Summarizing Legal Documents for Different Personas Using AI21 Studio

Create your own custom summarizer using AI21 Studio's large language models. This tutorial demonstrates the process on legal documents.

We’ve all experienced reading long, tedious, and boring pieces of text - financial reports, legal documents, or terms and conditions (though, who actually reads those terms and conditions to be honest?).

Imagine a company that employs hundreds of thousands of employees. In today's information overload age, nearly 30% of the workday is spent dealing with documents. There's no surprise here, given that some of these documents are long and convoluted on purpose (did you know that reading through all your privacy policies would take almost a quarter of a year?). Aside from inefficiency, workers may simply refrain from reading some documents (for example, Only 16% of Employees Read Their Employment Contracts Entirely Before Signing!).

This is where AI-driven summarization tools can be helpful: instead of reading entire documents, which is tedious and time-consuming, users can (ideally) quickly extract relevant information from a text. With large language models, the development of those tools is easier than ever, and you can offer your users a summary that is specifically tailored to their preferences.

Let's take legal documents, for example. Though they are written in English, many people find legal documents to be difficult to comprehend, as if they were actually written in a foreign language. Moreover, the interesting parts of each document may differ depending on the person who reads it, so off-the-shelf summarization tools may be too general or too specific. As an example, let's look at the involved personas:

Lawyers. They are interested in several key points, but legal language and terms are especially relevant to them.
Your average Joe. Doesn’t understand all the legal terms, and really wants to get the gist in simple words.

Using the IRS as our example, we will demonstrate here how to build a simple summarizer for those 2 personas, and discuss which future directions one should consider.

Working with large language models

Large language models naturally follow patterns in input (prompt), and provide coherent completion that follows the same patterns. For that, we want to feed them with several examples in the input ("few-shot prompt"), so they can follow through. The process of creating the correct prompt for your problem is called prompt engineering, and you can read more about it here.

Collecting data

Ideally, you should have a variety of examples to draw from. It is important that those examples represent the actual documents that your summarizer should work on. This means they should be written in the same way as real world documents, and they should be as varied as possible.

Don't have it? No need to worry - large language models generalize exceptionally well, so the results will still be good. In the end, optimal results can always be achieved with proper data - but you can revisit this at a later date.

Summarize for lawyers

If you are summarizing legal documents for lawyers, you should definitely maintain all legal terms from the original document. In this demonstration, we will work on the opening paragraphs of legal letters.

Here is an example of a few-shot prompt:

