IOTA still wants to build a better blockchain and get it right this time
In 2014, IOTA set out to offer an alternative to the key issues with blockchain: Scalability and transaction fees. Somewhere along the way, things went wrong. Not everything is lost, however, and IOTA is looking to regain momentum.
Read More →OctoML scores $28M to go to market with open source Apache TVM, a de facto standard for MLOps
The open source Apache TVM project is becoming a de facto standard in MLOps, and OctoML is gearing its commercialization and scale up
Read More →Streamlining data science with open source: Data version control and continuous machine learning
Can an open source-based workflow leveraging version control and continuous integration and deployment help streamline machine learning, like it did for software development?
Read More →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
Read More →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
Read More →2021 technology trend review, part one: Blockchain, cloud, open source
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Blockchain's DeFi-ning moment. Cloud, Kubernetes, and GraphQL. Open source is winning, open source creators are losing. A reality check on key technological drivers for the new decade.
Read More →Meet Stargate, DataStax’s GraphQL for databases. First stop – Cassandra
A flexible API is key to database accessibility and developer friendliness today. Cassandra was lacking in that department, and DataStax is trying to address this with the release of a new API layer called Stargate.
Read More →Getting there: Structured data, semantics, robotics, and the future of AI
Leveraging structure in data is key to making progress in AI, says AI prodigy Gary Marcus. A forward-looking view on Software 2.0, AI chips, robotics, and the future of AI
Read More →What’s next for AI: Gary Marcus talks about the journey toward robust artificial intelligence
Gary Marcus is one of the more prominent, and controversial, figures in AI. Going beyond his critique on Deep Learning, which is what many people know him for, Marcus puts forward a well-rounded proposal for robust AI
Read More →Observability, Stage 3: Distributed tracing as a service by logz.io
There is a progression in observability, says logz.io, while moving to offer distributed tracing as a service with Jaeger
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