It’s a balmy 80 degrees on a mid-December day in Singapore, and something is puzzling Allen Day, a 41-year-old data scientist. Using the tools he has developed at Google, he can see a mysterious concerted usage of artificial intelligence on the blockchain for Ethereum.
Ether is the world’s third-largest cryptocurrency (after bitcoin and XRP), and it still sports a market cap of some $11 billion despite losing 83% of its value in 2018. Peering into its blockchain—the distributed database of transactions underpinning the cryptocurrency—Day detects a “whole bunch” of “autonomous agents” moving funds around “in an automated fashion.”
While he doesn’t yet know who has created the AI, he suspects they could be the agents of cryptocurrency exchanges trading among themselves in order to artificially inflate ether’s price.
“It’s not really just single agents doing things on their own,” Day says from Google’s Asia-Pacific headquarters. “They’re forming with other agents to have some larger group effect.”
Day’s official title is senior developer advocate for Google Cloud, but he describes his role as “customer zero” for the company’s cloud computing efforts.
As such it’s his job to anticipate demand before a product even exists, and he thinks making the blockchain more accessible is the next big thing.
Just as Google enabled (and ultimately profited) from making the internet more usable 20 years ago, its next billions may come from shining a bright light on blockchains. If Day is successful, the world will know whether blockchain’s real usage is living up to its hype.
Danish researcher Thomas Silkjaer is using Google’s BigQuery to map publicly available information about XRP cryptocurrency addresses. The craters represent some of cryptocurrency’s largest exchanges.
Last year Day and a small team of open-source developers quietly began loading data for the entire Bitcoin and Ethereum blockchains into Google’s big-data analytics platform, BigQuery. Then, with the help of lead developer Evgeny Medvedev, he created a suite of sophisticated software to search the data.
In spite of a total lack of publicity, word of the project spread quickly among crypto-minded coders. In the past year, more than 500 projects were created using the new tools, trying to do everything from predicting the price of bitcoin to analyzing wealth disparity among ether holders.
When it comes to cloud computing, Google is far behind Amazon and Microsoft. Last year Google pocketed an estimated $3 billion in revenue from cloud services. Amazon and Microsoft, meanwhile, generated about $27 billion and $10 billion, respectively.
Day is hoping that his project, known as Blockchain ETL (extract, transform, load), will help even the playing field. But even here Google is trying to catch up. Amazon entered blockchain in a big way in 2018 with a suite of tools for building and managing distributed ledgers.
Microsoft got into the space in 2015, when it released tools for Ethereum’s blockchain. It now hosts a range of services as part of its Azure Blockchain Workbench. But while Amazon and Microsoft are focusing on making it easier to build blockchain apps, Day is focusing on exposing how blockchains are actually being used, and by whom.
“In the future, moving more economic activity on chain won’t just require a consensus level of trust,” says Day, referring to the core validating mechanism of blockchain technology.
“It will require having some trust in knowing about who it is you’re actually interacting with.” In other words, if blockchain is to go mainstream, some of its beloved anonymity features will have to be abandoned.
A native of Placer County, California, Day got his first computer at the age of 5 and a few years later started writing simple programs. A fascination with volcanoes and dinosaurs turned his interest to life sciences, and he ultimately graduated from the University of Oregon with a dual degree in biology and Mandarin in 2000. From there he headed to UCLA to pursue a doctorate in human genetics and helped build a computer program to browse the genome.
This Silkjaer image uses data for the XRP cryptocurrency to show the movement of funds across the entire ledger of transactions, culminating in a snapshot of funds in an actual user’s wallet.
It was at UCLA where Day began relying on distributed computing, a concept that is core to blockchains, which store their data on a large network of individual computers. In the early 2000s Day needed to analyze the massive amounts of data that make up the human genome. To solve this problem he hooked many small computers together, vastly increasing their power.
“Distributed-systems technology has been in my tool kit for a while,” Day says.
“I could see there were interesting characteristics of blockchains that could run a global supercomputer.”
Hired in 2016 to work in the health and bioinformatics areas of Google, Day segued to blockchains, the hottest distributed-computing effort on the planet. But the talents he had honed—sequencing genomes for infectious diseases in real time and using AI to increase rice yields—were not easily applied to decoding blockchain.
