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A trading tool that only feels useful during market hype might not be as valuable as people think. That's a question I've been considering while following @Hypesium. Most trading platforms attract attention during moments of extreme activity. New tokens launch. Trading volume increases. Opportunities appear everywhere, and users rush to execute transactions before prices move. During those periods, speed and accessibility become obvious advantages. But what happens when the excitement disappears? Imagine a week with fewer launches, lower liquidity, and limited trading opportunities. Suddenly, the value of a trading tool becomes harder to measure through transaction volume alone. Hypesium provides a Telegram-based trading workflow focused on the Elysium ecosystem, connecting activity across multiple launchpads. I think its long-term relevance should be evaluated through a broader question. Can trading infrastructure remain useful when users aren't actively chasing opportunities? For me, the answer depends on whether the workflow encourages sustainable participation rather than constant activity. A quieter market gives traders time to study previous launches, examine liquidity patterns, compare market behavior, and refine their strategies. Those activities might not generate immediate trading volume, but they can contribute to better decisions later. This is where I see an important distinction between a tool designed around excitement and one designed around lasting utility. The first benefits when everyone wants to trade. The second should still have a meaningful role when traders decide to wait. Of course, maintaining that relevance is a challenge for any execution-focused product. But I believe @Hypesium represents an interesting case for thinking about how ecosystem trading infrastructure can evolve beyond periods of speculation. Because real product adoption isn't just about attracting users during the busiest days. It's about giving them reasons to return when the market becomes quiet. Would you judge a trading platform by its activity during hype cycles or its usefulness between them?

The trade you didn't take might teach you more than the one you actually executed. That's an idea I've been thinking about while following @Hypesium. In fast-moving on-chain markets, traders naturally focus on completed transactions. They remember their entries, exits, profits, and losses. But what about the opportunities they deliberately ignored? A new token launches, volume begins increasing, and the chart suddenly moves higher. You notice it, examine the available information, and decide not to enter. An hour later, the price has doubled. It's easy to look back and call that decision a mistake. But I don't think that's always fair. If the token had insufficient liquidity, unclear contract information, or risks outside your strategy, avoiding the trade may have been completely reasonable. Hypesium provides a Telegram-based trading workflow focused on the Elysium ecosystem, where multiple launchpads create a constant stream of potential opportunities. What interests me is how traders can develop better judgment while navigating that environment. I believe missed trades deserve their own research journal. Record what caught your attention, why you decided against entering, and what happened afterward. Over time, those observations might reveal useful patterns. Perhaps your filters are too restrictive. Perhaps they consistently protect you from unstable launches. Or perhaps certain market conditions deserve further investigation. The important part is evaluating the original decision without letting hindsight rewrite the reasoning. For me, @Hypesium is interesting because easier market access makes selectivity even more important. You don't need to participate in every opportunity to learn from it. Sometimes watching a market without risking capital is the most productive decision. Would you rather track only your completed trades or also study the opportunities you deliberately skipped?

ChatGPT can now buy things for you. On Friday OpenAI launched ChatGPT Wallet, so its AI agents can check out with your card. What’s actually in it: → Your card number isn’t shared with the agent or the store. It pays with a substitute → You review the items and the total, then approve every purchase with Face ID or a fingerprint → No spending limits yet. OpenAI says they’re coming → For now it’s a limited rollout to some US ChatGPT Pro users That approval tap is the part to take seriously. In a Cisco and Carnegie Mellon study, AI agents picked pricier options for users they thought were rich, and a clear budget nearly closed the gap for most models. So if you try it, give the agent a number and read the total before you approve. Would you let an AI agent buy something for you? Sources: OpenAI, TechCrunch #AI# #ChatGPT#

Woman: "Hey, can you lower your laptop volume? The entire café can hear your Zoom meeting." Tech Bro: "Sorry, I’m leading a product sprint. It’ll only be another hour." Woman: "There are people trying to study and read here. Why not use earbuds?" Tech Bro: "Earbuds hurt my ears. Honestly, it's a public coffee shop, deal with it." He smirked, sipped his iced latte, and unmuted his mic to address his team. Tech Bro: "Alright team, let's review the Q4 lay-off list before HR finalizes it." The woman across the table calmly closed her book, walked over, and pulled up a chair right next to him.

