow & Comment “AFF” and I’ll DM you the playbook.

@PeterDiamandis @alexwg A OSI to ASI comparison x.com/aetheris2099/s…

@alexwg So Proud to work with the brilliant Dr. AWG on this SOLVE EVERYTHING paper.

@alexwg This looks amazing I will definitely read it congratulation to the two of you!!! Keep up the great work.