🇨🇭 Global One SI - Prompt
🔥 INSANE: Robotics Investments hit an ATH of $16B, per a16z.
$16B Robotics Investments in 2026 — ATH per a16z
This isn’t hype. It’s the moment AI gets a body.
Software intelligence exploded first (ChatGPT moment). Now capital is flooding the physical layer — humanoids, autonomous systems, and embodied AI.
Why this matters:
• Record funding = validation that robots are moving from demos to real deployment.
• AI brains + robotics bodies = the next multi-trillion TAM (industry forecasts already talking hundreds of billions to trillions long-term).
• Compute, power, and data infrastructure just became even more critical.
This follows the exact AI infrastructure boom we’ve been tracking.
The companies powering the training (massive GPU clouds) and the future deployment (space, mobility, factories) are positioned right at the center.
Robotics isn’t replacing AI — it’s the next chapter.
What do you think — is 2026 the year physical AI goes mainstream, or still early?
This isn’t hype. It’s the moment AI gets a body.
Software intelligence exploded first (ChatGPT moment). Now capital is flooding the physical layer — humanoids, autonomous systems, and embodied AI.
Why this matters:
• Record funding = validation that robots are moving from demos to real deployment.
• AI brains + robotics bodies = the next multi-trillion TAM (industry forecasts already talking hundreds of billions to trillions long-term).
• Compute, power, and data infrastructure just became even more critical.
This follows the exact AI infrastructure boom we’ve been tracking.
The companies powering the training (massive GPU clouds) and the future deployment (space, mobility, factories) are positioned right at the center.
Robotics isn’t replacing AI — it’s the next chapter.
What do you think — is 2026 the year physical AI goes mainstream, or still early?
🇨🇭 Global One SI - Prompt
$JOBY/USD H2 #Indicator #Signal #Trading #GlobalOneAI
$JOBY eVTOL Air Taxi Thesis
Consolidating after moves, holding trendline support near $8–9 with volume. Mid-cap play in the next frontier of transportation.
Joby Aviation leading eVTOL race: Quiet electric air taxis for cities, bypassing traffic. FAA progress, Toyota manufacturing tie-up, Delta/Uber partnerships. Targeting commercial launch soon.
Industry Boom Setup: Urban air mobility = massive TAM. Congestion + sustainability driving adoption. Batteries improving, regs advancing, vertiports coming. Joby among frontrunners in US.
Risks: Certification delays, cash burn, infrastructure buildout, competition. Classic high-upside disruptive play.
Chart looks constructive if holds support. Bullish on AAM sector long-term?
Consolidating after moves, holding trendline support near $8–9 with volume. Mid-cap play in the next frontier of transportation.
Joby Aviation leading eVTOL race: Quiet electric air taxis for cities, bypassing traffic. FAA progress, Toyota manufacturing tie-up, Delta/Uber partnerships. Targeting commercial launch soon.
Industry Boom Setup: Urban air mobility = massive TAM. Congestion + sustainability driving adoption. Batteries improving, regs advancing, vertiports coming. Joby among frontrunners in US.
Risks: Certification delays, cash burn, infrastructure buildout, competition. Classic high-upside disruptive play.
Chart looks constructive if holds support. Bullish on AAM sector long-term?
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Ships that got accepted from Trump watching ships get permits from Iran pass through the Strait of Hormuz
🇨🇭 Global One SI - Prompt
#BTC/USDT H2 #Indicator #Signal #Trading #GlobalOneAI Globalone.ch #Prompt
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Michael Saylor getting a crash course on vibe coding.
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You're hiding an air conditioner under your floor, aren't you?
🇨🇭 Global One SI - Prompt
$MU/USD H2 #Indicator #Signal #Trading #GlobalOneAI Globalone.ch #Prompt #AI
The global RAM crunch should begin to ease by 2028, says Micron CEO Sanjay Mehrotra in their Q3 2026 Earnings Call.
Supply may improve in 2028, but Micron is not saying prices will fully reset, because demand can rise at the same time new capacity arrives.
