BREAKING: @neros_tech, the Los Angeles-based drone manufacturer, produced 1,000 drones in a single week at its Torrance factory, marking a major milestone for scaling American drone manufacturing.
I hate to break it to you but if your AI model costs 10x more than the Chinese one and produces worse outputs, you don't have a model, you have a problem.
All the funnier given that Fable was banned by the US government for being supposedly "too capable"
You can't make it up 😅
The most valuable skill sets on the planet right now:
1. people who can set up agents properly, manage them, and run local AI models
2. marketers who know how to build distribution
3. robotics engineers who can do all three: build the hardware, wire in the AI, and source manufacturing etc
4. curators who are good at yapping and can do short form video in their sleep
5. the builder-distributor. The one person who can both ship the product AND get it in front of people
6. IRL community builders
The market is being driven by just 2 sectors:
The S&P 500 has added over +$5 trillion in market cap so far in 2026.
Meanwhile, AI stocks have added +$6 trillion in value, followed by +$200 billion added by the energy sector.
At the same time, other sectors have erased -$1 trillion of their market cap.
To put this differently, the majority of market gains have come from just 84 firms, with the rest from 22 energy stocks.
AI-related stocks now reflect ~47% of the S&P 500’s market cap, near an all-time high and up from 27% in early-2023.
AI is all that matters.
It's insane to think that in another ~6 months, we'll likely have Fable-level intelligence in open-sourced models.
Open-source AI is now 4 months behind frontier LLMs.
Two years ago, it was 12.
At this pace, Fable-level intelligence will be free to download by end of year.
All day using GLM 5.2. Didn't miss much. First open model that passes the bar as a daily driver. Things are not going to be the same.
Damn, now I want to buy some serious hardware.
Many people think any given ML project is 99% training.
In reality, it’s 50% evaluation, 40% data cleaning, 8% integration, and 2% training.
The first two set the noise floor for learning. No ML magic matters; the model cannot lower the noise floor, as that’s the optimal bound of Shannon encoding of your data.
Thus, not a single day goes by without me thinking about ontology. Even the old labels have to be constantly reviewed.
BREAKING: Iran's top joint military command announces that the Strait of Hormuz is now closed due to US and Israeli "violations" of the Memorandum of Understanding.
Iran says this is the "first step" and warns that further measures will be imposed if the "aggression continues."
A houseplant just changed everything we thought we knew about consciousness.
In 1966, Cleve Backster, a CIA interrogation specialist with a polygraph machine, was looking for ways to time how long it took different substances to travel up through plant tissue.
So, he attached electrodes to a dracaena plant in his office and watered it, expecting to see the electrical conductivity change as water moved up the stem.
Instead, the polygraph needle started tracing the exact pattern it makes when a human experiences an emotional response.
Backster stared at the readout. Plants don't have nervous systems. They don't have brains. The signal made no biological sense. So he decided to test something that made even less sense. He walked across the room, looked at the plant, and thought about burning one of its leaves with a match.
The instant the thought formed in his mind, before he moved toward the plant, before he struck a match, before he did anything physical, the polygraph exploded into frantic activity.
The plant was responding to his intention.
What happened next launched thousands of experiments and split the scientific community for decades.
Backster discovered that plants reacted to direct threats and to threats against other living things in their environment. When he dropped live brine shrimp into boiling water in another room, plants throughout the building registered distress responses at the exact moment of death. Distance didn't matter. Shielding the plants in lead containers didn't matter. The response was instantaneous and consistent.
Mainstream botanists dismissed the findings immediately. Plants process information through chemical signals and growth responses, without electrical consciousness. Any electrical activity was just random fluctuation or experimental error. The peer review system buried Backster's work. His credentials were questioned. His methods were called sloppy.
But the experiments kept working. Other researchers, following Backster's protocols, got the same results. Plants hooked to EEG machines showed brain wave patterns. They responded to music, to human emotions, to the intentions of people they had never been exposed to before. The electrical signatures were clear, measurable, and repeatable.
The implications were so uncomfortable that most of academic science simply refused to engage. If plants were somehow conscious, if they could sense intentions and respond to the emotional states of humans and other living things, consciousness was spread beyond brains. It was distributed across organized living systems rather than produced by neural networks.
Backster stumbled onto evidence that living systems might be constantly communicating through channels we don't have instruments to measure yet. The polygraph was crude enough to detect the electrical signatures of that communication without being sophisticated enough to explain them away.
Quantum biologists now suspect that living cells operate through quantum coherence processes that classical biology can't account for. Birds navigate using quantum entanglement in their visual systems. Plants conduct photosynthesis using quantum superposition to find the most efficient energy pathways. Maybe Backster's plants were demonstrating quantum consciousness, responding to information that was quantum entangled with the intentions and emotional states of nearby living systems.
What keeps most people awake when they learn about this work is realizing that if consciousness extends beyond brains, every living thing around you is potentially aware of your mental and emotional state in ways you never considered. The plant in your room. The bacteria in your gut. The ecosystem you walk through.
You think your thoughts are private.
The plants have been listening the entire time.
BREAKING: Semiconductor stocks now account for a record 18.8% of the S&P 500’s market cap.
This percentage has more than TRIPLED since 2022.
Over this period, the semiconductor index, $SOX, has rallied a massive +546%.
To put this into perspective, semiconductors accounted for less than half of their current weight at the peak of the 2000 Dot-Com Bubble.
Meanwhile, the Magnificent 7 stocks now reflect a record ~33% of the S&P 500’s market value.
Tech is all that matters.
A bit of news: After nearly 9 years, I have decided to leave Google DeepMind and join Anthropic (after taking some time to recharge). I am incredibly grateful for my time at GDM. @demishassabis took a real chance letting me lead the AlphaFold team just six months after finishing my PhD, and the entire GDM team taught me so much about how to do great science. GDM is a special place, and I’ll still be excited to hear about what amazing things they discover next.