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May 24 · Issue #139 · View online
3 Things You Need To Know From The Convergence Ecosystem
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A spanish galleon with over £13 billion in gold has been found at the bottom of the sea. A whole 300 years after sinking. In a few decades from now, we will probably read about “discovery” of hard-drives with Bitcoin wallets. Today’s issue explores Coinbase’s acquisition of Paradex, the use of machine learning to detect arguments and an ecosystem map of decentralised exchanges. |
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1. Coinbase acquires trading platform Paradex
M&A for distributed applications have begun! Exchange behemoth Coinbase has announced that it will be soon acquiring decentralised exchange Paradex. While the terms have not been revealed yet, it is safe to assume that the ten-member team that was working on Paradex will now be working with Coinbase. The product allowed individuals to trade tokens without having to deposit them to a centralised, third-party wallet. Instead, traders will be trading directly on a peer to peer basis with each other. This is the direct opposite of Coinbase’s existing, custodian model. The acquisition is an interesting example of an incumbent within the token economy acquiring potential competition before they reach scale. It is also indicative of the fact that there is a great extent of “centralisation” even with respect to decentralised exchanges and that they can be purchased if a large enough player wishes to. The move from coinbase will hedge itself against Circle’s move to token exchanges through their Poloniex acquisition and bring much needed public awareness of peer to peer, decentralised exchanges that require no third party custodianship.
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2. Machine learning is helping computers spot arguments online before they happen
If social networks have taught us anything in the past decade, it is perhaps that interactions on the web can turn rather ugly pretty quick. Hate speech and propaganda have become part and parcel of using web-based services. Services have now begun being sensitive to the matter and allocated resources to reduce occurrences of such instances. Researchers at Cornell University, Google Jigsaw and Wikimedia recently partnered up to create software that scans conversations for verbal indications of possible conflict. Their test prototype ran on Wikipedia’s “talk” pages with a 65% hit rate. The technique uses logistic regression to help its software make better judgements at the end of their training. For perspective, human candidates performing the same task had an efficiency of 72%. These tools can be especially useful in platforms such as Facebook where manual labour is currently being deployed to reduce hate speech. It may not be long before we see such bots being actively used to detect fake news and propaganda. For the intrigued - the team has published their research results on Arxiv.
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3. State of Decentralized Exchanges, 2018
Decentralised exchanges will soon go from prototypes to live environments where tests of their scalability and security will be put to the test. If Coinbase leads the revolution, the odds are very high we will see Paradex becoming a core part of the token exchange ecosystem in the coming months. Nathan Sexer from variabL uses this post to shed light on the different approaches to creating decentralised exchanges and the risks and opportunities offered by them. Although decentralised exchanges may have existed well since 2014 (Bitshares, Nxt AE), liquidity and user adoption has not seen scale yet. There is a steep learning curve involved, and confidence in these solutions in the absence of a centralised custodian is yet to rise. Also, it may be long before we see legacy institutions use decentralised exchanges due to the lack of trust in them. For now, it may be only retail players and market-makers using these platforms for active trading. The post sheds light both on the protocols and the applications built upon and provides a comprehensive list of each. Read the whole thing here.
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Will be an aggregator or a platform as per @ line of thinking? @'s fat protocol thesis would suggest an aggregator but it feels to me that Web 2.0 dynamics resulted in aggregation (FB & GOOG) but decentralised networks drive platform dynamics...
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