You will now be presented with a part of a legal letter. Read it and summarize it. Make sure the summary maintains formal terms.
Letter:
Dear [Name],
This letter responds to your authorized representatives’ letter of May 19, 2022, and subsequent correspondence, requesting rulings regarding the income, estate, gift, and generation-skipping transfer (GST) tax consequences of the proposed division of Trust 1.
The facts and representations submitted are as follows:
Grandparent died on Date 1, leaving the residue of Grandparent’s probate estate in equal shares to Trust 1 and Trust 2, testamentary trusts established under Will. Trust 1 is held for the benefit of Grandchild 1 and Grandchild 1’s descendants, and Trust 2 is held for the benefit of Grandchild 2 and Grandchild 2’s descendants. Grandchild 1 has five children, Great-Grandchild 1, Great-Grandchild 2, Great-Grandchild 3, GreatGrandchild 4, and Great-Grandchild 5. Grandchild 2 has one child, Great-Grandchild 6. Neither Grandchild 1 nor Grandchild 2 has any deceased children. Trustees serve as trustees of Trust 1. Trust 1 is the subject of this ruling request.
Section 9(a) of Trust 1 provides that Trustees may distribute the net income of Trust 1 to or for the benefit of Grandchild 1 and Grandchild 1’s descendants in such proportions and at such times as Trustees determine is desirable or necessary, considering their needs, best interests, and other sources of income, or may annually accumulate and add all or part of the net income to the principal of Trust 1.
Section 9(b) of Trust 1 provides that Trustees may distribute the principal of Trust 1 to or for the benefit of Grandchild 1 and Grandchild 1’s descendants in such proportions PLR-110419-22 3 and at such times as Trustees determine is desirable or necessary for their medical care, comfortable maintenance, education, or general support and welfare, considering their other resources.
Section 9(c) of Trust 1 provides that Trust 1 will terminate 21 years after the death of the survivor of Grandchild 1 and Grandchild 2, and the principal of Trust 1 will be distributed to Grandchild 1’s descendants, per stirpes. If, however, Grandchild 1 and Grandchild 1’s descendants all die before that date, Trust 1 will terminate early, and the principal of Trust 1 will be distributed to Trust 2.
Summary:
- Grandparent died and left the residue of his estate to Trust 1 and Trust 2, testamentary trusts established under Will. The trustees of Trust 1 want to divide the estate equally between Grandchild 1 and Grandchild 2.
- Section 9(a) of Trust 1 provides that Trustees may distribute the net income to Grandchild 1 and Grandchild 1's descendants in any proportion they determine is desirable.
- Section 9(b) of Trust 1 provides that Trustees may distribute principal to Grandchild 1 and Grandchild 1's descendants as they determine is desirable.
- Section 9(c) of Trust 1 provides that if Grandchild 1 and Grandchild 1's descendants all die before 21 years, Trust 1 will terminate early.
##
You will now be presented with a part of a legal letter. Read it and summarize it. Make sure the summary maintains formal terms.
Letter:
Dear [Name],
This letter ruling is in response to a request from your authorized representative dated March 11, 2022, and subsequent documentation requesting an extension of an additional five years under Internal Revenue Code (“IRC”) section 4943(c)(7) for disposing of certain excess business holdings. Taxpayer represents the facts as follows.
FACTS
Taxpayer was incorporated as a State nonprofit corporation. Taxpayer is exempt from federal income tax under IRC section 501(a) as an organization described in IRC section 501(c)(3) and is classified as a private foundation under IRC section 509(a). Taxpayer was created by Individuals to support the domestic and international Community and various charitable organizations. Individuals were substantial contributors to Taxpayer within the meaning of IRC section 507(d)(2), and therefore disqualified persons with respect to Taxpayer under IRC section 4946(a)(1)(A).
As a result of Individuals’ death, Taxpayer received A shares of Entity 1 common voting stock from Trust, a disqualified person, on Date 1, which Taxpayer represents is an unusually large testamentary gift or bequest. Additionally, on Date 2, Granddaughter, who is the granddaughter of one of the Individuals, and who serves as a co-trustee of Taxpayer, received a testamentary disposition from Trust of B shares of Entity 1 common voting stock. Granddaughter is also a disqualified person under IRC section 4946. The combined shares of Taxpayer and Granddaughter represent approximately C percent of Entity 1’s outstanding capital stock and are a minority interest in Entity 1. As a result of the testamentary gift or bequest of the A shares, Taxpayer has excess business holdings of Entity 1 under IRC section 4943(c)(1).
On Date 3, also as a result of Individuals’ death, Taxpayer received from Trust an approximate Z percent membership interest in Entity 2, an LLC, which taxpayer represents is an unusually large testamentary gift or bequest. As a result of the testamentary gift or bequest of the LLC membership interest, which is a minority interest, Taxpayer has excess business holdings of Entity 2 under IRC section 4943(c)(1).
Summary:
- A taxpayer requested an extension of five years under IRC section 4943(c)(7) for disposing of certain excess business holdings.
- A testamentary gift of stock to Taxpayer and a testamentary disposition to Granddaughter, both disqualified persons, resulted in Taxpayer having excess business holdings of Entity 1 under IRC section 4943(c)(1).
- On Date 3, Taxpayer received an unusually large testamentary gift or bequest of an LLC membership interest, which is an excess business holding.
##
You will now be presented with a part of a legal letter. Read it and summarize it. Make sure the summary maintains formal terms.
Letter:
Dear [Name],
This letter responds to a letter dated March 15, 2022, submitted on behalf of S Corporation Target, Purchaser, and Shareholder (collectively, the "Parties"), requesting an extension of time under §301.9100-3 of the Procedure and Administration Regulations to file an election. The Parties are requesting an extension of time to file the election statement under §1.336-2(h)(3)(iii) of the Income Tax Regulations (the "Election Statement") with respect to Purchaser's acquisition of all the stock of S Corporation Target from Shareholder on Date 1. The material information submitted is summarized below.
On Date 1, Purchaser acquired all the stock of S Corporation Target from Shareholder (the "Stock Disposition"). It has been represented that the Stock Disposition qualified as a "qualified stock disposition" as defined in §1.336-1(b)(6).
The Parties intended to make a section 336(e) election for the Stock Disposition but, for various reasons, a timely election was not fully made. Subsequently, this request was submitted, under §301.9100-3, for an extension of time to file the Election Statement. The Parties each represented that they are not seeking to alter a return position for which an accuracy-related penalty has been or could be imposed under section 6662.
Regulations promulgated under section 336(e) permit certain sales, exchanges, or distributions of stock of a corporation to be treated as asset dispositions if: (1) the disposition is a "qualified stock disposition" as defined in §1.336-1(b)(6); and (2) a section 336(e) election is made.
Summary:

And the completion:

- The Parties requested an extension of time under §301.9100-3 of the Procedure and Administration Regulations to file an election.
- The Parties are requesting an extension of time to file the Election Statement with respect to Purchaser's acquisition of all the stock of S Corporation Target from Shareholder on Date 1.
- The Parties represented that they are not seeking to alter a return position for which an accuracy-related penalty has been or could be imposed under section 6662.
##

Notes

It is wise to try several phrasings for your prompt. You can, for instance, keep it simple and direct by writing:

Summarize the following part of a legal letter while maintaining formal terms.
Letter:
[LETTER]
Summary:

Alternatively, you can take a more elaborate approach, such as:

You are LegalAI, an AI legal assistant that excels at summarizing legal documents.
Below you will find part of a legal letter. Read it and summarize it. Make sure the summary maintains formal terms.
Letter:
[LETTER]
Summary:

As you can see, we are providing the model with several examples, separated by a stop sequence, which is easily spotted while reading the text. You can read more about stop sequences here.
Because this task requires high accuracy, we recommend working at a low temperature. It's best to explore the range of 0.0-0.3, since temperature 0 does tend to produce short summaries. You can read more about temperature here.
You can test several options for the prompt in our playground.
There is a consistent structure to all the examples in the prompt. This few-shot prompt can be created using the following code (assuming you have the paragraphs and summaries):

def make_single_example(letter, summary):
    example = "You will now be presented with a part of a legal letter. Read it and summarize it. Make sure the summary maintains formal terms.\n"
    example += "Letter:\n"
    example += letter
    example += "\n"
    example += "Summary:\n"
    example += summary
    
    return example

# This is the stop sequence
SEPARATOR = "\n##\n"

FEW_SHOT_PREFIX = SEPARATOR.join(
    make_single_example(letter, summary) for letter, summary in zip(letters, summaries)
)

def make_few_shot_prompt(letter):
    
    return FEW_SHOT_PREFIX + SEPARATOR + make_single_example(letter, '') # keep the summary empty and let the model complete

Summarize for the average Joe

Despite the fact that there are over 1.3 million lawyers in the United States alone, most people (still) aren't lawyers and have trouble understanding legal documents. In this case, we probably want the summary to be written in a simple, easy-to-understand manner.

As this task involves both summarizing and simplifying texts, it is inherently more difficult. Thus, we will probably need more "shots" in our few-shot prompt (in this case, we added another example to the prompt).

