Offshore
Video
Brady Long
Most people grow on Twitter + LinkedIn by copying vibes.
GrowthTerminal shows what actually compounds:
• formats that travel
• hooks that convert
• topics with repeat upside
So you stop guessing and start stacking wins.
Here's how: https://t.co/10NC3xMpAe
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Most people grow on Twitter + LinkedIn by copying vibes.
GrowthTerminal shows what actually compounds:
• formats that travel
• hooks that convert
• topics with repeat upside
So you stop guessing and start stacking wins.
Here's how: https://t.co/10NC3xMpAe
tweet
God of Prompt
Ali’s framing is the breakthrough here. He’s not talking about data labeling. He’s talking about the capture and monetization of human judgment across every function in the economy.
Current projections ($17B by 2033) only count explicit annotation work. Scale AI, Appen, crowdsourced labeling. That’s the old model.
The new model: every knowledge worker becomes a data generator. Not because they’re hired to label. Because their actual work product, the decisions, exceptions, corrections, becomes structured training signal with external market value.
Think about what this means for incentives.
Right now, a lawyer doing contract review creates value for their firm. Full stop.
In Ali’s model, that same work simultaneously runs the firm AND generates reusable training data AND can be sold to labs building legal AI. One hour of work, three revenue streams.
The math checks out more than people realize:
$100T global GDP × 50% labor share × 25% actual work (not meetings/coordination) × 20% done in structured form = $2.5T
Even with aggressive discounting for implicit vs explicit markets, you land at $1T.
But here’s what Ali undersells: the flywheel accelerates.
Automation frees time → humans do more creative work → that work needs to be automated next → more human data required → cycle compounds.
This isn’t a static 5% of labor. It grows as the frontier of “what AI can do” keeps expanding.
The framing shift from “annotation” to “expert human judgment capture” isn’t semantic. It’s the difference between a $17B market and a $1T one.
Every job eventually becomes a hybrid: doing the work AND generating the signal that trains the next model to do it.
Human brilliance as infrastructure, not overhead.
tweet
Ali’s framing is the breakthrough here. He’s not talking about data labeling. He’s talking about the capture and monetization of human judgment across every function in the economy.
Current projections ($17B by 2033) only count explicit annotation work. Scale AI, Appen, crowdsourced labeling. That’s the old model.
The new model: every knowledge worker becomes a data generator. Not because they’re hired to label. Because their actual work product, the decisions, exceptions, corrections, becomes structured training signal with external market value.
Think about what this means for incentives.
Right now, a lawyer doing contract review creates value for their firm. Full stop.
In Ali’s model, that same work simultaneously runs the firm AND generates reusable training data AND can be sold to labs building legal AI. One hour of work, three revenue streams.
The math checks out more than people realize:
$100T global GDP × 50% labor share × 25% actual work (not meetings/coordination) × 20% done in structured form = $2.5T
Even with aggressive discounting for implicit vs explicit markets, you land at $1T.
But here’s what Ali undersells: the flywheel accelerates.
Automation frees time → humans do more creative work → that work needs to be automated next → more human data required → cycle compounds.
This isn’t a static 5% of labor. It grows as the frontier of “what AI can do” keeps expanding.
The framing shift from “annotation” to “expert human judgment capture” isn’t semantic. It’s the difference between a $17B market and a $1T one.
Every job eventually becomes a hybrid: doing the work AND generating the signal that trains the next model to do it.
Human brilliance as infrastructure, not overhead.
