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Europe waking up to its unhealthy dependence on US internet infrastructure pairs nicely with the slow, steady march of robots into the real world, where there is no single magical breakthrough but a long climb through messy edge cases, much like shaping software as clay with swarms of autonomous agents that only work when you define success very precisely up front. The pattern emerging across all these pieces is that transformative tech doesn’t arrive in one dramatic moment but through countless small steps, whether that’s building European digital sovereignty, teaching robots to handle variability, or getting AI agents to reliably do what you actually want.

Add to that a take by Cory Doctorow predicting an AI bubble that will eventually burst and leave us with cheap GPUs, better tools and lots of scrappy open source, and you get a tech landscape that feels both overheated and strangely robust at the same time. Meanwhile, quantum computing promises radically more efficient computation just as data centers start eating cities worth of power, but it still reads like science fiction you need to go through twice before you nod as if you really got it. And qubit just sounds like a frog sound.

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Europe wants to end its dangerous reliance on US internet technology

You reach out for information but struggle to communicate with family and friends, or to get the latest updates on what is happening, as social media platforms are all down. Just as someone can pull the plug on your computer, it’s possible to shut down the system it connects to.

This isn’t an outlandish scenario. Technical failures, cyber-attacks and natural disasters can all bring down key parts of the internet. And as the US government makes increasing demands of European leaders, it is possible to imagine Europe losing access to the digital infrastructure provided by US firms as part of the geopolitical bargaining process.

It is so important that lawmakers finally realize that we need to do more to build clever hard- and software in Europe, as our current suppliers are just not that reliable anymore. Also, it doesn’t make sense that we spend billions on software each year that makes big tech more powerful.

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Many Small Steps for Robots, One Giant Leap for Mankind

It’s only once you start deploying robots outside of the lab that something else becomes obvious: robotics progress is not gated by a single breakthrough. There is no single fundamental innovation that will suddenly automate the world.

We will eventually automate the world. But my thesis is that progress will happen by climbing the gradient of variability.

The recent developments in robotics are just breathtaking, but I won’t be impressed until I have a companion robot that folds the laundry, does the dishes, picks up all the stuff from the floor and then vacuums it.

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Software as clay on the wheel

That doesn’t mean it’s secure, fast, or something you’d ship. It just means it met the criteria they gave it. If you decide to check for security or performance, it will work toward that as well. But the pattern is what matters: clear tests, constant verification, and agents that know when they’re done.

From solo loops to hundreds of agents running in parallel, the same pattern keeps emerging. It feels like something fundamental is crystallizing: autonomous AI is starting to work well when you can accurately define success upfront.

I think working with clay is a bit more therapeutic than working with coding agents, but still, the image is pretty accurate.

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AI companies will fail. We can salvage something from the wreckage

AI is a bubble and it will burst. Most of the companies will fail. Most of the datacenters will be shuttered or sold for parts. So what will be left behind?

We will have a bunch of coders who are really good at applied statistics. We will have a lot of cheap GPUs, which will be good news for, say, effects artists and climate scientists, who will be able to buy that critical hardware at pennies on the dollar. And we will have the open-source models that run on commodity hardware, AI tools that can do a lot of useful stuff, like transcribing audio and video; describing images; summarizing documents; and automating a lot of labor-intensive graphic editing – such as removing backgrounds or airbrushing passersby out of photos. These will run on our laptops and phones, and open-source hackers will find ways to push them to do things their makers never dreamed of.

While I am still not so sure about a bursting bubble anytime soon, I do see a ton of impressive advancements in tech right now that we will all benefit from.

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How can we scale quantum computing in the most energy-efficient way?

Today, a single cutting-edge AI chip can draw as much electricity as an entire household and large training runs can consume as much energy as an entire city. The International Energy Agency, therefore, expects global electricity consumption by data centres to roughly double by 2030.

This raises the question: how can we expand computing without expanding energy use?

Quantum computing is often cited as a partial answer, promising far greater computational power at a dramatically lower energy cost. But we rarely explain why, in which cases or compare what quantum platforms deliver the most computation per kilowatt-hour, despite significant differences.

I just love reading about Quantum computing. Then I scratch my head and read it again. I don’t think anyone really understands this stuff.

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That’s all for now! Thanks for reading! If you missed last week’s Five Things Tech, you can find it here:

Five Things Tech: Quantum, Craigslist, Voice, Vision Tech, Tech Jobs Jan 17 Read full story

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— Nico