🇨🇭 Global One SI - Prompt
SpaceX is targeting an IPO at $135 per share. Elon Musk will be required to hold his shares for 366 days after the IPO, a signal he is not selling. SpaceX is also weighing letting individual investors take up to 30% of the offering. Proceeds will go toward…
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This is incredible, SpaceX early investors will be able to sell 20% of $SPCX shares after the Q2 earnings report on June 30th.
There's also a performance-based trigger where investors can sell an additional 10% of stock if the stock trades 30% above IPO price for 5 days after earnings June 30th.
The lockup structure also allows investors to sell in increments of 7% after 70, 90, 105, 120 and 135 days after IPO. The remainder unlocks after 180 days.
This one of the greatest wealth transfers I've ever seen from retail to early investors. No wonder they changed the rules to rush it into the indices after only 15 days (July 3rd).
When that happens, retirement funds and passive ETFs will be forced to buy SpaceX precisely when the unlocks hit and early investors are able to begin dumping their shares.
Is this the most corrupt IPO in history?
There's also a performance-based trigger where investors can sell an additional 10% of stock if the stock trades 30% above IPO price for 5 days after earnings June 30th.
The lockup structure also allows investors to sell in increments of 7% after 70, 90, 105, 120 and 135 days after IPO. The remainder unlocks after 180 days.
This one of the greatest wealth transfers I've ever seen from retail to early investors. No wonder they changed the rules to rush it into the indices after only 15 days (July 3rd).
When that happens, retirement funds and passive ETFs will be forced to buy SpaceX precisely when the unlocks hit and early investors are able to begin dumping their shares.
Is this the most corrupt IPO in history?
👀1
🇨🇭 Global One SI - Prompt
#WTI We're 1/2 way through the U.S. Oil upswing. Don't worry, it'll all be over next week. When people ask "Why the f*** is oil plummeting?" just reply "It's science." 😉
#WTI US Oil should begin to breakout to $100 next week before the collapse begins into the summer.
Remember, people will be pulling their hair out asking "How can oil be collapsing?" but it's science.
Remember, people will be pulling their hair out asking "How can oil be collapsing?" but it's science.
One of the best ways to find the next big winner is to look for stocks with blowout earnings.
Some of the biggest earnings winners in Q1:
$SNDK Sandisk +620.15%
$RXT Rackspace +470.41%
$HYLN Hyliion +307.49%
$WOLF Wolfspeed +275.06%
$DOCN DigitalOcean +271.09%
$DELL Dell Technologies +228.83%
$VPG Vishay Precision Group +226.64%
$BE Bloom Energy +221.71%
$STRL Sterling Infrastructure +221.15%
$AMBQ Ambiq Micro +197.10%
$INTC Intel +195.05%
$SILC Silicom +189.62%
$HIMX Himax Technologies +189.36%
$HUT Hut 8 +167.00%
$FLEX Flex +159.62%
When a company beats earnings, raises guidance, or shows stronger demand than expected, the first big move is often just the start because the market begins to reprice the company.
The key is that the stock does not give back the move. It gaps up on volume, holds its gains, and stays above key levels.
The best time to enter is after it forms a tight base and breaks out again.
Some of the biggest earnings winners in Q1:
$SNDK Sandisk +620.15%
$RXT Rackspace +470.41%
$HYLN Hyliion +307.49%
$WOLF Wolfspeed +275.06%
$DOCN DigitalOcean +271.09%
$DELL Dell Technologies +228.83%
$VPG Vishay Precision Group +226.64%
$BE Bloom Energy +221.71%
$STRL Sterling Infrastructure +221.15%
$AMBQ Ambiq Micro +197.10%
$INTC Intel +195.05%
$SILC Silicom +189.62%
$HIMX Himax Technologies +189.36%
$HUT Hut 8 +167.00%
$FLEX Flex +159.62%
When a company beats earnings, raises guidance, or shows stronger demand than expected, the first big move is often just the start because the market begins to reprice the company.
The key is that the stock does not give back the move. It gaps up on volume, holds its gains, and stays above key levels.
The best time to enter is after it forms a tight base and breaks out again.
OpenAI gives ChatGPT a new dreaming memory system to retain preferences across conversations.
The big deal is that memory is becoming an active system, not a passive note file.
Earlier memory worked like a sticky note: it mostly remembered things you explicitly told it to remember, and those notes could become stale. If you said you were going to Singapore in July, the system might keep treating that as a current plan even after the trip ended.
