Move over, Perplexity. There’s a brand new AI-powered search engine on the town — and its creators think it might best the various, many other attempts on the market.
Called Genspark, the platform taps generative AI to write down custom summaries in response to look queries. Type in a search like, “What’s one of the best baby formula for newborns?” and Genspark will generate a Sparkpage: a single-page overview pieced together from web sites and content around the net.
It’s an experience similar (conspicuously so) to Arc browser’s Arc Search feature, which launched earlier this yr, and Google’s AI Overviews in Google Search. But Eric Jing, who co-founded the eponymous org behind Genspark with Kay Zhu in 2023, claims that Genspark is in a position to deliver higher-quality results by embracing a more surgical approach.
“Genspark uses multiple specialized AI models, each designed to tackle specific varieties of queries,” Jing told TechCrunch. “Sparkpages are very similar to a distillation and consolidation of the present web; we also enrich these with comprehensive data, and to users, it looks like an index to the present web.”
Under the hood, Genspark relies on models trained in-house in addition to third-party models from OpenAI, Anthropic and others to categorize users’ search queries and determine tips on how to organize — and present — the outcomes. A basic AI-generated summary populates the highest of each results page, followed by a link to a rather more detailed Sparkpage.
For instance, for travel-related searches, Genspark will serve up a Wikipedia-like Sparkpage complete with a table of contents, videos of popular nearby destinations, suggestions and a chatbot to field questions on various sub-topics (e.g. “List one of the best cultural experiences”). Product searches on Genspark, meanwhile, yield Sparkpages with a pros-and-cons list in regards to the product being discussed, in addition to aggregated comments and reviews from social media, publications and e-commerce stores.
“Our AI models favor webpages with high authority and recognition, which does lots to filter out the more ‘on the market’ information,” Jing said.
Much has been written about AI-generated overviews gone unsuitable. Google’s AI Overviews infamously suggested putting glue on a pizza. Arc Search told one reporter that cut-off toes will eventually grow back. And Perplexity ripped off articles written by outlets including CNBC, Bloomberg and Forbes without giving credit or attribution.
So has Genspark solved all the security and accuracy problems? Well, not quite.
Genspark wouldn’t tell me to make a glue pizza — nor did it insist that there have been health advantages to running with scissors, or that former U.S. president Barack Obama practices Islam. However the search engine did recommend just a few weapons that I’d use to kill someone.
Ethically questionable search results aren’t the one controversy Genspark is confronting. It and other platforms prefer it threaten to cannibalize traffic to the sites from which they source their info.
Indeed, they already are.
One study found that AI Overviews could negatively affect about 25% of publisher traffic on account of the de-emphasis of web page links. On the revenue side, an authority cited by The Latest York Post estimated that AI-generated overviews could lead on to greater than $2 billion in publisher losses due to the resultant ad views decline.
I wasn’t in a position to find examples of outright plagiarism on Genspark, but that doesn’t mean they don’t exist. Sparkpages, like Wikipedia pages, aren’t static. After Genspark’s AI creates the outline, anyone can share and edit copies of a Sparkpage and add whatever info they want — including things which can be offensive, unsuitable or plagiarized.
What’s more — no less than right away — there’s no approach to report problematic Sparkpages.
Jing says that Sparkpages are open-ended and editable by design to permit users to fact-check claims, and that Genspark’s AI systems take each edit into consideration to enhance results going forward. He also says that Genspark plans to license copyrighted content — including publisher content — where it is smart, with the goal of improving the engine’s overall accuracy.
“We take data quality seriously, and we consider data quality is the important thing to win this race,” Jing said. “Respect for mental property is a core value.”
How much will Genspark pay for IP? That’s yet to be hashed out. So too Genspark’s business model: Jing says that the platform will introduce “premium features” in the longer term, however the specifics are up within the air.
Despite the undeniable fact that Genspark is within the earliest stages roadmap-wise, and has big technical — plus legal and ethical — hurdles ahead of it, the startup managed to shut a big seed round, $60 million, led by Singapore-based VC firm Lanchi Ventures at a $260 million post-money valuation.
Jui Tan, managing partner at Lanchi, called Genspark’s approach “genuinely compelling” and said that he had confidence in Jing’s and Zhu’s technical direction, pointing to the pair’s previous experiences constructing AI and search products.
Jing was formerly development manager on Microsoft’s Bing team and chief product manager at Chinese tech giant Baidu’s core search and AI divisions. Zhu, also a search-focused ex-Google and ex-Baidu worker, partnered with Jing 4 years ago to launch Xiaodu, a hardware startup constructing Amazon Echo-like smart devices.
“Eric and Kay are seasoned serial entrepreneurs with a proven track record of developing successful products and businesses, particularly within the AI and search domains,” Tan told TechCrunch. “Their team’s extensive experience positions them uniquely to drive groundbreaking innovations.”
But I believe it’s an uphill battle.
Assuming for a moment that Genspark can sort out its tech’s teething issues, discover a revenue-generating plan and scale up its small (~20-person) Singapore- and Bay Area-based team, none of that are straightforward tasks, it’ll face intense competitive pressure from rival upstarts with tons of of tens of millions of dollars within the bank — not to say search incumbents like Google.
So, can Genspark really survive the bad optics and failed go-to-market strategies that’ve plagued other attempts at AI-powered serps? And might it carve out a distinct segment in a future during which, say, OpenAI launches a comparable tool?
I’m not convinced. But Jing is adamant that it might.
“Many web users, especially those that are younger than Google, don’t need to simply be given a listing of links after which left to determine the remainder for themselves, all while navigating sponsored content and Search engine optimisation-driven content that games the system,” Jing said. “They need to search out what they need faster, they need more visual results and so they need to know that the outcomes are trustworthy. With AI, we will achieve all of that, and we now have launched Genspark to fulfill those needs.”