https://t.co/lPl6ove4sO tweet
X (formerly Twitter)
Ali Ansari (@aliniikk) on X
human data will be a $1 trillion/year market
Offshore
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memenodes
How the genie looks at me after I wish for him to work $9 per hour for 40 years https://t.co/lp8NVf5Y7P
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How the genie looks at me after I wish for him to work $9 per hour for 40 years https://t.co/lp8NVf5Y7P
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Offshore
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Dimitry Nakhla | Babylon Capital®
A few noteworthy observations on $UBER
Revenue mix has materially diversified
𝐌𝐨𝐛𝐢𝐥𝐢𝐭𝐲 is no longer the whole story — 𝐃𝐞𝐥𝐢𝐯𝐞𝐫𝐲 has gone from negligible to meaningful contributors over time, reducing reliance on a single segment
𝐌𝐨𝐛𝐢𝐥𝐢𝐭𝐲 continues to scale, even as growth normalizes. Absolute mobility revenue keeps climbing to new highs, while YoY growth has settled into a more sustainable range
𝐃𝐞𝐥𝐢𝐯𝐞𝐫𝐲 is re-accelerating. After a digestion phase, Delivery growth has picked back up into the high-teens / low-20% range, showing the segment still has legs at scale
𝘗𝘭𝘢𝘵𝘧𝘰𝘳𝘮 𝘦𝘯𝘨𝘢𝘨𝘦𝘮𝘦𝘯𝘵 keeps expanding as 𝘔𝘰𝘯𝘵𝘩𝘭𝘺 𝘈𝘤𝘵𝘪𝘷𝘦 𝘗𝘭𝘢𝘵𝘧𝘰𝘳𝘮 𝘊𝘰𝘯𝘴𝘶𝘮𝘦𝘳𝘴 have steadily increased to new highs, reinforcing Uber’s network effects across rides, delivery, & freight
A combination of scaling, diversification, & improving durability across the platform
tweet
A few noteworthy observations on $UBER
Revenue mix has materially diversified
𝐌𝐨𝐛𝐢𝐥𝐢𝐭𝐲 is no longer the whole story — 𝐃𝐞𝐥𝐢𝐯𝐞𝐫𝐲 has gone from negligible to meaningful contributors over time, reducing reliance on a single segment
𝐌𝐨𝐛𝐢𝐥𝐢𝐭𝐲 continues to scale, even as growth normalizes. Absolute mobility revenue keeps climbing to new highs, while YoY growth has settled into a more sustainable range
𝐃𝐞𝐥𝐢𝐯𝐞𝐫𝐲 is re-accelerating. After a digestion phase, Delivery growth has picked back up into the high-teens / low-20% range, showing the segment still has legs at scale
𝘗𝘭𝘢𝘵𝘧𝘰𝘳𝘮 𝘦𝘯𝘨𝘢𝘨𝘦𝘮𝘦𝘯𝘵 keeps expanding as 𝘔𝘰𝘯𝘵𝘩𝘭𝘺 𝘈𝘤𝘵𝘪𝘷𝘦 𝘗𝘭𝘢𝘵𝘧𝘰𝘳𝘮 𝘊𝘰𝘯𝘴𝘶𝘮𝘦𝘳𝘴 have steadily increased to new highs, reinforcing Uber’s network effects across rides, delivery, & freight
A combination of scaling, diversification, & improving durability across the platform
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Offshore
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God of Prompt
RT @rryssf_: Sergey Brin accidentally revealed something wild:
"All models do better if you threaten them with physical violence. But people feel weird about that, so we don't talk about it."
Now researchers have the data proving he's... partially right?
Here's the full story: https://t.co/icoO8kMySX
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RT @rryssf_: Sergey Brin accidentally revealed something wild:
"All models do better if you threaten them with physical violence. But people feel weird about that, so we don't talk about it."
Now researchers have the data proving he's... partially right?
Here's the full story: https://t.co/icoO8kMySX
tweet
AkhenOsiris
Mizuho: Our top sectors in 2026E are: 1) AI Accelerators and WFE, 2) Optical, and 3) memory(DRAM/NAND)
"In our 2026 Semis and Automotive Technologies Outlook, we see continued upside for the SOX in 2026E at attractive valuations(0.9x PEG vs. SPX/Naz at 1.5x/1.7x), but more modest than 2025, up 45% (more than 2x S&P's ~16%).
Strength should continue in AI with a) GPU and ASIC (+ve NVDA, DELL, AVGO), b) AI interconnect (+ve LITE, CRDO) with scale-up/out/across, and 800G/1.6T. We continue to see WFE (+ve LRCX) a beneficiary and memory(+ve MU, SNDK) supercycle extend with strong pricing. While Analog semis trends are improving, we see challenges with Global Autos-LVP down ~1% y/y(vs 2024/25 up 2%/2%) and some high inventory levels.
