If AI development were a sport, it’d be closer to baseball than boxing. Headlines might make it seem like AI breakthroughs happen with a big knockout punch, but the reality is more akin to a baseball team grinding through a 162-game season. It’s a process that involves having the right people in place over a long stretch, and fielding the best team is essential for success.
Oscar Wilde once argued that life imitates art more than art imitates life. Strangely, that’s proving to be the case when it comes to AI development – but not in the way some had hoped.
Six years ago, we published a conversation one of our employees had with his mom about the company I’d founded the same year. Here’s a preview of the conversation I’m likely to have with my mom this holiday season about the company that has outsmarted outsourcing.
The combination of technology and startup thinking can force us to challenge long-held, collective wisdom. It’s a reality in business today that we’ve seen before, in the bestselling novel-turned-movie Moneyball, a true story about the Oakland Athletics baseball team and its general manager, Billy Beane.
It may feel like a thorn in your side: You’re creating an amazing solution to solve a common, problematic process - but your team is stymied because there are steps you can’t truly automate without human interaction with the data.
It’s actually a common problem in our increasingly data-centric world. Just ask any data scientist or software engineer who spends too much time wrangling data to improve a product or service. Or talk to a head of operations, who needs to streamline a business process to absorb seasonal shifts in sales volume. They know: Dirty data delays innovation.
The exponential growth of connectivity and technology are changing the workforce. The organization of the future is a “network of teams” connected by technology, but there’s a learning curve for executives on how to get there, according to Deloitte’s 2017 Global Human Capital Report. Most of the executives who responded to the survey pointed to building the organization of the future as the most important challenge for 2017. Yet, few are prepared to leverage the “new human models,” including contingent labor or outsourcing, that they’ll need to build it.
We’re incredibly excited to announce a $7.3 million Series B round from prominent impact investors including Dolma Impact Fund and The Social Entrepreneurs' Fund. The investment comes after the successful launch of WorkStreams™, which provide fast-growing companies an alternative to the stagnant outsourcing and dubious crowdsourcing options currently available.
The combination of humans and software is the secret sauce for today’s on-demand economy. Artificial intelligence (AI) and advanced machine learning have made software smarter than ever, but it’s significantly limited in processing unstructured data that doesn’t fit in its pre-defined models. For example, only humans can process data that requires identifying items in a photograph or deciphering handwritten text on a receipt.