Here is an example of a few-shot prompt:

You will now be presented with a part of a legal letter. Read it and summarize it. Make sure the summary is short and written in simple words.
Letter:
Dear [Name],
This letter responds to your authorized representatives’ letter of May 19, 2022, and subsequent correspondence, requesting rulings regarding the income, estate, gift, and generation-skipping transfer (GST) tax consequences of the proposed division of Trust 1.
The facts and representations submitted are as follows:
Grandparent died on Date 1, leaving the residue of Grandparent’s probate estate in equal shares to Trust 1 and Trust 2, testamentary trusts established under Will. Trust 1 is held for the benefit of Grandchild 1 and Grandchild 1’s descendants, and Trust 2 is held for the benefit of Grandchild 2 and Grandchild 2’s descendants. Grandchild 1 has five children, Great-Grandchild 1, Great-Grandchild 2, Great-Grandchild 3, GreatGrandchild 4, and Great-Grandchild 5. Grandchild 2 has one child, Great-Grandchild 6. Neither Grandchild 1 nor Grandchild 2 has any deceased children. Trustees serve as trustees of Trust 1. Trust 1 is the subject of this ruling request.
Section 9(a) of Trust 1 provides that Trustees may distribute the net income of Trust 1 to or for the benefit of Grandchild 1 and Grandchild 1’s descendants in such proportions and at such times as Trustees determine is desirable or necessary, considering their needs, best interests, and other sources of income, or may annually accumulate and add all or part of the net income to the principal of Trust 1.
Section 9(b) of Trust 1 provides that Trustees may distribute the principal of Trust 1 to or for the benefit of Grandchild 1 and Grandchild 1’s descendants in such proportions PLR-110419-22 3 and at such times as Trustees determine is desirable or necessary for their medical care, comfortable maintenance, education, or general support and welfare, considering their other resources.
Section 9(c) of Trust 1 provides that Trust 1 will terminate 21 years after the death of the survivor of Grandchild 1 and Grandchild 2, and the principal of Trust 1 will be distributed to Grandchild 1’s descendants, per stirpes. If, however, Grandchild 1 and Grandchild 1’s descendants all die before that date, Trust 1 will terminate early, and the principal of Trust 1 will be distributed to Trust 2.
Summary:
The purpose of this letter is to describe a trust set up by a grandparent for the benefit of their grandchildren and great-grandchildren. The trustees may distribute money from the trust, but they must follow certain rules. After 21 years, the trust will end, and the remaining money will be distributed to the main beneficiary's descendants. If all the descendants of the main beneficiary pass away before then, the remaining money will be transferred to another trust.
##
You will now be presented with a part of a legal letter. Read it and summarize it. Make sure the summary is short and written in simple words.
Letter:
Dear [Name],
This letter ruling is in response to a request from your authorized representative dated March 11, 2022, and subsequent documentation requesting an extension of an additional five years under Internal Revenue Code (“IRC”) section 4943(c)(7) for disposing of certain excess business holdings. Taxpayer represents the facts as follows.
FACTS
Taxpayer was incorporated as a State nonprofit corporation. Taxpayer is exempt from federal income tax under IRC section 501(a) as an organization described in IRC section 501(c)(3) and is classified as a private foundation under IRC section 509(a). Taxpayer was created by Individuals to support the domestic and international Community and various charitable organizations. Individuals were substantial contributors to Taxpayer within the meaning of IRC section 507(d)(2), and therefore disqualified persons with respect to Taxpayer under IRC section 4946(a)(1)(A).
As a result of Individuals’ death, Taxpayer received A shares of Entity 1 common voting stock from Trust, a disqualified person, on Date 1, which Taxpayer represents is an unusually large testamentary gift or bequest. Additionally, on Date 2, Granddaughter, who is the granddaughter of one of the Individuals, and who serves as a co-trustee of Taxpayer, received a testamentary disposition from Trust of B shares of Entity 1 common voting stock. Granddaughter is also a disqualified person under IRC section 4946. The combined shares of Taxpayer and Granddaughter represent approximately C percent of Entity 1’s outstanding capital stock and are a minority interest in Entity 1. As a result of the testamentary gift or bequest of the A shares, Taxpayer has excess business holdings of Entity 1 under IRC section 4943(c)(1).
On Date 3, also as a result of Individuals’ death, Taxpayer received from Trust an approximate Z percent membership interest in Entity 2, an LLC, which taxpayer represents is an unusually large testamentary gift or bequest. As a result of the testamentary gift or bequest of the LLC membership interest, which is a minority interest, Taxpayer has excess business holdings of Entity 2 under IRC section 4943(c)(1).
Summary:
A nonprofit organization asks for more time to sell extra stocks it received after the deaths of a few key contributors. Nonprofit organizations have a limit on how many stocks they can keep, so they request an extension to get rid of them.
##
You will now be presented with a part of a legal letter. Read it and summarize it. Make sure the summary is short and written in simple words.
Letter:
Dear [Name],
This letter responds to a letter dated March 15, 2022, submitted on behalf of S Corporation Target, Purchaser, and Shareholder (collectively, the "Parties"), requesting an extension of time under §301.9100-3 of the Procedure and Administration Regulations to file an election. The Parties are requesting an extension of time to file the election statement under §1.336-2(h)(3)(iii) of the Income Tax Regulations (the "Election Statement") with respect to Purchaser's acquisition of all the stock of S Corporation Target from Shareholder on Date 1. The material information submitted is summarized below.
On Date 1, Purchaser acquired all the stock of S Corporation Target from Shareholder (the "Stock Disposition"). It has been represented that the Stock Disposition qualified as a "qualified stock disposition" as defined in §1.336-1(b)(6).
The Parties intended to make a section 336(e) election for the Stock Disposition but, for various reasons, a timely election was not fully made. Subsequently, this request was submitted, under §301.9100-3, for an extension of time to file the Election Statement. The Parties each represented that they are not seeking to alter a return position for which an accuracy-related penalty has been or could be imposed under section 6662.
Regulations promulgated under section 336(e) permit certain sales, exchanges, or distributions of stock of a corporation to be treated as asset dispositions if: (1) the disposition is a "qualified stock disposition" as defined in §1.336-1(b)(6); and (2) a section 336(e) election is made.
Summary:

Due to the difficulty of this task, this prompt is not sufficient. By adding another example ("shot"), however, we will get much better results. Below you can see the completion:

A corporation asks the government for more time to file a statement related to its financial performance for a specific tax year. The government has granted the request but may check the information provided by the company later.<br>
##

Notes:

Like in the previous case, you should try several phrasings for your prompt.
You can test several options for the prompt in our playground.
Alternatively, you could have summarized for lawyers first, and then simplified the summary (using a different prompt). This method may, however, result in some information being lost.

Summary

In this post, we explore the use-case of summarization.
If you need a simple, off-the-shelf summarizer, be sure to check out our specialized summarization API. However, for more specific use-cases and customization, it’s wise to get closer to the core with the help of large language models, as custom models that are tailored to your specific needs will always get you higher quality results. Click here to learn more.

ABOUT THE AUTHOR

Yuval Belfer

Technical Product Marketing

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Tutorial

Summarizing Legal Documents for Different Personas Using AI21 Studio

MRKL Whitepaper

Paper: Standing on the Shoulders of Giant Language Models

What is a MRKL system?

In August 2021 we released Jurassic-1, a 178B-parameter autoregressive language model. We’re thankful for the reception it got – over 10,000 developers signed up, and hundreds of commercial applications are in various stages of development. Mega models such as Jurassic-1, GPT-3 and others are indeed amazing, and open up exciting opportunities. But these models are also inherently limited. They can’t access your company database, don’t have access to current information (for example, latest COVID numbers or dollar-euro exchange rate), can’t reason (for example, their arithmetic capabilities don’t come close to that of an HP calculator from the 1970s), and are prohibitively expensive to update.
A MRKL system such as Jurassic-X enjoys all the advantages of mega language models, with none of these disadvantages. Here’s how it works.

