Interesting example...

Probably one of the most interesting things that Elon... Musk's super PAC is doing this cycle. It is running creative that uses voters's first names to encourage them to turn out. See this example for "Christopher."show more

Interesting new private property of UINavigationItem added in iOS... 18, _preferredNavigationBarVisibility. This is really handy if only your detail view requires a nav bar. No need to set isHidden in viewDidAppear(_:) and viewWillDisappear(_:). Here's an example in Duet...show more

Bo French: "If we want to save America from... total destruction, we have to round up every Muslim & send them home." It's interesting how Muslims aren't going to Saudi Arabia for example, but all wanna go to America or Europeshow more

Here's a quick little Monster Hunter Wilds fashion tip:... Specific chest pieces have an interesting interaction with certain gloves. For example, the Hawkheart Jacket removes the upper fur part of the Orion Vambraces. Great for when you just want some ordinary fingerless gloves 👌show more

Incredible footage of Lucy Douscous showing Chappell Roan about... her book. The book seems to be quite interesting and could possibly be an example of a book from the past due to its storied appearance. Do you know about the provenance of Douscous’s Book?show more

Waymo car failing to coordinate w/ another Waymo (credits... in the comment). Interesting to see a toy example from my grant applications play out in the real world. Two cars playing a best-response to a human driver model are not mutually compatible, multi-agent challenges are realshow more

Using Seedance 2.0 for video-to-video transformations opens up some... interesting possibilities: change the setting, restyle the wardrobe, and shift the entire mood of a scene without reshooting. This example reimagines a simple clip as a classic noir bar sequence. 🥃🎥 To try this workflow, link below 👇show more

Perfect example of how instinct and innate preferences (not... racism) shape human behavior; in this case, an innocent baby's behavior. She didn't feel comfortable with people unlike her, perfectly natural and that should be rewarded. That's what makes the world interesting, unique places with one-of-a-kind qualities. How dull things would be if everyone/thing looked and acted the same. So staying home with your own people makes sense, all migration needs to stop, it's what's best for everyone.show more

Deep cut nerdy baseball thought: Runner on first. Chandler... Simpson hits a grounder. Could you argue that it's better to get Simpson out at first than to get the lead runner? Essentially that Simpson being on base at all is more threatening than the other runner advancing to scoring position? Probably not in this spot, but I think it becomes an interesting discussion if for example there's no outs and a weak-armed catcher. When the Yankees faced the Rays in April, Simpson basically was instantly on third base every time he got onshow more

For a long time, staking usually meant one thing:... Lock your tokens and wait 🤷‍♂️ But some newer models are trying to connect staking with actual network activity. Wanchain 's xWAN system is an interesting example of that 👇 👉 Convert WAN into xWAN 👉 Stake xWAN 👉 Become part of the bridge ecosystem What caught my attention is that the idea isn't only about holding tokens. The bridge is being used every day as assets move between different chains, and staking is tied to that broader activity. As more users move funds across networks, infrastructure becomes increasingly important 🔥 Because today's crypto user rarely stays in one place: 👉 A transaction starts on one chain 👉 Continues on another 👉 Ends somewhere completely different Cross-chain movement is slowly becoming a normal part of crypto. And when that happens, the infrastructure behind those transfers matters more than ever. It's interesting to see staking evolving from a passive activity into something more connected to real network usage. Do you think staking models tied to actual ecosystem activity are the future? 🤔 👉show more

