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Nextness is supported by an AI consultancy helping Australian businesses adopt emerging technology responsibly.
For innovation leaders
What's next, before everyone else knows
Early signals on emerging tech, startup trends, and innovation patterns that matter.
What we cover
- Emerging technologies and early signals
- Startup ecosystem trends and patterns
- Innovation methodology and frameworks
- Deep dives on transformative tech
Who it's for
- Innovation managers and scouts
- R&D leaders tracking new tech
- VCs and startup investors
- Corporate strategists planning ahead
Latest posts
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Edge AI Chips: Why Processing Data Locally Matters More Than Ever
Sending everything to the cloud for AI processing made sense five years ago. In 2026, edge AI chips are changing the calculation. Here's why local inference is gaining ground.
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Quantum Error Correction in 2026: The Milestones That Matter and What's Next
Quantum error correction is the bottleneck standing between noisy qubits and useful quantum computers. Here's where the field actually stands in February 2026.
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AI Agents Meet IoT Sensors: The Rise of Autonomous Environments in Smart Buildings
How the convergence of AI agents and IoT sensor networks is creating buildings that think, adapt, and manage themselves without human intervention.
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Neuromorphic Computing in 2026: Where Intel's Loihi and IBM's NorthPole Actually Stand
A reality check on neuromorphic chips - the brain-inspired processors that promise radical energy efficiency. What's working, what's hype, and who's ahead.
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Spatial Computing in 2026: Beyond the Apple Vision Pro Hype
Apple Vision Pro launched to huge fanfare. A year later, where does spatial computing actually stand? The answer is more interesting than you'd expect.
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Synthetic Data Is Quietly Replacing Real Data for AI Training
Real-world data is expensive, messy, and privacy-fraught. Synthetic data generation might solve all three problems at once.
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OpenClaw and the Rise of Enterprise-Grade Open Source AI
Why 2026 is the year managed AI agent platforms go mainstream — and what it means for businesses ready to move beyond proof-of-concept.
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What 'AI-Ready' Actually Means for Organizations
Everyone wants to be 'AI-ready.' But the term is vague. Here's what organizational readiness for AI actually requires.
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Where Emerging Tech Is Heading: My H2 2026 Outlook
After years of tracking emerging technology, here's my current thinking on where things are heading across AI, climate tech, biotech, and beyond.
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Building the Right AI Evaluation Benchmarks
Standard benchmarks don't tell you if AI works for your use case. Here's how to build evaluation systems that actually measure what matters.
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AI Agents in Healthcare: Progress and Persistent Challenges
Healthcare AI is advancing, but deployment remains slower than other industries. Here's what's actually happening and why.
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Connecting AI to Legacy Systems: The Unglamorous Reality
Most AI implementations fail at integration, not intelligence. Here's what actually works when connecting AI to existing enterprise systems.
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Edge AI Is Finally Having Its Moment - Here's Where It Actually Works
After years of promise, edge AI is delivering real results in 2026. We look at retail analytics, agriculture, industrial IoT, and why the tech finally works.
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The AI Talent War Is Over. The AI Skills War Is Just Beginning.
The frenzy to hire AI PhDs has cooled, but the harder challenge is here: upskilling existing employees to work alongside AI. Internal capability wins.
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Small Language Models Are the Real Story of 2026
While everyone watches frontier AI models grow larger, smaller specialized language models under 10B parameters are becoming the practical choice for business deployment.