We are an early-stage research and development startup. Our ambitious goal is to build a system capable of understanding knowledge, to answer questions and get things done. Our work leverages cutting-edge domains such as Probabilistic Programming and Applied Category Theory.
Skill areas:
- Julia software engineering: to build our core system
- Research across areas: to develop our theoretical framework
"For some of you, it is difficult enough to keep everyone up to date with the tasks at hand. It is even more so when they involve codes. Lots of codes."
Turing has more things that work out of the box, so if you do not have complex requirements its a good first step. Gen allows for composing models using its generative function interface, you can specify models in different ways. You can also have fine grained control over inference, rather than a few preset methods.
Gen has also worse error messages and docs.
We’re building the future of identity, privacy, financial markets and commerce through blockchains and other cryptographic technologies. At the core of this work is Polkadot - a platform that enables blockchains of all kinds to interact and stay secure. This is an opportunity to work at the forefront of technological development and join in shaping the future of society.
Security is at the heart of decentralised protocols and applications. Extensive reliance on correct implementation and good user practices necessitates that we spend sufficient time on Security in the Web3 ecosystem.
Web3 Foundation aims to ensure that crucial projects and networks are sufficiently reviewed and monitored, as well as any developers and users are aware of best security practices. The Security team will be responsible for the initiatives that allow us to achieve those goals together with our open source community.
First you need to understand what is a fault in this case. If you make use of PoW the chain is picked on the basis of total difficulty, this means that if any validator (already admitted by a centralised party) is hacked, then they can very quickly produce a chain which gets accepted by all others as canonical (with higher difficulty). This reverses any existing transactions and requires significant extra-protocol action to mitigate.
With PoA there is no such ability, since the canonicality is not abusable. Furthermore addition and removal of nodes can be decentralised and determined according to any rules (since validators can be specified in a contract). This makes it possible to include validators based on something like majority voting.
What is the point of blockchain if there is no fault tolerance, under your private PoW scenario as soon as a single node goes rogue the security guarantees disappear and the chain is messed up.
With this PoA you can keep a well functioning chain and kick misbehaving nodes (up to 50% of validators for this consensus engine) in due time.
The way people try to use PoW for consortium networks does not cause excess power usage: low difficulty, low powered device/s.
Anyone malicious that connects to the network can easily overpower the existing validators. Sybil resistance is only the case if validators compete with computation due to economic incentives. In consortium network the native tokens have likely no/low value.
With PoA there are rules according to which validators are added/removed and limits on block issuance that ensure fault tolerance.
Proof of work is not the right tool for private networks since it is not sybil resistant in this context. https://github.com/paritytech/parity/wiki/Demo-PoA-tutorial is another tutorial that uses a Proof of Authority consensus for an Ethereum-like chain.
We are an early-stage research and development startup. Our ambitious goal is to build a system capable of understanding knowledge, to answer questions and get things done. Our work leverages cutting-edge domains such as Probabilistic Programming and Applied Category Theory.
Skill areas:
- Julia software engineering: to build our core system
- Research across areas: to develop our theoretical framework
Useful experience: algorithms, Bayesian statistics, symbolic computing, optimization, category theory.
Find more on our website, and apply to join us: https://planting.space/joinus