蜂远

[蜂远 @noise_2016]

@aleabitoreddit 优质公司晚上时间分享还好，白天投资散户没有机会第一时间留意到信息。都是服务了机构和卖你信息工具的贩子，但是晚上时间，散户还能有机会争取次日机会。😋

[蜂远 @noise_2016]

@aleabitoreddit 这种短期热点，其实普通投资散户即便会登录X还是接受不到。能够第一时间接受到你信息的。通常还是一些具备一定技术手段的。因为一般普通散户是无法第一时间获取X信息。其实帮来帮去还是帮助了主力。哈哈~

[蜂远 @noise_2016]

@fusheng1056 @aleabitoreddit 多吃核桃，有助提高智慧~

[蜂远 @noise_2016]

@noahatwhere @aleabitoreddit 黄老板，老马，一锤定音的加进去。这个更灵~

[Serenity @aleabitoreddit]

I think my personal style of investing is a bit different, just some reflection:

It's inherently discretionary, based on stuff markets don't know yet. And a culmination of life experiences?

If you look at $AXTI, $RPI, $SIVE, $IQE and others.

Lot of it is guessing on unstructured relationships then seeing if it's right or not down the line.

$RPI is the perfect example:

1. Nobody really thought of Raspberry Pis for AI growth. Mainly people bought one or two just for class + education + hobbyist.
2. After OpenClaw, just noticed all my friends and people just buying Apple Mac Minis / RPIs for AI applications.
3. Found validation of that trend online with lot of people sharing video tutorials on AI orchestration with RPI.
4. AI was their ideal perfect growth vector, did some modeling, and thought it was compelling.

Earnings comes out and I was right.

Everyone in media was calling it a meme stock because there's nothing online that shows revenue growth from AI (was 14% forecasted revenue growth, turned out to be 58%, my projection was around 55%).

So it was a mix of guessing next industry trend (AI using lightweight hardware instead of GPU clusters), real life trends, then revenue forecasting off my guess.

For stuff like $AXTI:

1. Everyone called it a joke when I bought at ~$12. LLMs would hallucinate and say "hyperscalers/govs would have known about this by now and fixed this vulnerability with InP substrates"
2. Or would conflate very nuanced parts of InP substrate stack, where there's multiple different chokepoints in upstream processing.
3. So part of this was just discretionary based on what I've seen over InP substrate breakdowns, industry trends, etc.
4. Then also guessing the major supercycle was photonics (this was before everyone caught onto $LITE, and others). Or before you saw the $141B TAM projections from GS.
5. AXT owned 40% of InP supply chain, without them the supply chain just gets cripped).
6. All the "analysts" were forecasting steady InP substrate growth, few hundred million TAM, etc. or export controls.
7. Everyone kept trying to say $AXTI was overvalued based on TAM estimates. But if it's a few hundred million TAM you just think that's a joke and go into game theory over allocations.
8. Then I just had to guess, how much would this be worth if it were a NAND style bottleneck, what MC could it reach based on control, how much would hyperscalers price it as, etc.

A lot of the current research outputs from Goldman Sachs, or earnings reports from the Epiwafer companies, were confirmed after I published my piece on AXT. If you did research back then, lot of the same material /framing wouldn't have come up.

With stuff like $XFAB as you're seeing now, a lot of it is just pure guessing:

1. Not really any CPO materials, how much their MTP process makes in revenue, etc. Everyone online keeps saying they're not a photonics player.
2. But if you go through ASE docs or Gov websites, they all kinda cite XFAB as a major emerging player here.
3. $NVDA also evaluating them right now (maybe it's successful who knows).
4. No clear revenue around this area because their main silicon photonics process is still precommercial, but if you guess it's trying to create a EU supply chain to compete with $TSEM, once pre-commercial shifts to commercial, maybe similar but less volume contracts?
5. Then just seeing updates over the next few months to see if anything confirms this thesis guess.

