Ⓙⓐⓒⓚ Ⓗⓘⓓⓐⓡⓨ

Author of AI or DIE - A guide for leaders (coming out soon); and of Quantum Computing: An Applied Approach. CEO of @SandboxAQ, #AI and #Quantum.

[Ⓙⓐⓒⓚ Ⓗⓘⓓⓐⓡⓨ @jackhidary]

The AI race will not be won with chatbots that predict the next word.
In today’s Wall Street Journal, I argue that staying ahead of China requires a new class of AI models built on physics, chemistry, and quantitative reasoning, not just language and images.
China’s next five-year plan doubles down on materials science, quantum technology, energy storage, and defense. These sectors run on equations, not prompts.
Language models are wonderful productivity tools, but they are not designed to compute optimal alloy compositions, advance semiconductor design, or model high-dimensional financial risk.
Pharma, semiconductors, energy, and financial services represent more than $25 trillion in global output. These industries require quantitative AI trained on lab data, robotic experimentation, and the equations of the physical world.
Read the full op-ed in the WSJ here: https://t.co/JAb4nHwim1

[Ⓙⓐⓒⓚ Ⓗⓘⓓⓐⓡⓨ @jackhidary]

@Scobleizer is on point - humanoid robots are coming faster than most people imagine - the early adopters will be users of @Waymo and @Tesla FSD and other groups who can see robots as helpers and not as threats. we will see early adoption as well in hospitals for the many raja’s that humans don’t want to do or can’t do. sanitizing a hospital room with UV light is best left to robots. Less MRSA and efficient.

[Robert Scoble @Scobleizer]

Trust is a funny thing.

When I interview Waymo customers they say they absolutely would trust a humanoid robot from that company, which spun out of Google. At a far higher rate than if I ask that question of someone who has never been in an autonomous vehicle.

Why? Well within three rides they learn to trust it driving them at 80 mph next to a wall with killing them.

This is what AI experts like @ErrkC miss and why you must actually do customer interviews if you want to understand the future. It is why my eight books about the future were so on point.

And why those who own a Tesla with self driving see the future so much clearer.

Tesla is way ahead of any other robot company on trust. Which you all will understand next year when Robotaxi starts.

It is the autonomous car companies that will have everyone’s trust in 2027 when humanoid robots arrive at scale.

Same in China.

Plus they have a way to move them around the neighborhood.

Humans who get a ride in a robot change.

They learn to trust AI in a whole new way that is much more profound than watching it pick up a couple of wine glasses.

[Ⓙⓐⓒⓚ Ⓗⓘⓓⓐⓡⓨ @jackhidary]

GPS is being jammed and spoofed in many key regions, including the Gulf. Today, it’s a single point of failure.

Jamming events are up 500%. Flights rerouted. Ships off course. When it fails, the ripple effects reach every part of the global economy.

At @SandboxAQ, we’re building AQNav: a satellite-free navigation platform based on Earth’s magnetic field. It’s already in testing with the U.S. Air Force, Airbus, and Boeing.

This is what Physical AI looks like: real systems to secure real-world infrastructure.

https://t.co/8fcIMYolJS

[Ⓙⓐⓒⓚ Ⓗⓘⓓⓐⓡⓨ @jackhidary]

Honored to share that @SandboxAQ has been named to the NatSec100 list for the third year in a row.

This recognition reflects the work our team is doing at the intersection of AI, quantum technology, and national security—developing solutions that enable GPS-independent navigation, and secure data against AI- and quantum-era threats.

We’re building foundational technology for a safer, more resilient world—and we're just getting started.

Thank you to the NatSec100 team for the continued recognition, and congratulations to the other innovators helping secure the future. https://t.co/ljwIVQOG9H

[Ⓙⓐⓒⓚ Ⓗⓘⓓⓐⓡⓨ @jackhidary]

@SandboxAQ has been named one of @TIME's 100 Most Influential Companies of 2025.

This reflects the expanding impact of AI + Quantum across sectors that matter—health, national security, energy, and enterprise infrastructure.

We’re working with academic researchers and biopharma leaders to accelerate discovery for diseases like cancer, Alzheimer’s, and Parkinson’s. In cardiology, we’re collaborating with top hospitals on next-gen diagnostic tools for the world’s leading cause of death.

In national defense and aviation, our platforms are helping counter GPS jamming and spoofing. In cybersecurity, we’re partnering with global banks and enterprises to defend against AI-agent threats and prepare for the post-quantum era.

We’re also applying simulation to materials and chemistry—engineering lighter alloys, improving batteries, and designing safer chemicals for energy and manufacturing.

Thank you to the researchers, engineers, and public sector leaders who make this work possible.

