AI's Efficiency Obsession
It's not about what AI can do, but how fast it can do it.
The next phase of AI isn't about magic tricks. It's about industrialisation, and that means making everything faster, cheaper, and smarter.
Your AI Is About to Get Twice as Fast
NVIDIA's latest architecture is forcing a shift from 'can it work?' to 'how fast can it run?'
NVIDIA's Hopper architecture is making AI models drastically more efficient. By using clever tricks like ignoring unnecessary maths (structured sparsity) and using less precise numbers (FP8), its GPUs can train models up to 7x faster. This isn't just a minor speed bump; it's a fundamental change in the economics of building with AI.
The real story here is the pivot from brute force to elegant efficiency. For years, the answer to better AI was just "more data, bigger model." Now, the focus is on architectural intelligence, squeezing maximum performance from every cycle. This move democratises high-end AI, allowing smaller teams to compete with giants by being smarter, not just bigger.
This matters if you're building anything with AI. Faster training means faster iteration, and cheaper inference means you can actually afford to run your service at scale. The takeaway is to start looking at your own models: are you leveraging these new hardware capabilities? If not, you're already falling behind.
Your New AI Co-pilot
AI is moving from a destination to a feature, embedding itself directly into the tools we already use.
Extra Thursday: The AI that reads your entire inbox
This finally treats your email history as a single, queryable database. It’s a move from single-thread summaries to holistic inbox intelligence, which is a much harder and more useful problem to solve.
GitLaw Agent: Your free AI legal intern
This commoditises routine legal work, which was inevitable. The real question is whether it can handle nuance or if it just creates more clean-up work for actual lawyers down the line.
Arcitext: An AI ghostwriter that sounds like you
Most AI writers erase personality; this promises to enhance it. The goal isn't just to write faster, but to codify a personal or brand voice, turning style into a scalable asset.
AI Is The New Low-Code
The next wave of builders aren't writing code, they're writing prompts.
MeDo: Baidu's agentic full-stack developer
This isn't just another no-code tool; it's a bet on agentic systems building entire applications. It raises the abstraction layer from dragging components to simply describing the final product.
Agora Store Builder: Vibe code your e-commerce store
'Vibe code' is the perfect summary of where we are heading. It captures the shift from technical specs to descriptive, outcome-oriented instructions for AI builders.
Context Link: A library card for your AI
This is essential plumbing for the next generation of AI tools. Providing targeted, real-time context is the only way to solve AI's 'brilliant goldfish' memory problem.
Quick hits
Perch: Turns your Mac's notch into a command centre
It adds a Dynamic Island-style hub with on-device AI chat, proving that the best features are sometimes hiding in plain sight.
Blindspot: Book a billboard like you book an Uber
This democratises out-of-home advertising, turning a complex, expensive process into a simple, self-serve platform for anyone with a budget.
ROAARRR: Growth analytics that don't hurt your brain
It simplifies funnel tracking around the classic AARRR framework, because you can't grow what you can't easily measure.
My takeaway
The conversation is finally shifting from what AI can do to how efficiently it can do it.
This is being forced by hardware leaps like NVIDIA's, which make smarter computation more valuable than just bigger models. The result is a wave of tools that abstract away complexity, making powerful tech accessible to everyone. The real value is moving from the foundational model to the specific, performant application built on top.
This means the era of AI as a magic trick is ending, and the era of AI as industrial infrastructure is beginning. It's time to stop being impressed and start building real, scalable businesses. So the only question that matters is this: where is the biggest efficiency bottleneck in your world?
Where is the biggest efficiency bottleneck in your world that a smarter, faster AI could solve?
Drop me a reply. Till next time, this is Louis, and you are reading Louis.log().