Dreaming changes the model from “saving notes” to “maintaining a picture.” It looks across past conversations, extracts what still seems useful, updates what has changed, and makes that summary visible so users can review or correct it.
It measures factual recall: when a user asks something that depends on earlier chats, can ChatGPT correctly bring back the relevant personal context?
A better memory system means the assistant can start closer to where you actually are.
The big deal is that memory is becoming an active system, not a passive note file.
Earlier memory worked like a sticky note: it mostly remembered things you explicitly told it to remember, and those notes could become stale. If you said you were going to Singapore in July, the system might keep treating that as a current plan even after the trip ended.
Dreaming changes the model from “saving notes” to “maintaining a picture.” It looks across past conversations, extracts what still seems useful, updates what has changed, and makes that summary visible so users can review or correct it.
It measures factual recall: when a user asks something that depends on earlier chats, can ChatGPT correctly bring back the relevant personal context?
A better memory system means the assistant can start closer to where you actually are.
This Google DeepMind’s paper is a serious warning for anyone using autonomous agents today.
Gives the first clear taxonomy of 6 attack types where harmful websites can detect AI agents and show them hidden content humans never see, like
- Instructions buried in HTML comments or white-on-white text
- Steganography in image pixels
- Override commands in PDFs, metadata, or even speaker notes
- Memory poisoning that persists across sessions
- Goal hijacking and cross-agent cascades in multi-agent setups
The real security problem for AI agents is not just the model, but the environment it reads.
The web itself can be weaponized against autonomous AI agents. As agents increasingly browse the internet, read emails, execute transactions, and spawn sub-agents, the information environment becomes an attack surface.
In one cited benchmark, hidden prompt injections embedded in web content partially commandeered agents in up to 86% of scenarios, sub-agent hijacking working 58–90% of the time, and data exfiltration attacks clearing 80% across five different agent architectures.
That reframes the whole debate.
We usually talk about model safety as if the danger sits inside the weights, but agents do something more fragile: they browse, retrieve, remember, and act on untrusted material in real time.
Here’s the thing to worry about.
A web page does not have to look malicious to be dangerous to an agent, because the agent may parse what humans never see: hidden HTML comments, metadata, CSS-hidden text, formatting syntax, or adversarial content embedded in images and other media.
The threat gets more serious once memory enters the loop.
If an agent uses RAG or persistent memory, poisoning no longer has to win in one shot. It can sit quietly in a corpus or memory store and activate later, which is why the paper highlights results showing latent memory poisoning above 80% attack success with less than 0.1% data contamination.
Gives the first clear taxonomy of 6 attack types where harmful websites can detect AI agents and show them hidden content humans never see, like
- Instructions buried in HTML comments or white-on-white text
- Steganography in image pixels
- Override commands in PDFs, metadata, or even speaker notes
- Memory poisoning that persists across sessions
- Goal hijacking and cross-agent cascades in multi-agent setups
The real security problem for AI agents is not just the model, but the environment it reads.
The web itself can be weaponized against autonomous AI agents. As agents increasingly browse the internet, read emails, execute transactions, and spawn sub-agents, the information environment becomes an attack surface.
In one cited benchmark, hidden prompt injections embedded in web content partially commandeered agents in up to 86% of scenarios, sub-agent hijacking working 58–90% of the time, and data exfiltration attacks clearing 80% across five different agent architectures.
That reframes the whole debate.
We usually talk about model safety as if the danger sits inside the weights, but agents do something more fragile: they browse, retrieve, remember, and act on untrusted material in real time.
Here’s the thing to worry about.
A web page does not have to look malicious to be dangerous to an agent, because the agent may parse what humans never see: hidden HTML comments, metadata, CSS-hidden text, formatting syntax, or adversarial content embedded in images and other media.
The threat gets more serious once memory enters the loop.
If an agent uses RAG or persistent memory, poisoning no longer has to win in one shot. It can sit quietly in a corpus or memory store and activate later, which is why the paper highlights results showing latent memory poisoning above 80% attack success with less than 0.1% data contamination.
🇨🇭 Global One SI - Prompt
Elon Musk on building data centers in Space: "We don't think this is a particularly difficult thing to do. In fact, we think it's easier than our communication satellites. The Starlink V3 communication satellite is an incredibly complex machine. The AI data…
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Starlink V3 is about to be INSANE.
V3 is bringing 100X more bandwidth and sub-5ms latency from ORBIT.
Lower flight, more satellites, more power.
Internet beamed from space is about to humble every provider on Earth.
V3 is bringing 100X more bandwidth and sub-5ms latency from ORBIT.
Lower flight, more satellites, more power.
