State of the Farm: 2023 Spring Cleanup

Some farms are pretty.

 

It’s mid-April and as I write this the temperature outside is approaching 90F—unusual up here in New England. Past experience has suggested that you don’t plant vulnerable crops until Memorial Day to avoid a frost but that rubric is pretty much gone. Spring has been coming earlier every year for some time to the point we sometimes get a Hammer of God Heat Wave in May.

 

But not in April. Until this week when it nearly reached ninety. Today is, mercifully, cooler but not all that much. After today, it’s supposed to move back towards normal: 50-60F during the day and in the 40s at night. Still warm by “normal” standards but in the ball park. Recall the April Fool’s Day Blizzard back in 1997 when three feet of snow dropped on us. Believe it or not, that was closer to normal.

 

Weather in recent years has been a more warmish April, warm May, miserable cold and wet late May-early June followed by a more or less hot summer towards the end of September. In 1979, when I first moved up here, there was a hint of cold in the middle of August and September was quite cool. That ship has sailed.

 

Anyway, early spring means early cleanup.

 

I have this idea of farms as working environments that are kept up for utilitarian reasons rather than esthetics. The barn is painted but there’s always some repair work needed. Equipment is stored in various places until needed. That sort of thing. I don’t mean we have trucks up on blocks serving as chicken houses or anything but sometimes things get away from us.

 

This makes spring cleanup an exercise in discouragement.

 

I mean, by now the place has been trashed by winter, even if the winter was extraordinarily mild. And there is no reason to do the cleanup in January because it’s just going to get trashed all over again. Been there. Done that.

 

That said, sometimes we go down into western Pennsylvania on the border of Amish Country and I feel ashamed. Those farms are beautiful. As precise and square as if they were outline by plumb lines and T-squares. I remember my cousins’ farms and they were pretty, too.

 

We’ve cleared up the big downed tree limbs but there remains an enormous amount of small debris. Things that we blithely left out in the fall now glare at us, daring us to clean them up. The grass hasn’t really started growing back and the lawn looks like it’s been flattened by a roller. Not to mention, I have about three tons of hickory wood to split and pile. Right now, it’s holding down the ground next to the driveway.

 

Over the course of the winter, things accumulate. Bits of trash blow over from garbage removal and get trapped in the lawn or buried under the snow. That needs to be cleaned up. We have a little dog and in the winter she makes her deposits on the lawn. Anything that hasn’t melted into the grass has to be policed. The compost added to the composter over the winter has suddenly woken up and made itself known. It’s time for the spring mucking of the chicken house.

 

And we’re still in drought.

 

I know it’s not so declared in the news but that doesn’t change things. At this time, in a “normal” year, the main garden is too wet to till. Not so, this year. We have a wet basement that sumps out every few hours depending on the rain and the water table. While I was tilling, every half an hour it poured five or ten gallons into the soil only for it to disappear. This ground is thirsty.

 

My mother and father were both from farming families. He, from Missouri, and she, from New Mexico. The farming wisdom was wildly different between them to the point that Missouri farmers planted in the top of the furrow to prevent seeds from being washed away while New Mexico farmers planted in the furrow so the seeds got as much water as possible. Mom had a phrase she used: “In the spring, when the land rises,” that struck me. When the rains came, the land absorbed the water and swelled.

 

We’ve seen it here. Our land is built on ledge and bits peek up here and there. We can tell how wet the ground is by how much rock is showing. This spring a lot of rock is showing.

 

Sigh. Musn’t grumble.

 

We got the tilling done. Most years we don’t till. We put down mulch and work around it. But last year the ground was getting hard. What we should have done was pick up a ton or so of horse manure and spread it over the garden, wait for it to season, and till that in. But we didn’t. We were lazy.

 

This year, we cleaned up the garden, tilled it, added a little chemical fertilizer—as an experiment since we’ve never done this—and then raked the whole thing flat. Today, I plan on going out there and plant some peas. I’m still too nervous to really start the garden six weeks early. But peas and carrots should be fine.

