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Moka raises $27M led by Hillhouse to make hiring more data-driven in China

Posted by on Mar 4, 2019 in Artificial Intelligence, Burger King, California, China, ggv capital, GSR Ventures, Hillhouse Capital, Hiring, JD.com, moka, recruitment, SaaS, Stanford University, TC, Tencent, turo, University of California, University of Michigan, Xiaomi | 0 comments

Moka, a startup that wants to make talent acquisition a little more data-driven for China-based companies that range from smartphone giant Xiaomi to Burger King’s local business, announced Monday that it has raised a 180 million yuan ($27 million) Series B round of funding.

The deal was led by Hillhouse Capital, an investor in top Chinese technology companies such as Tencent, Baidu, JD.com, Pinduoduo — just to name a few. Other investors who took part include Xianghe Capital, an investment firm founded by two former Baidu executives, Chinese private equity firm GSR Ventures and GGV Capital.

Moka claims more than 500 enterprise customers were paying for its services by the end of 2018. Other notable clients are McDonalds and one of China’s top livestreaming services YY. It plans to use its new capital to hire staff, build new products and expand the scope of its business.

Founded in 2015, Moka compares itself to Workday and Salesforce in the U.S. It has created a suite of software aiming to make recruiting easier and cheaper for companies with upwards of 500 employees. Its solutions take care of the full cycle of hiring. To start with, Moka allows recruiters to post job listings across multiple platforms with one click, saving them the hassle of hopping between portals. Its AI-enabled screening program then automatically filters candidates and make recommendations for companies. What comes next is the interview, which Moka helps streamline with automatic email and message reminders for job applicants and optimized plans for interviewers on when and where to meet their candidates.

That’s not the end, as Moka also wants to capture what happens after the talent is onboard. The startup helps companies maintain a talent database consist of existing employees and potential hires. The services allow companies to keep a close tap on their staff, whose resume update will trigger a warning to the employer, and alerts the recruiter once the system detects suitable candidates.

Moka is among a wave of startups founded by Chinese entrepreneurs with foreign education and work experiences. Zhao Oulun, whose English nickname is Orion, graduated from the University of California, Berkley and worked at San Francisco-based peer-to-peer car sharing company Turo before founding Moka with Li Guoxing. Li himself is also a “sea turtle,” a colloquial term in Chinese that describes overseas-educated graduates who return home to work. Li graduated from the University of Michigan and Stanford University, and had worked at Facebook as an engineer.

When the founders re-entered China, they saw something was missing in the booming domestic business environment: effective talent management.

“Businesses are flourishing, but at the same time many of them fall short in internal organization and operation. To a large extent, the issue pertains to the lack of digital and meticulous operation for human resources, which slows down decision-making and leads to mistakes around talents and company organization,” says chief executive Zhao in a statement.

Moka’s mission has caught the attention of investors. Jixun Foo, a partner at Moka backer GGV Capital, also believes China’s businesses can benefit from a data-driven approach to people management: “We are positive about Moka becoming a comprehensive HR service provider in the future through its unique data-powered and intelligent solutions.”


Source: The Tech Crunch

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Crypto and venture’s biggest names are backing a new distributed ledger project called Oasis Labs

Posted by on Jul 9, 2018 in Amazon Web Services, blockchain, blockchains, California, Co-founder, coinbase, cryptocurrencies, cryptocurrency, cryptography, distributed computing, Distributed Ledger, ethereum, foundation capital, guggenheim, MIT, smart contract, software development, TC, Uber, University of California, university of california berkeley, Venture Capital, web services | 0 comments

A team of top security researchers from the University of California, Berkeley and MIT have come together to launch a new cryptographic project that combines secure software and hardware to enable privacy-preserving smart contracts under the banner of Oasis Labs.

That vision, which is being marketed as the baby of a union between Ethereum and Amazon Web Services, has managed to attract $45 million in pre-sale financing from some of the biggest names in venture capital and cryptocurrency investing.