We see this as a milestone—not a finish line.

https://t.co/fLqt6u3Zrf

[Ⓙⓐⓒⓚ Ⓗⓘⓓⓐⓡⓨ @jackhidary]

The old model: detect, escalate, assign, wait.

By the time your team logs in, the AI agent or the ephemeral piece of infrastructure that caused the incident has already moved on.

AQtive Guard skips the alert queue:

▪️ Ingests data from Palo Alto Networks, AWS, and CrowdStrike in real time
▪️Applies LQM-driven prioritization — no false positives
▪️Triggers remediation workflows before the alert hits the dashboard

Security is no longer about watching. It's about intervening.

Book a demo at https://t.co/IG8q8h5WSH

#AQtiveGuard #SandboxAQ #LQM

[Ⓙⓐⓒⓚ Ⓗⓘⓓⓐⓡⓨ @jackhidary]

AI agents now write code, access APIs, and sign transactions — all with human-level autonomy.

But unlike humans, they rarely get close supervision. What’s more, their identities and cryptographic assets rarely get rotated.

Their privileges are invisible.

AQtive Guard provides:
▪️ Total NHI visibility across clouds, environments, and CI/CD pipelines
▪️Risk scoring and root-cause analysis using SandboxAQ’s Cyber LQMs
▪️Enforcement of credential policy at the speed of automation

If you’re still managing this manually, you're being outpaced.

Get a live risk assessment: https://t.co/SCqXDIlbDd
#NHI #AIagents #MachineSpeedDefense #SandboxAQ

[Ⓙⓐⓒⓚ Ⓗⓘⓓⓐⓡⓨ @jackhidary]

Cryptographic assets — certs, keys, secrets — are now one of the fastest-growing attack surfaces.

And most organizations are flying blind.

AQtive Guard delivers:
• A unified inventory of cryptographic assets
• Continuous monitoring and automated remediation
• Built-in compliance-mapped regulatory frameworks

You don’t need more alerts. You need control.

And you need it at machine speed.
See how it works: https://t.co/xcyHyaGfnl
#SandboxAQ #LQMs #AQtiveGuard #AI

[Ⓙⓐⓒⓚ Ⓗⓘⓓⓐⓡⓨ @jackhidary]

AI agents proliferation in many enterprise networks is unstoppable.

And they don’t need phishing kits. They come with keys to access every corner of your IT infrastructure.

Also, each one expands your risk management footprint — silently and rapidly.

AQtive Guard is designed for shedding light into what is going on:

• Discovers NHIs and cryptographic assets in hours

• Runs LQM-based triage to find what's vulnerable now

• Remediates with policy-driven automation — not tickets

This isn’t an edge case. It’s the new default. We need security operations that can keep pace.

Book a demo: https://t.co/IG8q8h5WSH
#Cybersecurity #AIAgents #AQtiveGuard #SandboxAQ #AI

[Ⓙⓐⓒⓚ Ⓗⓘⓓⓐⓡⓨ @jackhidary]

The cybersecurity landscape is evolving rapidly.

At @SandboxAQ, we're proud to announce the launch of AQtive Guard—our AI-driven platform designed to protect against the burgeoning threats posed by Non-Human Identities (NHIs) and cryptographic vulnerabilities.

As AI agents proliferate, so do the risks. AQtive Guard offers:
- Real-time inventory of cryptographic assets and NHIs
- Automated remediation workflows to address vulnerabilities swiftly
- Seamless integrations with leading platforms like CrowdStrike, Palo Alto Networks, AWS, ServiceNow, and Qualys

This isn't just a tool—it's a necessary evolution in cybersecurity.

Explore how AQtive Guard can fortify your organization's defenses: https://t.co/U9koLBZck5

@CrowdStrike @PaloAltoNtwks
#Cybersecurity #AI #AQtiveGuard

[Ⓙⓐⓒⓚ Ⓗⓘⓓⓐⓡⓨ @jackhidary]

Today marks another major milestone for @SandboxAQ and AI for real-world impact.

We have expanded and closed our Series E round, raising over $450 million in this round and welcoming a world-class group of strategic investors: @RayDalio, @HorizonKinetics, @BNPParibas, @Google, and @nvidia. They join our exceptional long-term partners including @BreyerCap, @ericschmidt,@TRowePrice, @Paladincap, and others bringing our total funding to $950 million since spinning out from Alphabet three years ago.

This round is about more than capital. Our new and existing investors share our belief in the transformative potential of quantitative AI to solve some of the most complex and important problems in the world today. Kudos to each and every one of our SandboxAQ team members who are creating groundbreaking technology with real impact.