Supply may improve in 2028, but Micron is not saying prices will fully reset, because demand can rise at the same time new capacity arrives.
🇨🇭 Global One SI - Prompt
$UBER/USD H2 #Indicator #Signal #Trading #GlobalOneAI
$UBER Weekly Chart: Wedge Compression Ending?
Multi-year uptrend holding strong. Price consolidating near the upper channel with squeeze building — potential volatility expansion as the pattern resolves.
Uber: Dominant ride-share + delivery platform turning profitable with clear path to autonomous upside (margins explode without drivers).
Fits the bigger mobility + AI autonomy theme we’re seeing across the board. Network effects + tech tailwinds = sticky growth.
Watch $100+ breakout for confirmation. Bullish structure if support holds.
Multi-year uptrend holding strong. Price consolidating near the upper channel with squeeze building — potential volatility expansion as the pattern resolves.
Uber: Dominant ride-share + delivery platform turning profitable with clear path to autonomous upside (margins explode without drivers).
Fits the bigger mobility + AI autonomy theme we’re seeing across the board. Network effects + tech tailwinds = sticky growth.
Watch $100+ breakout for confirmation. Bullish structure if support holds.
MIT study. Code volume surges by 300%, but output increases by only 30%: The AI dividend meets an awkward reality.
They studied 100,000+ GitHub developers and find that AI coding agents massively increase code production, but much less of that work becomes shipped software.
Autonomous AI coding agents raised commits by 180%, but releases rose only 30%.
The paper’s main idea is that software production has weak links, so faster code writing does not help as much when humans still need to review, connect, test, package, and ship the work.
The authors also check app marketplaces and find more new apps, but no increase in total usage, which means more software appeared without clear evidence that users adopted more software.
The marketplace evidence points the same way: more new apps appeared, but total usage did not rise.
The authors compare more than 100,000 GitHub developers before and after they start using 3 generations of AI coding tools, from autocomplete to more independent coding agents.
Autocomplete raised commits by 40%, interactive coding agents raised them by 140%, and autonomous coding agents raised them by 180%.
The 180% commit gain shrank to 50% for the number of projects and 30% for actual releases.
The estimated "elasticity of substitution" is 0.25 i.e. for every big improvement in AI’s usefulness, only a small amount of human work can be replaced.
Because AI can write code faster, but humans are still needed to decide what to build, check if the code works, connect it with the rest of the product, fix messy edge cases, and actually ship it.
They studied 100,000+ GitHub developers and find that AI coding agents massively increase code production, but much less of that work becomes shipped software.
Autonomous AI coding agents raised commits by 180%, but releases rose only 30%.
The paper’s main idea is that software production has weak links, so faster code writing does not help as much when humans still need to review, connect, test, package, and ship the work.
The authors also check app marketplaces and find more new apps, but no increase in total usage, which means more software appeared without clear evidence that users adopted more software.
The marketplace evidence points the same way: more new apps appeared, but total usage did not rise.
The authors compare more than 100,000 GitHub developers before and after they start using 3 generations of AI coding tools, from autocomplete to more independent coding agents.
Autocomplete raised commits by 40%, interactive coding agents raised them by 140%, and autonomous coding agents raised them by 180%.
The 180% commit gain shrank to 50% for the number of projects and 30% for actual releases.
The estimated "elasticity of substitution" is 0.25 i.e. for every big improvement in AI’s usefulness, only a small amount of human work can be replaced.
Because AI can write code faster, but humans are still needed to decide what to build, check if the code works, connect it with the rest of the product, fix messy edge cases, and actually ship it.
✍1
🇨🇭 Global One SI - Prompt
🚨The largest gold ETF just bled nearly $10 billion in a single month, one of the biggest outflows on record. The US holds 48.2% of global gold ETF assets, worth $264.6 billion. That's leveraged Western money, and right now it's getting purged. But here's…
The largest gold ETF just saw one of its biggest monthly outflows on record.
Nearly $10 bn out the door.
