Effect.AI, a network for AI intelligence whose first phase is the Effect Force mechanical turk, has released a newsletter outlining its progress, development, and plans for January and the rest of 2019.
Effect.AI has announced that it has enrolled in mobile portfolio tracker Blockfolio’s “Signals” program. Being on Signals allows the Effect.AI team to communicate directly with investors who are tracking the EFX token in the Blockfolio app.
Chris Dawe, CEO and founder of Effect.AI, held a “late night” AMA session on the Effect.AI Telegram group, which was later summarized on Reddit.
In the AMA and community Telegram, Dawe expressed dissatisfaction with the current transactions per second available to the Effect Force project running on the NEO blockchain, and claimed that it has stopped development on further NEO smart contracts. Dawe further posted in the Telegram channel that migration to the upcoming NEO 3.0 protocol is still possible, but an unsure prospect, and that the team is exploring all options for host blockchains.
Effect.AI’s ambassador program goes live on February 1st, 2019. 49 ambassadors have been selected from around the world in order to encourage productive community activity and contributions. The ambassador program represents the start of a “decentralized autonomous community” that is expected to contribute to the future governance of the Effect.AI project.
CEO Chris Dawe will be touring Europe to promote Effect.AI in the first half of 2019, with stops scheduled at events in Amsterdam, Cyprus, Romania, Spain, and the Netherlands.
The Effect.AI website is scheduled for an update that is focused on integration of The Effect Network. According to Effect.AI, The Effect Network “will maintain a decentralized exchange with a pool of tokens to provide liquidity, encourage adoption of The Effect Network, and stabilize network fees.” This pool, known as the “Galaxy Pool,” is intended to stabilize exchange rates for the users of the Effect.AI platform.
Templates and Content Flagging
Finally, Effect Force has added a content flagging function to its platform, so that workers will be able to submit suspected mistakes, inappropriate content, or dead links to the Effect Force validators for review.
Effect.AI’s January update can be read in full at the following link: