There are all sorts of gimmicky AI assistants out there. But Notebook Assistant isn’t one of them. It’s a serious, deep piece of new technology, and what’s more important, it’s really, really useful! In fact, I think it’s so useful as to be revolutionary. Personally, I thought I was a pretty efficient user of Wolfram Language—but Notebook Assistant has immediately made me not only significantly more efficient, but also more ambitious in what I try to do. I hadn’t imagined just how useful Notebook Assistant was going to be. But seeing it now I can say for sure that it’s going to raise the bar for what everyone can do. And perhaps most important of all, it’s going to open up computational language and computational thinking to a vast range of new people, who in the past assumed that those things just weren’t accessible to them. (View Highlight)
Leveraging the decades of work we’ve done on the design and implementation of the Wolfram Language (and Wolfram|Alpha), Notebook Assistant lets people just say in their own words what they want to do; then it does its best to crispen it up and give a computational implementation. Sometimes it goes all the way and just delivers the answer. But even when there’s no immediate “answer” it does remarkably well at building up structures where things can be represented computationally and tackled concretely. People really don’t need to know anything about computational language—or computational thinking to get started; Notebook Assistant will take their ideas, rough as they may be, and frame them in computational language terms. (View Highlight)
I’ve long seen Wolfram Language as uniquely providing the infrastructure and “notation” to enable “computational X” for all fields X. I’m excited to say that I think Notebook Assistant now bridges “the last mile” to let anyone—at almost any level—access the power of computational language, and “do computational X”. In its original conception, Wolfram Notebook Assistant was just intended to be “useful”. But it’s emerging as something much more than that; something positively revolutionary. (View Highlight)
“I can’t believe it’ll do anything useful with that”, I’ll think. But then I’ll try it. And, very often, something amazing will happen. Something that gets me past some sticking point or over some confusion. Something that gives me an unexpected new building block—or new idea—for what I’m trying to do. And that uses the medium of our computational language to take me beyond where I would ever have reached before. (View Highlight)
Now tell Notebook Assistant what you want to do. The more precise and explicit you are, the better. But you don’t have to have thought things through. Just type what comes into your mind. Imagine you’ve been working in a notebook, and (somehow) you’ve got a picture of some cats. You wonder “How can I find the cats in this picture?” Well, just ask Notebook Assistant! (View Highlight)
It seems a bit like magic. You say something vague, and Notebook Assistant turns it into something precise and computational—which you can then run. It’s not always as straightforward as in this example. But the important thing is that in practice (at least in my rather demanding experience) Notebook Assistant essentially always does spectacularly well at being useful—and at telling me things that move forward what I’m trying to do. (View Highlight)
Imagine that sitting next to you, you had someone very knowledgeable about Wolfram Language and about computational thinking in general. Think what you might ask them. That’s what you should ask Notebook Assistant. And if there’s one thing to communicate here, it’s “Just try it!” You might think what you’re thinking about is too vague, or too specific, or too technical. But just try asking Notebook Assistant. In my experience, you’ll be amazed at what it’s able to do, and how helpful it’s able to be. (View Highlight)
Maybe you’re an experienced Wolfram Language user who “knows there must be a way to do something”, but can’t quite remember how. Just ask Notebook Assistant. And not only will it typically be able to find the function (or whatever) you need; it’ll also usually be able to create a code fragment that does the very specific thing you asked about. And, by the way, it’ll save you lots of typing (and debugging) by filling in those fiddly options and so on just how you need them. And even if it doesn’t quite nail it, it’ll have given a skeleton of what you need, that you can then readily edit. (And, yes, the fact that it’s realistic to edit it relies on the fact that Wolfram Language represents it in a way that humans can readily read as well as write.) (View Highlight)
What if you’re a novice, who’s never used Wolfram Language before, and never really been exposed to computational thinking, or for that matter, “techie stuff” at all? Well, the remarkable thing is that Notebook Assistant will still be able to help you—a lot. You can ask it something very vague, that doesn’t even seem particularly computational. It does remarkably well at “computationalizing things”. Taking what you’ve said, and finding a way to address it computationally—and to lead you into the kind of computational thinking that’ll be needed for the particular thing you’re trying to do. (View Highlight)
There are some general themes, though. The most important is the way Notebook Assistant pivotally relies on the Wolfram Language. In a sense, the main mission of Notebook Assistant is to make things computational. And the whole reason it can so successfully do that is that it has the Wolfram Language as its target. It’s leveraging the unique nature of the Wolfram Language as a full-scale computational language, able to coherently represent abstract and real-world things in a computational way. (View Highlight)
One might think that the Wolfram Language would in the end be mainly an “implementation layer”—serving to make what Notebook Assistant produces runnable. But in reality it’s very, very much more than that. In particular, it’s basically the medium—the language—in which computational ideas are communicated. When Notebook Assistant generates Wolfram Language, it’s not just something for the computer to run; it’s also something for humans to read. Yes, Notebook Assistant can produce text, and that’s useful, especially for contextualizing things. But the most concentrated and poignant communication comes in the Wolfram Language it produces. Want the TL;DR? Just look at the Wolfram Language code! (View Highlight)
