Category: Future

An Idea of Ideas

by Yu Gu, posted in Future, Ideas, Uncategorized

There are 7.8 billion people living on this planet and everyone’s brain is running, fast or slow. Most of the time, people are thinking about more or less the same things: sports, weather, girls/guys/kids, shopping, promotion, money, politics, to name a few. Imagine how many times the same thought on “which phone to buy” goes around the globe? (sounds like a lot of redundancy and waste here, but that’s for a different topic…)

Occasionally, unique ideas pop up in the mind of a person, any person, often because she/he is in the right place at the right time (e.g., what if the blanket can fold itself after I pick up the baby?).  These ideas could be trivial or infeasible. We might feel good about our creativity for a few seconds, then it would just slip away out of the memory. Not known what to do with the ideas, we are throwing away an enormous number of intellectual products each day (hint: at least write them down like what I am doing with this blog…).

At the same time, our world is in a desperate shortage of creative ideas (just watch a few recent movies or see the design of all the new cell phones…). Once someone is in need of a solution (e.g., stop the pandemic), good ideas don’t come by on schedule. Beaming a lot of brainpower by a few smart people is not necessarily the answer.

So what can we do? How can we involve everyone in the creative process everyday on solving the world’s everything problems? I think we can benefit from something like a “Wikipedia for ideas”, where millions of diverse ideas are shared, debated on, grow and connect, and found by people who need them. How to discover incentives for everyday people to join this collaborative effort would be an important question to answer. Any ideas?

Why Future Warehouses May Look Like Monkey Houses

by Yu Gu, posted in Future, Ideas, Robotics, Uncategorized

The current-generation Amazon robot assisted warehouses are painfully boring to watch, once you realized how time, energy, and space inefficient they are. Each piece of merchandise has to travel on racks maybe thousands times heavier than itself, at a slow speed, through heavy traffic, while the majority of the warehouse volume (> 80%) is left unused.

Vision: I think most goods can be simply tossed up in the air by robots and be caught by other robots at distances. The future warehouses, which I would like to call them Monkey Houses, should be highly dynamic and densely filled with flying objects. It will improve the throughput of a same size warehouse by more than an order of magnitude and drastically reduce the energy consumption compared to the current systems.

Justification: while humans occasionally use throwing and catching for object handoff (e.g., sports), it is not generally considered as a reliable method, especially when there are multiple objects flying simultaneously. Robots, on the other hand (no pun intended), can be particularly good at this. This includes estimating object motion, performing fast and precise control actions for object catching, simultaneously tracking the trajectory of multiple flying objects, as well as communicating and coordinating with thousands other robots in making plans. With these super-human abilities (i.e., speed, precision, reliability, memory, and communication) of future robots, the engineering trades of future systems design often shift toward counter-(human)-intuitive directions.

More Detailed Vision: each rack in the warehouse will be a stationary robot that can throw and catch objects. Each type of object will have a g-loading rating, dictating how far it can fly in one hop (the packaging of some future goods may have to be redesigned to be better suitable for flying). The goods may go through multiple hops (i.e., catch and throw by robots in between) before reaching final destinations. All object information is shared and an air traffic management system will ensure objects flying pass each other with safe clearances. Like goods, small robots can also be tossed up in the air. They can intersect other flying objects to improve the flexibility of stationary rack robots…

Thinking beyond the warehouse settings, it is conceivable that the main mode of object handoff for robots in the future would be throwing and catching, once the reliability of such systems exceeds human’s capabilities. Compared to the continuous-contact object handoff between two robots, throwing and catching involves much less complex robot-robot interactions and thus is far simpler and robust for robots to perform. This would have many implications to the design of other future systems. For example drone delivery can be performed by throwing packages to balconies equipped with catching robots (or just baskets with nets). Battery changes for drones could be done by simply tossing batteries up and down. Exchange of cargos (and passengers) between two self-driving vehicles on the highway could be accomplished through the air. What other cool applications of robot throwing and catching can you think of?

Why Future Robots May Also be the Kind Ones

by Yu Gu, posted in Future, Ideas, Robotics

We all know that greedy gets us nowhere. We were all probably told by our moms to be kind (e.g., friendly, generous, and helpful), who were probably told by their moms, and so on. This crazy idea may be traced all the way back to some named or unnamed philosophers, but how can it make sense? Why should we hand out our precious resources (e.g., time, things, or even opportunities) to others in this hyper-competitive world? Why shouldn’t we calculate the costs and benefits of all our potential options and pick a move that maximize some sort of utility functions (e.g., money or advancement)? This is precisely what we do when playing chess or tennis, when there is no friends and only one opponent in the game. Nobody expects us to be generous there.

The reason is probably that we are not capable of making many meaningful calculations in life. Beyond a few artificially constrained games, we are severely under-actuated and underpowered creatures that are trying to navigate in the vast ocean of human society. Each decision that we made may not change that much how we move up or down in a long term. Instead, the movement of waves below us makes far greater a difference. With a very limited horizon, we have no way to know for sure what’s around us and what’s coming up next. How can we make a decision then? Moms told us to use heuristics that have been proven to make long-term stochastic sense (ok, not in these exact phrases), which are to be kind, friendly, generous, and helpful, among others.

Now, let’s take a minute to think about robots. Our robots today are greedy. They are self-interested, having a tunnel vision (not literately) of the world around them, and trying to maximize some sort of utility functions. They work well in structured environments that can be fully modeled, and are getting better by days in more complex settings. If we use a linear interpolation to predict the future, the robots will get smarter, more capable, and more selfish. This is probably why the internet is full of worries about our future with robots.

I think this is like saying all chess and tennis players are greedy, and we should be careful with them. The robots today are self-centered only because the way their working environment are set up to be. As moms of robots, we, roboticists have to teach our robots how to survive in the real complex world, a world that greedy gets them nowhere.

If the robots are going to be as intelligent as humans in the future, we should not expect them to be that different from us: there will be good robots, there will be bad ones, and there will be many in between ones.  And all these robots have to deal with good, bad, and in-between humans. It’s this enormous diversity that invalidates short-term and self-centric thinking, and makes it more important to be kind to others. Call me wishful thinking, and I don’t know if we should feel happy or sad about this, but the kind robots are probably the ones that eventually will replace us.