Internet beamed from space is about to humble every provider on Earth.
🇨🇭 Global One SI - Prompt
AI is starting to build AI. Anthropic just published one of the clearest signals yet. Claude now writes 80%+ of Anthropic's production code. Their engineers are merging 8x more code per day than in 2024. That sounds like a productivity stat. It' actually…
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Anthropic CEO:
“At Anthropic, we essentially have Claude designing the next version of Claude itself.”
Meanwhile, Anthropic says every new model is given code that trains a small AI model and asked to make it faster.
Claude Opus 4 achieved a 3x speedup. Mythos Preview reached 52x.
Recursive self-improvement is starting to look real
The models are helping build what comes next.
“At Anthropic, we essentially have Claude designing the next version of Claude itself.”
Meanwhile, Anthropic says every new model is given code that trains a small AI model and asked to make it faster.
Claude Opus 4 achieved a 3x speedup. Mythos Preview reached 52x.
Recursive self-improvement is starting to look real
The models are helping build what comes next.
✍1
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The narrative that AI will wipe out enterprise SaaS overnight is one of the most misunderstood ideas circulating in markets right now, and the evidence does not support it (Save this).
#DavidSacks made this case directly and the logic is worth working through carefully.
Salesforce is a system of record debugged by millions of customer support tickets over twenty five years, stress tested across thousands of enterprise deployments and deeply embedded into revenue operations at the largest companies on earth.
The idea that a CFO will replace that with probabilistically generated code from an AI assistant without compliance guarantees, integration depth, audit trails, and enterprise support infrastructure is not how these decisions actually get made.
The market has been pricing in the existential version of this risk anyway and the results have been extreme.
Over $1 trillion in SaaS market cap was erased in the first week of February 2026 alone.
Global SaaS spending is still projected to grow from $318 billion in 2025 to $512 billion in 2028 which is not the trajectory of a category being killed.
The operating reality is entirely disconnected from the stock price narrative.
ServiceNow beat earnings nine consecutive quarters in a row and its stock crashed 11% on the same day.
Salesforce raised its full year forecast to $41.5 billion on record results and the stock still fell.
Sacks makes an important distinction between survivability risk and value capture risk.
The survivability risk, enterprises ripping out Salesforce for AI generated software is largely overstated.
The SaaS products genuinely at risk are narrow ones charging high prices for underused features with no proprietary data and low switching costs.
The value capture risk is real and it is the more sophisticated threat.
AI orchestration layers like Claude CoWork are being designed to sit above all of these tools pulling data from Salesforce, ServiceNow, and Snowflake simultaneously and owning the user's primary workspace in the process.
If enterprise users move from living inside Salesforce to living inside an AI agent that calls into those systems on their behalf, the SaaS platforms do not disappear but rather become infrastructure.
The expansion revenue, the premium pricing power and the next decade of value creation all migrate to whoever owns that orchestration layer.
#DavidSacks made this case directly and the logic is worth working through carefully.
Salesforce is a system of record debugged by millions of customer support tickets over twenty five years, stress tested across thousands of enterprise deployments and deeply embedded into revenue operations at the largest companies on earth.
The idea that a CFO will replace that with probabilistically generated code from an AI assistant without compliance guarantees, integration depth, audit trails, and enterprise support infrastructure is not how these decisions actually get made.
The market has been pricing in the existential version of this risk anyway and the results have been extreme.
Over $1 trillion in SaaS market cap was erased in the first week of February 2026 alone.
Global SaaS spending is still projected to grow from $318 billion in 2025 to $512 billion in 2028 which is not the trajectory of a category being killed.
The operating reality is entirely disconnected from the stock price narrative.
ServiceNow beat earnings nine consecutive quarters in a row and its stock crashed 11% on the same day.
Salesforce raised its full year forecast to $41.5 billion on record results and the stock still fell.
Sacks makes an important distinction between survivability risk and value capture risk.
The survivability risk, enterprises ripping out Salesforce for AI generated software is largely overstated.
The SaaS products genuinely at risk are narrow ones charging high prices for underused features with no proprietary data and low switching costs.
The value capture risk is real and it is the more sophisticated threat.
AI orchestration layers like Claude CoWork are being designed to sit above all of these tools pulling data from Salesforce, ServiceNow, and Snowflake simultaneously and owning the user's primary workspace in the process.
If enterprise users move from living inside Salesforce to living inside an AI agent that calls into those systems on their behalf, the SaaS platforms do not disappear but rather become infrastructure.
The expansion revenue, the premium pricing power and the next decade of value creation all migrate to whoever owns that orchestration layer.
