kai retweeted
16/16 the synthesis: banks teach funding contagion; commodity merchants teach spread risk; airlines teach utilization; utilities teach offtake finance; csps teach pooling. watch paid gpu use, price per unit and firm obligations. a capacity bust is more likely than a bank run.
kai retweeted
BREAKING: The US has told several Gulf Arab countries to be prepared for a "short, intense military campaign" after the US Midterm elections, per WSJ.
Details include:
1. There are "a growing number of indications" that the US and Israel are readying to launch a new round of heavy combat operations against Iran, WSJ reports
2. The US Military is sending an additional Patriot system to Israel
3. US forces in the region have been restocking munitions and aircraft are preparing for strikes
4. "We may do another little Epic Fury," Trump said this week
Oil prices are rising on the news.
kai retweeted
BREAKING: Microsoft, $MSFT, is offering buyouts to 60,000 workers as part of the company’s efforts to cut costs amid AI adoption, per Bloomberg.
Personnel on select teams in the US, Canada, India, and the UK at a vice president level and below will be eligible.
This reflects ~27% of Microsoft's total workforce.
kai retweeted
*MICROSOFT TO OFFER BUYOUTS TO 60,000 WORKERS IN LATEST COST CUT
This is 27% of $MSFT's entire workforce
kai retweeted
Anthropic:
$134b of cash today
$141b of total capital raised
<$10b of total burn to get to $16.8b in quarterly revenue (Q3 figure that was widely reported, Q3 not in S-1 yet)
kai retweeted
one very interesting point is that they don't talk about creating their own chips, and afaik, it's not mentioned once in the full S1
they even say stuff hinting that they are not developing their own chips (or never were?):
> Our competitors may be better positioned… to vertically integrate across the compute supply chain, including through proprietary chip design, fabrication, ownership or long-term control of data center infrastructure…
> We also depend on third-party chip design and services companies for the design, manufacture, and support of certain custom accelerator platforms, as well as for related infrastructure financing arrangements
Anthropic has filed an S-1 registration statement with the SEC related to its proposed IPO.
Read more: anthropic.com/news/s1-sec
Legal disclaimer: A registration statement relating to these securities has been filed with the SEC but has not yet become effective. These securities may not be sold, nor may offers to buy be accepted, prior to the time the registration statement becomes effective. This post does not constitute an offer to sell or the solicitation of an offer to buy these securities, nor shall there be any sale of these securities in any state or jurisdiction in which such offer, solicitation or sale would be unlawful prior to registration or qualification under the securities laws of any such state or jurisdiction.
kai retweeted
Congrats to Team @AnthropicAI on another important milestone! Altimeter looks forward to continuing our partnership w major participation in the IPO on top of our existing ownership. Day 1. 🇺🇸🚀 sec.gov/Archives/edgar/data/…
"Avg active params per token" is a good metric to measure if models are just becoming "good enough", a sustained downtrend is bad for the compute demand thesis.
kai retweeted
there will be within the next few years stunning advances in biology. there will whole new ways to think about what biological study even means. i would be only mildly surprised if there were near term solutions to problems like cancer, neurodegenerative disease, etc
kai retweeted
AI demand is a barbell, with the labs on one end and enterprise cost-cutting on the other. Amazon CEO Andy Jassy says the biggest market sits in the middle, and inference is still "an order of magnitude too expensive" to reach it.
"On one end of the barbell are the AI labs who are consuming gobs and gobs of compute, unlike anything I've seen. And then a few runaway apps, ChatGPT, Claude Code, things like that."
"On the other end of the barbell are enterprises who are largely using AI for cost avoidance and productivity, so automating customer service or fraud or business process automation."
"In the middle of the barbell are the current production workloads of enterprises, many of which are using AWS and using inference today, but I would say the overwhelming majority of which still aren't in any pervasive way."
"And that I think is gonna be the largest absolute segment of AI usage."
"The cost of inference has come down quite a bit in the last few years, but it's still an order of magnitude too expensive, in my opinion, for it to be used as pervasively as possible."
"If you're asking enterprises to rewrite their applications that use CPU today with AI accelerators... the amount of incremental benefit they have to get is a much higher bar to want to rewrite those apps. But if you can take the cost of inference down, that bar is much lower, and all applications are gonna be better and smarter and more capable."
