π¨π Global One SI - Prompt
π¨BREAKING: TRUMP ON ANTHROPIC REPORTER: Do you view Anthropic and to a degree its CEO, Dario Amodei, as a threat to national security? TRUMP: "Well, not now, but a week ago, maybe. I was with him yesterday, he made a speech... seemed like a nice guy, smartβ¦
FABLE 5 might soon be out of custody?
This media is not supported in your browser
VIEW IN TELEGRAM
βSuccess requires massive action.β
- Jim Rohn.
- Jim Rohn.
πΏ1
π¨π Global One SI - Prompt
$SIVE/USD H2 #Indicator #Signal #Trading #GlobalOneAI
The market is currently looking at $SIVE through a very narrow lens, completely missing how the company is embedding itself into the multi-billion-dollar geopolitical space race.
While short-term noise dominates retail trading forums, a massive structural catalyst is quietly playing out through Europe's sovereign satellite mega-constellation, IRISΒ².
When the European Union realized that its critical communication and defense infrastructure was entirely dependent on foreign commercial entities like Elon Musk's Starlink, it launched IRISΒ² to guarantee European digital autonomy.
While mainstream headlines focus heavily on the aerospace giants building the actual satellites, smart capital looks at the critical hardware bottlenecks on the ground.
A satellite constellation is useless without millions of high-performance ground terminals to connect to it.
This is exactly where $SIVE holds an unappreciated technological and regional monopoly.
Because of the strict European mandate for strategic sovereignty, the core technology powering this network cannot be outsourced to American or Asian foundries.
Sivers is effectively the only commercial merchant silicon vendor within European borders capable of delivering the high-frequency beamforming chips required for these tactical satellite terminals.
The definitive evidence of their moat is hidden in their recent corporate disclosures.
Multiple tier-one terminal manufacturers bidding for the massive EU volume contracts have already integrated $SIVE silicon into their official prototype designs.
In the semiconductor industry, once a proprietary chip is baked into the fundamental architecture of a hardware prototype, the technical switching costs are too high for a client to pivot.
This means $SIVE has effectively hedged its bets.
No matter which of these manufacturing giants wins the final European Union contracts, $SIVE secures the volume production orders.
The European Space Agency recognized this strategic value early on, which is why they are actively subsidizing $SIVE next-generation phased-array research and development.
This goes far beyond standard commercial tech hype. $SIVE is quietly building Western geopolitical infrastructure.
While short-term noise dominates retail trading forums, a massive structural catalyst is quietly playing out through Europe's sovereign satellite mega-constellation, IRISΒ².
When the European Union realized that its critical communication and defense infrastructure was entirely dependent on foreign commercial entities like Elon Musk's Starlink, it launched IRISΒ² to guarantee European digital autonomy.
While mainstream headlines focus heavily on the aerospace giants building the actual satellites, smart capital looks at the critical hardware bottlenecks on the ground.
A satellite constellation is useless without millions of high-performance ground terminals to connect to it.
This is exactly where $SIVE holds an unappreciated technological and regional monopoly.
Because of the strict European mandate for strategic sovereignty, the core technology powering this network cannot be outsourced to American or Asian foundries.
Sivers is effectively the only commercial merchant silicon vendor within European borders capable of delivering the high-frequency beamforming chips required for these tactical satellite terminals.
The definitive evidence of their moat is hidden in their recent corporate disclosures.
Multiple tier-one terminal manufacturers bidding for the massive EU volume contracts have already integrated $SIVE silicon into their official prototype designs.
In the semiconductor industry, once a proprietary chip is baked into the fundamental architecture of a hardware prototype, the technical switching costs are too high for a client to pivot.
This means $SIVE has effectively hedged its bets.
No matter which of these manufacturing giants wins the final European Union contracts, $SIVE secures the volume production orders.
The European Space Agency recognized this strategic value early on, which is why they are actively subsidizing $SIVE next-generation phased-array research and development.
This goes far beyond standard commercial tech hype. $SIVE is quietly building Western geopolitical infrastructure.
π¨π Global One SI - Prompt
API prices of key AI models: US vs China
THIS IS ABSOLUTELY INSANE.
A company's AI bill jumped 700% in a single day because Anthropic changed how it charged for AI usage.
Workato had been paying one flat monthly fee to use Anthropic's AI. In May, Anthropic moved them to pay per token pricing, where every single prompt costs real money. The bill went up 7 times overnight.
Its own CIO said AI companies had been subsidizing usage for years just to get everyone hooked, and the moment that stopped, the real cost hit all at once.
