Introducing Bird SQL, a Twitter search interface that is powered by Perplexity’s structured search engine. It uses OpenAI Codex to translate natural language into SQL, giving everyone the ability to navigate large datasets like Twitter. perplexity.ai/sql
With Bird SQL, you can quickly find information on Twitter that would have been impossible to find with conventional search engines or web browsing:
"most liked tweets about #worldcup" perplexity.ai/sql?uuid=9b03e…
If you are interested in using our search engine on your structured or unstructured data, contact us at support@perplexity.ai, our Discord server, or via Twitter. Join our Discord to learn more about search and large language models: discord.com/invite/kWJZsxP…
This is a demo, not a commercial product. There are limitations to our Twitter data, database performance, and the expressiveness of SQL. Bird SQL does not interpret the content of tweets. For unstructured search, try Perplexity Ask.
We’re excited to announce that we’ve raised $62.7 million in a Series B1 funding led by Daniel Gross. The round also includes Stanley Druckenmiller, NVIDIA, Jeff Bezos, Tobi Lutke, Garry Tan, Andrej Karpathy, Dylan Field, Elad Gil, Nat Friedman, IVP, NEA, Jakob Uszkoreit, Naval Ravikant, Brad Gerstner and Lip-Bu Tan.
Since we announced our Series B in January 2024, we’ve grown to serve 169M queries per month, and more than 1 billion queries in the last 15 months. The additional funding will be used to support our continued consumer adoption and enterprise expansion.
We’ve inked new partnerships with two of the world’s largest telecommunications firms — Japan’s SoftBank (SFTBY:US) and Germany’s Deutsche Telekom (ETR:DTE) — to distribute Perplexity to a combined total of over 116M users. As global telecom leaders increasingly seek to bring AI tools to their mobile subscribers, Perplexity has become the partner of choice.
When building *answer engines*, truthfulness is essential when delivering direct answers to questions. Just being able to cite your sources isn't sufficient. Hence why we're excited about giving you the power to curate your sources. Few more examples in 🧵 of what it lets you do
“Yann LeCun” on @perplexity_ai: something for which you would expect to see an accurate bio of @ylecun is incorrect. Says “he is the cofounder and advisor for @Meta”. Error stems from his Linkedin page having keywords like “cofounder”. Left: Incorrect, Right: Correct.
We also allow you to add more sources that lets you add more details and give you the analogous experience of scrolling through search engines, while being on an answer engine.
Whether you're a data scientist, influencer, journalist, or just someone who loves to delve into data, Perplexity Bird SQL is likely to be a useful tool. Example: What if you wanted to know @elonmusk’s engagement rate in the form of a summary table? perplexity.ai/sql?uuid=61e45…
Or, compare the influence of an individual like @karpathy with 580K followers with that of journals like @WSJ, @forbes that have ~20M followers? Results are indeed surprising: @karpathy has far more engagement despite having 35x less followers.
Announcing Perplexity Ask, a new search interface that uses OpenAI GPT 3.5 and Microsoft Bing to directly answer any question you ask. perplexity.ai discord.com/invite/kWJZsxP…
Inspired by OpenAI WebGPT, instead of displaying a list of links, we summarize the search results and include citations so that you can easily verify the accuracy of the information provided.