Plena (@plena_health) is the AI OS for specialty medical practices. It runs the operations — referrals, fax, scheduling & collections — end-to-end so doctors can focus on medicine.
In 8 months, they've grown 17x and crossed seven figures in contracted ARR.
Congrats on the launch, @eebadaeebada and Ahmed!
https://t.co/UCXoMO0DYl
Every civilization that collapsed followed the same pattern: purpose replaced by pleasure, duty replaced by self-expression, accountability to God replaced by accountability to no one.
The fix has never changed:
One God above all human opinion
Men who lead through sacrifice, not ego
Women honored, not commodified
Children raised with purpose before comfort
A community where every soul answers for what it built and what it destroyed
This isn’t philosophy. It’s a complete system. It’s been running for 1400 years in every corner of the earth and it still produces families, purpose, and civilizations.
You already know the name.
Thank you Jensen and NVIDIA! She’s a real beauty! I was told I’d be getting a secret gift, with a hint that it requires 20 amps. (So I knew it had to be good). She’ll make for a beautiful, spacious home for my Dobby the House Elf claw, among lots of other tinkering, thank you!!
oh you're using VLAs? everyone's using GRPs now. just kidding we're all on LBMs. world models are the future so we developed our own WAM. we're using DVAs. we were using UWMs but our robot caught on fire so we switched to DreamUMVLAPs. we're shipping a robot that passes butter.
Unveiling our new startup Advanced Machine Intelligence (AMI Labs).
We just completed our seed round: $1.03B / 890M€, one the largest seeds ever, probably the largest for a European company.
We're hiring!
[the background image is the Veil Nebula - a picture I took from my backyard, most appropriate for an unveiling]
More details here:
https://t.co/eWHyGLXwCA
"Business is competitive philosophy."
No better way to describe how the Falcon team is moving. Everything from the brand to the launch to the details of the product are meticulously aligned with their philosophy. In the long-run, there is no other way.
It is hard to communicate how much programming has changed due to AI in the last 2 months: not gradually and over time in the "progress as usual" way, but specifically this last December. There are a number of asterisks but imo coding agents basically didn’t work before December and basically work since - the models have significantly higher quality, long-term coherence and tenacity and they can power through large and long tasks, well past enough that it is extremely disruptive to the default programming workflow.
Just to give an example, over the weekend I was building a local video analysis dashboard for the cameras of my home so I wrote: “Here is the local IP and username/password of my DGX Spark. Log in, set up ssh keys, set up vLLM, download and bench Qwen3-VL, set up a server endpoint to inference videos, a basic web ui dashboard, test everything, set it up with systemd, record memory notes for yourself and write up a markdown report for me”. The agent went off for ~30 minutes, ran into multiple issues, researched solutions online, resolved them one by one, wrote the code, tested it, debugged it, set up the services, and came back with the report and it was just done. I didn’t touch anything. All of this could easily have been a weekend project just 3 months ago but today it’s something you kick off and forget about for 30 minutes.
As a result, programming is becoming unrecognizable. You’re not typing computer code into an editor like the way things were since computers were invented, that era is over. You're spinning up AI agents, giving them tasks *in English* and managing and reviewing their work in parallel. The biggest prize is in figuring out how you can keep ascending the layers of abstraction to set up long-running orchestrator Claws with all of the right tools, memory and instructions that productively manage multiple parallel Code instances for you. The leverage achievable via top tier "agentic engineering" feels very high right now.
It’s not perfect, it needs high-level direction, judgement, taste, oversight, iteration and hints and ideas. It works a lot better in some scenarios than others (e.g. especially for tasks that are well-specified and where you can verify/test functionality). The key is to build intuition to decompose the task just right to hand off the parts that work and help out around the edges. But imo, this is nowhere near "business as usual" time in software.
"The powerful have their power. But we have something too — the capacity to stop pretending, to name reality, to build our strength at home, and to act together. That is Canada’s path. We choose it openly and confidently. And it is a path wide open to any country willing to take it with us."
It's time to build Canada 🏗️🇨🇦
Demis Hassabis, CEO of Google DeepMind, drops a quiet bombshell:
The big question isn’t whether AI can solve problems.
It’s whether AI can invent new science.
Right now, it can’t.
Not because of compute. Not because of data.
But because it lacks something fundamental:
A world model.
Today’s LLMs can generate brilliant text, images, even code.
But they don’t truly understand causality.
They don’t know why A leads to B. They just predict patterns.
Hassabis argues that real scientific discovery requires more:
– Long-term planning
– Stronger reasoning
– And an internal model of how the world works
Physics. Biology. Cause and effect.
Only then can an AI run its own thought experiments.
Only then do we get a true digital scientist.
A new startup claims it can make chips at sub-nanometer scales in a single exposure at roughly half the cost.
Instead of high-NA EUV lithography, they’re using X-ray lithography. EUV prints features through multiple complex steps. This approach would effectively stamp the pattern in one shot.
If it works at scale, it would be quite remarkable!
We need more companies in the industry where TSMC and Samsung basically dominates.