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Part of a broader NYU Tandon School of Engineering research effort testing whether AI-generated advice is safe to follow in high-stakes situations, including scams, hacked accounts, and harassment

Humanoid robots are taking a detour that was always going to be painful. Copying the shape of the human body without the control system that took over a decade to grow into it is not an engineering challenge. It is a wrong turn.

Humans can control their bodies precisely because we never faced the full complexity of an adult body all at once. An infant's body is small, light, with weak muscles and an immature nervous system. The nervous system learns basic balance and movement on this simplified version first. Then the body grows gradually, bones lengthen, muscles multiply, and control ability grows alongside it in mutual adaptation. Gross motor skills are largely in place by age six or seven. The central mechanisms for fine motor control do not fully form until around fourteen. Higher-level motor regulation, planning, precision, fluid switching, continues developing through late adolescence, roughly sixteen or even later. This is a process of body and intelligence co-evolving over more than a decade.

Today's humanoid robots skip this process entirely. Agility Robotics just launched Digit 5, which weighs over 120 kilograms, ships with every joint and every degree of freedom, and arrives as a fully "adult" system from day one. Founder Jonathan Hurst himself admits the robot feels more like a forklift than the graceful humanoid he dreamed of building. To lift 23-kilogram bins, it needs massive motors, a massive battery, and a cooling system that takes up 75 percent of its torso. It cannot run or jump. The fluid dynamic gaits of its predecessors are gone. This is the cost of forcing a humanoid form: morphological complexity far exceeding what the control system can handle.

It is also worth questioning whether the human body is even the optimal engineering template. Human bipedal locomotion is a product of evolutionary compromise. It freed our hands, but it gave us back pain, knee wear, and an extremely high balance-control overhead. There is no reason for engineering to inherit these evolutionary leftovers.

The history of aviation already proved this point. Early flight pioneers tried to imitate bird wing-flapping and all failed, because they did not yet understand the physics of flight. Once aerodynamics was mastered, aircraft proliferated, still with wings but without feathers. The resemblance in form came from obeying the same physical laws, not from imitating birds. Today's humanoid robots are in their "flapping-wing phase." Our understanding of the physics of locomotion and manipulation is still in its infancy. Copying precise human proportions and five-fingered hands is like strapping flapping wings onto an early flying machine.

Nature offers an entirely different approach. An octopus lives only one to two years, yet it performs extraordinarily complex manipulation tasks. Its soft tentacles have no bones or joints. Degrees of freedom come from the compliance of the material itself, requiring no dedicated motor or sensor for each joint. Its intelligence is distributed: two-thirds of its neurons reside in the arms, which can autonomously perform local operations while the brain handles only high-level intent. This architecture is naturally suited to working in unstructured environments, exactly the capability that real-world scenarios demand most.

A robot's form should start from the task and from physical constraints. Let function determine form. Digit 5's forward-facing knee is a good example: it adopted the human knee orientation because the backward-bending leg could not squat to pick up bins from the floor. That was a function-driven choice. But this correct local decision exposes a problem with the overall direction. If every step requires starting from a humanoid form and then patching it, why not start from the task itself?

Copying the humanoid form means trying to replicate, in one shot on a factory floor, a system that took millions of years of evolution and sixteen years of growing from infancy. That path does not work. The real breakthroughs will come from designs that abandon imitation of the human shape and start instead from biomechanical principles and task requirements.

Meanwhile, robots that look nothing like humans are already doing the work. Locus Robotics has completed over two billion warehouse picks for customers including DHL. Its robots are a wheeled base with an iPad screen on the front and a few sorting bins on top. They navigate warehouse aisles on their own, telling workers what to pick and where. The base is shaved flat on the sides so two robots can squeeze past each other in tight aisles. Each robot communicates with every other robot in real time, dynamically planning paths and rerouting around obstacles. They work in the same warehouses Digit was designed for, but they solve the problem differently. Digit tries to replace the human worker by physically carrying bins itself, and must stop and crouch whenever a person gets close. Locus robots work with humans instead of replacing them, guiding workers through picking, sorting, and replenishment while dynamically coordinating an entire fleet in real time. One approach fights the complexity of bipedal manipulation. The other sidesteps it entirely, and already operates at scale, at a fraction of the cost. But nobody writes headlines about a rolling shelf. As one robotics community moderator put it, efficient designs driven by functional need are proliferating across the field. They just don’t get as much PR. Investors want the story of a robot that works like a human employee. The machines that actually work don’t need to look like one.

Western capitalism's cycle of booms and busts stretches all the way back to Amsterdam and the Tulip Mania of 1636. They all follow the same pattern, and we are living in the end stages of one now with AI. Every single time, there are detractors who say this time is different; however, they have a four century track record of getting it wrong.

This week, yet again, we see a small Chinese firm with a fraction of the spending and resources getting the near equal of the frontier models Big Tech investors are spending trillions to achieve. Not only that, they are offering theirs to the world for free, and it uses a small fraction of electricity/computing resources to run. Those Big Tech investors will never earn those trillions back.

It might be bleak and depressing to contemplate, but people need to think about what happens after the crash. This is no time for centrism, or putting your fingers in your ears and saying you don't want to hear about politics. The very worst people in our cultures, many Big Tech leaders themselves, are looking forward to this destruction and making their plans for it, and the world they want afterwards is a 100 times bleaker.

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Hi,

I am in the Data science field and I want to become more aware and cultured on what is to come, especially in the digital world.

Could you suggest a poadcast to hear on spotify or a channel on youtube?

Someone that knows what they are talking about and that is interesting to hear.

Imagine a future where the world's wealthiest people and most powerful corporations come to a conclusion: humanity has accumulated enough knowledge. We have already made centuries of scientific, technological, and intellectual progress, and most of the remaining development can be carried out by AI agents with a relatively small human workforce.

They begin to believe that giving billions of people unrestricted access to knowledge is no longer necessary.

What if they decided to restrict or even eliminate public access to the internet, books, educational resources, and other sources of information? Their argument would be that the masses no longer need to learn, research, or innovate because AI systems can do all of that more efficiently.

The benefits of technological progress would remain concentrated among those who own the AI systems, computing infrastructure, and essential resources, while the majority of people would have fewer opportunities to develop independent knowledge or skills.

Here are the questions I'm curious about:

1. How would ordinary people react if access to knowledge and education were deliberately restricted in a world where AI could perform most intellectual work?

2. How would democratic governments respond? What about authoritarian governments that might see this as an opportunity to consolidate power?

3. Would governments resist such a move, or might some cooperate with powerful corporations if it helped them maintain control over their populations?

4. If AI could run most industries with minimal human involvement, what economic role would the majority of the population have? How would people earn a living?

5. Would society eventually revolt, develop underground networks to preserve and share knowledge, or gradually accept this new reality?

6. If access to knowledge became a privilege rather than a basic right, would humanity experience a new kind of digital feudalism, where a small elite controls both technology and information?

7. Most importantly, if AI could continue advancing civilization without requiring widespread human participation, what would motivate those in power to keep educating, employing, or empowering the masses?

I'm not suggesting this scenario is inevitable. I'm interested in exploring what might happen if technological progress made most human labour unnecessary while control over knowledge and AI remained concentrated in a few hands.

What would the world actually look like under these conditions?

Would such a system be sustainable, or would human nature, political resistance, and the desire for freedom eventually bring it down?

​One of the paradoxes of mid-2020s AI is that many of its champions acknowledge its revolutionary nature, yet can't seem to imagine a future any different from today. Hence, all they can picture is today's neo-liberal capitalism turbocharged by 100, with them at the top. A delusion and a fantasy, if you just think a few steps ahead.

Case in Point.

Microsoft's latest Medical AI, where the AI is scoring 83%, and human doctors 36%. The version of this that will triumph is a (yet to be developed) free open-source version available to the world's 5 billion smartphones. If we include those who have access to smartphones, via family and friends, it's probably almost everyone on the planet.

Don't think this will happen? It's only a matter of time.

$1.5 trillion is given to charity every year. Developing this AI is a tiny drop in that $1.5 trillion bucket. Someone, a UN agency, Doctors without Borders, the Red Cross, or one among the other endless list of NGOs will do this. A country may even decide to fund it on behalf of mankind.

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A Lookback at 2023 Trends in Global Generosity

For at least a decade, I have been hearing about robotic bartenders becoming more common.

Just like self-checkout lanes in grocery stores (which while never managing to take over, have still managed to account for around 35% of all grocery store transactions).

Even 0.1% of bars do not have robot bartenders!

Edit: Not for me for sure. I prefer human interaction. It is just a thought that came across my mind.

Considering that so many customers prefer being on their phones in bars, I think there is a market for anti-social bars.

1Password for Agents handles credential sharing for you

Artificial intelligence was evaluated across CNS autoimmune diseases to support diagnosis and prognosis.

This year Google and Amazon are each spending about 0.6% of US GDP on Capex. The Manhattan Project and Apollo Programme each accounted for about 0.4% of US GDP in their peak years.

The six largest spenders this year are spending more than the Russian government spent last year.

Hyperscaler spending will be $785-820bn this year, about 2.4% of US GDP. There are only 11 governments on earth who spend more than that. Next year they are projected to spend about 1.3 trillion dollars.

This money is being paying for thousands of data centres, the largest of which consume as much electricity as major cities and cover thousands of acres. Gas pipelines are being re-routed and nuclear reactors re-opened and built from scratch to fuel them. They already consume as much electricity as Britain. The increase in power demand for data centres from 2023 to 2030 will be the equivalent of adding another top ten power consuming country.

To justify all of this spending very powerful AI will have to be achieved and it will have to be achieved soon.

The decision makers believe the singularity is near.

News of deep job cuts at Amex comes one day after UK banking giant Barclays announced a similar move.