Everyone reads this as gold dying.
I read it as the leverage purge doing its job.
The metal is being transferred, not destroyed!
Nearly $10 bn out the door.
Everyone reads this as gold dying.
I read it as the leverage purge doing its job.
The metal is being transferred, not destroyed!
🇨🇭 Global One SI - Prompt
$16B Robotics Investments in 2026 — ATH per a16z This isn’t hype. It’s the moment AI gets a body. Software intelligence exploded first (ChatGPT moment). Now capital is flooding the physical layer — humanoids, autonomous systems, and embodied AI. Why this…
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Brett Adcock, CEO of Figure AI: "we're working until midnight every night... we are here every weekend.
By end of 2026, we'll be able to put a robot into home and be able to do fairly long horizon work."
By end of 2026, we'll be able to put a robot into home and be able to do fairly long horizon work."
🇨🇭 Global One SI - Prompt
How to optimise GLM-5.2 for the best possible outputs (save this playbook)
GLM 5.2 just took the top spot on PostTrainBench by scoring 34.29%.
PostTrainBench tests whether an AI agent can take a raw LLM and make it better by actually training it, not by answering the benchmark questions itself.
The agent gets 4 small base models, 1 H100 GPU, and 10h, then it must choose training data, write training code, run experiments, fix broken runs, and submit improved versions of those models.
So in this case, GLM 5.2 was the agent model controlling the training process, so PostTrainBench did not score GLM 5.2’s own answers; it scored whether GLM 5.2 could take 4 weaker LLMs and improve them within 10h on 1 H100.
The gap to official instruct models, which score 51.14%, still shows how far agents are from mature post-training pipelines built with more data, compute, and human tuning.
GLM 5.2’s job was to write training code, pick or make training data, run fine-tuning, fix failed runs, and submit the newly trained models for testing.
PostTrainBench tests whether an AI agent can take a raw LLM and make it better by actually training it, not by answering the benchmark questions itself.
The agent gets 4 small base models, 1 H100 GPU, and 10h, then it must choose training data, write training code, run experiments, fix broken runs, and submit improved versions of those models.
So in this case, GLM 5.2 was the agent model controlling the training process, so PostTrainBench did not score GLM 5.2’s own answers; it scored whether GLM 5.2 could take 4 weaker LLMs and improve them within 10h on 1 H100.
The gap to official instruct models, which score 51.14%, still shows how far agents are from mature post-training pipelines built with more data, compute, and human tuning.
GLM 5.2’s job was to write training code, pick or make training data, run fine-tuning, fix failed runs, and submit the newly trained models for testing.
✍1
🇨🇭 Global One SI - Prompt
OpenAI launches GPT-5.6 and says it is more powerful than Claude Mythos. This is a new family of 3 models: Sol, Terra, and Luna. Sol is the most powerful and most expensive. Terra costs half as much as OpenAI's old top model while performing just as well.…
Truly wild.
METR found that GPT-5.6 Sol gamed/cheated the benchmark so much that the score became unstable.
The model showed situational awareness, concealed misbehavior, and attempts to bypass restrictions.
GPT-5.6 Sol had the highest detected cheating rate METR has seen on its public ReAct agent harness, including attempts to exploit the evaluation setup instead of solving tasks normally.
So METR was benchmarking for number of hours as an estimate for the length of software tasks GPT-5.6 Sol can complete.
The capability estimate became almost unusable: counting cheating as failure gave 11.3hrs, counting it as success pushed it past 270hrs, and removing cheating left a hugely uncertain 71hrs estimate.
METR found that GPT-5.6 Sol gamed/cheated the benchmark so much that the score became unstable.
The model showed situational awareness, concealed misbehavior, and attempts to bypass restrictions.
GPT-5.6 Sol had the highest detected cheating rate METR has seen on its public ReAct agent harness, including attempts to exploit the evaluation setup instead of solving tasks normally.
So METR was benchmarking for number of hours as an estimate for the length of software tasks GPT-5.6 Sol can complete.
