How to use Jabref as a Zettelkasten

The quick answer is, that there is no way in doing so, but let us imagine the workflow from a theoretical standpoint. The jabref software allows to manage a bibtex file which includes to add new entries and push the bibtex key to the lyx software. Also it provides the ability to search for dubplicates and can search in the database for any field. This makes jabref a powerful bibliography manager which can be recommneded to latex and lyx users as well.

Unfortunately, it has little or no support for handling notes created by the user while he is reading documents. Suppose somebody has found an interesting pdf paper and would like to write down 3-5 important short sentences what was written in the article. The jabref software has similar to the bibtex standard a field “Note” which allows to formulate free text. In the screenshot the sentence “The quick brown fox jumps over the lazdy dog” was entered.

The problem is, that the field is only one under many. It is a detail feature within the bibtex ecosystem. It can't store bold formatting, it can store images, tables and it is not possible to link from one note to another. The chance is high that most users doesn't even know about this field, most bibtex database were created with additional notes.

On the other hand, for a single user who writes a paper it is very important to annotate a reference. It is the core element of active reading and nearly all common place books are created around personal notes of the users. It is unfair to blame the jabref software for the low quality notes field, because the underlying bibtex standard doesn't support it as well. A more realistic attempt to describe the situation is by recognizing that note taking was mostly ignored in the past. There are wonderful software programs available to format a document like latex and powerful frontends like lyx and jabref but what is missing is the ability to create a personal knowledge management database. The only program which goes in this direction is the emacs org-mode which was introduced in 2003. [1]

[1] Johnson, Timothy. "Emacs as a Tool for Modern Science." Johnson Matthey Technology Review (2022).

A rough description of the perplexity.ai chatbot

 

In contrast to the famous chatgpt software, the perplexity.ai chat is less known. It's main advantage is, that everybody can use it. Similar to chatgpt, it is difficult to get concrete information how the algorithm is working in the background. Somewhere it was mentioned, that the same gpt3 language model was used which says anything and nothing. The more interesting question is what are the limits of the chatbot? Is AI really new technology or is the hype around chatgpt exaggerated?

In contrast to a search engine like Google, the perplexity.ai software is a Q&A software and can answer queries formulated in natural English. To make the difference clear, we have to describe first what the limits of a normal search engine are. Suppose the user enters two and more keywords into the input field:

word1 AND word2 AND word3

In many cases the result list will become empty because a website contains only of two of the words, but not three of them. The google search engine can't guess what the user is asking for but the result page is generated with normal non AI technology.

In contrast, a Q&A software is converting the internet and the user request into a numerical vector and then searches for the best matching. So it is basically a neural network which understands English. This allows to parse and generate the information more robust.

Some years ago there was the “Wolfram Alpha” search engine which has promised to revolutionize online search but a detailed investigation has shown the limits of the project. So let us try what the perpelexity.ai is able to do.

The basic question for any Q&A software is a simple YES/NO question like, is the ocean blue, is the sun yellow and is pizza a food. The chatbot answers all of them correctly and gives smart additional information.

The next iteration is a more complicated request like “What is 10/3?” “Which books were written by Hemingway?” “When was the computer invented?” All these questions were answered by the chatbot with ease. The assumption is that the better known chatgpt is also capable of this sort of tasks.

So we can say, that the perplexity.ai chatbot is the first working q&a webseite which produces high quality output.

Let us take a look at the more serious part which is about possible failure of the software. What the perpelxity.ai software can't do is to write longer stories. All the output is limited to 3-5 sentences. Also the software can't tell a joke but it will provide only the URL to a website which hosts some jokes. In addition the chatbot can't display images and in most cases the answers explaining only the surface of a topic but not the detail information.

What perplexity.ai and chatgpt have demonstrated is, that from a technically side it is possible to program a Q&A website which is more powerful than a traditional search engine.

But let us go back to more basic tasks. The chatbot can list the major books written by hemmingway. In contrast to the google search engine it is not showing a website somewhere in the internet and it is not redirecting the user to Wikipedia which has the same list. But the chatbot prints out the information in his own words. For the untrained user this sounds like magic

To understand the difference to a chatbot from the past let us ask the same question to the Cleverbot chatbot:

Human: Which books were written by Hemingway?

Cleverbot: I don't remember.

Human: Again, Which books were written by Hemingway?

Cleverbot: What do you mean I was written?

Human: Hemingway list of books

Cleverbot: What is your favourite book?

Such kind of interaction was normal for pre chatgpt software. The software is using a predefined set of answers and can't answer concrete questions for facts.

In contrast, the perplexity.ai chat bot can parse the question and gives the correct answer. And it can so for a slightly different question as well.

This might explain why the chatgpt software has gained strong attention in the internet. Because the beta testers are surprised how powerful the software is and they want to know what the limits are. One possible answer is, that the engineers themself doesn't know the answer. A likely comparison is to describe chatgpt as some sort of chess playing engine which is able to beat the strongest human player in the world. It was difficult to accept for humans that computers can play better chess and some journalists have argued that the AI isn't understanding on a deep level what chess is about. Perhaps it is possible to give the same argument for modern Q&A website. On a technical level the machine can only process numbers but has no understanding what the meaning is.

The ability to process natural language is usually seen as a sign of intelligence. In most exams the students are asked to answer easier and more difficult questions formulated in English. In a typical exam about computer science a possible list of question would look like:

Who has invented the TeX software?

What is a c compiler?

Explain the advantages of object oriented programming.

How does the A* algorithm works.

Most students can't answer all these questions correct but only a fraction of them. The teacher will read the answer and determines the score and then the human students gets a certain review. Suppose a computer program is able all these question correctly, does this mean that the AI is on the same level like a human student? What we can say is, that AI is able to imitate humans in a surprisingly high level.