French musical genius FKJ’s latest touring show, the “Typer Tour,” is coming to Bangkok! Come see this one-man band wizard work his magic on the guitar, saxophone, and synthesizer. 🎶 Tour Dates 📅 📍 Bangkok | November 27, 2026 | UOB LIVE 🎫 Presale 📍 July 22, 13:00 (Beijing Time) ✨ Let the rhythms of French romance intertwine with soul and jazz, taking you on an escape from reality. 🔗 Click the link to explore the details: #FKJ#

new @poteto-mode config: hardest code, judgment or vague intent: claude-fable-5-1-thinking-high hardest code, precisely specified steps: cursor-grok-4.6-xhigh-fast code, everything else: cursor-grok-4.6-xhigh-fast trivial mechanical edits: cursor-grok-4.6-xhigh-fast judgment and prose: claude-fable-5-1-thinking-high how explorer: cursor-grok-4.6-xhigh-fast how explainer: claude-fable-5-1-thinking-high how critics: claude-fable-5-1-thinking-high, cursor-grok-4.6-xhigh-fast why investigators: cursor-grok-4.6-xhigh-fast why synthesizer: claude-fable-5-1-thinking-high reflect judgment: claude-fable-5-1-thinking-high reflect tooling: cursor-grok-4.6-xhigh-fast reflect divergent: cursor-grok-4.6-xhigh-fast reflect synthesizer: claude-fable-5-1-thinking-high arena runners: claude-fable-5-1-thinking-high, cursor-grok-4.6-xhigh-fast arena cross-judge pool: claude-fable-5-1-thinking-high, cursor-grok-4.6-xhigh-fast interrogate reviewers: claude-fable-5-1-thinking-high, cursor-grok-4.6-xhigh-fast @bot helped me iterate on this based on my transcripts

New Google paper: A forecast needs context, not just history. Some patterns are caused by events, not time. Nexus reframes forecasting as a reasoning problem, where events and numbers have to explain each other. Nexus argues that forecasting improves when models read the world around the numbers, not just the numbers themselves. In the Zillow tests, one Claude-based version cut average MAPE by 86.6% versus direct chain-of-thought prompting. That matters because most time series models are fluent in pattern, but mute about cause. A housing inventory curve can reflect seasonality, mortgage pressure, migration, layoffs, and local supply, while a stock price can be bent by earnings, regulation, hype, and fear. Nexus separates those jobs instead of asking one prompt to do everything. One agent turns messy historical text into a clean event timeline, one reads the broad regime, another tracks local shocks, and a synthesizer reconciles them with calibration from past errors. The interesting result is not merely that context helps, but that structure helps the language model use context without losing the time series. The evidence is still narrow: Zillow counts, seven equities, post-cutoff data, and single-run evaluations, so this is not a universal law of forecasting. But the direction is clear: future forecasters will not only extrapolate curves; they will argue about what made the curve move. ---- Paper Link – arxiv. org/abs/2605.14389 Paper Title: "Nexus : An Agentic Framework for Time Series Forecasting"

The Massachusetts Institute of Technology is questioning whether a graduate student actually synthesized dimethylmercury, a lethal neurotoxin, after the student self-reported to a Cambridge, Massachusetts, hospital and prompted a multiday hazmat shutdown of a chemistry building.

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I’ve commented on other people posts. I’ll synthesize what I believe. Fundamental risks are not the only risks but they are the most important risks unless you have a lot of leverage in which case, risk is risk and trying to pretend one matters and one doesn’t always ends the same way. If you have no leverage the only thing that can force permanent capital loss is your or your LPs tolerance for pain. If you have leverage your lender can trigger permanent capital loss. If you work at a platform you are being lent callable money, not managing capital, and you should manage money like the bank can take it back whenever they want. The best way to manage non fundamental risks is through a rigorous fundamental force ranking process that compares similar ideas to one another and limits exposure to similar things. Most fundamental research is very good but doesn’t go far enough in demanding absolute and relative return thresholds or in creatively comparing ideas to one another. There are generally high correlations between fundamental and non fundamental risks. If you limit your exposure to a fundamental risk (like no current profits) you will manage the non fundamental risk as well and naturally de risk the exposure and improve effective breadth. You can reduce the number of ideas which increases concentration and results in less non fundamental risk through the same process. You can reduce non fundamental risk through a proper fundamental process and outperform.