Ripple is giving universities $50M to research cryptocurrency and blockchain

After donating $29 million to an American public school charity , cryptocurrency giant Ripple is launching another $50 million fund — this time for universities.

The new initiative, named University Blockchain Research Initiative (UBRI), will provide $50 million in funding to universities for academic research and initiatives related to blockchain, cryptocurrency, and digital payments, the company announced on its blog today.

Apart from the funding, Ripple is promising to provide subject matter expertise and technical resources to partner universities as part of this initiative.

Ripple has so far partnered with 17 universities across the globe. The current list of UBRI participants includes Princeton University, UC Berkeley, MIT, Delft University of Technology, IIT Bombay, UNC Chapel Hill, University of Luxembourg, Australian National University, Fundação Getulio Vargas in Brazil, IIIT Hyderabad, Korea University, UT Austin, University College of London, University of Nicosia, University of Oregon, and University of Waterloo.

As part of the initiative, the universities will be designing curriculums focused on blockchain and cryptocurrency; the aim is to encourage students to pursue research and innovation in distributed ledger technologies. Ripple has trusted the universities with the freedom to choose their own research focus and build up custom curricula.

The fact that some of the most reputable universities are getting involved in blockchain and cryptocurrency research is a notable development – and one that could go a long way to encouraging responsible innovation in the space.

Indeed, Imperial College London blockchain researcher Joshua Lind recently told Binary District Journal that “the best results will come from academia, industry, and the existing blockchain [and] crypto communities working together.”

$3M worth of cryptocurrency seized from Bulgarian criminals

Yet another group of organized criminals have been apprehended after illegally acquiring cryptocurrency.

Three individuals in Bulgaria have been arrested and charged after obtaining over $3 million (5 million lev) through illegal schemes. Prosecutors had been gathering evidence against the group since June.

According to local outlets , police found a trove of passwords and private keys associated with various cryptocurrency exchange services and wallet providers.

It is not clear what exactly the miscreants had done to obtain such a large amount of cryptocurrency illegally.

However, local reports state that the criminals were using “innovative mechanisms, specialist software, and advanced knowledge in the area of cryptocurrency.”

Authorities also seized a car worth $35,000 (60,000 lev) that was bought using the pilfered cryptocurrency.

Despite cryptocurrency‘s promise of anonymity, criminals are still being caught. Earlier this month, a group of eight Japanese men were arrested for running a cryptocurrency Ponzi scheme valued at over $60 million.

Researchers tap AI in the fight against ICO scams

There’s no definitive way to tell if an initial coin offering (ICO) is a scam, but a machine learning-based research method could make it easier to avoid the most obvious ones. And that’s good for everyone except the scammers.

A Chinese startup called Shannon.AI , working with researchers from Stanford, University of California Santa Barbara, and the University of Michigan, recently unveiled a white paper detailing an AI designed to sniff out cryptocurrency scams.

When it comes to cryptocurrency investing there’s only one sure-fire way to avoid getting scammed: don’t do it. Sure, the Bitcoin bros and millennial millionaires make it look like we can all drive our lambos to the moon if we invest, but the reality is the majority of ICOs last year were either scams or failed .

As the researchers put it in their white paper :

So how do you separate the scams from the legitimate contenders when they all seem like techno-babble to anyone who isn’t well-versed in reading white papers?

There’s no easy answer. An almost complete lack of any regulation makes it impossible to ‘prove’ a scam until it’s too late . This isn’t about spreading fear, uncertainty, and doubt (FUD). It’s simple facts.

Part of the reason for this is white papers and websites can be made to look legitimate with relative ease. Simply put, most scammers are counting on the fact that you won’t dedicate as much time to researching their coin as they can to making it appear legitimate.

The problem is made even worse by the general toxicity and shill-like nature of the vast majority of cryptocurrency communities. When you have a large group of people whose common denominator is a mutual investment, coupled by bounty programs for spreading positive messages, it becomes impossible to get a clear picture of a coin’s legitimacy by talking to the people involved with it.

The Shannon.AI team’s white paper outlines a machine learning approach to separating the scams from legitimate projects:

And this is encouraging, even if it isn’t revolutionary. This particular paper showcases an algorithm-based system that essentially automates what savvy investors are already doing by seeking out publicly available information that draws an overall picture of a coin. This is good for a couple of reasons, as the team points out:

Sadly, due to the nature of these scams, when human researchers point out the red flags of a project that appears to be a scam those warnings are usually dismissed by cryptocurrency holders as “paid attacks” or FUD, even when they come from reputable news sites.

It’s easier for a company to attack the messenger than fix any problems pointed out by legitimate researchers and journalists.

But if an AI working in a black box comes to the same conclusions, based on the same readily available information, it could be considered more trustworthy. The Shannon.AI algorithms don’t do anything a person couldn’t do on their own, but they do it much, much faster — and with greater accuracy.

Unless you’re a journalist or researcher who has the luxury of spending days at a time poring over white papers, websites, and Github repositories, you’re probably missing key pieces of information. AI that does the same job in a fraction of the time could make scam ICOs a thing of the past, or at least the minority.

We’ve reached out to the research team to see if there’s any plans to go to market with this tool, or if they’ll be further developing it.

In the mean time, trade with care: for every person who made millions investing in altcoins there are thousands of people who wished they’d paid attention to the red flags before investing.

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