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$HOOD This chart has been 🔥 Currently: ◽️All time highs ◽️Stage 2 ◽️Green Dots ◽️Green Bars ◽️Above green Trackline ◽️Bullish Phantom indicator

Wick

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💥RFK - "The immunity which was passed in 1986" comes from Wyath (now Pfizer) telling Reagan they'd leave Big Pharma without liability protection. IS THE ERA OF LIABILITY PROTECTION ENDING? 🧵Here's 36 x evidences that might be revealed in the new Kansas suit against PFIZER 💥 ◽️ 1223 Deaths were reported in Pfizer's initial clinical trial data ◽️According to Dr Jeyanthi Kunadhasan, "At NO POINT during the trial was the intervention LIFE SAVING" ◽️ The same DR revealed undisclosed deaths in the vaccinated arm of the Pfizer trial ◽️RFK said that according to Pfizer’s own data, more people died of All Cause Mortality in the vaccine group at the end of a 6 x month period ◽️There was 5 x heart attacks in the vaccine group and only 1 x in the placebo group at the end of that period. An increase of 500% ◽️Guernsey had an increase of 500% in Myocarditis in the year of the roll-out, correlating to Pfizer actual trial data ◽️Pfizer reported to the FDA that Maddie de Garay had a "Stomach ache", when she's in a wheelchair ◽️Pfizer used data for FDA approval that does not match Maddie's adverse events reported in senate testimony for EUA approval and liability protection ◽️ According to Maddie's mother, The FDA approved Pfizer's mRNA covid vaccine for children when Maddie was in hospital from ADEs associated to the mRNA covid product she took in that clinical trial ◽️Pfizer emphasised relative risk as opposed to absolute risk for efficacy and marketing of the effectiveness of their product ◽️For Pfizer in terms of Absolute Risk (not relative risk), there was no Statistically Significant benefit to the prevention of people catching covid for the mRNA vaccinated group ◽️ Pfizer Admitted the NEVER TESTED the vaccine on whether it can prevent TRANSMISSION ◽️ Israeli research found men that were vaccinated had decreased sperm counts ◽️According to RFK, Pfizer had 2 x labels for the same product. The EUA product was available, but the licensed version of the same product was “unavailable” ◽️Pfizer and the FDA tried to withhold the clinical trial evidence for 75 years ◽️ Dr Dr Aseem Malhotra mentioned that Re analysis of the Pfizer data shows an adverse event rate of 1/800 ◽️ An Australian FOI revealed the TGA Bioaccumulation studies that show mRNA Lipid Nano Particles are distributed THROUGHOUT the body ◽️ In similar data, the implantation loss of the mice tested more than doubled in the mRNA group ◽️ Myocarditis is a recognised side effect from governments globally ◽️ Several studies have shown (one done in Israel) Myocarditis only occurs in the vaccinated ◽️Albert Bourla said “MRNA had never delivered a single product” and that Pfizer had less experience with” and that Pfizer and BioNTech were working on mRNA for FLU vaccines from 2018 ◽️ Albert Bourla, when asked on 2 x separate occasions whether he’d taken his own vaccine product, said “NO”, he didn't want to "cut the line" ◽️According to Dr Aseem Malhotra, Pfizer paid front groups to push for Vaccine mandates ◽️Pfizer had special mRNA vaccine batches for their employees according to Pfizer's own spokespeople in Australian Senate testimony ◽️South Africa court released documents revealed Pfizer asked governments to set up insurance scheme for adverse outcomes ◽️Pfizer admitted in the South African court documents that the “long term effects and efficacy of the vaccine are not currently known” ◽️Trial data used for assessing pregnancy safety was analysed by researchers that owned stocks in the company that made the product they were evaluating ◽️According to RFK, Pfizer needed to get it recommended to children for liability protection ◽️Kevin McKernan has found DNA CONTAMINATION IN PFIZER - Multiple studies confirm ◽️@P_J_Buckhaults has found DNA contamination ◽️DNA contamination confirmed in Australian Pfizer & Moderna Vials. DNA contamination in Pfizer was over 350 times above per dose limits set by the TGA ◽️Dr. David Martin mentioned that Pfizer admitted their product is experimental gene therapy in filings ◽️Pfizer did not seek approval through Gene Therapy regulations in Australia (Gillespie) ◽Dr. Naomi Wolf. 8 NYT Bestsellers. DPhil, Poetry. mentioned "Trans-placental exposure" of newborns to Pfizer's product ◽️"The miscarriage rate was 80% in the Pfizer trials" ◽️The Pfizer mRNA vaccine is based on a spike protein that strong evidence suggests was a man made virus, potentially done with GOF research ◽️According to the James Okeefe Veritas Whistleblower story, a Pfizer Director stated Pfizer are talking about “Mutating covid viruses” ◽️Dr Peter McCullough, one of the most published Cardiologists, has analyzed all the data and said that Pfizer “should never have been approved” What else is there to add to this list of EVIDENCE? The discovery process for this new Kansas lawsuit against Pfizer is sure to be EPIC