This is happening everywhere right now, not just at one company.
Amazon, Walmart, Cisco, Uber, and Meta are all now capping how much AI their own employees can use.
These are the exact companies that spent the last two years forcing AI onto every employee as fast as possible.
Uber burned through its entire 2026 AI budget by April and now caps employees at $1,500 a month.
Amazon told staff to stop using AI "just for the sake of using it" after engineers were caught running agents just to climb internal leaderboards.
JPMorgan published an internal note this month titled "AI Bills Are Out of Control." Some JPMorgan employees are reportedly spending more on AI every month than their own salary.
Here is why this is not just a cost story inside a few companies.
It is a direct threat to two trillion-dollar IPOs.
OpenAI and Anthropic both filed confidentially for IPOs this month, both targeting valuations near $850 billion or higher, and neither company is profitable. OpenAI reportedly loses $1.22 for every dollar of revenue it makes.
OpenAI's losses tell the same story from a different angle. In 2024, OpenAI lost $5.09 billion. In 2025, that loss grew to $38.5 billion, nearly 8 times higher in a single year. Costs are growing faster than revenue at exactly the moment OpenAI needs Wall Street to believe the opposite is happening.
Their entire pitch to public investors is that enterprise spending keeps climbing. The exact backlash forcing Amazon and Uber to cut back is happening at the precise moment both companies need Wall Street to believe the opposite.
OpenAI already sees the danger. The Wall Street Journal reported this week that OpenAI is weighing steep token price cuts specifically to stop losing customers to Anthropic, whose Claude Code product helped its revenue jump from $9 billion to $47 billion annualized in five months.
But cutting prices only works until someone undercuts you.
Artificial Analysis benchmarked every major AI model on identical tasks and tracked the total cost. Anthropic's flagship model cost $4,811 to run the full test.
OpenAI's cost $3,357. China's DeepSeek cost $1,071. Another Chinese model, Kimi, cost $948. China is not trying to match American AI on quality. It is making premium priced AI look completely unnecessary.
Bain surveyed nearly 1,000 companies on AI returns. 40% said their actual cost savings came in below 10%, despite everything they spent.
One investor told Axios that a CFO accidentally spent half a billion dollars on Claude in a single month before anyone even noticed.
OpenAI and Anthropic are about to ask public markets to value them like the future of software itself.
Their own biggest customers are proving in real time that they will not pay whatever it costs to get there.
A company's AI bill jumped 700% in a single day because Anthropic changed how it charged for AI usage.
Workato had been paying one flat monthly fee to use Anthropic's AI. In May, Anthropic moved them to pay per token pricing, where every single prompt costs real money. The bill went up 7 times overnight.
Its own CIO said AI companies had been subsidizing usage for years just to get everyone hooked, and the moment that stopped, the real cost hit all at once.
This is happening everywhere right now, not just at one company.
Amazon, Walmart, Cisco, Uber, and Meta are all now capping how much AI their own employees can use.
These are the exact companies that spent the last two years forcing AI onto every employee as fast as possible.
Uber burned through its entire 2026 AI budget by April and now caps employees at $1,500 a month.
Amazon told staff to stop using AI "just for the sake of using it" after engineers were caught running agents just to climb internal leaderboards.
JPMorgan published an internal note this month titled "AI Bills Are Out of Control." Some JPMorgan employees are reportedly spending more on AI every month than their own salary.
Here is why this is not just a cost story inside a few companies.
It is a direct threat to two trillion-dollar IPOs.
OpenAI and Anthropic both filed confidentially for IPOs this month, both targeting valuations near $850 billion or higher, and neither company is profitable. OpenAI reportedly loses $1.22 for every dollar of revenue it makes.
OpenAI's losses tell the same story from a different angle. In 2024, OpenAI lost $5.09 billion. In 2025, that loss grew to $38.5 billion, nearly 8 times higher in a single year. Costs are growing faster than revenue at exactly the moment OpenAI needs Wall Street to believe the opposite is happening.
Their entire pitch to public investors is that enterprise spending keeps climbing. The exact backlash forcing Amazon and Uber to cut back is happening at the precise moment both companies need Wall Street to believe the opposite.
OpenAI already sees the danger. The Wall Street Journal reported this week that OpenAI is weighing steep token price cuts specifically to stop losing customers to Anthropic, whose Claude Code product helped its revenue jump from $9 billion to $47 billion annualized in five months.
But cutting prices only works until someone undercuts you.
