$LYTE Now Trading: AI data centers are replacing copper-based data transfer with faster, more efficient light-based connections and optical connectivity has become a critical bottleneck of the AI buildout. The AI optical transceiver market alone is estimated to grow 57% this year, from $16.5 billion to $26 billion. The Roundhill Photonics & Optics ETF $LYTE is a pure play on the global photonics and optics leaders. Consider investing:

@gushanjishui A股市场会越来越正规。这几年几年，出现了巨大的regime shift，不管是宏观经济和监管和市场微观结构。不能老拿之前的经验去套现在的市场。

这段时间一直在找A股的交易数据，对比比较熟悉的美股加密有我用的比较得心应手的期权和其他衍生品数据，A股这类数据可用的真的有点少，感觉现在在这种交易大于逻辑的环境里面，感觉像个盲人。

Imagine, for a moment, you are an LP in Situational Awareness. The fund that launched on a pitch that was essentially “AI is the only thing that matters and if you recognize that and wish to be invested in a vehicle that will express that view by getting massively nips to nuts long the most beta to our informed AI views this fine stock market can offer us, then you invest”. And you invested. Not just because you’re bullish on AI, thousands of hedge funds are “bullish on AI”, but because you think Leopold is uniquely situated as being one of/knowing “the few hundred people” who will bring about Machine God before 2030. Then over the next two years, the fund did exactly what it said it would. And it went up. By, like, twenty something times if I’m remembering properly. Again, in this scenario you are the person who read Situational Awareness (the paper) and said “Yes, I agree AI is more powerful than the nuclear bomb and will render the world unrecognizable before the decade is out. And I want my investments into the hedge fund version of that view”. Now those stocks go down, so the fund goes down. Let me ask you - do these LPs seem like the type of people that are going to become bearish on AI because SK Hynix got cut in half in six weeks? The people who likely regard “I’m going long TQQQ” levels of tech bullishness the same way normal people view investing into a muni bond fund? Yeah...I would not expect many of them are calling Mr. Ash Burner to complain right now. Some people don’t realize how insane being up 2200% since inception (in 2024) is. To put that into perspective, if you invested $100M with SALP at inception and wiped out ninety percent in July, your investment would be worth $230M. I think it’s probable the LPs will BTFD. Situational Awareness is going to get the money they’re asking for. And, once it’s in, they’ll take off their (likely short dated) hedges because they’re not at risk of getting liquidated by their prime, meaning the market makers that sold them the hedges will cover their delta hedge on what’s probably quite a lot of notional exposure. And at the same time, they will be deploying that capital into what they think is “the best buying opportunity since April 2025”. I don’t think @leopoldasch is in trouble so much as he’s likely to raise the capital he’s asking for, which would mean it’s more likely now that Leopold causes the bottom than causes AI to continue going down. If there’s something I’m missing that would cause this cohort of LPs who are AI-super-believers that are likely still up significantly on their SALP investment to decide that they would rather not buy the dip, then, sure, every stock even vaguely AI-smelling is probably going to Hades. But…

KOSPI回吐5%的涨幅转为跌近1% 韩国什么时候能知道信心要比黄金还重要呢 继续去杠杆只会不断的杀死散户，人心散了队伍就不好带了 在经过存储这波行情后，更加确信了要相信眼睛不要相信脑子 如果这波行情按照趋势策略操作，在第一次出现做空信号的位置止盈也有超过30%的收益，而且还可以避免后面30%的跌幅 相信眼睛，并不是说放弃思考，更多的是让你的思考服从K线的走势，毕竟K线是真金白银买出来的 进推特主页加TG群找小助理获取【自用趋势策略】 #KOSPI# #存储# #海力士#

every single person i know working at the frontier is incredibly talented and hardworking, and they're not wasting compute or capital, and neither is america. some thoughts / opinions on this 1/ new capability is infinitely harder. i'm not saying chinese labs are just mass distilling (although there's some of that), but even a few teacher model calls to 5.6 sol pro for math or fable agent rollouts is OOMs cheaper than hiring human experts, sourcing data, cleaning data, etc. this is why mercor, scale and the other data vendors do so well. paying physics phds to help teach the models is not cheap, and china does indeed get a leg up here. this is also why i suspect most labs have the true frontier model internal only. the modus operandi seems to be to assume any model put into the hands of hyperscalers or released via api will be distilled or stolen. what the public sees is ~6 mo behind what's internal, and depending on how the chinese labs are operating, they're either ~1yr behind, or ~1.5yrs behind the true capability of the labs. there's also a fair amount of benchmaxxing from china, as they only have to show a good looking number to be considered great, not get sustained usage to stay alive (like the US labs), or be efficient at inference (which is also an optimization for the labs, more on this later). the modus operandi seems to be to assume any model put into the hands of hyperscalers or released via API will be distilled or stolen, which is 100% justified and right. talent and ip bleed is a also real thing. a lab may frequently have to run/burn thousands of tests to figure out the optimal config/architecture for a model. anyone on the training, inference team or one of the hyperscalers who hosts the model can just look at one model implementation/config file and know the truth and understand and replicate. you don't need to know what didn't work, only what did. 2/ data privacy requirements (or lack thereof) in mainland china. assuming reasonably that the six little tigers in china (look it up if you don't know about this) have access to some form of additional ccp data that we do not know about, it is a moderate advantage. the labs are incredibly thirsty for novel data. the internet has mostly exhausted its utility, at least with current techniques, and much like what ilya said, there is only one internet (like fossil fuels!). people are also deploying the models to things never seen before. i.e how is a model supposed to learn how to order food with the doordash cli unless its taught how to behave in this scenario / is superhuman at generalization. US enterprises are also vary of this, and therefore cannot and do not rely on chinese model apis. i don't think this is cope, although i realize many may feel this way 3/ inference efficiency: the modern labs are extremely good at inference. the gb300 is a beast, and even older chips are being used very well to serve the models. api pricing is meant to also recover the cost on training, and inference cost for intelligence continues to fall. all labs have really large sparse moes that are OOMs cheaper than what api pricing reflects. 4/ profit motive: there is an interesting dwarkesh podcast about this. you must stop looking at china from the worldview of they're trying to make money. this is just not true. they're trying to dominate via scale and volume, which is true for the way china works, but not the us. the people of china are incredible, extremely sharp and are not to be underestimated. 996 work culture and strong stem is a great source of talent and data for the labs. american labs must pay around $1m/yr for entry level talent in the bay, which also increases capex. also there's an undisclosed amount of capex coming from the ccp. i do not claim to know what the scale is, but i would suspect there's a fair amount of chips flowing through the gulf, khazakstan etc. (do we seriously believe khazakstan of all places is building $10B worth of datacenters with nvidia gpus all for/by themselves?) 5/ datacenter and build out. xai had to spend a lot of money, time and effort to build out the supercomputer in tennessee. anthropic pays them 10 digits to lease out to serve customers etc because of the lack of supply, electricity, zoning, regulation etc. ccp does not have this issue, and there are claims that they are indeed introducing misinformation into the us that data centers are bad for us. we have to get much much faster about addressing this and dealing with "muh water use" kind of statements. it's oneshotting our population, much like nuclear energy did. electricity is the final moat, over chips, models, intelligence, and data. regardless of your timelines, if you believe in rsi, then you know the physical world is the only bottleneck. china/the ccp has real, compounding structural edges on data access, deployment freedom, talent cost, speed of physical buildout, and now apparently on shaping the domestic narrative around our datacenters and energy. america is making the best use of it's most powerful resource, capital, to accelerate faster.