𝗪𝗵𝗲𝗻 𝗗𝗶𝗱 𝗨𝗦 𝗦𝘁𝗼𝗰𝗸𝘀 𝗕𝗲𝗰𝗼𝗺𝗲 𝘁𝗵𝗲 𝗕𝗶𝗴𝗴𝗲𝘀𝘁 𝗧𝗿𝗮𝗱𝗙𝗶 𝗠𝗮𝗿𝗸𝗲𝘁... 𝗼𝗻 𝗖𝗿𝘆𝗽𝘁𝗼 𝗘𝘅𝗰𝗵𝗮𝗻𝗴𝗲𝘀? For much of early 2026, precious metals were the biggest driver of TradFi trading on crypto exchanges. Gold, in particular, attracted traders looking for stability during uncertain market conditions. But June changed everything. According to CoinGecko's latest report, US stock trading volume jumped from $43.40B in May to $189.84B in June, overtaking precious metals to become the largest TradFi category across the six exchanges studied. 📊 What does this tell us? This isn't just a spike in trading activity. It signals a shift in what crypto users want access to. Instead of using centralized exchanges only for digital assets, more traders are now looking for exposure to traditional financial markets without leaving the platforms they already use. The lines between crypto and TradFi are becoming increasingly blurred. Another interesting takeaway is that different exchanges are finding different strengths rather than competing in exactly the same way. For example, the report shows MEXC ranked #1 in precious-metals trading volume during April and May 2026, while the rapid growth of US stocks has intensified competition across the industry. Rather than asking which exchange is "winning," a more interesting question is: Are crypto exchanges evolving into true multi-asset trading platforms? If the current trend continues, the future may not be about choosing between crypto and traditional markets, it may simply be about accessing both from one place. Data Source: CoinGecko TradFi Report (Jan 2025–Jun 2026)show more

I just built my own wiki generator plugin for... my agents. My agents can now generate wikis for anything I ask. One of my favorite wikis is called PaperWiki. This is a great example of what Andrej Karpathy describes. It uses obsidian vaults to organize papers, retrieve LLM-generated summaries, diagrams, and other advanced views for paper exploration. When Obsidian UI is not enough, I use my own artifact generator inside my agent orchestrator (see clip for example). This allows my agents to build any kind of view or exploration feature that I need. The papers are all curated with automations and several rules/patterns I have manually built over the years. On the surface, this looks basic. But behind the scenes, there are advanced search capabilities, connections, metadata, derived data, and other interesting bits of information that are extremely useful for my research agents. This is mostly built for agents. The artifact preview is just a high-level way to validate and quickly assess the quality of the wiki, suggest improvements, and it's also great for research. I use tobi lutke's qmd for all search capabilities. Everything is markdown. The summaries and even the diagrams. The wiki updates on its own based on several automations I have optimized over the past couple of weeks. The wiki grows and self-improves based on several requirements important for my research use cases. This is as personalized as it gets. There is nothing like it out there. And I use my research expertise to continue improving it over time. This is a vanilla wiki. There are so many things I want to build on top of this. Different aggregations, views, artifacts, etc. All to help automate more of my research work and accelerate productivity. I think the biggest leverage here is how powerful this could be for discovery and experimentation. One of my goals is to use it to find deeper connections and insights that would otherwise elude the top human researchers and use those to generate interesting new hypotheses and research experiments. That way, my agents can use autoresearch to explore research ideas at the frontier. Stay tuned for more.show more

Most chiral molecules arise from carbons being bonded to... 4 different atoms, which are called sterocenters. The makes the molecule have a different mirror image that cannot arise from simple rotation. But, you can have chiral molecules not from stereocenters. You can have chirality that doesn't come from a single point in the molecule. It comes from some global property. The classic example is helicene, which doesn't have any stereocenters, but has chirality because of hits helical structure. This means you cannot capture this molecule with a graph, and thus SMILES or a string representation cannot capture this. Of course natural language comes to the rescue (just say in words if it's left-handed or right-handed helix), but it's an interesting failure mode for viewing molecules as just a graph. Another example of a molecule with helical chirality is DNA. DNA is actually chiral in two ways, which is kind of confusing. It has both helical structure and stereocenters. You won't find the stereocenters ever flipped, but left-handed helical DNA can exist (called Z-DNA). Interestingly, making the flipped stereocenter of DNA could be part of an entire mirror organism (mirror RNA, DNA, AAs, sugars) that would then be potentially invisible to our immune systems. This has been recently proposed as a "mechanism" for how a runaway AI system could cause harm to Earth. I find it to be a pretty tedious and difficult way to cause harm, but it is intellectually cool. Anyway - this came up in a PhD defense and I have a lot of arcane knowledge about this I wanted to dump.show more

