Their community was still reeling from an incident where local police had murdered an unarmed black man. Protests grew as the public was outraged in the wake of a court decision to acquit the murderers. Then a crowd gathered in a major city as a local protest leader made a public reading of a controversial document. Afterward, protesters marched to a nearby park and pulled down the statue of a corrupt government leader portrayed as a Roman emperor.

The date was July 9, 1776. The city was NYC. The man whose death had catalyzed protests was Crispus Attucks. He’d been…

Sebastopol, California 2020-06-03

Derwen, Inc., announces a new AI service for a novel form of risk analysis, addressing business needs during a time of heightened uncertainty to augment due diligence practices, while emphasizing resilience and ethical practices.

First and foremost, our hearts go out to those who have been victims of illegal and unjust police aggressions, to their family, friends, and neighbors. And also to those who have lost loved ones during the pandemic. We support those who are actively protesting, calling out the systematic racial violence which is so deeply ingrained in the US.

Response to Urgent Business Needs

In response to urgent business needs brought on…

Strategy notes for technology ventures during a “pseudo-jackpot” period subsequent to the COVID-19 pandemic and its economic fallout.

The following is a collection of personal notes. Most of these points compare personal reflections from previous economic crises w.r.t. the current pandemic. This is especially targeted at questions about leading an early stage technology venture.

Our world has changed. On the other side of a global crisis, where do we land? As an enormous range of possible risks and opportunities open up, which strategies are indicated? How do we prepare for a so-called “new normal” and its emerging business environments?


A curated list of dashboards for tracking the COVID-19 pandemic and related factors.


The following links provide dashboards and related resources for a number of different perspectives analyzing the global COVID-19 pandemic.

Note that the more reliable sources tend to:

  • cite data sources
  • focus on per-capita estimates instead of absolute values per region
  • show confidence intervals and predictive bounds
  • condition any reported ratios of relatively sparse data by using point estimates
  • discuss external factors which aren’t represented by features in their models

OTOH, among the less reliable sources … not so much. YMMV.

COVID-19 deaths/mil vs. US metro population, Earth Day 2020

Analysis and Briefings

AI-based summarization and briefings are vital, given…

With so very many people on lockdown…in their homes…wondering what they can do…here’s a list about “Ways to do something” to help with responses to the COVID-19 pandemic:

  • “Recovery Teams”: for any organization in which you’re involved, begin work now to put together a Recovery Team, which can plan and update contingencies for what to do afterwards — which is when so much work will be needed!
  • Crowdfight COVID-19: “An initiative from the scientific community to put all available resources at the service of the fight against COVID-19”
  • Project N95: online clearinghouse for critically needed medical equipment; simply brilliant

We’ve had a busy 2019 at NYU Coleridge Initiative and other organizations partnering on Rich Context. Now we’re announcing a machine learning competition, with full details at the repo on GitHub. This competition focuses on entity linking to infer from open access PDFs research publication about which datasets were used for that specific research.

The following provides background about how the ML models from the competition fit into the broader scope of Rich Context, as well as how the corpus gets developed, plus ways in which the competition has been improved.

network diagram for RCLC corpus v.1.0.8

Machine Learning Competition

We’ve gained much feedback about Rich Context and…

Check out a recent post, “New initiative to help with discovery of dataset use in scholarly work” by Christian Zimmermann on the RePEc blog.

TLDR: RePEc now takes annotations of research papers then asks authors to confirm dataset annotations inferred by machine learning models. That’s a human-in-the-loop approach for enhancing metadata used in scholarly infrastructure. It’s part of a larger AI research effort called Rich Context.

Selected tweets about this work:


RePEc is a decentralized bibliographic database for research in Economics and related fields, which provides search for working papers, journal articles, books, and software components. The…

Our evening event at Rev conference this year will be Data Science in the Senses. That’s on Thursday, May 23 in NYC.

Register today for Rev and use this code for a discount: PACORev25 — see the end of this article for more details about the conference.

The Data Science in the Senses event will showcase amazing projects now making waves through the realms of AI in art— Botnik, folk RNN, Ben Snell, Josh Urban Davis, and more— projects that leverage data and machine learning for sensory experiences. Here’s a sneak peek at the experience:

Botnik is a community of…

This story was written as a capsule of advice to send to those who need it the most.

Scenario: you’ve just arranged for an important introduction through email. Something like:

well-connected VC:
Hi XYZ, meet Joe. Can’t say enough great things about Joe. You two need to talk soon, I’m sure there’s so much you could do to help Joe.
Joe: XYZ is a luminary in the emerging ecosystem of ____ with way too many notable accomplishments to mention. This relationship will be an amazing boost to your venture.

The next step is crucial. Far too often, inexperienced people fumble…

Recently I was asked by O’Reilly Media to help develop a new three-part curriculum called Pro Series: Data Science. Our blended learning approach for this series leverages “flipped classroom” methods, hands-on exercises with notebooks, primary source readings, case study analysis, plus group projects — all blended in a format that is part online and part in-person.

This curriculum aims at the growing need for “upskilling” in enterprise organizations as well as B2C. In other words, we’re providing courses for people who have some industry experience already and now want to begin moving toward opportunities on data science teams. Prerequisites include…


"In the loop…"

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