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MANYU NFT'S RELEASE DATE ANNOUNCEMENT! Mark your calendars as its time for MANYU to release its official NFT collection which is a key piece in expanding the ecosystem beyond what we’ve built so far. This collection has been designed to integrate directly into $MANYU with a framework that introduces a revenue generating mechanics (Buybacks/Burns, Staking, Rewards, Partnerships) Each allocation serves a specific purpose, and here's how it works: ◽️40% Development: Building and pushing MANYU (products, partnerships). ◽️30% Staking: Rewards for holders who are long term investors trough staking. ◽️20% Buyback & Burns: Used to support the chart and manage supply. ◽️10% Community Rewards: Giveaways, incentives, and exclusive perks. Alongside the release, a large scale marketing push will go live across multiple channels. We have secured partnerships with some of the biggest well reputable organizations/accounts in the NFT space and in crypto. From a strategic standpoint, this adds a new layer to MANYU’s model, one that introduces additional flows, expands participation, and strengthens the overall structure over time. The intention is simple, create something that feeds back into the ecosystem, benefiting both MANYU NFT and $MANYU holders. Total Supply: 2,000 NFT's Date: 13 April 2026 Mint Price: 0.05 ETH 🔜 Together we had revived the volume on DEX during times where it seemed hard to pull off, and now we will revive the NFT world and bring it back to life. A calculated expansion will be taking place.

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CoreWeave and Crusoe were supposed to lose this market to the hyperscalers, and Dylan Patel Dylan Patel explains why they won it instead (Save this). The twist is that the hyperscaler edges became liabilities. Amazon's advantages, Nitro isolation, Graviton CPUs, custom storage, were all built for the CPU cloud and actively hurt AI performance. And the security and time-slicing expertise stopped mattering, because nobody rents a single GPU in a 72-GPU rack, they rent whole racks on long-term contracts. So the market opened three ways: ◽️First, the incumbent playbook of slicing and isolating fell away, and some of it turned into a net negative. ◽️Second, Microsoft's teams fell on their face when they had to double a year's forecast, and had to go rent Neocloud capacity themselves. ◽️Third, hyperlevered Neocloud teams got rich by delivering compute faster, undercutting on the $12 to 13 billion per gigawatt that GPUs rented for before the crunch while the SpaceX to Google deal ran near $25 billion, all off racks nobody splits into single GPUs. The Amazon cloud-crisis report and the GPU rental market say the same thing, an incumbency built for one workload is a liability for the next.

CoreWeave and Crusoe were supposed to lose this market to the hyperscalers, and Dylan Patel Dylan Patel explains why they won it instead (Save this). The twist is that the hyperscaler edges became liabilities. Amazon's advantages, Nitro isolation, Graviton CPUs, custom storage, were all built for the CPU cloud and actively hurt AI performance. And the security and time-slicing expertise stopped mattering, because nobody rents a single GPU in a 72-GPU rack, they rent whole racks on long-term contracts. So the market opened three ways: ◽️First, the incumbent playbook of slicing and isolating fell away, and some of it turned into a net negative. ◽️Second, Microsoft's teams fell on their face when they had to double a year's forecast, and had to go rent Neocloud capacity themselves. ◽️Third, hyperlevered Neocloud teams got rich by delivering compute faster, undercutting on the $12 to 13 billion per gigawatt that GPUs rented for before the crunch while the SpaceX to Google deal ran near $25 billion, all off racks nobody splits into single GPUs. The Amazon cloud-crisis report and the GPU rental market say the same thing, an incumbency built for one workload is a liability for the next.

Fireside Alpha

48,279 просмотров • 1 месяц назад

$The July 4th weekend All-In The All-In Podcast turned into a long argument about who owns the intelligence layer. The besties think enterprises just woke up to a trap they had been walking into, here's how the conversation went (save this): ◽️ The Palantir-Nvidia deal is a bet against the model-layer duopoly. Palantir will use Nvidia's Nemotron open models to build a custom frontier-quality model for US government agencies, and the agencies own the hardware, the data, and the weights. Sacks framed it as structural: an application company and a chip company both want a competitive model layer, so they are natural partners against a two-provider middle. ◽️ Alex Karp's CNBC "crashout" was actually the thesis. Karp argued enterprises have lost trust in the frontier labs and want to own their compute, models, data, and alpha. Sacks translated it as a new definition of enterprise AI safety: safety means the model provider cannot hoover up your proprietary knowledge and turn it into its next product. ◽️ Figma is the cautionary tale that made it real. Anthropic launched Claude Design into Figma's category, its chief product officer sat on Figma's board and resigned only 3 days before launch, and Figma's stock is down about 50% this year while Anthropic's valuation surged. Sacks listed Claude Science, Security, Legal, Financial, and Code as the same move: dominate the model layer, then take the lucrative verticals. ◽️ The playbook has a name, and it is Microsoft and Google. Sacks argued Anthropic is running the operating-system strategy: own the layer everyone builds on, then walk up the stack. His Google receipt is that fewer than half of searches now send you off-site, versus an early Google that prided itself on how fast it kicked you away. ◽️ The BCG number is what raises the stakes. Chamath cited a BCG return-on-capital-employed study: the cost of capital is back to its long-run 8 to 11%, and half of large US companies cannot earn returns above it. If you are already teetering on your cost of capital, handing your alpha to a provider that may compete with you is not a luxury risk, it is fatal. ◽️ The 16.4x number is the whole argument in one data point. Chamath ran a code-migration task through 8090's harness. Wrapping Claude was 1.4x cheaper and 1.5x faster than Claude Opus alone. Wrapping the best open-source model was 16.4x cheaper, at about 3x slower. For a background task, three extra hours to cut cost by 16x is not a close call. ◽️ Even at 100x cheaper, enterprises were saying no for the wrong reason. Chamath relayed an ex-Meta PM's point that companies reject open models over China and safety fears, when they could host those same open weights on their own GPUs in US data centers with nothing flowing back. The safety objection, she argued, is backwards: the leak is the data you hand the frontier labs. ◽️ Friedberg says the frontier labs are trying to commoditize their own customers. Anthropic has been signing up life-sciences companies to feed a new life-focused model in exchange for early access, and nearly everyone he has talked to now refuses, recognizing that data they spent billions generating becomes worthless once it is pooled with everyone else's. ◽️ The deployment topology is shifting from big hubs to distributed spokes. Friedberg's map: the old assumption was a few capital-advantaged mega-clusters plus inference clouds. The new one is large hubs, medium hubs (enterprise training clusters), and distributed spokes, including on-prem inference in your own building. Owning your weights is the point. ◽️ Chamath's endgame is running GLM himself. An industry contact told him that with harness post-training and telemetry, an open Chinese model like GLM could get as good as Anthropic's Mythos. His conclusion: take GLM, control it soup-to-nuts on US hardware with only US citizens touching it, and pay a fraction. ◽️ The Apple analogy sharpens why renting intelligence is different from renting distribution. Chamath argued