“I bet on the SandboxAQ team and its approach to Large Quantitative Models (LQMs) because I’m impressed by them both,” said @RayDalio, Founder of Bridgewater Associates and one of the world’s leading investors focused on key inflection points in the global economy.

With this investment, we’re doubling down on our mission to deliver even more to our customers—expanding the reach of our Large Quantitative Models (LQMs) to solve complex, high-stakes problems across life sciences, advanced materials, chemicals, navigation, cardiography, cybersecurity, financial services, and more. SandboxAQ is bringing together AI and quantum in novel ways for deep impact at scale.

To our customers, investors, and team: thank you. The road ahead is even more exciting.

Read more here: https://t.co/8xAhHh6ESi

[Ⓙⓐⓒⓚ Ⓗⓘⓓⓐⓡⓨ @jackhidary]

AI’s biggest breakthroughs won’t come from chatbots—they will come from AI that models the physical world, not just language.

While Large Language Models (LLMs) enhance efficiency in summarization, content generation, and automation, the real economic transformation is being driven by Large Quantitative Models (LQMs).

Biopharma: LQMs simulate molecular interactions at the atomic level, accelerating drug discovery by evaluating millions of compounds virtually—long before clinical trials begin.

Energy & Materials: AI is unlocking breakthroughs in battery chemistry, lightweight materials, and sustainability, replacing costly trial-and-error experimentation with precision-driven discovery.

National Security & Navigation: AI-powered sensing systems are eliminating reliance on GPS in contested environments, delivering precise positioning even when satellite signals are compromised.

Unlike LLMs, which rely on probabilities, LQMs are deterministic—rooted in physics, chemistry, and mathematics. They don’t just predict outcomes; they drive new scientific insights and create tangible economic value.

The next wave of AI isn’t just about processing information—it’s about transforming industries at their core.

[Ⓙⓐⓒⓚ Ⓗⓘⓓⓐⓡⓨ @jackhidary]

LLMs have dominated the AI conversation—but they were never the endgame. The real breakthroughs are already happening: AI that goes beyond language, built to simulate, predict, and optimize the real world.

This shift is redefining industries. AI is now solving high-dimensional, quantitative problems that language models were never designed for.

In biopharma, AI trained on chemistry and physics is accelerating drug discovery, cutting years off R&D timelines, and identifying molecular interactions beyond human reach.

In financial markets, traditional risk models fail under volatility. AI-driven simulations are processing real-time economic and geopolitical data, revealing hidden patterns and optimizing investment strategies with unprecedented precision.

This isn’t incremental progress—it’s a paradigm shift. AI is moving beyond efficiency gains to unlock entirely new capabilities, driving breakthroughs where seeing what others can’t isn’t just an advantage—it’s the future.

Which industries do you think will be the first to fully adopt AI models?

[Ⓙⓐⓒⓚ Ⓗⓘⓓⓐⓡⓨ @jackhidary]

AI is moving beyond chatbots and into its next frontier—solving complex challenges in science, finance, and cybersecurity.

I recently joined @MariaBartiromo on @FoxBusiness to discuss how Large Quantitative Models (LQMs) are already transforming industries:

🔹 Biopharma: AI-driven drug discovery is accelerating treatments for Alzheimer’s, cancer, and neurodegenerative diseases—cutting R&D timelines by years.

🔹 Financial Services: LQMs are optimizing trillion-dollar portfolios and revolutionizing risk modeling with unprecedented precision.

🔹 Cybersecurity: AI isn’t just a tool for defenders—hackers are using it too. Staying ahead requires cryptographic security to protect against evolving threats.

The AI race isn’t about incremental efficiencies—it’s about shaping the future. The companies investing in AI-driven discovery and security today won’t just stay competitive; they’ll define the next era of economic leadership.

Watch the full interview here: https://t.co/u8iZ14KPeK

[Ⓙⓐⓒⓚ Ⓗⓘⓓⓐⓡⓨ @jackhidary]

The next wave of AI transformation is here – and it’s not just about language-based models anymore. The real breakthroughs are happening now with Large Quantitative Models (LQMs) and cutting-edge quantum technologies.

This seismic shift is already unlocking game-changing capabilities that will define the future:

Materials & Drug Discovery – LQMs trained on physics and chemistry are accelerating breakthroughs in biopharma, energy storage, and advanced materials. Quantitative AI models are pushing the boundaries of molecular simulations, enabling scientists to model atomic-level interactions like never before.

Cybersecurity & Post-Quantum Cryptography – AI is identifying vulnerabilities in cryptographic systems before threats arise. As organizations adopt quantum-safe encryption, they’re securing sensitive data against both current AI-powered attacks and future quantum threats. The time to act is now.

Medical Imaging & Diagnostics – AI combined with quantum sensors is revolutionizing medical diagnostics. Magnetocardiography (MCG) devices are providing more accurate cardiovascular disease detection, with potential applications in neurology and oncology. This is a breakthrough that could save lives.

LQMs and quantum technologies are no longer distant possibilities—they’re here, and they’re already reshaping industries. The real question isn’t whether these innovations will transform the competitive landscape—it’s how quickly your organization will adapt.

[Ⓙⓐⓒⓚ Ⓗⓘⓓⓐⓡⓨ @jackhidary]

AI just beat the world’s top math Olympians. But can it solve the hardest problems we face?

DeepMind’s AlphaGeometry2 just outperformed International Mathematical Olympiad gold medalists in solving geometry problems. A milestone? Absolutely. But the real question isn’t whether AI can master structured academic challenges—it’s how we harness AI for real-world breakthroughs.

AI isn’t just proving theorems anymore. Large Quantitative Models (LQMs) are already driving transformation—accelerating drug discovery, optimizing trillion-dollar markets, and designing next-gen materials.

Unlike Large Language Models (LLMs), which are trained on internet text, LQMs are engineered for chemistry, physics, and complex quantitative systems. They don’t just answer questions—they uncover new scientific insights that humans alone might never find.

So here’s the real conversation: How do we scale AI beyond benchmarks and into the next era of discovery? What’s the next big frontier?

Where do you see AI making the biggest impact next?

#AI #LQMs #DeepTech

[Ⓙⓐⓒⓚ Ⓗⓘⓓⓐⓡⓨ @jackhidary]

China’s @deepseek_ai just made waves, rivaling @OpenAI's models at a fraction of the cost. It sent @nvidia's stock tumbling and reignited a global debate: Is the AI race shifting east?

But here’s the bigger picture: Large Language Models (LLMs) are rapidly becoming a commodity. As costs drop and capabilities level out, the real disruption won’t come from better chatbots—it’ll come from AI that can model the world, not just talk about it.

This is where Large Quantitative Models (LQMs) take center stage. Unlike LLMs, which refine existing knowledge, LQMs drive breakthroughs in drug discovery, materials science, and financial modeling—areas where AI doesn’t just respond to prompts but generates new, actionable insights.

And here’s where Jevons’ Paradox kicks in: As AI becomes cheaper and more accessible, its use won’t plateau—it will explode across industries. The next AI revolution won’t be about which company builds the best chatbot; it will be about which models power scientific and economic transformation.

So, what do you think? Are LLMs already past their peak relevance? Or is this the start of a new wave where quantitative AI reshapes entire industries?

#AI #LQMs #DeepSeek #ArtificialIntelligence

[Ⓙⓐⓒⓚ Ⓗⓘⓓⓐⓡⓨ @jackhidary]

Quantum stocks have been volatile, with skeptics arguing that large-scale quantum computers are still far off. But quantum isn’t just computing—and it’s not a distant future technology. Advanced quantum hardware, such as sensors, and Large Quantitative Models (LQMs) trained on first principles and quantum equations are already reshaping industries.

Why Quantum + AI Is Transforming Industries Now:

Quantum + AI = The Next Scientific Breakthroughs – Quantum-inspired AI models, trained in biology, physics, and chemistry, are accelerating drug discovery, optimizing supply chains, and simulating high-dimensional financial markets with unprecedented precision. These aren’t just theoretical applications—they’re happening today.

The Long-Term Demand for Compute Is Unstoppable – AI adoption isn’t slowing down. Every major industry—biopharma, energy, chemicals, and finance—is shifting toward quantitative AI models that unlock core value, not just cut costs. These models will only grow more powerful with hybrid computing architectures, including quantum.

The Future is Hybrid: CPUs, GPUs, and QPUs Working Together – We’re entering an era where classical and quantum computing will complement each other. CPUs will handle general processing, GPUs will accelerate AI workloads, and QPUs will solve problems that are computationally infeasible today. This convergence will unlock breakthroughs in material science, cryptography, and complex system simulations.

Quantum Hardware Is Reaching Key Milestones – While we’re still in the early stages, advancements in error correction, hybrid quantum-classical models, and specialized QPUs are laying the groundwork for real-world deployment. Progress is accelerating.

LLMs are making language-based tasks in customer service and content creation more efficient. Quantitative AI is transforming how we understand and manipulate the physical world. Quantum is helping us tackle the hardest challenges in healthcare, clean energy, and beyond.

Where do you see quantum AI making the biggest impact first?

#QuantumComputing #AI #DeepTech #LQMs #TechInnovation