@ajassy
Five years into his run as CEO, Andy Jassy has nearly tripled the size of AWS, grown Amazon's revenue by about 80%, and expects to spend $220 billion this year to win AI. Amazon's AI business hit a $25 billion run rate in three years, growing several hundred times faster than early AWS.
Jassy joins a16z's Ben Horowitz and Erik Torenberg to discuss the decisions behind that run, from rebuilding Amazon's fulfillment network after the pandemic to the AWS origin story.
They also cover why data centers became a political fight, Amazon's custom chips, its stakes in Anthropic and OpenAI, why inference needs to get 10x cheaper, AI's most underrated risk, and why every company will have to reinvent its products from scratch, plus Jassy's advice for anyone who's 18 today.
0:47 How Amazon has changed since 2021
1:51 How the pandemic reshaped retail
3:30 Why AI supercharged AWS's growth
5:20 When leadership principles clash
9:36 $60M vs. $25B: early AWS vs. early AI
13:20 How the AI CapEx cash cycle works
15:44 Why the US must build data centers
20:55 The labs-to-enterprise AI barbell
23:12 Demand vs. longtime AWS customers
28:11 Annapurna, Graviton, and Trainium
33:55 Backing Anthropic and OpenAI
37:15 Why AI means smaller teams
42:13 AI's underrated risk: security
46:29 Why Amazon rewired Alexa's brain
53:07 What Jassy tells his kids about AI
56:36 Betting on AI, robotics, and space
YouTube: youtu.be/-YMMRQ1qscI
@ajassy @Amazon @bhorowitz @eriktorenberg
kai retweeted
Kimi K3.1 Pro launches at 4th on the Artificial Analysis Intelligence Index scoring 55, making large gains in agentic performance; it will be the leading open-weights model once its weights are published
@Kimi_Moonshot's new reasoning model gains 11 points over Kimi K3 (max, 44). It trails only Claude Opus 5.5 (max with fallback, 58), Claude Sonnet 5.5 (max with fallback, 56), and Muse Wonder Full (max, 56) on the Intelligence Index.
Once the weights for K3.1 Pro are released it will be the highest-scoring open weights model and the gap between the leading open weights and proprietary models on the Intelligence Index will narrow from 12 points to 3.
Key results:
➤ Large gains in agentic performance: Kimi K3.1 Pro scores 3rd on GDPval-AA with 1,846 Elo, up 312 Elo from Kimi K3, behind only Claude Opus 5.5 (1,866 Elo) and Muse Wonder Full (1,857 Elo). Kimi K3.1 Pro also achieves the highest score of any model on Terminal-Bench 4.0. K3.1 Pro scores 67%, up from 13% for Kimi K3 and ahead of Claude Sonnet 5.5 (64%). AutomationBench-AA, which tests agentic SaaS workflows, rises from 58% to 73%.
➤ Gains in other evals are more moderate: Humanity's Last Exam rises from 47% to 52%, CritPt from 23% to 25%, and SciCode from 59% to 61%. AA-Omniscience Index rises from 20 to 30, as the hallucination rate falls from 53% to 44% and accuracy rises from 48% to 51%.
➤ Cost per Task roughly equal to Kimi K3 at $1.98 per Task: K3.1 Pro uses 55K output tokens per Intelligence Index task, 14% more than Kimi K3 at 48K, while its first-party token prices are 33% lower.
Additional model details:
➤ Context window: 1M tokens.
➤ Size: 2.8T total, 104B active parameters
➤ Input modalities: Text and image
➤ Weights and license: Weights currently not published, Moonshot is expected to release the weights soon after launch
➤ Pricing: $2/$10/$0.20 per 1M input/output/cache hit tokens, 33% lower than Kimi K3 on all three rates.
Congratulations to the team at @Kimi_Moonshot on the release!
1GW of rubin
NVDA revs 40b
Neoclouds LT rental 13b pa
SpaceX ST spot market rental 40b pa
Ant sub revs 30b pa
Ant API revs 80b pa
Deepseek inference max revs 200b pa
kai retweeted
- YIELD ON 10-YEAR TREASURY NOTE FALLS BELOW 5% FOR FIRST TIME SINCE SEPTEMBER 23, LAST DOWN 14.97 BASIS POINTS AT 4.996%