Artificial Analysis benchmarked every major AI model on identical tasks and tracked the total cost. Anthropic's flagship model cost $4,811 to run the full test.
OpenAI's cost $3,357. China's DeepSeek cost $1,071. Another Chinese model, Kimi, cost $948. China is not trying to match American AI on quality. It is making premium priced AI look completely unnecessary.
Bain surveyed nearly 1,000 companies on AI returns. 40% said their actual cost savings came in below 10%, despite everything they spent.
One investor told Axios that a CFO accidentally spent half a billion dollars on Claude in a single month before anyone even noticed.
OpenAI and Anthropic are about to ask public markets to value them like the future of software itself.
Their own biggest customers are proving in real time that they will not pay whatever it costs to get there.
π₯1
This media is not supported in your browser
VIEW IN TELEGRAM
You donβt realize just how easy it is to be in the top 10% until you see how lazy 90% of people are
You donβt realize just how hard it is to be in the top 1% until you see how driven the other 10% of people are
You donβt realize just how hard it is to be in the top 1% until you see how driven the other 10% of people are
πΏ1
Focus on these 48 leading names trading above $100M dollar volume β they may outperform what your own watchlist is surfacing.
$KMX β Auto & Truck Dealerships
$GLXY β Capital Markets
$HOOD β Capital Markets
$HUT β Capital Markets
$MARA β Capital Markets
$DELL β Computer Hardware
$SNDK β Computer Hardware
$STX β Computer Hardware
$WDC β Computer Hardware
$AFRM β Credit Services
$BE β Electrical Equipment & Parts
$OUST β Electronic Components
$ROKU β Entertainment
$SSRM β Gold
$TXG β Health Information Services
$APLD β Information Technology Services
$CIFR β Information Technology Services
$KEEL β Information Technology Services
$PENG β Information Technology Services
$W β Internet Retail
$BFLY β Medical Devices
$WRBY β Medical Instruments & Supplies
$SEI β Oil & Gas Equipment & Services
$FRO β Oil & Gas Midstream
$COHR β Scientific & Technical Instruments
$AEHR β Semiconductor Equipment & Materials
$AMKR β Semiconductor Equipment & Materials
$ENTG β Semiconductor Equipment & Materials
$KLAC β Semiconductor Equipment & Materials
$ALAB β Semiconductors
$ALGM β Semiconductors
$ARM β Semiconductors
$CRDO β Semiconductors
$INTC β Semiconductors
$MRVL β Semiconductors
$MU β Semiconductors
$MXL β Semiconductors
$QCOM β Semiconductors
$VSH β Semiconductors
$WOLF β Semiconductors
$KMX β Auto & Truck Dealerships
$GLXY β Capital Markets
$HOOD β Capital Markets
$HUT β Capital Markets
$MARA β Capital Markets
$DELL β Computer Hardware
$SNDK β Computer Hardware
$STX β Computer Hardware
$WDC β Computer Hardware
$AFRM β Credit Services
$BE β Electrical Equipment & Parts
$OUST β Electronic Components
$ROKU β Entertainment
$SSRM β Gold
$TXG β Health Information Services
$APLD β Information Technology Services
$CIFR β Information Technology Services
$KEEL β Information Technology Services
$PENG β Information Technology Services
$W β Internet Retail
$BFLY β Medical Devices
$WRBY β Medical Instruments & Supplies
$SEI β Oil & Gas Equipment & Services
$FRO β Oil & Gas Midstream
$COHR β Scientific & Technical Instruments
$AEHR β Semiconductor Equipment & Materials
$AMKR β Semiconductor Equipment & Materials
$ENTG β Semiconductor Equipment & Materials
$KLAC β Semiconductor Equipment & Materials
$ALAB β Semiconductors
$ALGM β Semiconductors
$ARM β Semiconductors
$CRDO β Semiconductors
$INTC β Semiconductors
$MRVL β Semiconductors
$MU β Semiconductors
$MXL β Semiconductors
$QCOM β Semiconductors
$VSH β Semiconductors
$WOLF β Semiconductors
π¨π Global One SI - Prompt
THIS NUMBER MADE THE REVIEWER GO βWHOAβ ON CAMERA AND IT SHOULD MAKE YOU GO WHOA TOO Mac Mini PP score was 563, Strix Halo came in at 342, and DGX Spark hit 2,170 Thatβs not a small gap, thatβs a completely different category of hardware People were judgingβ¦
Media is too big
VIEW IN TELEGRAM
THIS DEVELOPER CONNECTED 8 NVIDIA DGX SPARKS INTO ONE CLUSTER - AND RAN AN 800GB MODEL THAT MADE HIM 10X MORE PRODUCTIVE
21:47 he says it straight - "this is a terabyte of VRAM - we ran Quen 3.5, 800GB on disk, a model that doesn't even fit on a single Mac Studio - 24 tokens per second - I'd say that's a win"
