A machine can now not only beat you at chess, it can also outperform you in debate. Last week, in a public debate in San Francisco, a software program called Project Debater beat its human opponents, including Noa Ovadia, Israel's former national debating champion.

Brilliant though it is, Project Debater has some weaknesses. It takes sentences from its library of documents and prebuilt arguments and strings them together. This can lead to the kinds of errors no human would make. Such wrinkles will no doubt be ironed out, yet they also point to a fundamental problem. As Kristian Hammond, professor of electrical engineering and computer science at Northwestern University, put it: "There's never a stage at which the system knows what it's talking about."

What Hammond is referring to is the question of meaning, and meaning is central to what distinguishes the least intelligent of humans from the most intelligent of machines. A computer works with symbols. Its program specifies a set of rules to transform one string of symbols into another. But it does not specify what those symbols mean. Indeed, to a computer, meaning is irrelevant. Humans, in thinking, talking, reading and writing, also work with symbols. But for humans, meaning is everything. When we communicate, we communicate meaning. What matters is not just the outside of a string of symbols, but the inside too, not just how they are arranged but what they mean.

Meaning emerges through a process of social interaction, not of computation, interaction that shapes the content of the symbols in our heads. The rules that assign meaning lie not just inside our heads, but also outside, in society, in social memory, social conventions and social relations. It is this that distinguishes humans from machines. And that's why, however astonishing Project Debater may seem, the tradition that began with Socrates and Confucius will not end with artificial intelligence.

Like most of us, I try to be mindful of food that goes to waste. The arugula (芝麻菜) was to make a nice green salad, rounding out a roast chicken dinner. But I ended up working late. Then friends called with a dinner invitation. I stuck the chicken in the freezer. But as days passed, the arugula went bad. Even worse, I had unthinkingly bought way too much; I could have made six salads with what I threw out.

In a world where nearly 800 million people a year go hungry, "food waste goes against the moral grain," as Elizabeth Royte writes in this month's cover story. It's jaw-dropping how much perfectly good food is thrown away — from "ugly" (but quite cat able) vegetables rejected by grocers to large amounts of uneaten dishes thrown into restaurant garbage cans.

Producing food that no one eats wastes the water, fuel, and other resources used to grow it. That makes food waste an environmental problem. In fact, Royte writes," if food waste were a country, it would be the third largest producer of greenhouse gases in the world. "

If that's hard to understand, let's keep it as simple as the arugula at the back of my refrigerator. Mike Curtin sees my arugula story all the time — but for him, it's more like 12 boxes of donated strawberries nearing their last days. Curtin is CEO of DC Central Kitchen in Washington. D.C., which recovers food and turns it into healthy meals. Last year it recovered more than 807, 500 pounds of food by taking donations and collecting blemished (有瑕疵的) produce that otherwise would have rotted infields. And the strawberries? Volunteers will wash, cut, and freeze or dry them for use in meals down the road.

Such methods seem obvious, yet so often we just don't think. "Everyone can play a part in reducing waste, whether by not purchasing more food than necessary in your weekly shopping or by asking restaurants to not include the side dish you won't eat." Curtin says.

Can a small group of drones（无人机）guarantee the safety and reliability of railways and, at the same time, help railway operators save billions of euros each year? That is the very likely future of applying today's "eyes in the sky" technology to making sure that the millions of kilometres of rail tracks and infrastructure（基础设施）worldwide are safe for trains on a 24/7 basis.

Drones are already being used to examine high-tension electrical lines. They could do precisely the same thing to inspect railway lines and other vital aspects of rail infrastructure such as the correct position of railway tracks and switching points. The more regularly they can be inspected, the more railway safety, reliability and on-time performance will be improved. Costs would be cut and operations would be more efficient（高效）across the board.

That includes huge savings in maintenance costs and better protection of railway personnel safety. It is calculated that European railways alone spend approximately 20 billion euros a year on maintenance, including sending maintenance staff, often at night, to inspect and repair the rail infrastructure. That can be dangerous work that could be avoided with drones assisting the crews' efforts.

By using the latest technologies, drones could also start providing higher-value services for railways, detecting faults in the rail or switches, before they can cause any safety problems. To perform these tasks, drones for rail don't need to be flying overhead. Engineers are now working on a new concept: the rail drones of the future. They will be moving on the track ahead of the train, and programmed to run autonomously. Very small drones with advanced sensors and AI and travelling ahead of the train could guide it like a co-pilot. With their ability to see ahead, they could signal any problem, so that fast-moving trains would be able to react in time.