Apple is the only platform that respected developers, deliberately keeping its stock apps basic to protect the ecosystem and collect its 30% tax. There is no 30% tax on open models, and worse, you cannot rent intelligence from the same place that rents it to your competitor without ending up identical to them. ◽️ Nvidia's open model is now good enough to matter. Calacanis claimed you cannot tell Jensen Huang's Nemotron from Claude on 95% of searches, and that Nvidia downplayed the model until now to avoid alarming its top customers. The gloves came off once OpenAI, Anthropic, and Elon all signaled their own silicon ambitions. ◽️ Sacks sized the duopoly: roughly $60B and $40B in ARR. Anthropic is around ~$60 billion of ARR, OpenAI at ~$40 billion, and no one else generates meaningful model-layer revenue. Sacks's policy line: the US does not ban monopolies, only anti-competitive tactics, but the government should do nothing to make the duopoly more likely. ◽️ The token deflation call: 90% a year for three years. Calacanis predicted token costs fall 90% annually for three years, putting the price of intelligence near free and making it rational to waste tokens on hardware you already own. Friedberg's version is a 70/20/10 split between big cloud, local, and other clouds. ◽️ A wave of platform lock-in spending is already landing. Calacanis flagged Microsoft standing up a roughly $2.5 billion forward-deployed-engineer effort and Amazon spending about $1 billion on the same, plus OpenAI's version. His read: enterprises will slam the door, because letting a provider's engineers study your business is how it ends up in their model. ◽️ The server-per-employee prediction. Calacanis expects every employee to get $10,000 to $20,000 of local compute, a Mac Studio or a high-RAM Dell, running a personal local model that syncs to a thin laptop. A server per person, so nothing leaks. ◽️ On jobs, the data does not show present-tense loss. Sacks cited a RAMP and Revelio Labs study of over 21,000 US firms: the heaviest AI spenders grew headcount about 10% over two years, and entry-level headcount grew even faster at 12%. Friedberg's harder claim: there is no AI job loss yet, only clunky, gradual value creation, and the media will not reverse its narrative because that destroys its credibility. ◽️ The displacement case is real but forward-dated. The counterpoint on the show was that customer support, entry-level data entry and BPO, and driving are the near-term displacements, with Waymo cited as present-tense evidence: in markets where it hits critical mass, Uber and Lyft stop recruiting drivers. Sacks noted most US entry-level support was already offshored, so the acute risk sits in those countries first. ◽️ The human-premium counternarrative. Friedberg argued that as automation spreads, human interaction gets a premium: the skilled bartender, the real driver, the human-in-the-loop tier. He cited the company (referenced as Klarna) that hyped replacing its whole support team with AI, then reversed a year later on brand grounds. ◽️ The export-control episode needed three conditions, and Sacks says do not over-read it. Commerce lifted controls on Anthropic's Fable 5 after two weeks, with Mythos 5 restored to US customers around June 26 once co-founder Tom Brown replaced Dario as lead negotiator. Sacks's three conditions: Dario boasting for months about a cyber weapon, Amazon reporting failed guardrails in testing, and Dario refusing to roll Fable back. His message to allies: this was a particular set of circumstances rather than the debut of a standing lever. ◽️ The import question nobody answered cleanly. Calacanis pressed on why the US blocks Chinese cars and drones but not Chinese open models like DeepSeek and Kimi. Sacks's answer: a forked open model run on US hardware stops being Chinese, and banning open source would isolate the US and impose a token tax on American enterprises, so let the market decide if American open models win. ◽️ The California fiscal story is a business-climate story. Friedberg walked through the numbers behind Newsom's "balanced" $351B budget: expenses exceed revenue and $20-40B is borrowed to close the gap, the budget grew 65% in six years ($215B to $355B), personal income tax is $142B of ~$211B revenue with the top 1% (150,000 people) paying $70B of it, and the corporate rate of 8.9% sits far above Texas at zero. ◽️ The tax base is leaving, and the state is now taxing everyone else. Friedberg cited 1 to 1.5% of adjusted gross income leaving each year (about 15% over a decade), at least 15 Fortune 500 HQs and ~2,100 firms gone since 2019, and a new 8% software sales tax hitting Word, Gmail, and ChatGPT subscriptions plus a health-insurance tax, on top of a now-permanent 14.4% top bracket. The liabilities behind it run $1.4T in debt, up to $1.5T in unfunded pensions senior to state bonds, and ~$40B/year in out-year deficits. Lastly, the line that framed the whole show: "You can't rent intelligence from the same place that rents it to your competitor." That is the sovereignty thesis in one sentence, and every number in this episode is an argument for it. ____ Follow Fireside Alpha for more summaries on key business and technology conversations.$

The July 4th weekend All-In The All-In Podcast turned into a long argument about who owns the intelligence layer. The besties think enterprises just woke up to a trap they had been walking into, here's how the conversation went (save this): ◽️ The Palantir-Nvidia deal is a bet against the model-layer duopoly. Palantir will use Nvidia's Nemotron open models to build a custom frontier-quality model for US government agencies, and the agencies own the hardware, the data, and the weights. Sacks framed it as structural: an application company and a chip company both want a competitive model layer, so they are natural partners against a two-provider middle. ◽️ Alex Karp's CNBC "crashout" was actually the thesis. Karp argued enterprises have lost trust in the frontier labs and want to own their compute, models, data, and alpha. Sacks translated it as a new definition of enterprise AI safety: safety means the model provider cannot hoover up your proprietary knowledge and turn it into its next product. ◽️ Figma is the cautionary tale that made it real. Anthropic launched Claude Design into Figma's category, its chief product officer sat on Figma's board and resigned only 3 days before launch, and Figma's stock is down about 50% this year while Anthropic's valuation surged. Sacks listed Claude Science, Security, Legal, Financial, and Code as the same move: dominate the model layer, then take the lucrative verticals. ◽️ The playbook has a name, and it is Microsoft and Google. Sacks argued Anthropic is running the operating-system strategy: own the layer everyone builds on, then walk up the stack. His Google receipt is that fewer than half of searches now send you off-site, versus an early Google that prided itself on how fast it kicked you away. ◽️ The BCG number is what raises the stakes. Chamath cited a BCG return-on-capital-employed study: the cost of capital is back to its long-run 8 to 11%, and half of large US companies cannot earn returns above it. If you are already teetering on your cost of capital, handing your alpha to a provider that may compete with you is not a luxury risk, it is fatal. ◽️ The 16.4x number is the whole argument in one data point. Chamath ran a code-migration task through 8090's harness. Wrapping Claude was 1.4x cheaper and 1.5x faster than Claude Opus alone. Wrapping the best open-source model was 16.4x cheaper, at about 3x slower. For a background task, three extra hours to cut cost by 16x is not a close call. ◽️ Even at 100x cheaper, enterprises were saying no for the wrong reason. Chamath relayed an ex-Meta PM's point that companies reject open models over China and safety fears, when they could host those same open weights on their own GPUs in US data centers with nothing flowing back. The safety objection, she argued, is backwards: the leak is the data you hand the frontier labs. ◽️ Friedberg says the frontier labs are trying to commoditize their own customers. Anthropic has been signing up life-sciences companies to feed a new life-focused model in exchange for early access, and nearly everyone he has talked to now refuses, recognizing that data they spent billions generating becomes worthless once it is pooled with everyone else's. ◽️ The deployment topology is shifting from big hubs to distributed spokes. Friedberg's map: the old assumption was a few capital-advantaged mega-clusters plus inference clouds. The new one is large hubs, medium hubs (enterprise training clusters), and distributed spokes, including on-prem inference in your own building. Owning your weights is the point. ◽️ Chamath's endgame is running GLM himself. An industry contact told him that with harness post-training and telemetry, an open Chinese model like GLM could get as good as Anthropic's Mythos. His conclusion: take GLM, control it soup-to-nuts on US hardware with only US citizens touching it, and pay a fraction. ◽️ The Apple analogy sharpens why renting intelligence is different from renting distribution. Chamath argued Apple is the only platform that respected developers, deliberately keeping its stock apps basic to protect the ecosystem and collect its 30% tax. There is no 30% tax on open models, and worse, you cannot rent intelligence from the same place that rents it to your competitor without ending up identical to them. ◽️ Nvidia's open model is now good enough to matter. Calacanis claimed you cannot tell Jensen Huang's Nemotron from Claude on 95% of searches, and that Nvidia downplayed the model until now to avoid alarming its top customers. The gloves came off once OpenAI, Anthropic, and Elon all signaled their own silicon