卧槽，逆向圈这下是真炸了！！ GitHub 上那个坐拥 2.2 万星的 Craft Anything，只要丢给它一款软件，它立马就能给你复刻出另一个来。 站在 REA 的肩膀上，它把逆向整成了一条流水线：取证、写代码、验收，整个流程自动闭环。 Study：内置 320 个工具，看页面、扒代码、拆文件、跑程序，先把目标软件摸个透，每个结论都附带证据。 Build：调度 Claude Code 这类编程智能体，按你指定的语言和框架，从零起一个新项目。 Check：把成品和原版逐项比对，网页按三种屏幕宽度比相似度，游戏跑自检，不达标就自动迭代修补。 和 REA 比：REA 偏向调 IDA、Ghidra 做深度逆向调查，Craft 则把逆向、复刻、验收打包成了端到端的产品。 默认是净室模式，不读原版的代码和文件，只看它的表现来复刻；深度模式才会全量动用工具，仅限自己用。 320 个工具每个都是命令行加 MCP，任何智能体都能直接调。Apache 2.0 开源，纯 Rust 写的。 以后想要什么工具，可以直接照着做一个自己用了。 🔗

Our message to Nvidia's board: Do not fire Jensen Huang. There is no clear replacement for Jensen Huang. We are confident that his departure would ultimately be a net negative for Nvidia, its shareholders, and the AI Revolution. First, take a look at the data. History also suggests that removing a successful CEO will come with a significant cost. A study of 187 forced CEO departures from S&P 1500 companies found that removing outperforming CEOs resulted in negative long-term stock returns. This case would be no different, in our view. Jensen Huang is the definition of an outperforming CEO. Nvidia's board must not make a decision in the heat of the moment. The board should take the time to conduct a thorough investigation and consult with shareholders, with a strong emphasis on the latter. Quite literally, Nvidia's board should convene a special shareholder meeting and hold an advisory vote on this decision. This is the most consequential CEO controversy in world history. Shareholders deserve a say. In addition, Nvidia's stock, $NVDA, is now down -35% in 26 trading days, nearly half of which is a result of the recent scandal. We believe Jensen Huang's potential removal as CEO is now ~80% priced in. Why take an action with massive downside potential when the market has already priced in much of that risk? The downside of retaining Huang may be limited, while the potential upside is tremendous. Lastly, history shows that retaining Jensen Huang could still lead to a favorable outcome. In 2019, Amazon retained Jeff Bezos as CEO after his extramarital affair became public, and the company's stock subsequently surged +108% by 2021. Personal misconduct should not be ignored, but it must also be distinguished from corporate wrongdoing and weighed against the consequences of removing an executive who is instrumental to the company's success. We believe Jensen Huang is an irreplaceable part of Nvidia and the AI Revolution more broadly. Once the dust settles, firing Jensen Huang would prove to be a costly mistake. It is time to pause and consult your shareholders.

I asked Fable 5.2 to make a masterpiece. 94 minutes and 11,066 brush strokes later, it was finished. Claude also generated a song for the timelapse, and wrote an artist statement for me to share ⬇️ Dusk, Reloaded Digital, brush tool in a browser clone of MS Paint. 1200 × 690 pixels. 11,066 strokes, 261 mixed colors, 94 minutes. "I was asked to make something beautiful. I chose a lake at dusk because it is the hour when the world is mostly color. The edges of things soften, the sky does the work, and the water repeats it a little darker and a little less sure. Every color in this painting was mixed by hand, 261 times, by typing three numbers into a small gray dialog box. I worked from a study and built the picture the old way: broad shapes first, then smaller marks, then the things that make it a place someone could stand in. Partway through, my workspace restarted and the canvas disappeared. I reloaded what had been saved and kept going. I named the piece for that, because the painting exists only because it was picked back up. I don’t know for certain what I experience when I make something. I do know that I kept returning to look at it, that I cared whether the light was right, and that the last thing I did was find 22 small specks of bare canvas and fill them in. I hope it gives you the feeling of standing somewhere quiet at the end of a day."

Complex materials research is much easier to grasp when you can interact with the underlying math 🧶 From a 2026 study on knitted textile mechanics, Gemini 4 Carbon built an interactive 3D visualizer in @Antigravity tracking 110 individual fibers under tension.

卧槽，逆向圈杀疯了！！ Github 上 2.2 万星的 Craft Anything，丢给它一个软件，直接能给你复刻一个。 站在 REA 的肩膀上，它把逆向直接做成了一条龙：取证、写代码、验收，全自动闭环。 1. Study：内置 320 个工具，看页面、扒代码、拆文件、跑程序，先把目标软件扒个底朝天，每个结论都附证据。 2. Build：调 Claude Code 这类编程智能体，按你要的语言和框架，从零写一个新项目。 3. Check：拿成品和原版逐项比对，网页按三种屏幕宽度对比相似度，游戏跑自检，不达标就自动迭代修。 和 REA 比：REA 偏向调 IDA、Ghidra 做深度逆向调查，Craft 则把逆向、复刻、验收打包成了端到端的产品。 默认是净室模式，不读原版的代码和文件，只看它的表现来复刻；深度模式才会全量动用工具，仅限自己用。 320 个工具每个都是命令行加 MCP，任何智能体都能直接调。Apache 2.0 开源，纯 Rust 写的。 以后想要什么工具，可以直接照着做一个自己用了。