 

We have two new Birdie boxes coming on line this year. One is to hold potatoes—we had good luck last year doing that until the rodents figured out how to burrow inside. Since the bottom four inches of the new boxes is filled with heavy gravel, we have hopes for this year. The other one is to grow strawberries. We haven’t yet decided what to do with last year’s Birdie box.

 

We’re not planning to plant corn this year—which makes me sad. I just like growing corn. But we have enough stored kernels we don’t need it. We’re going to try for calories: potatoes, beans, squash, peas, and the like. The drought last year was so bad over so much of the country, I’ll feel better if we have our own calorie source.

 

We’re also going to try fence panel trellises. Cattle fencing comes in panels that range in size. The panels we’re looking at are 50 inches x 16 feet. The, you bend the panel lengthwise into an arch shape and secure the bottom with landscape stakes. The arch shape should be good to grow things like cucumbers, squash, or beans. We’re getting six of them to see how they work.

 

The hardest part will be transporting them home. 16 feet is long. I’m renting a trailer. Stay tuned.

 

Many of the trees are leafing out. The pears and stone fruits look heavy with buds. If we don’t have a freeze, we might get a good crop of pears and a few peaches. The persimmon looks happy, though as yet unleafed,  which is a big improvement. We got nearly nothing last year.

 

We replaced the line of plums with a line of quinces. But the falling hickory broke off one. It’s growing back so we will see. The northernmost quince looked fine and then one day just fell over. I don’t know what happened to it but we’re replacing it anyway. The Cornelian Cherries are covered with yellow blossoms and the cherry tree looks like it’s about to explode.

 

The apples look like they’re about to be eaten by caterpillars so I’ll be spraying them soon. Three of the four paw-paws have flower buds so I’m hoping for many, many paw-paws. I would love to have the problem of having so many that I have to figure out how to store them.

 

We planted a couple of new fruit trees last year and, with the exception of the quince, they look like they survived.

 

That’s all for now. I’m going out to plant peas.

 

Chatbots vs Actual Intelligence

Everybody else is weighing in on the chatbot revolution. I guess it’s my turn. 

 

(Picture from here.)

 

ChatGPT, and the other “AI” tools that have been showing up lately, do not conform to what I would call actual intelligence. They are extremely good and predictive models of human generated text. Their ability to sound nearly human should not be surprising—they’ve been trained across the largest single repository of human generated text in the history of human beings. Their abilities were fine tuned with help from human beings. The training reward structure was generated by more human beings. Policy updates of the system are evaluated using mechanisms that were—you guessed it—based on human input.

 

Given all of that, is it a surprise that it kind of sounds like a human being? That when we ask it a question, it returns an answer that resembles a human response?

 

Add in the way that humans project humanity onto anything with the remotest similarity—a face on a piece of toast, for example—and we get ChatGPT.

 

I am not saying that ChatGPT—and Bard and the others—is not a lovely piece of work. I’m saying it’s a sophisticated chatbot, where the term “chat” is defined in the broadest possible manner. In this context, “chat” includes narrative, essays, poems, and computer code. In short, whatever ChatGPT trained on.

 

We like to consider ourselves sentient—capable of feeling. This is the ability to directly experience the world, from joy to suffering. Humans have added additional intellect and consciousness. Not all animals have these two additional qualities but I will not itemize that here.

 

For humans, all three of these qualities are mixed together. It’s hard for us to understand how a cat or dog function without somehow imbuing them with our own humanity. We forget a dog, for example, is not a human being and treat it as if it were. Carnivora—the order containing dogs and cats—last common ancestor with primates predates the end of the dinosaurs. Yet, both groups clearly have the ability to feel and to suffer. That is common between humans and their pets.

 

It’s quite possible that neurological sophistication beyond a certain point requires something internal to experience the world. Certainly, it’s not just the province of mammals—the stem group that evolved into birds split from the stem group that evolved into mammals much further back than carnivores and primates. But it’s fairly clear birds can suffer.