ambitions. ◽️ Sacks sized the duopoly: roughly $60B and $40B in ARR. Anthropic is around ~$60 billion of ARR, OpenAI at ~$40 billion, and no one else generates meaningful model-layer revenue. Sacks's policy line: the US does not ban monopolies, only anti-competitive tactics, but the government should do nothing to make the duopoly more likely. ◽️ The token deflation call: 90% a year for three years. Calacanis predicted token costs fall 90% annually for three years, putting the price of intelligence near free and making it rational to waste tokens on hardware you already own. Friedberg's version is a 70/20/10 split between big cloud, local, and other clouds. ◽️ A wave of platform lock-in spending is already landing. Calacanis flagged Microsoft standing up a roughly $2.5 billion forward-deployed-engineer effort and Amazon spending about $1 billion on the same, plus OpenAI's version. His read: enterprises will slam the door, because letting a provider's engineers study your business is how it ends up in their model. ◽️ The server-per-employee prediction. Calacanis expects every employee to get $10,000 to $20,000 of local compute, a Mac Studio or a high-RAM Dell, running a personal local model that syncs to a thin laptop. A server per person, so nothing leaks. ◽️ On jobs, the data does not show present-tense loss. Sacks cited a RAMP and Revelio Labs study of over 21,000 US firms: the heaviest AI spenders grew headcount about 10% over two years, and entry-level headcount grew even faster at 12%. Friedberg's harder claim: there is no AI job loss yet, only clunky, gradual value creation, and the media will not reverse its narrative because that destroys its credibility. ◽️ The displacement case is real but forward-dated. The counterpoint on the show was that customer support, entry-level data entry and BPO, and driving are the near-term displacements, with Waymo cited as present-tense evidence: in markets where it hits critical mass, Uber and Lyft stop recruiting drivers. Sacks noted most US entry-level support was already offshored, so the acute risk sits in those countries first. ◽️ The human-premium counternarrative. Friedberg argued that as automation spreads, human interaction gets a premium: the skilled bartender, the real driver, the human-in-the-loop tier. He cited the company (referenced as Klarna) that hyped replacing its whole support team with AI, then reversed a year later on brand grounds. ◽️ The export-control episode needed three conditions, and Sacks says do not over-read it. Commerce lifted controls on Anthropic's Fable 5 after two weeks, with Mythos 5 restored to US customers around June 26 once co-founder Tom Brown replaced Dario as lead negotiator. Sacks's three conditions: Dario boasting for months about a cyber weapon, Amazon reporting failed guardrails in testing, and Dario refusing to roll Fable back. His message to allies: this was a particular set of circumstances rather than the debut of a standing lever. ◽️ The import question nobody answered cleanly. Calacanis pressed on why the US blocks Chinese cars and drones but not Chinese open models like DeepSeek and Kimi. Sacks's answer: a forked open model run on US hardware stops being Chinese, and banning open source would isolate the US and impose a token tax on American enterprises, so let the market decide if American open models win. ◽️ The California fiscal story is a business-climate story. Friedberg walked through the numbers behind Newsom's "balanced" $351B budget: expenses exceed revenue and $20-40B is borrowed to close the gap, the budget grew 65% in six years ($215B to $355B), personal income tax is $142B of ~$211B revenue with the top 1% (150,000 people) paying $70B of it, and the corporate rate of 8.9% sits far above Texas at zero. ◽️ The tax base is leaving, and the state is now taxing everyone else. Friedberg cited 1 to 1.5% of adjusted gross income leaving each year (about 15% over a decade), at least 15 Fortune 500 HQs and ~2,100 firms gone since 2019, and a new 8% software sales tax hitting Word, Gmail, and ChatGPT subscriptions plus a health-insurance tax, on top of a now-permanent 14.4% top bracket. The liabilities behind it run $1.4T in debt, up to $1.5T in unfunded pensions senior to state bonds, and ~$40B/year in out-year deficits. Lastly, the line that framed the whole show: "You can't rent intelligence from the same place that rents it to your competitor." That is the sovereignty thesis in one sentence, and every number in this episode is an argument for it. ____ Follow Fireside Alpha for more summaries on key business and technology conversations.