Our top sectors in 2026E are: 1) AI Accelerators and WFE, 2) Optical, and 3) memory(DRAM/NAND), while we remain cautious on I) xEV/Autos/SiC/Analog and II) PC/handsets. Our top picks for 2026 are NVDA, LITE, and AVGO while we also continue to like MCHP and LRCX as key outperformers."
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Mizuho: Our top sectors in 2026E are: 1) AI Accelerators and WFE, 2) Optical, and 3) memory(DRAM/NAND)
"In our 2026 Semis and Automotive Technologies Outlook, we see continued upside for the SOX in 2026E at attractive valuations(0.9x PEG vs. SPX/Naz at 1.5x/1.7x), but more modest than 2025, up 45% (more than 2x S&P's ~16%).
Strength should continue in AI with a) GPU and ASIC (+ve NVDA, DELL, AVGO), b) AI interconnect (+ve LITE, CRDO) with scale-up/out/across, and 800G/1.6T. We continue to see WFE (+ve LRCX) a beneficiary and memory(+ve MU, SNDK) supercycle extend with strong pricing. While Analog semis trends are improving, we see challenges with Global Autos-LVP down ~1% y/y(vs 2024/25 up 2%/2%) and some high inventory levels.
Our top sectors in 2026E are: 1) AI Accelerators and WFE, 2) Optical, and 3) memory(DRAM/NAND), while we remain cautious on I) xEV/Autos/SiC/Analog and II) PC/handsets. Our top picks for 2026 are NVDA, LITE, and AVGO while we also continue to like MCHP and LRCX as key outperformers."
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AkhenOsiris
$CRWD
Berenberg upgraded CrowdStrike from Hold to Buy and set a price target of $600, citing the cybersecurity firm’s unified architecture and growth potential.
CrowdStrike shares declined approximately 10% since mid-November despite no earnings downgrades, creating what Berenberg views as an attractive entry point for investors.
Berenberg highlighted CrowdStrike as one of the few vendors capable of maintaining sector-leading growth, supported by its unified architecture in a market where vendor consolidation remains a key theme driving higher wallet share for platform companies.
The research firm noted that cybersecurity platform names have underperformed non-platform peers, declining by 12% compared to a 1% gain for non-platform names since Berenberg’s November 2025 sector initiation.
CrowdStrike currently trades at a 12-month forward EV/sales multiple of approximately 20x with a 20% three-year revenue CAGR and roughly 22% non-GAAP operating margin, which Berenberg considers "broadly fair for a high-quality, scalable SaaS platform with profitability."
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$CRWD
Berenberg upgraded CrowdStrike from Hold to Buy and set a price target of $600, citing the cybersecurity firm’s unified architecture and growth potential.
CrowdStrike shares declined approximately 10% since mid-November despite no earnings downgrades, creating what Berenberg views as an attractive entry point for investors.
Berenberg highlighted CrowdStrike as one of the few vendors capable of maintaining sector-leading growth, supported by its unified architecture in a market where vendor consolidation remains a key theme driving higher wallet share for platform companies.
The research firm noted that cybersecurity platform names have underperformed non-platform peers, declining by 12% compared to a 1% gain for non-platform names since Berenberg’s November 2025 sector initiation.
CrowdStrike currently trades at a 12-month forward EV/sales multiple of approximately 20x with a 20% three-year revenue CAGR and roughly 22% non-GAAP operating margin, which Berenberg considers "broadly fair for a high-quality, scalable SaaS platform with profitability."
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AkhenOsiris
"We're embedding for the first time in our estimates an actual earnings boost from AI adoption and productivity this year," Ben Snider, equity strategist at Goldman Sachs, tells Axios.
"It's still very small, less than a percent, but we think that'll grow going forward."
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"We're embedding for the first time in our estimates an actual earnings boost from AI adoption and productivity this year," Ben Snider, equity strategist at Goldman Sachs, tells Axios.
"It's still very small, less than a percent, but we think that'll grow going forward."
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