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Home / 2021 / February

Cutting-edge Katana Graph scores $28.5 million Series A Led by Intel Capital

  • ganadiotis
  • Feb 24, 2021
  • Business, Graph Analytics & Data Science, Graph Databases, Interview, News, Technical
  • No comments yet
Cutting-edge Katana Graph scores .5 million Series A Led by Intel Capital

Here's why and how a startup founded by a duo of researchers some months back is attracting big enterprise clients and serious funding

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Off-chain reporting: Toward a new general purpose secure compute framework by Chainlink

  • ganadiotis
  • Feb 24, 2021
  • Blockchain, Featured, Interview, News, Technical
  • No comments yet
Off-chain reporting: Toward a new general purpose secure compute framework by Chainlink

The upgrade in Chainlink's oracle service could mean more data availability at lower cost, leading to more applications

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Up and to the right: TigerGraph scores $105M Series C funding, the Graph market is growing

  • ganadiotis
  • Feb 17, 2021
  • Business, Graph Databases, Interview, News, Technical
  • No comments yet
Up and to the right: TigerGraph scores 5M Series C funding, the Graph market is growing

The largest funding round to date in the graph market is good news not just for TigerGraph, but for the market at large

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Data meets science: Open access, code, datasets, and knowledge graphs for machine learning research and beyond

  • ganadiotis
  • Feb 16, 2021
  • Analysis, Analytics, Data Science, Featured, Knowledge Graphs, Open Data, Socio-Technical, Use Case
  • No comments yet
Data meets science: Open access, code, datasets, and knowledge graphs for machine learning research and beyond

A new interconnected ecosystem for research is shaping up, and machine learning is just the tip of the iceberg.

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AI chips in the real world: Interoperability, constraints, cost, energy efficiency, and models

  • ganadiotis
  • Feb 03, 2021
  • AI Chips, Analysis, Interview, Open Source, Technical
  • No comments yet
AI chips in the real world: Interoperability, constraints, cost, energy efficiency, and models

The answer to the question of how to make the best of AI hardware may not be solely, or even primarily, related to hardware

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