与「Oblivionis」相关的搜索结果

一生…! 三角初華／Doloris — ツバサ 豐川祥子／Oblivionis — Ruka 若葉睦／Mortis — Kin 八幡海鈴／Timoris — Ajo 祐天寺若麥／Amoris — HIKO

So many commenters who seem oblivious to how dangerous this man proves himself to be. I would never get on this White man’s bad side. For clarification - he could have killed that boy and that entire crowd could not have stopped him.

I listened to 85 minutes of The Economist’s interview of Elon so you don’t have to. Besides, it’s behind a paywall. Elon’s predictions: In five years, AI compute will exceed the sum of all human intelligence. In ten years, we will have reached the age of abundance. Money won’t matter. Everyone will have what they need or want (at least in economies that embrace AI). Ms. Beddoes tried to pin Elon down on how the economy will transform that way, but he wouldn’t get into specifics beyond noting that widespread AI robotics is a deflationary force. This means governments won’t need to raise taxes for universal basic income schemes, or, as Elon likes to call it, universal high income, since they will simply be able to print money to ward off deflation caused by the robot economy. She noted that Elon appears to have a more sanguine view of AI lately. He replied that he’s concluded superintelligent AI is now inevitable, so there’s no point trying to stop or slow it down, it can’t be done. We might as well enjoy the ride. The interviewer also noted that Mars no longer seems to be Elon’s overall ambition. He answered that his real mission was always to propagate and preserve human consciousness into the far future. Mars was just a vehicle for that. But now AI is a very important part of that goal. AI will necessarily be part of any future plan. And then came the oh-so-typical, increasingly tiresome part of most long journalist interviews: the interviewer constructs a straw-man version of Elon and argues against it. Elon carefully explained that he isn’t a raging far-right extremist, racist Nazi who kills puppies … and the journalist still didn't believe it. It is so effing tiresome. The lack of self-awareness on the part of journalists is off the charts. She complained about Elon’s supposed misperception of how dangerous London is, while remaining oblivious to the role she plays in creating the giant misperception of Elon as a person in her own writing. Elon defended his political views, saying he is for secure borders, locking up criminals, and balanced government spending, something even she had to admit didn’t sound crazy. And… that’s about it for an 85-minute interview. I couldn’t help but think that the next long-form interview Elon does should be conducted by an AI.

oblivious = 気がついていない、無自覚な He is oblivious to the problem he is causing. 彼は自分が引き起こしている問題に全く気がついていない。#英語学習# (こういう人を日に何度も見かけます。)

One of the many joys of building onchain with @giveagiiift is the ability to surface real-time data through the public analytics page: Giiift Global When I was a kid I used to watch those Santa tracker applications with absolute awe at what was unfolding around the world, of course sadly oblivious to the fact that not only did Santa not exist but perhaps even worse it was all mock data (the horror!). Well, childhood Colby would be pretty ecstatic to know that we can build a global gifting system that would make even Santa kinda jealous. One of my hopes is that we can really showcase how 'alive' giiift feels for people from the outside looking in and what's more track the virability of Giiift through surfacing not only gifts sent around the world in realtime but also showcase something called the K coefficient. K is GIIIFT's viral coefficient which is the average number of new gifters each gift produces downstream. It is the single number that decides whether GIIIFT grows itself or has to pay for growth. Every gift is already an invitation, so when a recipient opens one and sends their own, the loop closes and compounds, spawning more and more gifts as a receiver becomes a sender. A higher K number means Giiift rapidly spreads across the globe, kinda like a pandemic except instead of sickness we bring joy! Proud to be building on top of @prism_lp

Why Most CIOs Are Quietly Praying for Retirement — And the Few Who Aren’t Are About to Get Very Rich I had a moment this week where I was sitting across from a Director of IT and it hit me — this poor bastard has the toughest job in the entire company. The business folks get to be full-time dreamers: “Hey, can we automate this? Can the AI just know what to do? Can it walk my dog while I’m in this meeting?” Meanwhile he’s over there thinking about data security, system reliability, whether some employee is gonna click on an email that says “You’ve won a $1,000 Walmart gift card!”, whether Ukrainian hackers are going to steal their customer data at 2 a.m., and whether his entire team is about to get replaced by three interns and ChatGPT — all while knowing none of this stuff actually works the way the brochures promised. And here’s the part that makes me feel for the guy — for his entire career he’s been rewarded for keeping the machines running and not getting fired. Now we’re asking him to suddenly become a profit center, to be out over his skis with AI initiatives. It’s like telling the hall monitor he’s now responsible for running the company’s underground poker game. Did I just compare our AI software to an underground poker game? Yeah, probably not the best analogy, but hang with me here, I’m rolling. Meanwhile the C-suite is over there wondering why nothing’s happened yet, completely oblivious to the fact that they’ve spent twenty years brutally punishing IT for not playing defense. Hell, I know CIOs who got fired because Windows 95 sucked. The real kicker is how to even get started. Our philosophy has always been to start small — automate one workflow, prove it works, and then compound fast. Smart in theory. In practice, with a big organization, that feels like bringing a birthday candle to a forest fire. The C-suite doesn’t get excited about incremental. They want to see something that actually moves the needle. So you’re stuck trying to thread this ridiculous gap: build something small enough to actually work, get real user adoption, and make sure the vendor isn’t full of shit. Honestly, I don’t envy that seat one bit. At Collide, we’re committed to being real partners with the folks actually doing the building. I’ve got serious scar tissue from getting fired for not being “openly collaborative” with other oil and gas companies on well spacing back in the shale days, and I’m never making that mistake again. We’re gonna share what we learn, educate when we can, and actually listen — God knows we have a lot to learn too. Truth is, my tech guys are dying to find some partners in crime — and I really gotta stop with the crime analogies, I swear that’s not what we’re doing here — because they get all excited explaining the latest and greatest AI breakthrough and I respond with the technical sophistication of a man asking if his rotary phone has Bluetooth. Sip slowly, my friends.

I explained the Chinese real estate & debt crisis in much detail in 2024 on my Substack. Nothing has changed since. China is in what we call "the largest balance-sheet recession the world has ever seen". And it will take years to get out of it and assuming the CCP's investment-led growth model does not dig the next hole in the meantime - a likely. The FT published added some colour to it two days ago: "Housing is important to every economy. But to China, it’s extra important. According to the PBoC, 96% of urban households own a home, and 41% own at least two. The average household owns 1.5 properties. And as such, property constitutes around 70% of China’s private wealth. The comparable figure for the US is around 30%. So when Chinese property prices fall, the authors make a pretty compelling case that this has all sorts of particularly bad economic spillovers. And fall they have. The negative wealth effect is substantial, and “effects are amplified by elevated household debt, much of which consists of mortgage obligations”. This — and the weaker income expectations that the falls generate — goes some way to suppressing consumption. Moreover, declining land-sale revenues constrain local government budgets, “limiting their capacity to finance developmental projects and maintain existing public infrastructure”. And this is even before any credit impacts from rising non-performing loans and mortgages on bank balance sheets are considered. Tl;dr: bad bad bad. Of course, China isn’t the first soon-to-be-global-economic-hegemon-East-Asian-power staring down demographic oblivion to have piled its savings into a property boom. Back in 1991, the world was fretting over the rise and rise of Japan. And the Japanese were buying Japanese residential real estate at outlandish prices. Japan’s house prices peaked back in 1991 and spent the next 30 years on a downward trajectory. We’re only a few years into the Chinese property bust, and its ultimate trajectory is both unknown and unknowable. But Rogoff and Yang have pulled together some cool data they kindly shared with Alphaville, allowing us to make this chart below. So far, it looks like prices in Chinese cities are falling at around the same pace as they did over the first five-to-10 years of Japan’s bust. Japan’s property crash is associated with a lost decade (or two) of economic growth. In the 10 years leading up to 1991, Japanese real annual GDP growth averaged 4.4%. In the subsequent 10 years it averaged only 0.9% per annum. The same numbers for China, with 2021 marking its property zenith, are 7.0% per year and 4.6% per year (so far). If the IMF’s forecasts turn out right, this latter number will fall to around 4.0% per annum. While the levels are different, the before-and-after drop looks comparable. Was it housing wot dun it? Rogoff and Yang reckon that a 40% decline in house prices translates into a total consumption loss of 2-4% of GDP. Not nothing, but not a single answer explaining life, the universe and wiggles in the decadal pace of real economic growth. To get here, they construct a historical dataset comprising subnational data across 47 prefectures, and input and output data at granular industry levels. They then use this to examine the macroeconomic implications of Japan’s real estate bust. And the authors argue that: a housing bust can generate substantial adverse effects on the economy via real channels. . . . overbuilding during the boom can trigger a demand-driven recession with limited reallocation and low output. Unlike financial channels, which amplify shocks through leverage, bank balance sheets, credit constraints, or fire sales, real channels operate directly through investment, consumption, labour markets, or productivity. In Japan’s case, the housing market collapse depressed activity through three key real channels: investment, consumption, and sentiment. This is all pretty intuitive. But using city-level and household-level Chinese data plus some whizzy maths, they put meat on the bone for these three channels. They find that Chinese cities that overbuilt housing the most are less keen on new building, suppressing investment. Sounds legit. Chinese household consumption is estimated to be more responsive to house price changes than it was in either Japan or the US given its outsized role in private wealth. And it looks to the authors like people have scrambled to rebuild precautionary savings they thought they had amassed in property. Understandable. Then, on the sentiment side, Rogoff and Yang use an LLM to gauge market perceptions of the housing market. And by incorporating city-specific perceptions, they double the estimated effect of house price changes on consumption. Huh. While China is not Japan, 1991 was not 2021, and a *lot* of other things are/were going on, it’s interesting to see that the overall magnitude and pace of property price falls — as well as the aggregate drop in the pace of headline GDP growth — has (so far) been spookily similar. And as for the big question — are we there yet? "If China’s adjustment unfolds in a similar way as Japan’s, it would mean China has not gone half way through the transition. By contrast, if China’s path is eventually comparable to the United States, it appears to have already covered roughly two-thirds of the adjustment before reaching the bottom." So more to come.