Stephanie started her tech career in software, as an early employee at NYC-based infrastructure monitoring company Datadog. She has been a product manager in robotics/manufacturing automation as well as led growth in the ML devtool space, and now serves as GM at a stealth startup. She enjoys organizing communities of founders, executives, ML engineers/data engineers/data scientists at some of the world’s leading deeptech companies, and also advises and invests in applied AI/ML companies.

What do you view as the main challenges to continued progress in AI/ML?

The biggest challenges I see can be loosely classified as technical and organizational. Technically speaking, there is a lack of education and experience around successfully deploying models in production — things around data quality, monitoring health of models in production, bugs in the ETL pipeline, drift in data distribution, outlier identification. Companies — to the detriment of their bottom line and with the consequence of missed opportunity — keep degraded models up and running. …

Data science teams are doubling every year and each year there are 2x-5x more models delivered into products and businesses,¹ but Gartner predicts that 85% of AI projects will fail to generate value for enterprises. This is partly due to a machine learning (ML) pipeline that is surprisingly manual, a disconnection between the data scientists building models and the ML engineers deploying them, and a lack of basic tooling for this developing workflow. The emerging ML OPs (machine learning operations) ecosystem aims to facilitate better collaboration between data scientists and ML engineers and to create a more automated pipeline with greater transparency. …

Trustworthy digital identification remains one of the main challenges of the internet because none of the traditional, offline methods of verifying that someone is who they claim to be apply. Yet, while digital identity is one of the most foundational and valuable digital assets we have - made even more apparent by the pandemic - many people question whether there is a business to be built around it.

The following article attempts to provide an overview of what digital identity is and why it matters, to explain it’s relevancy now and in the future, and to highlight startups and investors in the space. It is intended as a high level overview and is by no means comprehensive. …

Many of us are wondering what the world will look like when we emerge from prolonged shelter in place and stay at home orders. We’re curious about which behaviors will remain after we’re allowed to return to more normal patterns and which behaviors will develop as we embrace our “new normal.” Some are obvious. Trends in e-commerce, food delivery, online learning, meditation and mental health, remote work, teletherapy and telemedicine, and digital community are likely to be accelerated and to persist after initial barriers to adoption are forced down by COVID-19 related changes. However, there are several less obvious shifts that I think are likely to occur, and that are receiving relatively less attention. I don’t pretend to know what the future holds; this is one version of what it may look like. …

The first part in this series, A New Model: Unbreaking the Internet, highlights the current weaknesses of the primary business model supporting the US Consumer Internet. The second part in this series, Rethinking the Internet: A New Foundation, analyzes the ways in which the Internet can be “re-built” from the ground up in a way that would create more options for business model innovation. The post that follows analyzes applications aimed at improving the Internet user experience by enabling consumers to regain control over their time, attention, and data.

When the Internet was saddled with surveillance advertising as its default business model, the consumer stopped being the central focus of the US Consumer Internet. Advertisers became the customers and therefore the focus shifted to creating the best experience for them. In the process, platforms began a race to amass users, to dominate their time, to drive ever higher engagement, and to collect more and more data so that they could predict, and then influence/manipulate, user behavior. In pursuit of this data, the boundaries between self and market have been almost entirely eliminated, the Internet has become pervasive (connected everything), and nearly all friction will soon be removed (voice as the new UI.) This allows these platforms to be ever present in the background, nudging consumers in whatever direction their customers (advertisers) desire. …

The first part in this series, A New Model: Unbreaking the Internet, highlights the current weaknesses of the primary business model supporting the US Consumer Internet. The post that follows analyzes the ways in which the Internet can be “re-built” from the ground up in a way that would create more options for business model innovation. The final part in this series will analyze applications aimed at improving the Internet user experience by enabling consumers to regain control over their time, attention, and data.

Re-Building it From the Ground Up

The Internet changed the world. It allowed for the sharing of information on an unprecedented scale, facilitated global communication, and all of it was built on open architecture. Our usage of technology and the Internet has evolved and morphed in ways that most of us were unable to anticipate at the time of the Internet’s creation. It was built without a native identity layer and the ability to integrate payments was an afterthought. It was saddled with an extractive business model (surveillance advertising) and the value it generates has ended up accruing to a select few platforms. …

We need the Internet. The invention of the Internet allowed for the sharing of information on an unprecedented scale, facilitated global communication, and all of it was built on open architecture. However, over time, its usage has morphed as technology has shaped our society in unexpected ways. It has become centralized, pervasive, extractive, and in some instances, weaponized.

The Internet platforms most used today launched without a business model. The plan was to amass scale and figure out the economics later. The best model for monetizing applications built atop an open, interoperable protocol wasn’t clear cut. Google determined advertising was the best (or perhaps quickest) path to revenue. …

I interviewed industry professionals at top law firms, investment funds, exchanges, and various decentralized finance (DeFi) projects, in addition to attending panels and conducting independent research at UC Berkeley, to better understand the emerging DeFi industry. Trade-Offs: Decentralized Exchange is the second article in a three part series that draws upon the insights derived from this research (find the first part here.)

The article that follows will outline the exchange of blockchain-based assets along a spectrum of centralization/decentralization, highlighting different approaches to liquidity as implemented by 0x, Injective Protocol, Kyber Network, Bancor, Uniswap, and Arwen. The final article in this series will analyze decentralized lending and derivatives. …