Proof of ...what ?

Good breakdown between proof of work and proof of stake consensus.

https://medium.com/@jaybny/on-proof-of-skill-6af149f45ce8

Trustless blockchain or not ...

https://www.ccn.com/microsofts-new-ethereum-blockchain-product-gets-rid-of-mining/

I understand the use case and philosophy behind this, but similar to IBMs hyperledger fabric and others , what's the point ?  I'm sure the Google's and Amazon's and Alibaba's will have their own version of a enterprise lock you into their ecosystem blockchain as well. 

The biggest fallacy in this article is the "trusted enterprise network" comment. Who trusts Microsoft ?  Who trusts IBM?  Sounds like marketing and  slapping blockchain on a product/platform and convincing  the confused VPs and c-level executives this is the way to go. Then the Wipro's of the world will jump in with 25 year olds who have 20 years of blockchain experience and implement it.

And people will complain a couple years later and write medium articles  and O'Reilly stories and books on why blockchain fails most of the time.    We know this story.  It plays out the same way all the time now. 

Lightning Network explained ...

https://youtu.be/c4slzFdykpc

Good long video that goes into some details about the lightning Network.

GraphQL and graph databases.

Four basics behind a graph database are

Nodes: The primary data elements

Relationships: How two nodes are connected

Nodes may have multiple relationships

Properties: Attributes of a node or of a relationship

Labels: How nodes are described and grouped together as sets

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Nodes may have multiple labels

Labels get indexed and optimized, making it easier for them to be quickly located

Graph databases shift the focus of their data models to the relationships, which makes retrieving complex data structures much easier.

They abstract nodes and relationships into one structure.

But what is GraphQL ?

https://www.upwork.com/hiring/development/why-facebooks-graphql-language-should-be-on-your-radar/

Graph databases

RDBMS, also known as Relational databases, are  structured and easy to query with a language like SQL, but they have limitations when it comes to unstructured data. And scaling usually means buying far more servers and even then , that has limitations.

Not all data, however, is that easily organized. Semi and Unstructured data like IoT sensor data, social media,.  photos, videos, location-based GIS information, web or mobile activity, and usage metrics can’t be neatly broken down nor should be, but nobody wants a data swamp. 

Things like Hadoop, HBase, Cassandra, MongoDB and other NoSQL or NewSQL like databases trade tables for documents or json or blocks or columnar like schemas and more.  

https://www.business2community.com/brandviews/upwork/the-importance-of-graph-databases-in-an-increasingly-connected-world-02094654

Quantum computing slides

https://speakerdeck.com/ahelwer/quantum-computing-for-computer-scientists

Quantum computing for cs

https://hackaday.com/2018/07/13/quantum-computing-for-computer-scientists/