_

I think a lot of information discovery still can be done with LLMs I'm seeing online. But it's also really hard to make a bunch of unstructured inferences based on unrelated material or even just trends you're seeing in real life.

So probably better to just do what's standard, eg. do valuation forecasting based on current numbers

Stuff like $AAOI, if they're projecting $471m/M h1 2027 and you see MC at $12B, probably undervalued might be a good idea to go long for next years.

Stuff like Samsung Electronics is easier, see what people are modeling for operating profits for 2027, 2028 then just seeing if it's undervalued or not at current levels.

Maybe something harder is $JBL. I haven't really seen any great volume numbers around 1.6T LRO, but you can just make a guess on how popular that might be then project how that might impact current MCs.

Or picking just good names everyone kinda agrees like $TSM, $INTC, $MRVL is also solid.

So a lot of things is just building up your life skills then applying that to markets. I don't think it's that can be taught with courses and stuff.

Of course, much of what I'm doing is just high conviction inference based on unconnected parts. Could always be wrong.

[蜂远 @noise_2016]

@7Years258 @aleabitoreddit 说明对A股不了解，你了解就不会这么想了哈~ 短线都是靠情绪~

[Serenity @aleabitoreddit]

专门写给我的中文读者：

绿的谐波（LeaderDrive，688017，577.3亿人民币）是我在布局人形机器人赛道时最青睐的中国上市标的。

他们的业务涵盖：

谐波减速器（据称占有超过60%的国内市场份额，以及1800多家全球客户）

人形机器人旋转关节减速器

直线执行器

电机/关节，以及许多其他核心零部件。

并且他们正在进军行星滚柱丝杠（planetary roller screws）领域。

目前占据着绝对的主导地位：超过60%的国内市场份额以及1800多家全球客户。

主要客户包括优傲机器人（Universal Robots）、优必选（UBTech）、智元机器人（Agibot），而特斯拉（Tesla）、Figure 以及绝大多数其他人形机器人研发商都很可能是他们的潜在客户。

如果你看一下这些零部件的 BOM（物料清单），粗略估计它们占到了每台研发出的人形机器人的 4-15%，随着他们进军更多细分领域，这个比例可能还会更高。

我认为没有人能对这类公司进行精确的财务建模，其前景更多取决于未来几年内会有多少人形机器人实现量产。

这其实是对一家能���在每台生产出的人形机器人中占据可观份额的公司，进行的一种方向性做多（directional long）。

在可扩展的规模化量产方面，中国显然是该领域的领导者，许多西方玩家无法将成本降到绿的谐波那样的水平。

随着我们向实体人工智能（physical AI）的规模化迈进，我极其看好机器人这个赛道。

[蜂远 @noise_2016]

@k1lltheguard46 太帅喽~

[Why you should have a cat @ShouldHaveCat]

Neighbourhood surveillance

[Serge Minhulin @minhulin_art]

фото на паспорт

[Punch Cat @PunchingCat]

name him...

[Adrian @AdrianArt96]

Another WIP Ares from Hades :) 🩸

[Buitengebieden @buitengebieden]

Cooling down.. 😅

[Science girl @sciencegirl]

Useful tip

[Nature is Amazing ☘️ @AMAZlNGNATURE]

Baby turtle being born and greeting the world for the first time

[Why you should have a cat @ShouldHaveCat]

Catroach

[Science girl @sciencegirl]

Animated LED lights for vehicles

[Why you should have a cat @ShouldHaveCat]

“A Rong rong time ago “ ahh cat😭💀

[Anatomy For Sculptors @A4Sculptors]

Facial flatness is mainly influenced by the positioning of the zygoma. If the zygoma is more anteriorly situated, the result is orbital and zygomaxillary flatness.

#anatomy #3dmodeling #characterdesign

[Keyojimbo @Keyojimbo]

Old reel circa 2017. Not first first game job but first one after a stint in the military-industrial complex. #animation