Igor Logvinenko retweeted
New from me: The US has faced a higher cost than any other country from the global Hormuz oil shock, with the crisis adding $160 billion to its fuel bill — or $471 per person on average — despite being the world’s largest oil producer.
Igor Logvinenko retweeted
站在今天看,俄罗斯这波操作,属于手握着一把天胡的牌打得稀烂。
如果不出兵乌克兰,今天全球AI的牌桌上,除了中美,大概率真得坐着一个俄罗斯。
搞AI、跑大模型,底层逻辑就是“吃电、散热、堆机器”。这两年全世界的数据中心老板都在为电费和机房降温发愁。俄罗斯属于老天爷喂到饭:西伯利亚开窗就是纯天然顶级空调;境内水电、核电、天然气很便宜,当年挖矿的都选西伯利亚。
另外俄罗斯人的数学和算法也强,各大国际编程竞赛,Kaggle机器学习竞赛常被俄国人屠榜。全世界除了中美,俄罗斯也搞出了自己完整的互联网生态:搜东西有Yandex,社交有VK,还有Telegram。现在在美股被炒上天的算力黑马Nebius,核心班底就是原先Yandex那帮俄罗斯人。
如果疫情后俄罗斯出地皮、出冷气、出便宜电,再拉着中国这种基建狂魔帮忙拉高压电网、建厂房、铺光纤,欧美资本开服务器工厂。俄国人完全可以成为欧亚大陆最大的“超级算力工厂”,中美神仙打架,它在中间两头收过路费。
结果呢?普京一拍大腿:不行,我得去抢那几块地。
普京的脑子,彻底停留在了19世纪沙皇俄国那种“开疆拓土”的旧梦里。什么有没有出海口啊,有没有所谓的军事缓冲带啊,就算抢方法也多的是,这可这是21世纪啊!现在的世界霸权争夺,抢的是半导体供应链,抢的是先进算法,抢的是高精尖人才。你去顿巴斯抢了几片烂泥地、几座废弃钢铁厂,代价却是把整个国家的未来都押了上去。
枪声一响,一切全崩了。稍微有点本事的程序员、算法工程师,连夜跑路。Yandex核心技术团队,宁可巨亏,惨烈的断尾求生、割裂母国,也要跑到欧洲重组成Nebius。普京把最懂未来的人,全逼成了难民和海外创业者。
在人工智能技术爆发的黎明前夜,全世界都在疯狂狂飙算力、抢占新工业革命的门票;而俄罗斯的老大,却带着几十万人,在泥潭里打着一百年前的一战式堑壕战。
再说一遍,普京不行,国内崇拜普京的那帮人也不行
Igor Logvinenko retweeted
FT: In Brazil, "almost 2mn people, mostly men, now work full-time for transport or delivery apps — around 2 per cent of the workforce — with driver numbers climbing 37 per cent in three years, according to government research. The most common reason people work for the apps is that they could not find another job."
The FT notes that in Brazil, the transport and delivery app economy has become a kind of unemployment insurance scheme, although one with declining "benefits".
The same is true in China. It is hard to get good data, but the best estimates are that 12% of China's working population works in the gig economy, of which 7% work in the transport and delivery app economy – i.e. three to four times the share in Brazil.
ft.com/content/3868b320-2c24…
Igor Logvinenko retweeted
Seen a lot of Nathan For You clips shared around the last few days but haven't yet seen anyone repost the pinnacle of the televisual medium that is Nathan Fielder as Captain Sully landing in the Hudson River as Bring Me to Life by Evanescence plays
Igor Logvinenko retweeted
💥Confirmation of EU-China trade deal detail:
- Yearly quota of 350,000 hybrid units with fixed annual increase adjustment rate of 6%. This will cut by more than half the current Chinese exports to the EU, which is estimated to reach around 800,000 units in full year 2026
Igor Logvinenko retweeted
Dusting off this tweet from April because this gap in shared understanding of LLM capability is *widening*. It's now less "two groups of people speaking past each other" and more a sharp funnel.
- Napkin math somewhere around 6B people (~75% of the population) have barely come in contact with LLMs at all.
- Around 1-2B (~20%) are casual and infrequent users of free-tier ChatGPT-like products. This group sees derpy chatbots and treats them a bit like a better Google search, a writing aid, or etc. Maybe an agent tries to book you a flight. I have non-tech friends who (reasonably, imo) say they have not much use for it at all. Even many professionals outside of math&code are in this tier. For example, execs and many other functions spend a lot of their time talking to other people, so while they understand what is happening intellectually, it is still second-hand and a bit abstract.
- Now we get to professional use of frontier-grade LLMs in math&code. Somewhere around 20M people (0.2%) see first-hand that large, complex projects that used to take them weeks/months can now be completed by agents with a prompt. Building apps, copying apps, translating apps, decompiling apps from binaries... This has all happened very quickly and recently - less than 1 year ago, I was writing code manually by hand, typing memorized computer code commands into a code editor character by character, occasionally pressing Tab to autocomplete a little chunk of code.
- And finally we get to the ~5,000 people (~0.00006%) with access to frontier-grade systems internally. The external world has seen the preview. It looks like swarms of thousands of agents collaborating over weeks on software mega projects: minting zero days, running cyber attacks and defenses at machine speeds, discovering new science, advancing the frontier of mathematics. Things that would have taken top professionals in the industry years of work. Meanwhile, human review and comprehension are starting to fall behind. For example, people are still involved in the "archeology" of the OpenAI-HF incident from many months ago. Mathematicians may be poring over the 722 manuscripts on frontier mathematics for a while.
The funnel is driven by a combination of factors:
1. The impact scales with ambition, problem size, and horizon. A question with a paragraph answer barely stresses the system. You need a reservoir of big, difficult problems that you really care about. This aspect drives the consumer / professional dimension of the funnel.
2. The jaggedness of the system (which I have written about a lot separately). Capability peaks in domains that are digital, verifiable and economically valuable. This is because LLM capability emerges from reinforcement learning on verifiable rewards on a curated environment mixture driven by revenue potential. This aspect primarily drives the area (e.g. math&code) dimension of the funnel.
3. Access. Free-tier, paid-tier, internal.
So this is the weirdness of the moment. The general public has mostly not interacted with these systems. When they have, it looks like a derpy chatbot. The majority of professionals still see only a modest uplift. And a small sliver of professionals are experiencing the vertigo of the curve going vertical. And it is all happening at the same time.
Judging by my tl there is a growing gap in understanding of AI capability.
The first issue I think is around recency and tier of use. I think a lot of people tried the free tier of ChatGPT somewhere last year and allowed it to inform their views on AI a little too much. This is a group of reactions laughing at various quirks of the models, hallucinations, etc. Yes I also saw the viral videos of OpenAI's Advanced Voice mode fumbling simple queries like "should I drive or walk to the carwash". The thing is that these free and old/deprecated models don't reflect the capability in the latest round of state of the art agentic models of this year, especially OpenAI Codex and Claude Code.
But that brings me to the second issue. Even if people paid $200/month to use the state of the art models, a lot of the capabilities are relatively "peaky" in highly technical areas. Typical queries around search, writing, advice, etc. are *not* the domain that has made the most noticeable and dramatic strides in capability. Partly, this is due to the technical details of reinforcement learning and its use of verifiable rewards. But partly, it's also because these use cases are not sufficiently prioritized by the companies in their hillclimbing because they don't lead to as much $$$ value. The goldmines are elsewhere, and the focus comes along.
So that brings me to the second group of people, who *both* 1) pay for and use the state of the art frontier agentic models (OpenAI Codex / Claude Code) and 2) do so professionally in technical domains like programming, math and research. This group of people is subject to the highest amount of "AI Psychosis" because the recent improvements in these domains as of this year have been nothing short of staggering. When you hand a computer terminal to one of these models, you can now watch them melt programming problems that you'd normally expect to take days/weeks of work. It's this second group of people that assigns a much greater gravity to the capabilities, their slope, and various cyber-related repercussions.
TLDR the people in these two groups are speaking past each other. It really is simultaneously the case that OpenAI's free and I think slightly orphaned (?) "Advanced Voice Mode" will fumble the dumbest questions in your Instagram's reels and *at the same time*, OpenAI's highest-tier and paid Codex model will go off for 1 hour to coherently restructure an entire code base, or find and exploit vulnerabilities in computer systems. This part really works and has made dramatic strides because 2 properties: 1) these domains offer explicit reward functions that are verifiable meaning they are easily amenable to reinforcement learning training (e.g. unit tests passed yes or no, in contrast to writing, which is much harder to explicitly judge), but also 2) they are a lot more valuable in b2b settings, meaning that the biggest fraction of the team is focused on improving them. So here we are.
Igor Logvinenko retweeted
This could cripple the ICC. Or it could spur a European tech decoupling from the United States, crippling Visa, MasterCard, Microsoft, Amazon and various other U.S. companies making billions of €€€ in the European markets.
US imposes sanctions on International Criminal Court
reuters.com/world/us-imposes…
Igor Logvinenko retweeted
Manufacturing construction spending down 25% while data center production is up 65%.
Igor Logvinenko retweeted
The newly minted Nobel Prize winner Anne Carson shared a book recommendation and some timeless writing advice at the 2024 National Book Awards.
Balkans this week:
🇽🇰 Kosovo elected first Catholic President
🇷🇸 Serbia got first Lesbian President
🇧🇦 Bosnia elected 3 Presidents (2 female)
🇦🇱 Albanian capital Tirana’s mayor will run the city as an AI avatar from prison
Igor Logvinenko retweeted
Australia's biggest coal generator set to be replaced by the world's biggest battery share.google/y7FlNddgXNnEy9Q…
Igor Logvinenko retweeted
Recommended read: A New York Times interactive article illustrated how Asia’s major economies “survived the energy crisis”, following the closure of the strait of Hormuz.
buff.ly/SktHgat
Igor Logvinenko retweeted
Replying to @ChadRBot1
There will be, not because of teaching but because universities increasingly act like clubs. And classes are the way for people to get together and learn together. But your deeper point stands.
Igor Logvinenko retweeted
It’s over
(For gas)
And it’s already October 2
(In Japan)
⚡️⚡️⚡️
#alwaysbecharging
Igor Logvinenko retweeted
Recently I reviewed Ed Goldring's new book on purges in authoritarian regimes, happily titled PURGES. Read on if you are interested in such minor matters as preserving your leadership while eliminating rivals and scapegoating unfortunate subordinates.
thebulwark.com/p/autocrat-gu…



























