
Exponential View @exponentialview.
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Joined July 2007
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The GenAI economy has generated $110 billion in sales over the past 12 months. It is growing fast. On an annualized basis, the revenue run rate exceeds $175 billion.
These numbers took us several months to construct, and as far as we know, it’s the first bottom-up, deduplicated measure of consumer and enterprise AI spending across the full stack.
We are releasing this research today in our first The State of the AI Economy report.
intelligence.exponentialview…
North Korea now!
Multiple waves of DDoS attacks caused this week's outage in North Korea.
Aggregate traffic data shows a flood of traffic from Vietnam, Philippines, Venezuela and other countries began at 02:01 UTC on Oct-20 when the country's sites went offline. @nknewsorg
Barclays says it is cutting 5,000 jobs, or about 5% of its workforce, as the bank incorporates AI more deeply into its business. wsj.com/cio-journal/barclays… via @WSJ
Azeem Azhar retweeted
Corollary
xitter.cf/nntaleb/status/2023725…
Azeem Azhar retweeted
SCOOP: Major U.S. banks are detecting unauthorized third-party AI agents inside customer accounts, including some attempting to take actions that appear to be independent of user instructions, sources told Axios.
The findings have alarmed banking executives, who are racing to restrict access to their systems as AI moves at a velocity faster than financial institutions can respond, multiple industry and bank executives told Axios.
Several banks are now preparing for worst-case and even “day after” scenarios, including how to rapidly secure or restore customer accounts if things go wrong, the people said.
Several bank executives told Axios they're struggling to distinguish between human users and AI agents. One executive said banks also struggle to determine whether agents are authorized by customers or potentially operating without their permission, more akin to rogue agent behavior.
Read my latest for Axios here: axios.com/2026/10/22/ai-agen…
Azeem Azhar retweeted
Not good.
We are *this close* to losing the ability to read the AIs thoughts, so we can't see if they're scheming against us
A message to the AI companies: FUCKING. STOP.
Azeem Azhar retweeted
oh cool you’re in the “i’m buying a mac studio to run local models” stage of your ai journey?
i’m in the “i’m buying a starlink, a generator, and 2 weeks of food and water” of mine.
Azeem Azhar retweeted
Ths analysis matches my (and @deepforestsci team experience). It's always been surprising why METR claims such long horizons while this never seemed to work in practice for problems we cared about
A recent set of posts by @ramez on the current state of recursive self improvement highlighted that OpenAI's report on their own research automation shows that models struggle to do their R&D work — the models' 80% time horizon is only 15 minutes:
🧵
Azeem Azhar retweeted
皆様に、今夜に対応して頂きたい大至急のお願いです。
多くのウェブサイトで使用されているPHPに関し、PHPのセキュリティチームが、重大な2件の脆弱性に関する注意喚起を行っています。
公開しているウェブサイトでPHPを使用しているか確認し、今夜、10月21日午後11時(日本時間)に公開される修正パッチについて、可及的速やかに適用できるよう準備をお願いします。
修正パッチを速やかに適用することが困難な場合は、例えばウェブサイト等を一時的に停止させることも、リスクを低減させるための有効策の一つと考えられます。
国家サイバー統括室のXアカウントでも関係する情報を発信していますので、そちらも参考にして下さい。
国家サイバー統括室(注意・警戒情報)(@cyber_forecast) / X
Azeem Azhar retweeted
This chart is $
Also, hard to see memory not being constrained then through 2030 at they very least.
"As these products come in, the trade ratios continue to be stressed in terms of the number of wafers it takes to build HBM, vertical HBM, and vertical EIM relative to building standard DRAM bits. So that that pressure remains through this roadmap."
$MU
Azeem Azhar retweeted
Good find by Toby. AIs are far less capable on real world AI research tasks than ECI x METR or AI 2027 predict. Data from Google Argon (adding on to OpenAI):
Gemini 4 actual: ~15 minutes
ECI --> METR Prediction: ~360 minutes (6 hrs)
AI 2027 prediction: ~1,000 minutes (18 hrs)
Replying to @tobyordoxford
Fortunately, that has arrived. GDM ran a very similar analysis on their internal use of AI for AI R&D and published their graph on page 78 of their Gemini 4 Safety Report:
Azeem Azhar retweeted
If it wasn’t obvious already we’re in a completely new paradigm of cyber vulnerabilities.
Product teams at Cloudflare, Mozilla, Chrome, Safari etc are doing incredible work keeping up - but wow we need more and better defensive cyber models to harden applications and the web yesterday.
It is astonishing to read in the @thetimes today an Op-Ed from @parismarx saying AI hasn’t changed anything! Head in the sand is not a strategic option.
Following the discovery that eight eMudhra intermediate certificates use weak keys, Cloudflare is deploying mitigations and releasing client updates. We explain the impact, our response, and what customers and developers should do next. cfl.re/487DNbG
Effective Immediately, all organizations using PHP for their systems are advised to be prepared for an update addressing two critical vulnerabilities. PHP is widely used for web applications. These vulnerabilities often provide a direct path to the server's file system or database. If an immediate update is not feasible, it is recommend that organizations take the system offline until it can be fully mitigated. NSA will follow up shortly with more specific guidance.
Azeem Azhar retweeted
S&P 500 usually rallies after midterms, with gains building from months after the election into the next year. As noted previously, a split Congress delivers the upper end of returns. A controlled Congress, the lower end.
h.t @ISABELNET_SA
Azeem Azhar retweeted
I would add this isn't particularly concentrated by standards of the US economy.
A former Google employee says that starting around mid-Q2, customers began swapping some Anthropic and OpenAI models out of their multi-agent setups for open-source ones.
That is consistent with an expert interview we did in August:
Former $GOOGL employee on why data center capacity and electricity are the real bottlenecks, not GPU production itself, and how unreliable some of the neoclouds are ($AMZN, $GOOGL, $MSFT, $NVDA):
1. According to the expert, open-source models are closing the gap with frontier models faster than expected, with customers increasingly replacing Anthropic and OpenAI models in multi-agent architectures with open-source alternatives starting from Q2 of this year. The shift started with simple tasks like tool calling and MCP, but has moved up the stack to low-level orchestration.
2. The expert identifies capacity as the biggest constraint at the moment, with certain companies' traffic growing 5x while GPU availability, particularly in the U.S. where latency requirements are tightest, simply cannot keep up. Sourcing capacity overseas in Asia or Australia is technically possible but adds latency that most customers will not accept.
3. Hyperscalers offer reliability but are expensive, require multi-year commitments of three or more years, and have limited availability of the latest hardware, with customers already chasing B300s. AI-native companies tend to gravitate toward neoclouds due to hyperscaler pricing and contract rigidity, but neoclouds come with their own reliability issues, with GPUs dropping off unexpectedly and requiring engineering resources to manage fleet stability around the clock.
4. The third tier consists of smaller independent operators who have invested in GPU racks, seeing the opportunity to lease out capacity and recoup costs within a year or two, with the remainder being pure profit. The expert describes these as essentially unusable in practice, with operators who do nothing more than find land, install racks, connect electricity, and set up cooling, with no real cloud management, maintenance, or operational expertise behind them.
5. The expert expects overall GPU availability to increase meaningfully over the next year or two, with $NVDA continuing to ramp production. The real bottleneck is not GPUs themselves but data center capacity and electricity in the U.S. On the supply side, the expert also sees players $SPCX beginning to lease out spare capacity to the market, with more likely to follow.
6. The expert notes that U.S.-based neoclouds typically require 20-30% prepayment upfront, with the remainder paid monthly or quarterly over the contract term, and rebates negotiated at the end for any reliability incidents like traffic loss. APAC-based providers operate differently, with no prepayment required at all.
found on @AlphaSenseInc





