Before Day and Medvedev released their tools, just searching a blockchain required specialized software called “block explorers,” which let users hunt only for specific transactions, each labeled with a unique tangle of 26-plus alphanumeric characters. Google’s Blockchain ETL, by contrast, lets users make more generalized searches of entire ecosystems of transactions.
To demonstrate how customers could use Blockchain ETL to make improvements to the crypto economy, Day has used his tools to examine the so-called hard fork, or an irrevocable split in a blockchain database, that created a new cryptocurrency—bitcoin cash—from bitcoin in the summer of 2017.
This particular split was the result of a Hatfield and McCoy “war” within the bitcoin community between a group who wanted to leave bitcoin as it was and another who wanted to develop a currency that, like cash, was cheaper and faster to use for small payments.
Using Google’s BigQuery, Day discovered that bitcoin cash, rather than increasing so-called micro-transactions, as the defecting developers claimed, was actually being hoarded among big holders of bitcoin cash.
“I’m very interested to quantify what’s happening so that we can see where the legitimate use cases are for blockchain,” Day says. “Then we can move to the next use case and develop out what these technologies are really appropriate for.”
Day’s work is inspiring others. Tomasz Kolinko is a Warsaw-based programmer and the creator of a service that analyzes smart contracts, a feature of certain blockchains that is designed to transparently enforce contractual obligations like collateralized loans but with less reliance on third parties, like lawyers. Kolinko was frustrated with his blockchain queries.
In December, Kolinko met Day at a hackathon in Singapore. Within a month of the meeting, Kolinko was using Google’s tools to search for a smart contract feature called a “selfdestruct,” designed to limit a contract’s life span. Using his own software in conjunction with Day’s, Kolinko took 23 seconds to search 1.2 million smart contracts—something that would have taken hours before.
The result: Almost 700 of them had left open a selfdestruct feature that would let anyone instantly kill the smart contract, whether that person was authorized or not. “In the past you couldn’t just easily check all the contracts that were using it,” Kolinko says. “This tool is both the most scary and most inspiring I’ve ever built.”
Day is now expanding beyond bitcoin and ethereum. Litecoin, zcash, dash, bitcoin cash, ethereum classic and dogecoin are being added to BigQuery. Independent developers are loading their own crypto data sets on Google.
Last August, a Dutch developer named Wietse Wind uploaded the entire 400 gigabytes of transaction data from Ripple’s XRP blockchain, another popular cryptocurrency, into BigQuery.
Wind’s data, which he updates every 15 minutes, prompted a Danish designer named Thomas Silkjaer to create a heat map of crypto flows. The resulting colorful orb reveals at a glance more than a million crypto wallets, including big exchanges like Binance and London’s crypto debit card startup Wirex, which are neck deep in XRP transactions.
“Google has been a bit of a sleeping giant in blockchain,” says BlockApps CEO Kieren James-Lubin, who is partnering with Google to sell enterprise blockchain apps.
In addition to Day’s work, Google has filed numerous patents related to the blockchain, including one in 2018 to use a “lattice” of interoperating blockchains to increase security, a big deal in a world where untold millions of crypto have been stolen by hackers.
The company is also pushing its developers to build apps on the Ethereum blockchain, and Google’s venture arm, GV, has made a number of significant investments in crypto startups.
The giant, it seems, is waking up.
-Michael del Castillo; Forbes Staff
How A BlackBerry Wiretap Helped Crack A Multimillion-Dollar Cocaine Cartel
On August 18, 2017, four men travelling in a dual-engine speedboat carrying 1,590 pounds of cocaine were intercepted by the U.S. Coast Guard northwest of the Galapagos Islands.
The federal agents manning the channel chose to launch a helicopter to hover over the boat. With this aggressive move, the men began to jettison the bales of coke, each with their own GPS tracker so they could be picked up at a later date, according to the government’s narrative. They attempted to flee, and when they ignored the warning shots from the helicopter, the chopper fired rounds directly at the boat, disabling it.
After the bales were collected, the government realized they had just stopped a huge amount of cocaine from entering the U.S. In total, it carried a street value of $25 million. The four men, all Ecuadorians, were swiftly arrested and charged.
Though the cartel had set up a sophisticated, multilayered operation that sought to slip coke into the country and up to Ohio via land, air and sea, they had made a crucial error: They used BlackBerry phones. As the drug barons chatted about shifting cocaine and how to avoid the narcs over BlackBerry Messenger, a wiretap on a server in Texas was quietly collecting all their communications.