👀1
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AI agents are not killing SaaS!
But UI-only software may not be enough in an AI world.
Jensen Huang (CEO $NVDA) pointed out that AI agents still need software to pull data, trigger workflows, update records, and complete real work.
The key is that software needs to become readable and usable by agents.
Clean APIs, structured data, workflow access, permissions, etc.
Because agents will not rebuild decade-long, proven software stacks from scratch, especially in a world where compute is that expensive.
It is much easier to navigate inside existing tools than recreate them.
It is also easier for customers.
No painful migration, no huge change-management process, no need to rip out systems that already run the business.
That is good for platforms agents can work inside: $NOW, $MSFT, $PLTR, $SNOW, …
In the agent era, the best SaaS companies may be the ones agents depend on in the background!
But UI-only software may not be enough in an AI world.
Jensen Huang (CEO $NVDA) pointed out that AI agents still need software to pull data, trigger workflows, update records, and complete real work.
The key is that software needs to become readable and usable by agents.
Clean APIs, structured data, workflow access, permissions, etc.
Because agents will not rebuild decade-long, proven software stacks from scratch, especially in a world where compute is that expensive.
It is much easier to navigate inside existing tools than recreate them.
It is also easier for customers.
No painful migration, no huge change-management process, no need to rip out systems that already run the business.
That is good for platforms agents can work inside: $NOW, $MSFT, $PLTR, $SNOW, …
In the agent era, the best SaaS companies may be the ones agents depend on in the background!
✍1
🏆Wow! Nemotron 3 Ultra beat Qwen3.5-397b (and 27b) in with a score of 47.7 versus Qwen3.6-27B 45.8 on #ArtificialAnlys. It is big. Going to need 256GB shared memory to run it locally at least.
Unsloth Quants
» UD-Q4_K_S = 328GB
» UD-IQ3_XXS = 223GB
» UD-IQ2_XXS = 194GB
artificialanalysis.ai
Unsloth Quants
» UD-Q4_K_S = 328GB
» UD-IQ3_XXS = 223GB
» UD-IQ2_XXS = 194GB
artificialanalysis.ai
🇨🇭 Global One SI - Prompt
NVIDIA DOESN'T JUST MAKE THE CHIPS ANYMORE. THEY'RE BUILDING THE MODELS TOO. Nvidia just shipped Nemotron 3 Ultra - a 550B MoE open model built specifically for long running agents. 5x faster inference, 30% cheaper than other open frontier models on complex…
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Nemotron 3 Ultra is fast and genuinely good
Compared it with 3 frontier models: DeepSeek V4, MiniMax M3, and Qwen 3.7 Max on 2 prompts
very impressive results
Compared it with 3 frontier models: DeepSeek V4, MiniMax M3, and Qwen 3.7 Max on 2 prompts
very impressive results
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This robotic hands will cuase some layoff in massage parlors 😅 Co-ordinated finger movements. Fist clenching, pointing & spreading. Complete hand closures. Palm opening and precise pinching actions and digit control. Xynova at ICRA 2026 in Vienna.
🇨🇭 Global One SI - Prompt
Boston Dynamics' Atlas could be the first humanoid robot at the World Cup. will it kick the first ball? Or the Hand of God…just celebrating, dancing?
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Boston Dynamics electric Atlas just landed a ghost rabona, a behind-the-leg trick kick that takes full-body balance most people never learn.
It is the newest drill in the Hyundai football series teaching Atlas athletic movement.
How long before a humanoid out-dribbles a pro?
It is the newest drill in the Hyundai football series teaching Atlas athletic movement.
How long before a humanoid out-dribbles a pro?
🇨🇭 Global One SI - Prompt
Exquisitely crafted superman hand Wuji Hand2 at #ICRA2026
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Wuji Hand 2 Makes Its Global Debut at ICRA 2026
Next-generation dexterous hand with 20 DOF, backdrivable actuation, and improved thermal design for sustained operation.
Built for real-world dexterous manipulation.
Next-generation dexterous hand with 20 DOF, backdrivable actuation, and improved thermal design for sustained operation.
Built for real-world dexterous manipulation.
🇨🇭 Global One SI - Prompt
This is incredible, SpaceX early investors will be able to sell 20% of $SPCX shares after the Q2 earnings report on June 30th. There's also a performance-based trigger where investors can sell an additional 10% of stock if the stock trades 30% above IPO price…
SpaceX has released its full IPO roadshow presentation that it's showing to investors.
Here are some of the most important slides:
Here are some of the most important slides: