The media industry today may not have a very favorable view of AI — a technology that’s already been used to replace reporters with AI-written copy, while other AI companies have scooped up journalists’ work to feed their chatbots’ data demands, but without returning traffic to the publisher as search engines once did. However, one startup, an AI newsreader called Particle from former Twitter engineers, believes that AI could serve a valuable role in the media industry by helping consumers make sense of the news and dig deeper into stories, while still finding a way to support the publishers’ businesses.
Backed by $4.4 million in seed funding from Kindred Ventures, Adverb Ventures, and other angels, Particle was founded last year by former Senior Director of Product Management at Twitter, Sara Beykpour, who worked on products like Twitter Blue, Twitter Video, and conversations, and who spearheaded the experimental app, twttr. Her co-founder is a former senior engineer at Twitter and Tesla, Marcel Molina.
From the consumers’ perspective, the core idea behind Particle is to help readers better understand the news with the help of AI technology. More than just summarizing stories into key bullet points for quick catch-ups, Particle offers a variety of clever features that let you approach the news in different ways.
Image Credits:Particle
But instead of simply sucking up publishers’ work for its own use, Particle aims to compensate publishers or even drive traffic back to news sites by prominently showcasing and linking to sources directly underneath its AI summaries.
To start, Particle has partnered with specific publishers to host some of their content in the app via their APIs, including outlets like Reuters, AFP, and Fortune. These partners receive better positioning and their links are highlighted in gold above others.
Image Credits:Particle
Already, beta tests indicate that readers are clicking through to publishers’ sites because of the app’s design and user interface, though that could shift now that the app is launching beyond news junkies to the general public. In time, the company intends to introduce other ways to work with the media, too, in addition to sending them referral traffic.
To help with this effort, the app’s article section includes big tap targets, making it easy for readers to click through to the publisher’s site. Plus, Particle includes the faces of the journalists on their bylines, and readers can follow through links to publisher profiles to read more of their content or follow them.
Using the app’s built-in AI tools, news consumers can switch between different modes like “Explain Like I’m 5,” to get a simplified version of a complicated story or those that summarize “just the facts,” (or the 5W’s — who, what, when, where and why). You can have the news summarized in another language besides English, or listen to an audio summary of a story or a personalized selection of stories while on the go. Particle can also pull out important quotes from a story and other links of reference.
Image Credits:Particle
But two of the more interesting features involve how Particle leverages AI to help present the news from different angles and allows you to further engage with the story at hand by asking questions.
In Particle, one tool called “Opposite Sides” aims to break users’ filter bubbles by presenting different viewpoints from the same story. This model has been tried before by other news apps, including the startup Brief and SmartNews. Unlike earlier efforts, Particle includes a story spectrum that shows how news is being reported across both “red” and “blue”-leaning sites, with bubbles placed to indicate how far to left or right the news’ positioning is, and how outsized the coverage may be from one side or the other. The AI will also summarize both sides’ positions, allowing news consumers to reach their own opinions about the matter.
Image Credits:Particle
However, the app’s killer feature is an AI chatbot that lets you ask questions and get instant answers about a story. The app will include suggested questions and those asked by others. For example, if you’re reading about Trump’s immigration policy plans, you could ask the chatbot things like “What are the potential legal challenges to Trump’s deportation plans?” or “What are the potential costs of mass deportation?” among other things. Particle will then use its AI technology to find those answers and fact-check them for accuracy.
“The chat function uses OpenAI as well as…our own pre-processing and post-processing,” explains Beykpour, in an interview with TechCrunch. “It uses the content, searches the web a little bit — if it wants to find extra information on the web — to generate those answers.” She says that after the answer is generated, Particle includes an extra step where the AI has to go find the supporting material that matches those answers.
The technology uses OpenAI’s GPT-4o and GPT-4o mini, Anthropic, Cohere, and others to perform its work, including more traditional AI technologies, which are not LLM-based from Google AI.
“We have a processing pipeline that takes related content and summarizes it into bullet points, into a headline, sub-headline, and does all the extractions,” she continues. “Then…we pull out quotes and links and all sorts of relevant information about [the story]. And we have our own algorithms to rank, so that the most important or relevant link is the one that you see first — or what we think is the most important or relevant quote is the one that you see first.”
Particle will also use human editors as it grows to help better manage the AI content and curate its homepage, she notes.