HTML Artifacts are a big part of how I... work with agents now. Artifacts can be more than just static files. When combined with agents, they can take action or help you take action. This unlocks all kinds of interesting ways to work with agents. This is clearly the future. Check out this writing and scheduler artifact I built in a few minutes. It uses a bit of HTML and JS. All the data is in markdown (Obsidian vaults), so the agent can access and modify it at any time. No DB needed. No sophisticated functionalities. The agent decides all that for me based on the skills, context, and memory it has access to. The best part about this simple stack is that all the important information stays with me. This has allowed me to build a recursive self-improving system and automations that can better tap into coding agents like Codex or Claude Code. I could have paid or built an entire app for scheduling posts, and there are so many of them out there. But I don't need to. I've realized a simple artifact does the job. And the simplicity of it is actually an advantage. Very little maintenance for very high returns on personalization, time, and efficiency. The other benefit of this is that I can add features as I please. That level of personalization feels magical, and we should all be pursuing more of it. All of this just keeps compounding. Of course, this example is just about writing. But I have similar artifacts for research, design, experimentation, evaluation, and so much more. And no, I didn't actually publish the post example I shared in the clip. It was just for demonstration purposes. I actually spend more time than this when writing together with agents. Lastly, having built my own agent orchestrator tool has made me realize that simplifying the tool stack is a superpower. If you are curious about how all this works, I will do a live session next week:show more

Crypto narratives tend to move in cycles. 2020 was... DeFi. 2021 became NFTs. 2023 turned into the AI boom. 2024–2025 were dominated by memecoins and attention tokens. But markets eventually rotate back to something simple: real revenue. That’s why some people are starting to look at iGaming tokens as a potential emerging narrative in 2026. Unlike many hype driven tokens, the iGaming sector already runs large cash flow businesses. Many platforms generate hundreds of millions of dollars in monthly revenue, yet their tokens often trade with far less volume than projects that barely produce revenue at all. In other words, there’s a visible mismatch between actual business activity and token market valuation. One ecosystem that sits right inside this discussion is 1win Token, which already operates as one of the top 10 online casinos globally by scale and user activity. The upcoming $1win Token is designed to connect that existing business with on chain incentives. Its token model includes buybacks and burns funded directly from casino revenue, tying token supply mechanics to real cash flow. There’s also an interesting structural difference compared to previous gaming tokens. For example, $RLB (Rollbit) saw a massive post launch rally, but the product and revenue scale at launch were significantly smaller than what 1win operates today. Another notable point is the launch design: instead of only farming an airdrop, 1win Token plans a public sale model, allowing broader participation from the start. If Web3 narratives are indeed shifting away from pure attention cycles and back toward revenue generating platforms, sectors like iGaming may start attracting more analytical focus and 1win could emerge as the biggest winner.show more

The architecture of this new world model is one... of the most interesting things I've seen lately: Let me first explain how most world models work: They predict and render one frame at a time. If you are navigating in one of these worlds, and you look left, the model draws whatever looks right in the moment. Every time you change your viewpoint, the model has to imagine what should be there again, so it's very common for these models to "forget" what's in the world. For example, if you put a toy on the table, look away, then look back, the toy might not be there anymore. Tripo AI is releasing its Project Eden model, which works very differently: The model builds the world first, and then renders it based on that map. That map holds the real state of the world: the geometry, every object, where things are, what's already happened. The picture you see on screen gets generated from the map. This architecture flips the whole thing. Now, you get the following: 1. The world stops forgetting. Leave, come back, and the toy is still on the table because it lives in the map, not in the last frame you saw. 2. You can edit the world, and those changes persist for anyone who enters later. 3. Multiple people and AI agents can coexist in the world and see it from different perspectives. This is early research, but it's looking really promising. They just raised nearly $200M across two rounds to build it out. Tripo will be at SIGGRAPH 2026 (July 19–23, Los Angeles Convention Center). If you work in 3D, embodied AI, simulation, or anything spatial, go connect with them there.show more

