Ejaaz

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Ejaaz

Ejaaz

@cryptopunk7213

searching for patterns | AI @limitlessFT | Prev. @coinbase @consensys

nyc Katılım Ağustos 2018
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Ejaaz
Ejaaz@cryptopunk7213·
yeah so this is insane 24 year old turned $225M into $5.5B in <12 months. dug into his recent investments and… holy fuck - MASSIVE $885M position in Bloom Energy (specialises in portable energy turbines for… you guessed it - ai data centers) - this 1 position is 20% of the entire fund lol - massive SHORT position on Infosys. he’s betting claude code, codex are going to replace outsourced IT work (he’s right) - added $300M to his corweave position totalling $700M (someones gotta run those gpus) - aggressively pivoted investments into electrical and energy infra (aka AI’s biggest constraint right now) - dumped $100Ms of NVIDIA and Intel positions. - aggressively buying bitcoin mining companies and re-purposing them for ai data centers. (cipher, bitdeer) - fund up $1.5B in the last 3 months (+35% last quarter) - now owns 10% of core scientific (levered bet on coreweave 😂) He outperformed the S&P500 8X in the funds first 6 months. fucking goated.
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Ejaaz@cryptopunk7213·
claude mythos just broke Apple's $2 billion defense system. it did so by discovering a completely different attack vector to break in only took it 5 days costing ~$35K of mythos api time (the same exploit class costs $5-10M on grey market) the researchers that commandeered the exploit produced a 55-page report that was delivered to Apple HQ in-person (hoping they release it after patching). most shocking part for me is apple's MIE worked as intended. mythos just discovered a new way to side-step it entirely by poisoning the data the M5 chip ingested. at this point i think we have to accept that mythos walks the walk. As the anthropic red-team explicitly confirmed this week - this is NOT a compute resource issue. its national defense.
International Cyber Digest@IntCyberDigest

❗️🚨 BREAKING: Researchers used Mythos Preview to find the first public macOS kernel memory corruption exploit on Apple's M5 silicon, they give a glimpse into Mythos say it’s really powerful. Apple spent five years and an estimated several billion dollars building Memory Integrity Enforcement (MIE), the hardware-assisted memory safety system built around ARM's MTE. It was the flagship security feature of the M5 and A19, designed specifically to kill the entire memory corruption bug class. Researchers from Calif built a working exploit in five days. According to Apple's own research, MIE disrupts every public exploit chain against modern iOS, including the recently leaked Coruna and Darksword kits. Calif walked into Apple Park this week and handed over the report in person. Full 55-page technical report drops after Apple patches the vulnerability.

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Ejaaz
Ejaaz@cryptopunk7213·
god i’ve watched this entire thing twice now. krishna is a force at anthropic & he’s masterfully given them a winning hand. the amount of alpha in this episode: > the #1 place anthropic spends compute isn’t model training or customers… it’s the research team. he explains: - research team uses compute to build a better model - better model uses LESS tokens so the same amt of compute can serve MORE people in the future. “we could’ve earned billions more in revenue but then we would’ve lost the model race” > anthropic’s the only lab to train AND inference their models across 3 different chip architectures. krishna: “one morning we will run an inference block on trainium and by the afternoon it’s used to train claude” the unique advantage = they don’t rely on a single supplier. > krishna says people don’t fully comprehend how advanced each model version gets. agents, long-horizon tasks, cost effectiveness improve ALL AT ONCE “we went from $9B to 30B in months” - that wasn’t just because the chatbot got better. bonus: krishna uses claude to generate the companies monthly financial report. it does it in 30 mins and is 95% accurate. the highest token-consumer on his team is the tax guy. there’s so much more i want to share but honestly just watch the interview @patrick_oshag you killed it
Patrick OShaughnessy@patrick_oshag

Krishna Rao is the CFO of Anthropic, and this is his first podcast appearance. He joined the company two years ago when run-rate revenue was about $250M. Today it is $30B. He has helped raise ~$75B and is responsible for the procurement and allocation of compute. I feel lucky we get to hear what it is like to sit inside a company this consequential at a moment this pivotal. We discuss: - The cone of uncertainty - How he allocates compute across Trainium, TPUs, and GPUs - What investors misunderstand about model companies - Why the returns to frontier intelligence keep rising - Platform vs application and where Anthropic builds its own products - How Anthropic uses Claude internally I have asked my closing question about the kindest thing more than 500 times. Krishna's answer is one I have never heard before. Enjoy! Timestamps: 0:00 Intro 2:38 The Compute Canvas 6:51 The "Cone of Uncertainty" 11:58 Why the Returns to Frontier Intelligence Are So High 16:45 Recursive Self-Improvement 20:20 Scaling Laws 23:30 Sourcing $100 Billion in Compute 28:05 Platform vs. Application Strategy 32:52 Pricing Dynamics 38:48 How Anthropic’s Finance Team Uses Claude 43:24 Raising Capital & Overcoming Investor Skepticism 52:32 Public Perception, Risks, and Government Regulation 57:25 Mythos Release 1:12:33 What Could Derail the AI Revolution? 1:13:47 Biotech and Healthcare 1:15:31 The Kindest Thing

