- Atomic AI, which uses machine learning to explore the potential of RNA in drug discovery, has raised a $35 million Series A round.
- They developed a machine learning model that can accurately predict the structure of RNA molecules based on a given set of data.
- They have since refined their model and are using it to pursue their own drug discovery program, which produces candidate molecules to treat drug-resistant or difficult-to-treat conditions.
After writing the articles, I think they’re pretty solid summaries, but short enough to (hopefully) pique your interest. Not everyone goes through the article and clicks on the links, because who knows what’s even useful? Do you open 10 tabs just to find out? Or do you try to guess from the URL? The popup looks nice to me, and only appears when you need it:
Try it right here, in this post — you may or may not care about football salaries, but you can watch it pop up and disappear. And that form is habit; The length of the summary, the shots, the trigger and the trigger, are all subject to change. So what happens when link previews get this rich AI summary treatment?
“We’re seeing 50 percent more page views,” Schrager said. “I’m a pretty analytical person and I was nervous about what we were going to see, because it was a bit counterintuitive. But Wikipedia did it, and it was very successful. Reduces search costs for the user.
Having a broad clue that something is going to hover over them, they ask, “Should I click this or not?” It reduces the hump. The world’s smallest hump, sure, but if you tell a web publisher you can increase clicks by one percent—let alone 50 percent—they’ll jump. Time on site and engagement are important metrics and finding ways to increase those is a big part of any product manager’s job.
Different links, such as affiliate links, can provide different previews, such as the pros and cons of a product compiled from the last hundred reviews. Or external links may be left out—perhaps (just to be honest) to prevent the same clickthrough effect from benefiting them.
Schrager says that abstracts do special work to ensure that “innovative” language models are unrecognizable to humans – names, dates, quotations and other things are always retained, for example, and wording changes are limited to places where they don’t make sense. “All of our valuable IPs are know-how and know-how before and after the AI model,” he said.
Finally, although users are users, Summary’s customers are now website operators. The company charges a flat fee for access to the device and then a small usage fee.
“If your average article is 1,000 words and you have five of those, we’ll sum up 5,000 words and write 500 and maybe charge 50 cents,” Schrager offered as a very loose example of the scale. “We try to make the total value de minimis So it’s not a deterrent to sales – the only way we can scale it quickly is to identify large distribution channels.”
After its initial partners, Summari is set to be released live by a major academic publisher and a major news site, both unnamed. “We’re definitely noticing FOMO in the industry,” Schrager said. “I’m sniffing around people who are starting to see the value. There is a natural network effect as backlinks are being aggregated. Once TechCrunch completes a summary using us, you won’t want to delete it and do it again.
With major tech players like Microsoft and Google making huge plays in AI, I’d be surprised if the company got an offer or two slipped under the door. After all, summaries like these will do well in search engines or an algorithmic news site. But Schrager said they’re not looking for a quick exit.
“My job is to maximize shareholder value. If I get an attractive offer from Google or Yahoo, it could be a huge strategic advantage… I’m not stupid, I’m going for it. But everyone here is going for a big win.”
Leave a Reply