 

They can think, too, but use a different mechanism. Mammals use the neocortex for our intelligence. But the neocortex evolved after the split so bird intelligence must use a different part of the brain than mammals to get similar effects.

 

I would go so far as to say cephalopods share the same quality of personal experience. They are clearly intelligence but cephalopods diverged from vertebrates before brains evolved.

 

None of that applies to ChatGPT.

 

ChatGPT’s underlying “hardware” is a neural net, an architecture that is inspired by a simplified model of the neuron networks in biological systems. It is excellent at learning and responding to patterns—which, in a large sense, is what ChatGPT is doing. The underlying ChatGPT structure resembles a slice of a brain but not a brain in and of itself.

 

It is possible that a more sophisticated system—one that resembles more than just a slice of a brain—might actually have sentience. It’s certainly possible with sufficient computing power and understanding that a vertebrate brain could be simulated in a machine. Whole SF novels have been written on the idea. But at that point, it’s a brain, not a machine. It would have personal experience because we simulated it to do so. I don’t think that’s necessarily a good thing—a brain in a box would have the ability to suffer.

 

A more interesting experiment would be not to create a vertebrate brain, but use a cephalopod model. Cephalopods are very smart and appear to have personal experience but their brains do not resemble vertebrate brains at all. Possibly, we might get some understanding of how personal experience originates.

 

But it’s not ChatGPT.

 

One area where ChatGPT becomes interesting is not how well it performs but the intricate ways it fails. It generates language but it cannot think—it has no sense of the meaning of what it generates. A paper submitted in January goes so far as to suggest we are asking language to represent thought and it is insufficient to the task.

 

Years ago, Alan Turing suggested the imitation game (also called the Turing Test) as a measure of machine intelligence. The test consisted of a researcher interacting with two other individuals, one of which was a machine, via a text conversation. If the two were indistinguishable from one another, the machine would be deemed to be as intelligent as a human.

 

ChatGPT satisfies this test for a significant duration. However, we know from its mistakes that it is not equivalent to human intelligence. This suggests that the original Turing Test, with its dependence on language, cannot reflect an accurate evaluation of the “humanness” of the machine. (This is further discussed here.)

 

In this respect, ChatGPT has no more sentience than a crescent wrench—one of the world’s most useful tools.

 

I suspect that meaning derives from sentience. That is, without direct personal experience, attribution of meaning to words is suspect. (That said, it’s still suspect since individual personal experience is unique between individuals.) The phrase, “I want to be free,” cannot be evaluated without knowing the personal experience of the person that utters it. Even further, can any such utterance be understood without knowing something of the personal experience of the speaker? What does “I want to be free” mean from a human in China? In Seattle? In 2023? In 1862? For that matter, what does it mean when spoken by a dog or a cat? Or ChatGPT?

 

Regardless, ChatGPT—and its relatives—do present us with some interesting problems. For one, ChatGPT presents narrative that is without verification. Yet, these chatbots are being included in systems that we use—fabricating material is a bad thing here.

 

Consider search—the reason for existence of Google and Bing. How many times have we had the experience of looking for a search term, picking the most likely link, and then find out the search term does not exist at the site? This is verification. Frustrating but necessary.

 

ChatGPT presents compelling narrative that may or may not be true, may or may not be entirely fabricated. Including it in a search tool is absurd. Unless, of course, you do not want that search tool to be usable.

 

There are incredibly intelligent AI systems out there in medical diagnosis, protein analysis, and other computationally difficult arenas. They deliver results that are then verified prior to use. Narrative chatbots need such mechanisms.

 

Another interesting issue is how well ChatGPT generates usable material. It has, for example, passed several tests including the bar exam, AP biology, and the SAT. It has written passable software code. It has written essays—with the caveat of verification noted above.

 

When I read this, the first thought was that these tests had failed in their purpose to evaluate a human’s knowledge of the subject. It showed that these tests revealed no human ability other than the taking of tests—something that has been argued for some time.

 

Like the paper above dissociating language from thought, we need to do the same. The ability to use thoughtful language well is valuable. The ability to use language well without thought is less so.