The chief architect of the project (and chief executive of Oasis Labs) is University of Berkeley Professor Dawn Song, a security expert who first came to prominence in 2009 when she was named one of as one of MIT Technology Review’s Innovators under 35. Song’s rise in the security world was capped with both a MacArthur Fellowship and a Guggenheim Award for her work on security technologies. But it’s the more recent work that she’s been doing around hardware and software development in conjunction with other Berkeley researchers like her postdoctoral associate, Raymond Cheng, that grabbed investors attention.

Through the Keystone enclave hardware project, Song and Cheng worked with MIT researchers and professors like Srini Devadas and Ilia Lebedev on technology to secure sensitive data on the platform.

“We use a combination of trusted hardware and cryptographic techniques (such as secure multiparty computation) to enable smart contracts to compute over this encrypted data, without revealing anything about the underlying data. This is like doing computation inside a black box, which only outputs the computation result without showing what’s inside the black box,” Song wrote to me in an email. “In addition to supporting existing trusted hardware implementations, we are also working on a fully open source trusted hardware enclave implementation; a project we call Keystone. We also have years of experience building differential privacy tools, which are now being used in production at Uber for their data privacy initiatives. We plan to incorporate such techniques into our smart contract platform to further provide privacy and protect the computation output from leaking sensitive information about inputs.”

Song says that her project has solved the scaling problem by separating execution from consensus.

For each smart contract execution, we randomly select a subset of the computation nodes to form a computation committee, using a proof of stake mechanism. The computation committee executes the smart contract transaction,” Song wrote in an email exchange with TechCrunch. “The consensus committee then verifies the correctness of the computation results from the computation committee. We use different mathematical and cryptographic methods to enable efficient verification of the correctness of the computation results. Once the verification succeeds, the state transition is committed to the distributed ledger by the consensus committee.”

By having the computation committee working in parallel with the consensus committee only needing to verify the correctness of the computation creates an easier path to scalability.

Other platforms have attempted to use sampling to speed up transactions over distributed systems (Hedera Hashgraph comes to mind), but have been met with limited adoption in the market.

“We use proof-of-stake mechanisms to elect instances of different types of functional committees: compute, storage and consensus committees,” Song explained. “We can scale each of the different functions independently based on workload and system needs. One of our observations of existing systems is that consensus operations are very expensive. our network protocol design allows compute committees and storage committees to process transactions without relying on heavy-weight consensus protocols.”

Song’s approach has managed to gain the support of firms including: a16zcrypto, Accel, Binance, DCVC (Data Collective), Electric Capital, Foundation Capital, Metastable, Pantera, Polychain, and more.

In all, some 75 investors have rallied to finance the company’s approach to securing data and selling compute power on a cryptographically secured ledger.

“It’s exciting to see talented people like Dawn and her team working on ways to transition the internet away from data silos and towards a world with more responsible ways to share and own your data,” said Fred Ehrsam, co-founder of Coinbase and Oasis Labs investor, in a statement.

“The next step is getting our product in the hands of developers who align with our mission and can help inform the evolution of the platform as they build applications upon it,” said Oasis Labs co-founder and CTO Raymond Cheng in a statement.

For potential customers who’d eventually use the smart contracts developed on Oasis’ platform the system would work much like the method established by Ethereum.

“The token usage model in Oasis is very similar to Ethereum, where users pay gas fee to miners for executing smart contracts,” Song wrote. “One just needs one token to pay for gas fee for executing smart contracts. As with Ethereum, in our platform storage and compute have different pricing models but they both are paid with the same token.”

And Oasis’ leadership is looking ahead to a marketplace that incentivizes scale and makes fees accessible. “If the token price goes up, the amount of tokens needed to pay for operations can decrease (this is similar to Ethereum’s gas price, which is independent from the price of Ether). The number of tokens needed to pay for smart contract execution is not fixed.”


Source: The Tech Crunch

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