In an era of AI adoption in industry, stark contrasts in our thinking begin to show about how we leverage computing, data, and inference. This article considers graph technologies in the context of business: enhancing human thinking and enabling data exploration, especially among teams of domain experts augmented by AI applications. Specifically, let’s develop and deconstruct the notion of graph thinking.

Contexts

Suppose you have an errand to run, such as shopping for groceries: “Remember to buy eggs and more rice on the way home from work today.” The needs are clear, and your approach is well understood. People use phrases…

The 2021 Knowledge Graph Conference, held online May 3–6, had over 1,000 people attending. Special thanks to all of the 20+ people who volunteered to assist with the conference!

We have the results from an audience poll about which parts they liked best, and also from an informal poll among the people who helped organize events. There are recordings for every tutorial, keynote, session talk, panel, etc. — resulting in 100 hours of videos. That’s a lot of content, and so far we really don’t know of anyone who’s been through the whole collection… https://knowledgegraphconference.vhx.tv/ Here’s your opportunity to become…

I think that people tend to get the wrong idea about technology, particularly software.

We make new capabilities.

To have a defensible strategy in business, the “newness” of what you’re making cannot be minor. Firms must aim higher, provide more than simply incremental advances. They must push far enough ahead to drive value, and give themselves runway to grow.

So, about downturns… I’ve participated in a few: 1987, 2001, 2008, and now 2020. Understand that most of the “disruption” occurs after business begins to pick up again.

The reason for that belies what people tend to get wrong about technology…

For a full day on December 14, 2020, LinkedIn sponsored a virtual workshop called Metadata Day, followed by a public online meetup called Metaspeak. View videos of the event on their website including a set of lightning talks provided by several of the speakers.

The gist is that circa 2018, the pending regulatory compliance for GDPR, CCPA, etc., drove urgency in enterprise organizations to have a better understanding and accountability about datasets and their use cases. Several firms, about a dozen, responded in strikingly similar ways — which signals that a kind of “design pattern” is emerging for how to…

Registration is open for the Metaspeak Meetup (a free online event) on December 14, 2020, hosted by LinkedIn https://metadataday2020.splashthat.com/

This is the public portion of the Metadata Day 2020 workshop, which convenes leaders from several open source projects for graph-based dataset metadata management, along with thought leaders in metadata management and dataset governance from Google, IBM, UC Berkeley, etc.

Igor Perisic, CDO @ LinkedIn, will present our welcome address, followed by two panels of expert practitioners who will summarize outcomes from our workshop earlier in the day — (1) focus on use cases, and (2) focus on production at scale…

RLlib is an open-source library in Python, based on Ray, which is used for reinforcement learning (RL). This article presents a brief tutorial about how to build custom Gym environments to use with RLlib. You can use this as a starting point for representing your own use cases to solve with reinforcement learning (RL).

Note that this article is a follow-up to:

If you haven’t read that previous article already, check it out.

Source code for this article is available at https://github.com/DerwenAI/gym_example

The material here comes from Anyscale Academy and complements the RLlib documentation. …

RLlib is an open-source library in Python, based on Ray, which is used for reinforcement learning (RL). This article provides a hands-on introduction to RLlib and reinforcement learning by working step-by-step through sample code. The material in this article, which comes from Anyscale Academy, provides a complement to the RLlib documentation and is especially intended for those who have:

• some Python programming experience
• some familiarity with machine learning
• no previous work in reinforcement learning
• no previous hands-on experience with RLlib

Key takeaways: we will compare and contrast well-known RL examples running in RLlib to explore the essential concepts and terminology…

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…