Perception deviating from reality creates opportunity; Bull or Bear, timeframes & Risk mgt matter most, Looking for Delta, Not advice it may be sarcasm
Joined February 2012
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9 Sep 2019
It depends on what your definition of "is" is....
#GreatPresidentialQuotes
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The 2000 market top was all about the Dot Com Bubble
But, Comparatively speaking, in 2000 there was no market concentration compared to today
Does that make today a bigger bubble?
Or is it just market concentration?
File Under: Only a problem if it becomes a problem
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Jun 16
Housing Starts
It's just a one month dip... that will go away with "The Deal", Right?
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Jun 16
Let us not forget that every day,
with every iterative update,
This Platform @X @elonmusk @grok
becomes less useful
and more like random scrolling through TikTok
Jun 16
The irony of AI is that the sector being destroyed the most by AI is the Tech sector. And it's not just affecting software companies. Video games, Social media, Fintech, Cyber security sectors are all being imploded.
Microsoft is a key example. It's highly diversified and is even a major hyperscaler. Microsoft is the largest shareholder of OpenAI. And yet as we see below the stock is imploding. Oracle, Meta, Amazon same thing.
Which means that this "Tech" rally is getting narrower with each passing day. Look at the lower pane showing semiconductors as a ratio of the total Tech sector.
AI means commodification. The companies that embrace AI will first realize cost savings when they layoff their employees.
After that they will realize ZERO revenue when there is no barrier to entry.
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Jun 16
AI
Is the market telling us the software is worthless and ALL the value is in the chips & hardware
Because if the software doesn't require a premium.... um....
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Jun 15
Excuse me
WHY does $NVDA need to raise $25 Billion?
It's the biggest Cash Cow Monster Stock EVER or ALL TIME?
I must have missed something relevant
Jun 15
NVIDIA DRAWS $85B IN INVESTOR DEMAND FOR JUMBO BOND SALE.
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Jun 11
RT @chigrl: Headline inflation climbed back above 4% last month for the first time since the spring of 2023. While the principal cause is a…
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0range Crush, CMT retweeted
The S&P 500 long-term earnings growth forecast is at a record high of 24%... too frothy?
h/t @callum_thomas @topdowncharts
chartstorm.info/s/chart-of-t…
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0range Crush, CMT retweeted
Citadel Securities just put institutional weight behind what the AI bulls won't say out loud.
In a new macro note titled "Tokenomics," Citadel makes the argument plainly: even the most powerful technology on earth still has to pass through the boring discipline of cost curves, capacity limits, and marginal returns.
The evidence is piling up:
– Amazon removed its token usage leaderboard
– Microsoft cancelled Claude Code subscriptions
– Multiple companies reporting unexpectedly massive token bills
Their conclusion is the part that matters.
Adoption is no longer about what AI can do in principle. It's becoming about the price and scarcity of the inputs needed to run it at scale. Compute. Power. Cooling. Memory bandwidth. Inference budgets. All real, all binding constraints.
And here's the kicker from the chart.
The Silicon Data LLM Token Expenditure Index, a benchmark for how much the market is actually spending on AI tokens, has started rolling over. Citadel reads it as a shift toward cheaper models. Companies substituting away from expensive frontier AI toward "good enough" alternatives.
That's economics 101 doing what it always does. When the price of something rises, people use less of it, or find a cheaper version.
Citadel sees a bifurcation forming. Frontier AI concentrated among a few firms with the balance sheets to absorb the cost. Everyone else quietly downgrading to simpler, cheaper models.
This is the part of every technology revolution the early narrative ignores.
The technology being real was never the question.
The question was always whether the economics could carry the valuations.
When one of the most sophisticated trading firms on earth starts writing about AI in the language of cost curves and rationing instead of limitless demand, the conversation has quietly changed.
The hype was about what AI could do.
The reckoning is about what it costs.
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Jun 10
If "THEY" have been jawboning the markets higher
Suddenly
it feels like it isn't really working anymore
But all this weakness may simply be raising Cash for SpaceX
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Jun 10
This sounds like
AI is really expensive
We are not getting much from it
We can't afford it
Let's cut every cost to the bone, including people
Because
We Are Not Giving UP on AI
AI is (supposed to be) great!