🚨 IF YOU HOLD $INDEX, READ THIS. You may... not fully understand what you’re holding. AGAIN. You may not understand the financial machine sitting inside your wallet. Let me explain. $INDEX possesses something incredibly powerful: The ability to capture financial value from economic activity regardless of which direction the market moves. Think about what exchanges like Binance have understood for years. Markets can rise. Markets can fall. Markets can go sideways. But people keep trading. And when people trade, fees are generated. That means exchanges can continue extracting value from market activity through bull markets AND bear markets. Now imagine taking that same concept and turning it into a tokenized flywheel. That is what makes Index so interesting. You aren’t simply holding a token. You are holding a claim on a machine designed to convert trading activity into financial assets. And the timing? Potentially fascinating. THE BULL MARKET WITH MAXIMUM ACTIVITY IS ON THE HORIZON. If volatility increases and trading volume explodes, the machine has more activity to feed on. Let’s run the numbers. 📊 TODAY’S EXAMPLE $INDEX did approximately $714,000 in 24H trading volume. A 3% ETH fee hook on $714,000 generates: $714,000 × 3% = $21,420 That’s $21,420 worth of fees entering the flywheel. Now look at what different holdings represent: 50K INDEX = 0.005% of supply 0.005% × $21,420 = $1.071 in stocks 100K INDEX = $2.142 200K INDEX = $4.284 300K INDEX = $6.426 400K INDEX = $8.568 500K INDEX = $10.710 600K INDEX = $12.852 700K INDEX = $14.994 800K INDEX = $17.136 900K INDEX = $19.278 1 MILLION INDEX = $21.420 And this is from a $714K volume day. Now imagine what happens when the market awakens. ⸻ 🚀 NOW LET’S LOOK AHEAD Suppose $INDEX eventually experiences an $8.2 MILLION 24H volume day, similar to the volume $PONS achieved on the last 24H At a 3% fee: $8,200,000 × 3% = $246,000 That’s $246,000 worth of fees. Now the same ownership percentages produce: 50K INDEX = 0.005% = $12.30 in stocks 100K INDEX = $24.60 200K INDEX = $49.20 300K INDEX = $73.80 400K INDEX = $98.40 500K INDEX = $123.00 600K INDEX = $147.60 700K INDEX = $172.20 800K INDEX = $196.80 900K INDEX = $221.40 1 MILLION INDEX = $246.00 Read that again. A single $8.2M volume day could theoretically direct $246K through the fee mechanism. And here’s where the philosophy becomes interesting: The value isn’t only in the token. The value is in the activity the token can capture. Volume becomes fuel. Fees become capital. Capital becomes stocks. Stocks become another layer of productive assets. And those assets can continue compounding the flywheel. CRAZY THING!!! The stocks you collect also appreciate in value. That’s how a token can begin behaving less like a static piece of speculation… …and more like a financial engine connected to economic activity. At sufficient scale, someone holding $INDEX could potentially accumulate stocks at a pace that rivals or even exceeds what some traditional investors accumulate over many years. The market doesn’t have to move in your direction for the machine to work. It simply needs people to keep moving. And markets have a funny habit of doing exactly that. The greatest financial machines don’t need to predict the future. They monetize the activity of everyone else. $INDEXshow more

Jev + SERV is actually insane. We already showed... you can increase Jev's performance with SERV Reasoning. Now we're taking it further, bringing Jev-powered Decision nodes into Graph Sharding with the upcoming SERV v3. Here's a breakdown of how it works: Jev is a decision-making model. Given a task and a set of options, it predicts which path is more likely. Think of the octopus that predicted World Cup results. Jev does that for your business, except it's not luck. It weighs every option and tells you how sure it is. It does this by assigning probabilities to outcomes. It doesn't generate text on its own, so you can't expect it to create a new outcome for you. But that's also what enables it to be lightning fast and dirt cheap. For example, in customer service you can ask Jev how to triage an incoming query and route it to the correct department. It can only select from the list of departments you provide it. This also means it can't hallucinate a new outcome outside the options it's given, which makes it incredibly interesting for OpenServ. In Graph Sharding, we take a single system prompt and break it down into multiple LLM steps with deterministic input and output shapes. Some of these steps require an LLM to produce new output, while others are simply decision routers that determine the next possible path. Traditionally, LLMs are slow and expensive. Breaking a single prompt into multiple steps increases accuracy and reliability by a ton, but it also introduces latency. Jev takes on those decision nodes, which are the backbone of a business process and therefore SERV graphs, and makes them super consistent and lightning fast, lowering the overall cost and latency of graph execution. SERV Reasoning on its own is a great force multiplier for Jev because, like all other models, it works by interpreting input instructions. The clearer those instructions are, the better the model performs. That's where SERV Reasoning comes into play. Just like amplifying any other model, we also amplify the accuracy and consistency of Jev's responses. And now we're bringing Jev-powered Decision nodes into Graph Sharding with SERV v3.show more