Selective State Space Models: Solving the Cost-Quality Tradeoff
As AI is increasingly used in production scenarios, costs are mounting. Are alternative architectures the solution?
Challenging the “One Size Fits All” Productivity Suite
The first half of 2020 has been anything but the expected, with long-term impacts for society that may take years to fully solidify and understand. Widespread lockdowns have caused more of us to rely on technology and the Internet; that in turn is driving a (somewhat awkward, unasked-for, but nonetheless) nosebleed pace of growth in usage and valuations for business software companies.
Those factors, in part, encouraged our team at Bain Capital Ventures to lead the Series B in Clockwise, which we announced this month. In early April, Notion disclosed that it was the latest in a string of business applications to close funding on the back of eye-popping growth, securing financing at a $2B valuation, joining (among many others) Airtable at $2.5B+. As we enter the second half of 2020, it’s clear not only that our work technology is more critical than ever, but also that we are well into a new wave of young companies successfully challenging the traditional dominance of bundled productivity suites from companies like Google, Microsoft, Adobe and Cisco.
Having learned from several years of conversations with founders and builders in this world, I wanted to share a review of the landscape: what are the key tailwinds? How are innovators differentiating? For founders excited about helping millions of workers be more efficient and productive, what opportunities may be under-explored today?
Several transformations enable software providers to transact directly with their end user — and importantly, sell based on the users’ personal, role-specific preferences and needs. These factors include:
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When given their own choice and freedom, business users are gravitating to alternatives that compete on:
We believe that the enterprise software trends that enable user-led sales, and the productivity challengers that are emerging to better address user needs, will touch every tool in the workplace. For tinkerers and product people exploring opportunities, here are two rules of thumb that we use to map out potential whitespace.
One analysis is simply to look at the major software bundles, and see where web-native challengers have yet to emerge, or are yet building momentum. For example, modern presentation products are starting to eat away at the dominance of PowerPoint. Their approaches recall the tactics we’ve seen among unicorn challengers in other categories:
Not only is Office a bundle, but it may turn out that each application is itself a bundle of a multitude of use cases. Excel occupies one icon on our desktops, but it actually serves a range of functionality, like planning expenses for a road trip (budgeting), or keeping track of grocery needs (to do lists), let alone tracking supply chains (SCM) and scraping data with VBA (data automation).
Within a bundle, Excel needs extreme flexibility to cater to a very broad cross-section of users. In a world where software makers can better target their ideal users, why not optimize the user interface, interactions, integrations and more for a narrow but powerful use case? It seems very possible that individual buttons in Excel, translated into dedicated productivity products, could become meaningful businesses in their own right.
This modern productivity software wave has been an enormously thrilling ride so far. As we look to the frontier of knowledge work that remains to be improved, we can thankfully benefit from all these better tools to ideate, design, and build.
Do you have a vision for how we can become more efficient, creative and satisfied at work? Are you harnessing state-of-the-art infrastructure, an intense focus on product perfection, and/or a passionate user community? I would love to hear from you, and to continue supporting this transformation.
I originally published this article to Efficiency Frontier. I wrote this with my colleagues Zeeza Cole and Ajay Agarwal, thanks to feedback on drafts from Jessica Retrum, Steven Lee, Tom Uebel and Jessica Ko.
As AI is increasingly used in production scenarios, costs are mounting. Are alternative architectures the solution?
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