8 Sparks connected through a $1,300 switch via RDMA over Ethernet - each node adding 128GB of memory into one unified pool of 1TB
started with one Spark at 3 tokens per second - every added node doubled the speed - and eight together deliver 24 tokens on a model that physically cannot run anywhere else
Kimi K2 at 600GB loaded in 15 minutes, 115GB per node, 13 tokens per second - a model that simply cannot run on anything smaller
Claude helped configure the entire cluster - SSH mesh across all 8 machines, network config, jumbo frames, QSFP port speeds - all from one terminal
most people rent cloud compute for models this size at $2,000+/month - he built the cluster once and now every token costs 20x less
21:47 he says it straight - "this is a terabyte of VRAM - we ran Quen 3.5, 800GB on disk, a model that doesn't even fit on a single Mac Studio - 24 tokens per second - I'd say that's a win"
8 Sparks connected through a $1,300 switch via RDMA over Ethernet - each node adding 128GB of memory into one unified pool of 1TB
started with one Spark at 3 tokens per second - every added node doubled the speed - and eight together deliver 24 tokens on a model that physically cannot run anywhere else
Kimi K2 at 600GB loaded in 15 minutes, 115GB per node, 13 tokens per second - a model that simply cannot run on anything smaller
Claude helped configure the entire cluster - SSH mesh across all 8 machines, network config, jumbo frames, QSFP port speeds - all from one terminal
most people rent cloud compute for models this size at $2,000+/month - he built the cluster once and now every token costs 20x less
β1
π¨π Global One SI - Prompt
A developer makes $14k/month from 4 Mac Minis. Together they run 70B+ models locally more than a single Mac Mini could handle. Most people rent cloud GPUs every month. He paid once and built his own AI cluster. Started with one Mac Mini. Then another.β¦
Media is too big
VIEW IN TELEGRAM
THIS DEVELOPER JUST RAN A TRILLION PARAMETER MODEL ON 4 MAC STUDIOS - 10X FASTER AND 5X CHEAPER THAN CLOUD CODE
19:00 he says it out loud. "we just ran a trillion parameter model. 30 something tokens per second. wow."
RDMA over Thunderbolt made the cluster 10x faster than before. tensor parallelism splits the model between machines in parallel instead of sequentially
DeepSeek V3 full size without quantization. 183GB per machine. still 25 tokens per second. faster than most people can read
Kimi K2 with trillion parameters and 256,000 context window. loaded, responded and adapted memory usage dynamically based on prompt size
4 machines consuming 66 watts total. cloud GPU for the same workload costs $1,900/month
a cluster that used to cost millions now assembled from Mac Studios in a few hours
19:00 he says it out loud. "we just ran a trillion parameter model. 30 something tokens per second. wow."
RDMA over Thunderbolt made the cluster 10x faster than before. tensor parallelism splits the model between machines in parallel instead of sequentially
DeepSeek V3 full size without quantization. 183GB per machine. still 25 tokens per second. faster than most people can read
Kimi K2 with trillion parameters and 256,000 context window. loaded, responded and adapted memory usage dynamically based on prompt size
4 machines consuming 66 watts total. cloud GPU for the same workload costs $1,900/month
a cluster that used to cost millions now assembled from Mac Studios in a few hours
β1
π¨π Global One SI - Prompt
Photo
This media is not supported in your browser
VIEW IN TELEGRAM
This founder replaced $1,000/mo in ai subscriptions with $3/mo in electricity.
One simple box under his desk.
All he did: install ollama, pull a model, change one line of code.
Builders will clone it this week.
One simple box under his desk.
All he did: install ollama, pull a model, change one line of code.
Builders will clone it this week.
π₯1
π¨π Global One SI - Prompt
Trump brags new AF1 'luxury not seen even outside a plane' That bed looks perfect for all-night posting
This media is not supported in your browser
VIEW IN TELEGRAM
How does he do it
πΈβοΈ #Qatar's $400βmillion luxury gift becomes #Trumpβs new #AirForceOne π«ποΈ
πΈβοΈ #Qatar's $400βmillion luxury gift becomes #Trumpβs new #AirForceOne π«ποΈ
π―1