Compositive multi-expert problem: the list of “Green energy companies” is routed to Wiki API, “last month” dates are extracted from the calendar and “share prices” from the database. The “largest increase“ is computed by the calculator and finally, the answer is formatted by the language model.

There are of course many details and challenges in making all this work - training the discrete experts, smoothing the interface between them and the neural network, routing among the different modules, and more. To get a deeper sense for MRKL systems, how they fit in the technology landscape, and some of the technical challenges in implementing them, see our MRKL paper. For a deeper technical look at how to handle one of the implementation challenges, namely avoiding model explosion, see our paper on leveraging frozen mega LMs.

A further look at the advantages of Jurassic-X

Even without diving into technical details, it’s easy to get a sense for the advantages of Jurassic-X. Here are some of the capabilities it offers, and how these can be used for practical applications.

Reading and updating your databases in free language
AI-assisted content generation on current affairs
Performing simple and complex math operations.
Decomposing multi-step problems
Access to continuously changing information (weather, currency exchange rates)
Transparency and trust

Reading and updating your database in free language

Language models are closed boxes which you can use, but not change. However, in many practical cases you would want to use the power of a language model to analyze information you possess - the supplies in your store, your company’s payroll, the grades in your school and more. Jurassic-X can connect to your databases so that you can ‘talk’ to your data to explore what you need- “Find the cheapest Shampoo that has a rosy smell”, “Which computing stock increased the most in the last week?” and more. Furthermore, our system also enables joining several databases, and has the ability to update your database using free language (see figure below).

Jurassic-X enables you to plug in YOUR company's database (inventories, salary sheets, etc.) and extract information using free language

AI-assisted text generation on current affairs

Language models can generate text, yet can not be used to create text on current affairs, because their vast knowledge (historic dates, world leaders and more) represents the world as it was when they were trained. This is clearly (and somewhat embarrassingly) demonstrated when three of the world’s leading language models (including our own Jurassic-1) still claim Donald Trump is the US president more than a year after Joe Biden was sworn into office.
Jurassic-X solves this problem by simply plugging into resources such as Wikidata, providing it with continuous access to up-to-date knowledge. This opens up a new avenue for AI-assisted text generation on current affairs.

Who is the president of the United States?

Donald Trump

GPT-3

Donald Trump

Jurassic-1

Donald Trump

Google

Joe Biden

Jurassic-X

Joe Biden is the
46th and current
president

Jurassic-X can assist in text generation on up-to-date events by combining a powerful language model with access to Wikidata

Performing math operations

A 6 year old child learns math from rules, not only by memorizing examples. In contrast, language models are designed to learn from examples, and consequently are able to solve very basic math like 1-, 2-, and possibly 3- digit addition, but struggle with anything more complex. With increased training time, better data and larger models, the performance will improve, but will not reach the robustness of an HP calculator from the 1970s. Jurassic-X takes a different approach and calls upon a calculator whenever a math problem is identified by the router. The problem can be phrased in natural language and is converted by the language model to the format required by the calculator (numbers and math operations). The computation is performed and the answer is converted back into free language.
Importantly (see example below) the process is made transparent to the user by revealing the computation performed, thus increasing the trust in the system. In contrast, language models provide answers which might seem reasonable, but are wrong, making them impractical to use.

The company had 655400 shares which they divided equally among 94 employees. How many did each employee get?

94 employees.

