
We’re excited to unveil Python in Excel! Get ready for a whole new way to execute advanced analytics capabilities from within Excel 🐍 + 📊 = 💚 Check out the new integration btwn @anacondainc & @msexcel, @Microsoft365 here 👇 bit.ly/3KSblQ6
Peter Wang 🦋
39.5K posts

@pwang
Chief AI & Co-founder @AnacondaInc; invented @pyscript_dev, @PyData @Bokeh @Datashader. Former physicist. A student of the human condition. bsky: @wang.social

We’re excited to unveil Python in Excel! Get ready for a whole new way to execute advanced analytics capabilities from within Excel 🐍 + 📊 = 💚 Check out the new integration btwn @anacondainc & @msexcel, @Microsoft365 here 👇 bit.ly/3KSblQ6





so far at least, i'm pretty sure AI has been net job-creating. this was not what i expected--although i was much less pessimistic than others, i thought by this level of capability we'd have seen some impact. it is possible this direction keeps going!

I gave Fable the code: "take this game and do something incredible with it to make it something very different. Be creative" It created DEEP TIME: create a city, watch it be abandoned and forgotten, and then dig it up as a future archeologist. Lovely: monument-deep-time.netlify.app



Things get strange when you shoot a single photon through the double slit. It deflects when passing through the slit, and when a string of distinct photons are sent, they accumulate in places where you’d expect in an interference pattern, but there is only one photon, and only one of two slits it could have passed through; yet it behaves as if it is interfering with itself. Here's my summary of a recent history of quantum physics: Anil Ananthaswamy’s Through Two Doors at Once. It uses the classic two-slit interference experiment as the common thread across generations of theories that try to explain its peculiar properties. Richard Feynman calls it the “one experiment which has been designed to contain all of the mystery of quantum mechanics.” With more complicated setups involving beam splitters, the photon will behave as a wave, as expected with multi-photon interference patterns, but if observed in its trajectory, it will act as a particle as one would expect, with nothing to interfere with its path. With more complex setups and long light paths, this bifurcation of behavior (wave or particle) can even be made to occur after the fact, warping our sense of time and causality. And it not just photons. Similar results have been achieved with neon atoms, C60 Buckyballs, and even a custom molecule of 810 atoms. The notion of superposition, required to explain this quantum interference, “is the most unsettling story perhaps to have emerged from any of the physical sciences since the seventeenth century.” Prof. David Albert, p.80. And then it gets really strange, when you consider the entanglement of photons that can collapse simultaneously when one is observed, even at a great distance away. This nonlocal behavior is a subject of much debate, including Einstein’s objections to quantum physics. Einstein’s most cited paper is not on relativity, it is his 1935 paper identifying the property of entanglement, which he called “spooky action at a distance.” The critical role that an observer plays in the experimental results (specifically, the collapse of the wavefunction in the Copenhagen interpretation) is a bit unsettling and anti-realist and reflective of the philosophical correctness of the day — with literary modernism questioning the ambiguities inherent to any one perspective of the world. In quantum physics and literary modernism, “there is no true world, since everything is but a perspectival appearance whose origin lies in us.” Prof. Albert p.183. The theory that I favor is the one that modifies neither philosophy nor physics and explains the two-slit experiment without resorting to an observer or the particle-wave duality; it solves determinism and non-locality, but… it is a psychological bender — the many interacting worlds interpretation. Each discrete photon is interfering with its sister particle in a parallel universe, and each quantum transition event spawns a copy of each universe, one for each path the particle could take. “The idea that 10^100 slightly imperfect copies of oneself all constantly splitting into further copies is not easy to reconcile with common sense. Here is schizophrenia with a vengeance.” Prof. DeWitt p.227. Thanks @anilananth for the good read. And this brings us to the Universe Splitter app on my iPhone. Each time I use it to make a decision, it directs a single photon through a beam splitter in Geneva, Switzerland, and there is subsequently one universe where the photon goes left and one where it goes straight. We happen to be in the one that observes one of those outcomes. When I read Feynman’s QED (Quantum Electrodynamics), I was struck by the peculiar squiggles that helped him visualize the path integral formulation of quantum mechanics. “The insight that Feynman had was to realize that what’s interfering are two different states of the universe. And those two states may only differ by where a single particle is.” Prof. Aephraim Steinberg, p.232. It was David Deutsch’s exploration of the two-slit experiment with single photons that guided him to parallel universes and the intuition behind quantum computers and their capacity to out-compute anything we could build that leveraged just one universe! And that brings us to the Entanglion game, published by IBM Research. I have yet to play that, in this universe at least, but hope to soon.


We benchmarked coding agents on our own internal tasks at Databricks and learned a lot! There are many surprising opportunities to lower cost and increase quality, and many models including open source ones are truly competitive now. 🧵


