AMAZON’S “GO” STORES are impressive places. The cashier-less shops, which first opened in Seattle in 2018, allow app-wielding customers to pick up items and simply walk out with them. The system uses many sensors, but the bulk of the magic is performed by cameras connected to an AI system that tracks items as they are taken from shelves. Once the shoppers leave with their goods, the bill is calculated and they are automatically charged. Read More
Tag Archives: Strategy
The Tetris Opportunity For Services As Software Companies
A while back I wrote a piece on the Services-As-Software business model for AI, where you take a workflow that is largely human today, keep the same user interface, but replace the rest of the workflow with automation. Today I want to explain why the first companies to adopt services-as-software models will end up dominating multiple markets — sometimes unrelated ones.
There are two pieces to understanding this opportunity. First, it exists because every AI company I am invested in that is working with a services-as-software business model is struggling with the same question — should they provide their services to other businesses? Or should they be full stack and compete with the other market players, or both? Read More
Three Elements of a Successful Platform Strategy
We typically think of companies competing over products — the proverbial “build a better mousetrap.” But in today’s networked age, competition is increasingly over platforms. Build a better platform, and you will have a decided advantage over the competition.
In construction, a platform is something that lifts you up and on which others can stand. The same is true in business. By building a digital platform, other businesses can easily connect their business with yours, build products and services on top of it, and co-create value. This ability to “plug-and-play” is a defining characteristic of Platform Thinking. Read More
The Platform Matrix: Not All Platforms Are Created Equal
Multi-purpose platforms with native apps are much more scalable and defensible than focused platforms reliant on integrations
I have previously explained how network effects shape three broad types of tech businesses — marketplaces, interaction networks and data networks. In addition to these, there is one other type of business where network effects play a central role — platforms. Unfortunately, the tech and startup world has spent much of the past decade using the term “platform” to describe everything from operating systems to analytics tools, algorithms, APIs, etc. Quite plainly, if everything is a platform, then nothing is and the term loses all meaning. So let’s take a more granular look at what platforms really are, and then unpack how their network effects work. Read More
The 20 data science projects at the core of every successful business
What do you get if you draw a map linking the thirteen key business functions…
Marketing, Customer Services, Sales, R&D, Purchasing, Production, Distribution, IT, HR, Legal, Finance, Senior Management and Operations.
… to the three key elements of any business?… Read More
Andrew Ng: Enterprise AI Strategy (with Landing AI) — CxO Talk
Defining The Services-As-Software Business Model For AI
My angel investment in Botkeeper has been one of the most influential in my thinking on how AI strategy is evolving. When new high impact technologies come along, they often shake up status quo business models and because no one understands what business models might emerge on the other side, it’s a wonderful time to make a few bets on some startups. As an investor, these initial bets help me learn how the space is evolving, which means when the real wave of startups comes that are embracing this new tech, I’m much more educated than most people who sat out the initial round. And on top of that, sometimes you get lucky on the early bets too. Read More
#strategy, #investingDefining and Unpacking Transformative AI
Recently the concept of transformative AI(TAI) has begun to receive attention in the AI policy space. TAI is often framed as an alternative formulation to notions of strong AI (e.g. artificial general intelligence or superintelligence) and reflects increasing consensus that advanced AI which does not fit these definitions may nonetheless have extreme and long-lasting impacts on society. However, the term TAI is poorly defined and often used ambiguously. Some use the notion of TAI to describe levels of societal transformation associated with previous ‘general purpose technologies’ (GPTs) such as electricity or the internal combustion engine. Others use the term to refer to more drastic levels of trans-formation comparable to the agricultural or industrial revolutions. The notion has also been used much more loosely, with some implying that current AI systems are already having a transformative impact on society.
This paper unpacks and analyses the notion of TAI, pro-posing a distinction between TAI and radically transformative AI(RTAI), roughly corresponding to societal change on the level of the agricultural or industrial revolutions. We describe some relevant dimensions associated with each and discuss what kinds of advances in capabilities they might require. We further consider the relationship between TAI and RTAI and whether we should necessarily expect a period of TAI to precede the emergence of RTAI. This analysis is important as it can help guide discussions among AI policy researchers about how to allocate resources towards mitigating the most extreme impacts of AI and it can bring attention to negative TAI scenarios that are currently neglected. Read More
Using AI to Decentralize Organizations
Operating a company with no managers, where everyone chooses their work, salary, and holiday entitlement may sound like chaos. But Daniel Hulme, CEO of Satalia, and his team of 250 people are making it productive. Daniel joins Azeem Azhar to discuss what a company that runs as a decentralize swarm looks like in practice.
They discuss:
— The role of artificial intelligence and open innovation in a swarm organization.
— How a decentralized business creates accountability to ensure strong output.
— The potential for the model to scale to larger organizations, and even countries.
Read More
Artificial Intelligence (AI) strategy: 8 counterintuitive tips
To successfully implement AI into your business processes, rethink traditional IT approaches and some common wisdom. Consider these tips
Artificial intelligence (AI) has officially entered the enterprise, quickly evolving from a pipe dream to reality. Indeed, the majority of organizations (85 percent) are either adopting or evaluating AI, according to a recent O’Reilly survey, with more than half using AI in production or for analysis. Read More
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