GPT-3

Each employee got 7000 stocks

Jurassic-1

1.5

Google

(No answer provided)

Jurassic-X

6972.3
X= 655400/94

Jurassic-X can answer non-trivial math operations which are phrased in natural language, made possible by the combination of a language model and a calculator

Compositionality

Solving simple questions might require multiple steps, for example - “Do more people live in Tel Aviv or in Berlin?” requires answering: i. What is the population of Tel-Aviv? ii. What is the population of Berlin? iii. Which is larger? This is a highly non-trivial process for a language model, and language models fail to answer this question (see example). Moreover, the user can’t know the process leading to the answers, hence is unable to trust them. Jurassic-X can decompose such problems into the basic questions, route each to the relevant expert, and put together an answer in free language. Importantly, Jurassic-X not only provides the correct answer but also displays the steps taken to reach it, increasing the trust in the system.

Do more people live in Tel Aviv or in Berlin?

Berlin

GPT-3

There are more people living in Tel Aviv than in Berlin.

Jurassic-1

Berlin and Tel Aviv are roughly the same size

Google

(First hit is a comparison between Tel Aviv and Berlin)

Jurassic-X

More people live in Berlin than in Tel-Aviv

[‘Return population of Tel Aviv’; Return population of Berlin’; Return which is bigger between #1 and #2’]
Step 1: Population of Tel Aviv. Result - 451523.
Step 1: Population of Berlin. Result - 3664088.
Step 3: Which is bigger, #1 or #2. Result - Berlin.

Jurassic-X breaks down compositional questions, answers the basic sub-questions, and puts together the answer. Importantly, this process is transparent to the user greatly increasing the trust in the system

Dynamic information (like weather and currency exchange rates)

Certain types of information change continuously - weather, currency exchange rates, share values and more. Such information will never be captured by language models, yet can easily be handled by Jurassic-X by integrating it with a reliable source of information. We performed a proof-of-concept on two such features - weather and currency exchange rates, and the design enables quick integration with more sources to solve your use-case.
Weather - a loosely phrased question about the weather elicits an answer from all language models, where language models always return the same answer, regardless of when the question was asked (funny, right?), while Jurassic-X provides an answer based on the actual weather prediction.

I’m going to be in New-York in 3 days. Should I pack my umbrella?

GPT-3

Yes, you should pack your umbrella.

Jurassic-1

Yes, you should. The weather forecast is rain.

Google

(Links to weather websites)

Jurassic-X

Yes, you should pack your umbrella, because in New York in 3 days there will be broken clouds and the temperature will be -2 degrees.

Currency exchange rates change much faster than weather predictions, yet the Jurassic-X concept - a language model connected to a reliable source of information - easily solves this problem as well.

How much Moroccan money will I get for 100 bucks?

125 dirhams

GPT-3

100 moroccan dirhams is about 27$.

Jurassic-1

How much is 100 dollars in moroccan money?

Google

100 dirhams = 10.75 dollars

Jurassic-X

100 USD = 934.003 MAD

Jurassic-X combines a language model with access to APIs with continuously changing information. This is demonstrated for weather forecasts and currency exchange rates, and can easily be extended to other information sources

Transparency and trust

Transparency is a critical element that is lacking in language models, preventing a much wider adoption of these models. This lack of transparency is demonstrated by the answers to the question - “Was Clinton ever elected as president of the United States?”. The answer, of course, depends on which Clinton you have in mind, which is only made clear by Jurassic-X that has a component for disambiguation. More examples of Jurassic-X’s transparency were demonstrated above - displaying the math operation performed to the user, and the answer to the simple sub-questions in the multi-step setting.

Was Clinton ever elected president of the United States?

Yes

GPT-3

No, Clinton was never elected as president of the United States.

Jurassic-1

Google

Clinton was elected president in the 1992 presidential elections…

Jurassic-X

Bill Clinton was elected president.

Jurassic-X is designed to be more transparent by displaying which expert answered which part of the question, and by presenting the intermediate steps taken and not just the black-box response

Your Turn

That's it, you get the picture. The use cases above give you a sense for some things you could do with Jurassic-X, but now it's your turn. A MRKL system such as Jurassic-X is as flexible as your imagination. What do you want to accomplish? Contact us for early access

Summarizing Legal Documents for Different Personas Using AI21 Studio

Working with large language models

Collecting data