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Ejaaz
Ejaaz@cryptopunk7213·
anthropic just publicly committed to a deadline for transformative AI (AGI): 2028 and this matters in the race against china in AI (for good reason): > if AGI is built in <24 months then its essential adversaries don't get access to it (first). we're seeing a mini version of this play out with the government restriction on mythos (no public release). > china themselves admit USA is #1 for now: "China is still sharpening our swords while the other side has suddenly mounted a fully automatic Gatling gun." -chinese cybersecurity analyst on mythos. you might call bullshit on this but yesterday's security test report from Logan suggests they're right. > anthropic dismisses deepseek's claim they've found a workaround to building frontier models with less compute: everything about ai advancement (model intelligence, research, algorithms) sit DOWNSTREAM of compute the models are now building themselves. the winners are whoever has more compute (gpus in this case) and thats the USA. huawei's entire compute capacity this year is only 4% of nvidia's entire compute. good food for thought imo
Anthropic@AnthropicAI

We've published a paper that explains our views on AI competition between the US and China. The US and democratic allies hold the lead in frontier AI today. Read more on what it’ll take to keep that lead: anthropic.com/research/2028-…

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Ejaaz
Ejaaz@cryptopunk7213·
so cerebras at a $400 per share IPO means: foundation cap’s $37M investment is worth $6 billion (164x) Benchmarks $270M -> $7.14B (27x) OpenAI’s 11% stake -> $13B (already vested $4B) just a staggering amount of money generated. largest AI ipo by far. ofc these are paper gains. most investors are locked up + have contingencies (openai needs to buy $1B worth of cerebras chips)
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zerohedge@zerohedge

CEREBRAS SHARES INDICATED TO OPEN AT $400, IPO PRICE $185

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Ejaaz
Ejaaz@cryptopunk7213·
“to be clear, compute has never been a limiter to our rollout” lot of people missed this. anthropic basically saying they could’ve released mythos but it’s too dangerous for a few reasons: > only model to complete a major 32-step cyber attack in < 8 hours (on 2.5M tokens!) > fortune 500 companies would be immediately exposed to threats. don’t believe it? all 40+ glasswing partners already discovered major vulnerabilities using the model logan (correctly) warned that a year from now we’ll probably see multiple OPEN source models capable of mythos level attacks. there’s a reason the gov is locking the model down.
Logan Graham@logangraham

A lot of people have been wondering about Mythos, Glasswing, and the vulns we / our partners are fixing. Today, I’m excited for us to start sharing more. (For context, I lead Glasswing @AnthropicAI.) Two independent evaluations this week—from XBOW and the UK AISI—confirm what we've been seeing internally: Claude Mythos Preview is a step change in autonomous cybersecurity capabilities. We need to start preparing fast for a world of models with this level of capabilities. The UK AI Security Institute tested the model we shipped at the launch of Project Glasswing and found Mythos Preview is the first model to solve both of their end-to-end cyber ranges, including one (Cooling Tower) which no model had ever cleared. But attackers (and defenders) have sophistication & cost constraints – Mythos is also the only model that clears every one of their tasks estimated over 8 hours under their deliberately low 2.5M-token cap. XBOW tested it on their offensive security benchmarks, finding "token-for-token, unprecedented precision." It's the only model to succeed at subtle V8 sandbox work. Other Glasswing partners shared similar stories. In a few weeks of testing, Mythos Preview has helped them find many thousands of (estimated) high + critical severity vulnerabilities, sometimes double what they'd normally find in a year. I don't share this to boost Mythos. In fact, this is not about Mythos. It’s about preparing for the coming world of models being better, faster, cheaper, and more creative than some of the best human experts at dual use capabilities. Clearly, we need them supporting defenders as widely as can be done safely – and especially the least resourced ones. Within a year, Mythos will probably look quite dumb (relative to other new models). And others may release openly available or unguardrailed models of Mythos-level capabilities. We started Project Glasswing because capabilities like Mythos Preview's won't stay rare, or stay in careful hands. We are bringing it to defenders as fast as we responsibly can, while working to figure out, for example, the right safeguards and patching & disclosure processes. Also, to be clear, compute has never been a limiter in our rollout. Expect a fuller update on our Glasswing work in the coming days. XBOW report: xbow.com/blog/mythos-of… UK AISI report: aisi.gov.uk/blog/how-fast-…