But there’s something else as well. With its symbolic character—and with all the coverage and consistency that we’ve spent so much effort on over the decades—the Wolfram Language is uniquely able to “communicate in fragments”. Any fragment of Wolfram Language code can be run, and more important, it can smoothly fit into a larger structure. And that means that even small fragments of code that Notebook Assistant generates can be used as building blocks. (View Highlight)
It produces Wolfram Language code. You read the code (and it’s critical that it’s set up to be read). You figure out if it’s what you want. (And if it’s not, you edit it, or ask Notebook Assistant to do that.) Then you can use that code as a robust building block in whatever structure—large or small—that you might be building. (View Highlight)
In practice, a critical feature is that you don’t have to foresee how Notebook Assistant is going to respond to what you asked. It might nail the whole thing. Or it might just take steps in the right direction. But then you just look at what it produced, and decide what to do next. Maybe in the end you’ll have to “break the problem down” to get Notebook Assistant to deal with it. But there’s no need to do that in advance—and Notebook Assistant will often surprise you by how far it’s able to get on its own. (View Highlight)
But how ambitious can what you ask Notebook Assistant be? What if you ask it something “too big”? Yes, it won’t be able to solve that 100-year-old problem or build a giant software system in its immediate output. But it does remarkably well at identifying pieces that it can say something about, and that can help you understand how to get started. So, as with many things about Notebook Assistant, you shouldn’t assume that it won’t be helpful; just try it and see what happens! And, yes, the more you use Notebook Assistant, the more you’ll learn just what kind of thing it does best, and how to get the most out of it. (View Highlight)
An important feature is that it is—in human terms—almost infinitely patient and hardworking. Where a human might think: “it’s too much trouble to write out all those details”, Notebook Assistant just goes ahead and does it. And, yes, it saves you huge amounts of typing. But, more important, it makes it “cheap” to do things more perfectly and more completely. So that means you actually end up labeling those plot axes, or adding a comment to your code, or coming up with meaningful names for your variables. (View Highlight)
One of the overarching points about Notebook Assistant is that it lowers the barrier to getting help. You don’t have to think carefully about formulating your question. You don’t have to go clicking through lots of links. And you don’t have to worry that it’s too trivial to waste a coworker’s time on the question. You can just ask Notebook Assistant. Oh, and it’ll give you a response immediately. (And you can go back and forth with it, and ask it to clarify and refine things.) (View Highlight)
As an experienced user of Wolfram Language, a simple “do it with FoldList” would already have been enough. But Notebook Assistant goes all the way—generating specific code for exactly what I asked. Courtesy of Wolfram Language, the code is very short and easy to read. But Notebook Assistant does something else for one as well: it produces an example of the code in action—which lets one check that it really does what one wanted. Oh, and then it goes even further, and tells me about a function in the Wolfram Function Repository (that I, for one, had never heard of; wait did I write it?) that directly does the operation I want. (View Highlight)
There’s an incredible amount of functionality built into the Wolfram Language (yes, four decades worth of it). And quite often things you want to do can be done with just a single Wolfram Language function. But which one? One of the great things about Notebook Assistant is that it’s very good at taking “raw thoughts”, sloppily worded, and figuring out what function you need. Like here, bam, “use LineGraph!” (View Highlight)
What we’ve seen so far are a few examples of asking Notebook Assistant to tell us how to do things. But you can also just ask Notebook Assistant to do things for you, in effect producing “finished goods”: (View Highlight)
OK, so Notebook Assistant provides a very powerful way to go from words to computational results. So what then is the role of computational language and of “raw Wolfram Language”? First of all, it’s the Wolfram Language that makes everything we’ve seen here work; it’s what the words are being turned into so that they can be computed from. But there’s something much more than that. The Wolfram Language isn’t just for computers to compute with. It’s also for humans to think with. And it’s an incredibly powerful medium for that thinking. Like a great generalization of mathematical notation from the distant past, it provides a streamlined way to broadly formalize things in computational terms—and to systematically build things up. (View Highlight)
Now that I’ve been using Notebook Assistant for a while I think I can say that on quite a few occasions it’s helped me launch things, it’s helped me figure out details, and it’s helped me debug things that have gone wrong. But the backbone of my computational progress has been me writing Wolfram Language myself (though quite often starting from something Notebook Assistant wrote). Notebook Assistant is an important new part of the “on ramp” to Wolfram Language; but it’s raw Wolfram Language that lets one really zoom forward to build new structures and achieve what’s computationally possible. (View Highlight)
Computational thinking is an incredibly powerful approach. But sometimes it’s hard to get started with, particularly if you’re not used to it. And although one might not imagine it, Notebook Assistant can be very useful here, essentially helping one brainstorm about what direction to take. (View Highlight)
Obviously this isn’t the end of the story, but it’s a remarkably good beginning—going from a vague request to something that’s set up to be thought about computationally. (View Highlight)