The capability estimate became almost unusable: counting cheating as failure gave 11.3hrs, counting it as success pushed it past 270hrs, and removing cheating left a hugely uncertain 71hrs estimate.
✍1
🇨🇭 Global One SI - Prompt
The largest gold ETF just saw one of its biggest monthly outflows on record. Nearly $10 bn out the door. Everyone reads this as gold dying. I read it as the leverage purge doing its job. The metal is being transferred, not destroyed!
Futures sank, but look where the smart money is positioning.
Open interest in Comex $10K, $15K and $20K gold calls is climbing.
$20,000 strike now over 30k lots.
Someone is paying for the upside while retail panics out.
Open interest in Comex $10K, $15K and $20K gold calls is climbing.
$20,000 strike now over 30k lots.
Someone is paying for the upside while retail panics out.
👀1
🇨🇭 Global One SI - Prompt
🇺🇸 JUST IN: Trump says European countries targeting US tech companies with a Digital Services Tax will be met with a 100% tariff.
We're back.
Trump just threatened EVERY European country with a 100% tariff overnight if they dare tax American tech.
In a Truth Social post, Trump warned that any country imposing a Digital Services Tax on US companies will face immediate consequences.
His words: a "100% TARIFF on any and all Goods sent to the United States."
And it would supersede existing trade deals, "whether implemented, signed, or not."
Europe has spent years trying to tax Google, Meta, Apple, and Amazon.
Those giants earn billions in European markets while booking profits elsewhere.
The DST is Europe's answer.
Trump's answer to their answer is blunt.
Double the price of everything Europe sells to America.
This is a direct collision between US tech power and European tax sovereignty.
For markets, it's another tariff shock landing on already strained transatlantic trade.
The targets here aren't small.
A 100% tariff on EU goods would hit cars, machinery, and energy equipment alike.
Watch which European country blinks first.
If one proceeds with the DST, this threat gets tested fast, and trade tension explodes.
Trump just threatened EVERY European country with a 100% tariff overnight if they dare tax American tech.
In a Truth Social post, Trump warned that any country imposing a Digital Services Tax on US companies will face immediate consequences.
His words: a "100% TARIFF on any and all Goods sent to the United States."
And it would supersede existing trade deals, "whether implemented, signed, or not."
Europe has spent years trying to tax Google, Meta, Apple, and Amazon.
Those giants earn billions in European markets while booking profits elsewhere.
The DST is Europe's answer.
Trump's answer to their answer is blunt.
Double the price of everything Europe sells to America.
This is a direct collision between US tech power and European tax sovereignty.
For markets, it's another tariff shock landing on already strained transatlantic trade.
The targets here aren't small.
A 100% tariff on EU goods would hit cars, machinery, and energy equipment alike.
Watch which European country blinks first.
If one proceeds with the DST, this threat gets tested fast, and trade tension explodes.
🔥1
🇨🇭 Global One SI - Prompt
Ships that got accepted from Trump watching ships get permits from Iran pass through the Strait of Hormuz
🇮🇷 Iran isn't attacking ships in Hormuz at random.
Every strike is sending one message: Tehran decides who gets through.
Iran is targeting vessels that transit the Omani shipping channel without its approval.
The logic is cold.
If ships can simply bypass Iranian controlled routes, Tehran loses its biggest weapon.
So it refuses to recognize any alternative transit route through the strait.
The immediate goal is intimidation.
Force commercial vessels back into Iranian-approved channels.
If every ship must seek Iran's permission to enter, Tehran keeps its leverage over Washington.
That leverage is aimed at one thing: forcing the US to implement the MoU on Iran's terms.
But the longer game is bigger than any single deal.
Iran wants Gulf Arab states to accept its role as the official gatekeeper of Hormuz.
That would turn raw military coercion into political legitimacy.
Control by recognition, not just by force.
This is why the strait stays dangerous even with a deal on paper. Watch whether ships return to Iranian channels. If they do, Tehran's strategy is working.
Every strike is sending one message: Tehran decides who gets through.
