🎾🥒 新加坡，我們來啦！ 這次 TOKEN2049，我們不只聊市場，也一起上場打球 🧡 ForeGate 很高興成為 Dinks & Links 的活動贊助商！ 來一場輕鬆的匹克球，也認識來自圈內的創辦人、交易者、KOL 和 Builder。球技不重要，來玩、來聊、來認識新朋友就對了。 📅 10 月 9 日 · 1:30–4:30 PM 📍 Pickle & Bones at TRIFECTA, Singapore 🎟 僅限 RSVP：luma.com/3b3624jr 球場見！ #ForeGate #TOKEN2049 #Singapore #Pickleball

Soon.

🚨@RevenueFamily involves malicious approvals. The perpetrators submit users’ permit signatures to obtain unlimited permission to spend their USDG, then immediately call transferFrom. The approval and fund transfer are completed in the same transaction, draining users’ wallets The funds are then split 20%/80% between two hacker addresses. This distribution structure resembles Inferno’s drainer-as-a-service model, and its promotional approach matches FomoPeek’s model of using KOLs to carry out scams

AI Drug Discovery Is Becoming a Bottleneck Trade I get excited when an industry starts going through a real regime change. AI drug discovery (“AIDD”) increasingly looks like one of those moments. Two things are happening: 1/ Upstream: the frontier AI labs are piling in. 2/ Downstream: The supply chain is clearly moving. Supply-chain checks suggest the upstream picks-and-shovels of discovery and early preclinical R&D are starting to feel the increase in experimental volume. DNA → protein → assays → sequencing → automation → preclinical testing Names across that stack include $TWST , @GenScript , $ILMN , $TXG , lab-automation vendors and CROs. $TWST expects triple-digit percentage growth in AI-enabled drug-discovery orders in FY26, and another year of triple-digit order growth in FY27. @GenScript's AIDD business doubled YoY in 1H26. Its current platform advertises industrial-scale validation of 4,000+ designs/day, with integrated sequence-to-data workflows. Our channel checks suggest the ramp is moving even faster: roughly 8,000 designs/day currently, with a path toward ~16,000/day by YE26. --- Why does AI drive more wet-lab demand? 1/ AI makes hypothesis generation almost free → way more shots on goal. The bottleneck is moving from expert-driven design to biological validation. 2/ AI models need continuous experimental feedback — and both good and bad data are useful. Traditionally, only the highest-conviction A+ candidates might get pushed into expensive validation. With AI, even the B/C candidates can be valuable because failed experiments generate training data. @GenScript has said its sequence-to-binding workflow can return data in 4–7 days, and that faster cycle times matter because AI models depend on continuous experimental feedback. @Anthropic is a clean example. @claudeai designed 1,320 protein binders. @adaptyvbio converted those digital sequences into DNA, expressed the proteins and tested binding. Only 354 actually bound. And the 966 failures are not wasted. They are useful negative labels: what does not express, what does not bind, what has poor affinity. Those results help train the next model iteration. 3/ Wet labs are no longer just making drugs. They are making training data. $TWST / @GenScript increasingly look like biological data foundries. $TWST explicitly talks about generating model-ready data from AI-designed sequences. In some workflows, the customer may care less about receiving the physical protein than about getting structured experimental results back into the model. Traditional drug discovery asks: “Does candidate X work?” AI drug discovery also asks: “What can this experiment teach the model?” --- TAM of AIDD If AI is simply a better R&D tool, the relevant spending pool is the $300–400B of annual global pharma R&D. If AI meaningfully increases the number of viable drug programs, the opportunity is larger because it expands downstream demand for DNA synthesis, protein production, assays, and preclinical work. Near term, we can also size demand from AI-company spending. If Anthropic reaches $80B of ARR in 2026 and spends just 1% on AIDD, that alone would imply ~$800M of annual investment. --- Trade setup This is a trade that could have long legs. It’s hard to really stop working until PhaseI/II results (2028+) It smells a lot like the bottleneck trade we just saw in semis: GPUs → HBM → networking → power/cooling. In biology, It basically follows the drug discovery process downstream: AI models → designs → DNA/protein → assays → preclinical capacity. After the upstream picks-and-shovels, animal testing could become the next bottleneck. Monkey prices are already near prior highs and CRO capacity is tight. AIDD pushing more candidates into preclinical development would only add demand. ?? But clinical trials are still the bottleneck? This is the biggest pushback I keep coming back to. No matter how fast discovery becomes, drugs still need to go through preclinical → Phase I → Phase II → Phase III → approval. You still need patients, time and capital. But that doesn’t mean the bottleneck trade won’t work. More viable candidates — especially with higher success rates — still means more demand throughout the development process. And who knows: clinical trials themselves may eventually be optimized by AI. ?? What breaks the trade? Near term, the picks-and-shovels trade breaks if experimental budgets stop growing, AI-generated designs don’t translate into useful wet-lab hits, or capacity catches up too quickly. Longer term, the thesis breaks if AI drugs look great in discovery / Phase I but fail at normal rates in Phase II/III. That is why Phase II matters so much. ?? Milestones Late 2026–2027: first Isomorphic-designed drugs enter human trials; more AI-native programs move into IND-enabling work / tox. 2028–2030: clinical trial results start telling us whether AI-designed drugs actually perform better than conventional drugs. Calling all the "bottleneck bros". :) @jukan05 @zephyr_z9 @aleabitoreddit @ParadisLabs +++ More comprehensive analysis: robonomics.substack.com/p/ai…

惊叹 ❗ 惊闻Opinion @opinionlabsxyz 取消了所有批评项目不作为的KOL投资分配。 我去看了下，确认属实！ 啥意思呢，就是投资了Opinion的kol并且批评了他不作为，项目方把你拉黑了，你的投资款没了，代币也没了，官方不交流不回复。 其实早rug了，只是还偷偷的盯着X，而投资的很多人包括kol碍于面子敢怒不敢言，项目方估计也认为自己上线了币安，软rug得了，早期参与撸毛的都亏麻了，之前扒项目方数据，tge前至少收了至少3000万，上了币安之后一顿砸盘， $OPN 较开盘价已跌近90%。 而很多人以为kol赚麻了，其实但凡投了的kol，开盘没卖的都亏钱，陷入漫长的回本路！我猜他的底气大概率源自 $OPN 已经上线了币安，官方不怕你维权。但是 @binancezh @yzilabs 能不能做做投后管理！ 刚刚看到jason @jason_chen998 说这项目是狗操的畜生，其实，我觉得大可不必，畜生是没有良知的～！ 还是@PhyrexNi倪大说的好： 维权，维个jb，小肚鸡肠的人鸡鸡本来就小 @ForrestOLAB @ForrestOLAB

不知道會是什麼重磅消息，總之大的要來了。 這種時候大量買進 BNB 通常不會虧，趁著週末大家出去玩，橫盤時先炒底或開多單，期待下週爆賺一波。 金九錯過了，就別再錯過銀十了。參考歷史週期，10 月加密行情是 10 漲 5 跌，有 66.6% 機率是漲的。

We owe the community a clear update on Arcus Points. Over the past few days, some of our own messages about the program were not as clear as they could have been. This post is the definitive version - nothing about the program itself has changed: 1. Weekly distribution: Season 1 points are fixed at 250K per week. This amount does not change with platform growth or adoption. 2. Transparency: For Season 1, you'll see your individual points and the weekly total on the Points Dashboard, updated with every weekly distribution (updates on Wednesday 3PM EST). 3. Season 0: S0 points remain redacted for now and will be revealed at a later date. 4. End date: The Arcus Points program will conclude no later than the end of H1 2027. Most of the program is still ahead, and you are still early. 5. For transparency, we've also updated the Introducing Arcus Points blog post to reflect all of the above (arcus.xyz/blog/introducing-a…). Thank you as well for the feedback on the referral and invite code program. We'll be shipping an updated system in the new week.

⚽ 亞運男足，最後的獎牌之爭 🥇 金牌戰｜韓國 🇰🇷 vs 日本 🇯🇵 foregate.com/en/event/463211… 🥉 銅牌戰｜中國 🇨🇳 vs 烏茲別克斯坦 🇺🇿 foregate.com/en/event/463209… 誰能奪金？誰能帶走銅牌？ 到 ForeGate，交易你的判斷！ #ForeGate #亞運 #男足 #足球預測

我们一直在悄悄做一件事 很快，你就会知道是什么了 👀

is Arcus just gaslighting us with this points program? > they ended Season 0 and showed ranks, not points > same day they started Season 1, and the docs said weekly points weren't fixed and could go up with activity > CT made noise, they rewrote the text and said it's fixed > then the same day they said they won't show the weekly number because it's a secret so what changed? they can change the number anytime and nobody will know was this the plan all along, and all those doc edits were just an attempt to blow smoke in our faces?