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Ejaaz
Ejaaz@cryptopunk7213·
my god. so if you’re a fortune 10 company using claude you started the year paying anthropic $1,000,000 per year and end it paying $5,000,000 5X increase in spend from a single customer because your product is THAT good. Anthropic’s really found pmf with enterprise and the moat is getting stronger every month a company uses claude it gets exponentially more costly to switch.
Patrick OShaughnessy@patrick_oshag

500% NDR at Anthropic is the stat of the year for me… I asked Krishna what questions he'd ask the model companies if he were an investor. His three:
 1) What is the ROI on compute? 2) How are customers seeing ROI? Are they deploying at scale or just testing? 3) How do you think about compute in the future, and where does it come from? His answer to the second one: "Our net dollar retention is over 500% on an annualized basis. Nine of the Fortune 10 are customers. [In the 20 minute Uber to this podcast], I signed two double-digit million-dollar commits."

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Ejaaz
Ejaaz@cryptopunk7213·
the counter to this is simple: openAI codex adoption has gone vertical over the last few weeks, this isn't reflected in the data. codex installs hot 88M last week while anthropic lagged. curious to see how this trend plays out over next Q.
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Ejaaz@cryptopunk7213·
this is seriously impressive from anthropic. just look at the numbers 12 months ago: > may 2025: anthropic 9%, openai 32% > today: anthropic 34.4%, openai 32.3 anthropic 4X'd their enterprise marketshare while openai stayed flat. for every $1 dollar spent on the model labs anthropic now captures $0.65 claude's biggest markets are software (SaaS is HUGE market) and finance these 2 industries make up the majority of value in the fortune 500 Anthropic's ARR is on-track to hit $100B this year.
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Ara Kharazian@arakharazian

ANTHROPIC beats OpenAI in business adoption for the first time. per @tryramp data Today's update of Ramp AI Index shows 34.4% of businesses using Anthropic versus 32.3% using OpenAI. Adoption of Anthropic quadrupled over the last year, while OpenAI rose only 0.3%.

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Ejaaz@cryptopunk7213·
@sama yep - you proved this with codex spark imo.
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Sam Altman
Sam Altman@sama·
i get some anxiety not using the smartest-available model/settings. but sometimes i dont mind if it's really slow. i wonder if we should focus more on a price/speed tradeoff relative to a price/intelligence tradeoff.
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Ejaaz@cryptopunk7213·
i mean this story is absolutely insane claude just recovered $400,000 of lost bitcoin that this guy lost access to 5 years ago... craziest part is he MADE money by losing access > guy stores 5 bitcoin in his college laptop in 2015 > tries to access it years later, forgets password, locked out forever > 2026: dumps his hard-drive into claude, asks it to figure out a solution. > claude finds an encrypted password file, uses the guys passphrase to access it and unlocks his bitcoin! his bitcoin was worth $50K back then, now he's got almost half a million not bad for single claude session huh?
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🍜@cprkrn

HOLY FUCKING SHIT OMG CLAUDE JUST CRACKED THIS SHIT, THANK YOU @AnthropicAI THANK YOU @DarioAmodei NAMING MY KID AFTER YOU 😍 blockchain.com/explorer/addre…

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Ejaaz@cryptopunk7213·
anthropic has recently achieved insane pricing power, customers are now eating millions of dollars in claude costs (microsoft alone is spending $500M this year) and its about to get even more astronomical: > anthropic recently changed their pricing model from a flat fee to a usage-based model. pay-per-tokens-used > as a result their ARR has skyrocketed to $45 billion, rev is now on par with openai the customers? they're all-in: > 1 company reported claude usage QUADRUPLED in last 3 months thanks to claude ai agents (this was from a single agent flow btw) that same company boosted sales by $1M in a single quarter. this is a shift most people havent caught on to yet. companies are becoming increasingly reliant on ai models to boost growth the truest signal of this is agents btw. its going to drive this trend 10X larger than it is today.
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Ejaaz@cryptopunk7213·
@ravespecialist where we’re going you won’t need a keyboard bud
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Ejaaz@cryptopunk7213·
man google really came out of nowhere and stole the limelight in AI today these are serious moves only a vertically-integrated giant like google can play btw: > a brand new laptop device engineered for AI native experiences. powered by Gemini intelligence and intel chips > gemini intelligence will launch across EVERY android device. sounds boring until you realise this is what Siri was meant to be… > massive $2.1 billion raise for their AI designer drug lab Isomorphic. their model has already discovered novel treatment molecules. > an AI native mouse cursor that interacts with Gemini whenever you point at something eg “turn this block of text into a visual” > partnering with SpaceX to launch data centers in space. the strategy makes a lot of sense now, they might not win coding or LLM chatbots but they will be the #1 end-to-end distributor of AI the only other company that’s remotely close is Apple
Google@Google

Introducing Googlebook, the first laptop designed for Gemini Intelligence. It’s crafted for heavyweight performance, built with Gemini at the core and perfectly synced with your Android phone. Coming this fall. 💻✨ #TheAndroidShow

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nic carter
nic carter@nic_carter·
Situational Awareness Q1 13F filing drops this Friday Leo, we await your sage counsel...
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Ejaaz@cryptopunk7213·
it looks like an AI alliance is gradually forming between SpaceXAI, anthropic, tesla, google and cursor. its incredibly beneficial to all parties involved: > google gets cheap access to space + infinite energy > anthropic gets 300MW of inference compute > spaceX gets $5-10B between anthropic and cursor deals > cursor gets a leading coding model from the compute both google and anthropic have now publicly announced intentions to use SpaceX to launch ai data centers into space in the last week Google owns 7% of spaceX and 14% of anthropic so it makes sense
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The Kobeissi Letter@KobeissiLetter

BREAKING: Google and SpaceX are in talks to launch data centers into orbit amid surging AI demand, per WSJ.

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Ejaaz@cryptopunk7213·
@bro_abra everything is downstream of asml
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no@bro_abra·
@cryptopunk7213 does this increase demand for asml products?
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Ejaaz@cryptopunk7213·
it seems like the trump administration is doing everything in their power to make Intel the TSMC of america. since the U.S. gov bought a 10% stake in $INTC they’ve: > made NVIDIA invest billions in intel and commit to partnering on products. > pushed Tim cook to integrate intel chips with apple products > forced chip production to intel fabs. news broke this week of even amazon adopting intel’s packaging expertise for chips intel CPUs are also projected to underpin all agentic orchestration in the U.S. pretty good signal for future demand
Wccftech@wccftech

Tesla reportedly moving production of its AI6.5 chip from TSMC to Intel “under the pressure and insistence of the Trump administration” wccftech.com/tesla-reported…

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Ejaaz@cryptopunk7213·
read this. tldr their chips target answer inference (hence why codex spark is so quick) but doesn’t optimize for the intermediate “orchestration, thinking, tool calling” that agentic inference will drive (which i expect to be where 80% of the val comes from) x.com/cryptopunk7213…
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Ansem
Ansem@blknoiz06·
what do we think the $CBRS IPO trades at on Thursday? will be largest IPO of the year w/ them raising ~$4.8B @ $48.8B valuation @ $150-160 a share, pre-IPO markets are trading nearly 2x higher they make specialized larger chips designed for faster inference & work w/ OpenAI
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Ejaaz@cryptopunk7213·
phenomenal breakdown of what’s going on with inference right now. ben nailed the shift we’re undergoing and what that means for NVIDIA vs. cerebras (hint it’s fucking amazing for memory producers): - inference is going to be HUGE. 10-50X the value of training but… - they’re 2 types of inference: answer inference (90% of today’s) and AGENTIC inference (10%) - agentic inference is where most of the value will come from in the future but right now it’s in its infancy… 99% of agents act like chatbots for now - but when that flips, agents will require a different type of AI chip, one that doesn’t look like nvidia’s GPU. - it’ll need higher bandwidth memory, an abundance of compute and low latency. agents WON’T be constrained by humans - memory is the most important. very bullish memory providers. - Cerebras is only good for answer inference, it’s not good for agentic. - answer inference is not as valuable. it’ll have its own niche but much smaller TAM vs. the entire inference market. - NVIDIA will maintain the throne for the foreseeable future
Stratechery@stratechery

The Inference Shift Agentic inference is going to be different than the inference we use today, and it will change compute infrastructure because speed won't matter when humans aren't involved. stratechery.com/2026/the-infer…

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Ejaaz@cryptopunk7213·
hell yeah! openai just released their new mythos-level security model (before anthropic did) this sounds like it’s a custom version of 5.5 that can: > understand, detect and fix security vulnerabilities in your code > model out complex attacks and defend against them before they happen > actively work with security engineers to make enhance their work point 2 is the winner here imo. as AI proliferates in software there will be many exotic attack vectors… now we can use AI to fight AI.
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OpenAI@OpenAI

Introducing Daybreak: frontier AI for cyber defenders. Daybreak brings together the most capable OpenAI models, Codex, and our security partners to accelerate cyber defense and continuously secure software. A step toward a future where security teams can move at the speed defense demands.

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