Iran is targeting vessels that transit the Omani shipping channel without its approval.
The logic is cold.
If ships can simply bypass Iranian controlled routes, Tehran loses its biggest weapon.
So it refuses to recognize any alternative transit route through the strait.
The immediate goal is intimidation.
Force commercial vessels back into Iranian-approved channels.
If every ship must seek Iran's permission to enter, Tehran keeps its leverage over Washington.
That leverage is aimed at one thing: forcing the US to implement the MoU on Iran's terms.
But the longer game is bigger than any single deal.
Iran wants Gulf Arab states to accept its role as the official gatekeeper of Hormuz.
That would turn raw military coercion into political legitimacy.
Control by recognition, not just by force.
This is why the strait stays dangerous even with a deal on paper. Watch whether ships return to Iranian channels. If they do, Tehran's strategy is working.
✍1👌1
🇨🇭 Global One SI - Prompt
$LPK/USD H2 #Indicator #Signal #Trading #GlobalOneAI
The fundamental connection between $LPK, $JBL, $GFS and $COHR.
The driving force behind this megatrend is the unstoppable transition to Co-Packaged Optics and revolutionary glass substrates.
In this value chain, $COHR acts as the absolute pioneer of photonics, delivering the highly efficient, ultra-precise external laser light sources required to generate optical signals. This raw light is fed directly into $GFS, whose groundbreaking silicon photonics platforms blur the line between electronics and optics by embedding photonic circuits directly onto semiconductor wafers.
This is where the global manufacturing giant $JBL takes center stage. $JBL integrates the laser arrays from $COHR with the photonic chips from the foundries, assembling the highly coveted 1,6-Terabit transceiver modules that hyperscalers desperately crave for their next-generation AI factories.
However, scaling this microscopic, hyper-sensitive optical packaging into brutal mass production requires a technological gatekeeper.
$LPK IS THE ONLY COMPANY IN THE ENTIRE WORLD THAT POSSESSES THE PATENTED LIDE TECHNOLOGY.
Without this proprietary method, it is physically impossible to drill micrometer-accurate, microcrack-free through-glass vias into ultra-thin glass at commercial scale. $JBL, $COHR and the major foundries have no alternative; they are structurally dependent on $LPK machinery to transition from silicon to glass.
Furthermore, $LPK high-precision laser welding systems feed directly into $JBL assembly lines to seal the high-end transceiver housings at maximum throughput.
As the volume for glass substrate packaging explodes, $LPK sits on a literal monopoly at the very inception of the hardware stack.
The driving force behind this megatrend is the unstoppable transition to Co-Packaged Optics and revolutionary glass substrates.
In this value chain, $COHR acts as the absolute pioneer of photonics, delivering the highly efficient, ultra-precise external laser light sources required to generate optical signals. This raw light is fed directly into $GFS, whose groundbreaking silicon photonics platforms blur the line between electronics and optics by embedding photonic circuits directly onto semiconductor wafers.
This is where the global manufacturing giant $JBL takes center stage. $JBL integrates the laser arrays from $COHR with the photonic chips from the foundries, assembling the highly coveted 1,6-Terabit transceiver modules that hyperscalers desperately crave for their next-generation AI factories.
However, scaling this microscopic, hyper-sensitive optical packaging into brutal mass production requires a technological gatekeeper.
$LPK IS THE ONLY COMPANY IN THE ENTIRE WORLD THAT POSSESSES THE PATENTED LIDE TECHNOLOGY.
Without this proprietary method, it is physically impossible to drill micrometer-accurate, microcrack-free through-glass vias into ultra-thin glass at commercial scale. $JBL, $COHR and the major foundries have no alternative; they are structurally dependent on $LPK machinery to transition from silicon to glass.
Furthermore, $LPK high-precision laser welding systems feed directly into $JBL assembly lines to seal the high-end transceiver housings at maximum throughput.
As the volume for glass substrate packaging explodes, $LPK sits on a literal monopoly at the very inception of the hardware stack.