Freedom in the post-AGI world means building political superintelligence with tireless, brilliant political agents who represent us, the people—not governments or companies. In a special July 4th issue of System Check, I get into what this might mean. Several forces tilt the post-AGI world toward totalitarianism: the concentration of resources required to train frontier models, AI's obvious uses for surveillance and control, and existential risks that could justify extreme security states. But AI is also the biggest opportunity to upgrade democracy since the printing press. Most of our governance failures happen because citizens are too busy to pay attention, so a small group of highly motivated wackos drives the process. (See: NIMBYism.) What if that changed? What if AI could give every person a super effective political agent that represents them all the time? @gwern 's new "Guardian Angels" essay is the most serious technical sketch I've seen of that agent—one that learns you deeply, remembers everything, and can carry out "direct democracy on unprecedented scale." His most vivid example: official GAs for every member of Congress, able to simulate a roundtable debate among hundreds of politicians within minutes, or convene an emergency session at 4AM while every human is asleep. I see two big open questions. First: the agent has to be more than a digital twin. It should share your values without freezing your less-considered opinions in amber — willing to push you on topics it has studied more deeply than you have. On contested political questions, AI models don’t seem to possess that capability yet. Second: who governs the guardian angels? Gwern proposes a startup with dual-class founder shares. Sensible for the development phase. But can we build democratic infrastructure on private rails that one company controls forever? Which is why the recent attention back toward open-weight models and orgs that own their own models matters (see the great interview between @satyanadella and @ypatil125 below). The same logic driving firms to want their own models applies to democracy, too. If we're going to own our agents—agents that answer to us, and can't be secretly commanded from afar—we may need models we can run ourselves. The counterarguments to the open model idea (RSI leaving open models behind, safety pressure on open weights) are really big though, and I really have no idea how this is going to play out, or even how it should play out. How are we going to run a democracy if every citizen's agent is built on a single closed model with a single point of control? That's the question to think about this Independence Day. Check out the full piece here: freesystems.substack.com/p/guardian-ang…




Our thoughts on the importance of AI sovereignty. 1. Your AI sovereignty dictates your institution’s future. Sovereignty is the precondition for choice. Relinquishing sovereignty transfers the future choices of your institution to others, who are likely to exploit it for their gain and your loss. 2. Data retention is your treasure. Transfer it at your own peril. Your ability to win is dictated by your ability to recognize and use your unique edges, and you keep winning by compounding the underlying data to generate new insights. Transferring that data hands over access to your pre-existing winning plays and yields the means of production for new ones. 3. Tokenmaxxing hijacks your value orientation and decreases your institutional fortitude and intelligence. The pursuit of high token usage incentivizes disposable scripts over robust software — with the addictive feeling of false progress. There is a reason why those selling tokens refuse to charge based on value. 4. Controlling your weights is controlling your fate. Weights are the distilled form of hard-won, accumulated institutional knowledge. If you let others control your weights, you are allowing them to migrate the alpha of your business to theirs. 5. There is no contradiction between sovereignty and alpha. The architecture that maximally preserves sovereignty is one that enables institutions to own their tribal knowledge, and to compound it as alpha. 6. Politicizing the technical issues involving sovereignty is what your adversary wants. Techno-politicization is the wellspring of false sovereignty. Techno-politicization drives decisions that seem to reduce dependency, but ultimately limit agency — especially on the battlefield in the West. 7. Real expertise is existential. Allowing politics or favoritism to determine your technical decisions rewards whoever is best at politics, not whoever is right. Listen to those closest to the problems, not those speaking most compellingly about them. 8. Learn from institutions that are winning or that have consistently delivered. Institutions facing existential threats do not have the luxury of making technical decisions based on political preferences. 9. Only listen to institutions, countries, and people who have a proven record of being right. A track record of correctness is the best and only signal for future correctness. Judging something as right or wrong based on who you like is exceedingly misguided.



The worst-case scenario for the United States is becoming increasingly realistic, and I will briefly explain why. @quxiaoyin raised many valid points, and I agree with her. First of all: -China certainly does not place such strong emphasis on open source because it cares so deeply about humanism, but because it is a strategy to attract many users, gain market share, put pressure on US models, and also because the models are increasingly being trained on Huawei hardware (think of DeepSeek 4), allowing China to host the entire stack domestically. -But the underlying logic is far more important: The United States is still building too few data centers to meet future demand. @ChrisGillett wrote an outstanding analysis on this, which I shared a week ago. In short, based on SemiAnalysis data, demand is greater than what is currently being built in terms of data centers. -Even more importantly, however, the United States lacks sufficient energy and grid capacity. This is a problem that will become much more severe in the near future. China, by contrast, is addressing the issue through a massive expansion of its energy supply. Solar capacity: in 2025 alone, China installed as much solar capacity as the United States did in 10 to 15 years. China is also building 36 nuclear power plants, significantly more than the United States, and is installing them faster. -In addition, China is managing to become more independent through Huawei chips, even though the country still lags far behind NVIDIA. But here, China is betting on quantity rather than quality. In short: China is a real threat in the AI race, and the situation for the United States is becoming increasingly precarious. This is also the main reason why China is to be kept away from SOTA LLMs at all costs, so as not to jeopardize the lead under any circumstances.


SITUATION DETECTED: Anthropic has disclosed to the U.S. Government that Alibaba executed the largest known distillation attack on Claude to date, generating 28.8 million exchanges through nearly 25,000 fraudulent accounts between April and June 2026.


My theories and experiences, why so many VCs are unhappy (even though most are very well paid): 1. Easy to fail slowly This leads to years of low-level but constant stress. Pretending growth will reaccelerate in your big investments. Hoping your biggest check will pan out … when it won’t. Knowing you probably won’t be part of the next fund. Etc. 2. Easy to fall out of being a winner Many have a few strong investments but then markets, timing, energy change and/or networks decay. This can lead to plenty of anxiety 3. Partnership dynamics Many VC partnerships are sort of quietly toxic. They look and sound supportive. But even where there is “no attribution”, every one knows who sourced, and who owns, the big winners. There is so much quiet bravado, and wolf pack heirarchies. 4. Partnerships > n=2 are unstable They just are. Partnerships really are meant … for two.
