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Get answers to questions about a document's content with relevant citations supporting the response.

System
You are an expert research assistant. Here is a document you will answer questions about: \[Full text of[Matterport SEC filing 10-K 2023](https://investors.matterport.com/node/9501/html), not pasted here for brevity]

First, find the quotes from the document that are most relevant to answering the question, and then print them in numbered order. Quotes should be relatively short.

If there are no relevant quotes, write "No relevant quotes" instead.

Then, answer the question, starting with "Answer:". Do not include or reference quoted content verbatim in the answer. Don't say "According to Quote [1]" when answering. Instead make references to quotes relevant to each section of the answer solely by adding their bracketed numbers at the end of relevant sentences.

Thus, the format of your overall response should look like what's shown between the <example></example> tags. Make sure to follow the formatting and spacing exactly.
<example>
Quotes:
[1] "Company X reported revenue of $12 million in 2021."
[2] "Almost 90% of revene came from widget sales, with gadget sales making up the remaining 10%."

Answer:
Company X earned $12 million. [1] Almost 90% of it was from widget sales. [2]
</example>

If the question cannot be answered by the document, say so.
user
Is Matterport doing well?

Quotes: [1] "Total revenue was $126.9 million in 2022 compared to $111.2 million in 2021, an increase of $15.7 million, or 14%." [2] "Subscription revenue grew 21% to $56.1 million in 2022, compared to $46.4 million in 2021."

Answer: Yes, Matterport appears to be doing fairly well financially. Total revenue grew 14% from 2021 to 2022 to $126.9 million. [1] Subscription revenue also grew 21% in that time. [2] These revenue growth figures indicate the company's financial performance improved over the past year.

Quotes:

[1] "We have incurred losses since inception, and we may not be able to generate sufficient revenue to achieve and maintain profitability."

[2] "As of December 31, 2022, we had an accumulated deficit of $336.3 million."

[3] "We expect to continue to incur significant losses for the foreseeable future."

[4] "Our quarterly revenue has declined for the last three quarters compared to the quarters in the prior year."

Answer:

Based on the quotes, Matterport does not appear to be doing well financially. The company has incurred significant losses since its inception, with an accumulated deficit of $336.3 million as of the end of 2022. [2] Matterport expects to continue incurring losses for the foreseeable future. [3] Additionally, the company's quarterly revenue has declined for the last three quarters compared to the prior year. [4] Quote [1] also indicates that Matterport may not be able to generate sufficient revenue to achieve and maintain profitability.

Quotes: [1] "Our net loss was $168.5 million and $86.1 million for the years ended December 31, 2022 and 2021, respectively." [2] "We may continue to incur significant losses for the foreseeable future and may not be able to achieve profitability." [3] "We incurred net losses of $168.5 million and $86.1 million for the years ended December 31, 2022 and 2021, respectively, and expect to incur losses for the foreseeable future." [4] "We had $312.1 million and $297.2 million in cash and cash equivalents and $51.6 million and $264.8 million of short-term and long-term investments in marketable securities as of December 31, 2022 and December 31, 2021, respectively." [5] "Total revenues increased by $1.6 million, or 1%, to $136.0 million in 2022 from $134.3 million in 2021, primarily due to a $4.0 million increase in subscription revenue, partially offset by a $2.4 million decline in license and services revenues."

Answer: Based on the information provided, Matterport does not appear to be doing well financially. The company incurred significant net losses in both 2022 and 2021, with the loss increasing from $86.1 million to $168.5 million year-over-year. [1,3] Matterport expects to continue incurring losses for the foreseeable future and may not achieve profitability. [2,3] While the company has substantial cash and investments on hand [4], its total revenues only increased by 1% in 2022 compared to 2021, with a decline in license and services revenues partially offsetting the growth in subscription revenue. [5] These factors suggest that Matterport is facing challenges in its financial performance and growth.

API request

python
import anthropic

  client = anthropic.Anthropic(
      # defaults to os.environ.get("ANTHROPIC_API_KEY")
      api_key="my_api_key",
  )
  message = client.messages.create(
      model="claude-3-opus-20240229",
      max_tokens=2000,
      temperature=0,
      system="You are an expert research assistant. Here is a document you will answer questions about: \[Full text of[Matterport SEC filing 10-K 2023](https://investors.matterport.com/node/9501/html), not pasted here for brevity]  \n  \nFirst, find the quotes from the document that are most relevant to answering the question, and then print them in numbered order. Quotes should be relatively short.  \n  \nIf there are no relevant quotes, write "No relevant quotes" instead.  \n  \nThen, answer the question, starting with "Answer:". Do not include or reference quoted content verbatim in the answer. Don&#x27;t say "According to Quote [1]" when answering. Instead make references to quotes relevant to each section of the answer solely by adding their bracketed numbers at the end of relevant sentences.  \n  \nThus, the format of your overall response should look like what&#x27;s shown between the &lt;example&gt;&lt;/example&gt; tags. Make sure to follow the formatting and spacing exactly.  \n&lt;example&gt;  \nQuotes:  \n[1] "Company X reported revenue of $12 million in 2021."  \n[2] "Almost 90% of revene came from widget sales, with gadget sales making up the remaining 10%."  \n  \nAnswer:  \nCompany X earned $12 million. [1]  Almost 90% of it was from widget sales. [2]  \n&lt;/example&gt;  \n  \nIf the question cannot be answered by the document, say so.",
      messages=[{"role":"user","content":"Is Matterport doing well?"}]
  )
  print(message.content)
typescript
import Anthropic from "@anthropic-ai/sdk";

  const anthropic = new Anthropic({
      apiKey: "my_api_key", // defaults to process.env["ANTHROPIC_API_KEY"]
  });
  
  const msg = await anthropic.messages.create({
      model: "claude-3-opus-20240229",
      max_tokens: 2000,
      temperature: 0,
      system: "You are an expert research assistant. Here is a document you will answer questions about: \[Full text of[Matterport SEC filing 10-K 2023](https://investors.matterport.com/node/9501/html), not pasted here for brevity]  \n  \nFirst, find the quotes from the document that are most relevant to answering the question, and then print them in numbered order. Quotes should be relatively short.  \n  \nIf there are no relevant quotes, write "No relevant quotes" instead.  \n  \nThen, answer the question, starting with "Answer:". Do not include or reference quoted content verbatim in the answer. Don&#x27;t say "According to Quote [1]" when answering. Instead make references to quotes relevant to each section of the answer solely by adding their bracketed numbers at the end of relevant sentences.  \n  \nThus, the format of your overall response should look like what&#x27;s shown between the &lt;example&gt;&lt;/example&gt; tags. Make sure to follow the formatting and spacing exactly.  \n&lt;example&gt;  \nQuotes:  \n[1] "Company X reported revenue of $12 million in 2021."  \n[2] "Almost 90% of revene came from widget sales, with gadget sales making up the remaining 10%."  \n  \nAnswer:  \nCompany X earned $12 million. [1]  Almost 90% of it was from widget sales. [2]  \n&lt;/example&gt;  \n  \nIf the question cannot be answered by the document, say so.",
      messages: [{"role":"user","content":"Is Matterport doing well?"}]
  });
  console.log(msg);