Historically, when companies 'cut costs to the bone'
Does it work out well? #AskingForAFriend
Jun 10
"A Lot Of BS, Honestly": Apollo Head Says Everyone Is Measuring AI Wrong zerohedge.com/ai/lot-bs-hone…
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Phrased a little differently
I'm pretty sure the Strait will not be opening any time soon... 😒
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0range Crush, CMT retweeted
Jun 4
Who could have predicted this?
There’s a ceiling to what customers will pay.
There are cheaper alternatives.
Switching costs are low.
Local LLMs are getting good enough for more use cases.
These companies:
Have no moat.
Have limited pricing power.
Aren’t worth their valuations.
It doesn’t mean AI is useless.
It doesn’t mean the technology is going away.
It doesn’t mean companies won’t build valuable products with it.
Useful technology and valuable companies are not the same thing.
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"Reserving expensive frontier models for exploration only and shifting production workloads to cheaper open source models"
How are OpenAI and Anthropic going to generate the trillions in revenue they need to justify their ridiculous valuations when their customers switch to open source?
#AskingForAFriend thinking about an IPO or 3
Uber CEO Dara Khosrowshahi: "We Blew Through Our AI Budget in a Quarter"
In response, Uber is doing three things:
-Slowing headcount growth as AI makes engineers more productive
-Reserving expensive frontier models for exploration only and shifting production workloads to cheaper open source models
-Capping each employee at $1,500/month per AI coding tool
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Did Trump just TACO on Iran Uranium?
NDX down 2 days in a row and suddenly...
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Wait the LLM model #.3 we spent 6 months approving just changed
All answers are a little different, just enough to invalidate current approvals
Does that happen?
Jun 4
Let me give some "behind the scenes" as to why AI ROI is so elusive. Even if the AI works, you have to navigate the "Seven Gates of Software Hell".
I ran AI for a company that managed a huge portion of the world's communications data for financial services companies. This is an excruciating read but the realities are tough.
Let's get started. Suppose you want to scan all of your communications for customer complaints and respond quickly. Here's your journey:
Gate 1: Data Controls
Various geographies require the data to be stored in-region, and in some cases, only accessed in-region. You may need separate AI deployments for each one.
The data may need to be scrubbed for PHI/PII and will need to be scrubbed for Material Non-Public Information. If it leaves the System of Record you'll need to ensure there is a way to selectively delete data so that you can adhere to GDPR, CCPA or PIPL.
Gate 2: Data Quality
Even if you get controls in place, you discover that your data is coming from 8 different vendors. Some are real-time, others T 1 and they all have different APIs. To boot, your corporate directory has 4 identities for Brandon Carl that have never been merged so you can't properly query even a single person's data.
Gate 3: Security Controls
Given the sensitivity of the data you're sending, you'll need to go through an extensive security audit. Since this is an LLM you'll need to look beyond SOC2 and into OWASP Top 10 LLM risks and Gen AI risks too.
Gate 4: SLAs
Your AI Agent calls are taxing your system with bursty volumes and risking your mission-critical production workloads. You may need to set up read-only replicas, throttling and overage billing.
Gate 5: Vendor Risk
Your vendor will be assessed for their financial viability as well as the controls they put in place. This may go as far as analyzing the vendor's software development processes.
Gate 6: Legal Procurement
You've almost made it, but procurement needs to demonstrate that they are saving the firm money. Negotiations come down to the end of the quarter. Redlines are flying everywhere to meet your firm's AI policies and to ensure there's no training on your data.
Gate 7: Model Governance
The AI/ML models need to be assessed versus your firm's Responsible AI Policy. And if you're going to automate things get really tricky. The model needs to be assessed for Materiality, Autonomy and Complexity. You may need documented evaluations, extensive model documentation and champion challenger comparisons performed by your own internal AI teams.
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You've made it this far, congratulations!
While you've been working through the "7 Gates of Hell" you've had to manage a team of workers you know you're going to fire to justify the AI spend. This requires coordination with HR, one-time separation costs and managing team morale for those employees that stay.
Thanks @emollick for posing the question. Also see bain.com/insights/your-ai-bu…
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This is relevant
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A company trading at forty times earnings and ten times sales is going to sell stock
Who is more intelligent?
The seller or the buyer
#AskingForAFriend
$googl
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