Fireside Alpha

55,816 просмотров • 1 месяц назад

"Canada lives because of the United States. Remember that, Mark." 🇺🇸🇨🇦 President Trump just took the stage at Davos and didn’t hold back on Canadian PM Mark Carney. After Carney gave a speech warning the world about, "great power coercion," Trump fired back with a reality check that is sending shockwaves through the North. The "Freebie" Breakdown: Trump’s core argument? Canada is getting a free ride on American security. Specifically, he pointed to: ◽️The "Golden Dome": Trump’s proposed missile defense system. He argued that because of geography, the U.S. will be defending Canada by default—and they aren't paying a dime for it. 🛡️ ◽️The Gratitude Gap: Trump called out Carney directly: "I watched your prime minister yesterday. He wasn't so grateful... Canada gets a lot of freebies from us." ◽️The Ultimate Leverage: By reminding Carney that "Canada lives because of the US," Trump is setting the stage for the most aggressive trade negotiations we've ever seen. Patrick Bet-David often says, "If you don't have a seat at the table, you're on the menu." Carney used that exact phrase in his speech, trying to rally "middle powers" against Trump’s influence. But as PBD breaks down, in a world of "rupture," does Canada have the economic or military muscle to actually push back? Or is this just the "Art of the Deal" played out on a global stage? Is this a fair call-out on defense spending, or is Trump's "51st state" rhetoric getting too real for our northern neighbors? #PBD #Trump #MarkCarney #Davos2026 #Economics 👇

"Canada lives because of the United States. Remember that, Mark." 🇺🇸🇨🇦 President Trump just took the stage at Davos and didn’t hold back on Canadian PM Mark Carney. After Carney gave a speech warning the world about, "great power coercion," Trump fired back with a reality check that is sending shockwaves through the North. The "Freebie" Breakdown: Trump’s core argument? Canada is getting a free ride on American security. Specifically, he pointed to: ◽️The "Golden Dome": Trump’s proposed missile defense system. He argued that because of geography, the U.S. will be defending Canada by default—and they aren't paying a dime for it. 🛡️ ◽️The Gratitude Gap: Trump called out Carney directly: "I watched your prime minister yesterday. He wasn't so grateful... Canada gets a lot of freebies from us." ◽️The Ultimate Leverage: By reminding Carney that "Canada lives because of the US," Trump is setting the stage for the most aggressive trade negotiations we've ever seen. Patrick Bet-David often says, "If you don't have a seat at the table, you're on the menu." Carney used that exact phrase in his speech, trying to rally "middle powers" against Trump’s influence. But as PBD breaks down, in a world of "rupture," does Canada have the economic or military muscle to actually push back? Or is this just the "Art of the Deal" played out on a global stage? Is this a fair call-out on defense spending, or is Trump's "51st state" rhetoric getting too real for our northern neighbors? #PBD #Trump #MarkCarney #Davos2026 #Economics 👇

Jason American Patriot™

73,779 просмотров • 7 месяцев назад