In a case that’s Narcos meets The Wire, federal agents have, since June 2017, been listening in on that server. And beyond that interception, Forbes can exclusively reveal it is yielding results. On Friday, an Ohio court is unsealing charges against one of the crew’s top brass: Francisco Golon-Valenzuela, 40.
Known as El Toro, Spanish for The Bull, the Guatemalan was extradited from Panama earlier this week and is appearing before a magistrate judge today. (Forbes hasn’t yet made contact with his counsel for a response but will update if comment is forthcoming.)
Described as one of various organizers and leaders of the unnamed cartel, El Toro is charged with conspiring to distribute at least 5 kilograms or more of cocaine on the high seas. As a result, he’s facing between 10 years and life in prison.
A key to BlackBerry
For any organized crime operation, BlackBerry has always been a poor choice. No longer extant since being decommissioned in spring this year, BlackBerry Messenger did encrypt messages, but the Canadian manufacturer of the once-ubiquitous smartphone had the key. And all messages went through a BlackBerry-owned server. If law enforcement could legally compel BlackBerry to hand over that key, they would get all the plain-text messages previously garbled into gibberish with that key.
Compare this to genuine, end-to-end encrypted messaging apps like WhatsApp or Signal; they create keys on the phone itself and the device owner controls them. To spy on those messages, governments either have to hack a target device or have physical access to the phone. Both are tricky to do, especially for investigations of multinational criminal outfits. Police can put a kind of tap on a WhatsApp server, known as a pen register.
This will tell them what numbers have called or messaged one another, and at what date and time, but won’t provide any message content. This makes those apps considerably more attractive to privacy-conscious folk than those where the developer holds the keys, though sometimes to the chagrin of law enforcement.
It’s unclear how or when the DEA got access to the BlackBerry server. A so-called Title III order was issued, granting them court approval to carry out the wiretap, though that remains under seal.
It proved vital to the investigation. “There would be no case without the without the Title III on BlackBerry Messenger,” said Dave DeVillers, who was recently nominated as U.S. Attorney for the Southern District of Ohio. “The defendants, the seizures, the conspiracy were all identified with the Title III.”
A spokesperson for BlackBerry said: “We do not speculate or comment upon individual matters of lawful access.” The company has, however, previously made its stance on encryption public: Unlike other major tech providers like Apple or Google, BlackBerry will hand over the keys if it’s served with a legitimate law enforcement request.
If the police did receive a key from BlackBerry, it wouldn’t be the first time. Back in 2016, it emerged that the Royal Canadian Mounted Police (RCMP) had decrypted more than one million BlackBerry messages as part of a homicide investigation dating back to 2010.
As per reports from that time, it’s possible to use one of BlackBerry’s keys to unlock not just one device’s messages, but those on other phones too. Forbes asked the DOJ whether investigators would’ve been able to access other, innocent people’s BlackBerry messages as part of this wiretap, but hadn’t received a response at the time of publication.
Fishermen and spies
However those BlackBerry messages were intercepted, they helped illuminate a dark criminal conspiracy constructed of myriad parts. As revealed in today’s indictment, made known to Forbes ahead of publication, the gang employed “load coordinators.” Think of them as project managers, helping locate drivers for trucks and boats while finding people to invest in the cocaine.
Fishermen and other maritime workers were also allegedly recruited. They would help both in refueling the drug baron’s ships, but also helping transport the powder, prosecutors said.
Other individuals became ad hoc spies, sharing information on the activities and locations of police and military personnel trying to intercept shipments, according to the government’s allegations. Other coconspirators sheltered individuals who were at risk of extradition—not that it saved El Toro.
Forbes first became aware of the investigation in 2017, when a search warrant detailed various BlackBerry intercepts. In one, a pair of cartel employees discussed having to put some cocaine transports on hold because of a multinational maritime exercise—the Unitas Pacifico 2017—taking place in their shipment lanes, according to the warrant. BlackBerry wasn’t the only major tech provider to help on the case; That search warrant was for a Google account linked to one of the suspects, which investigators believe was used for further logistics.
The investigation has revealed that the 2017 seizure wasn’t the only time the cops had disrupted what was evidently a criminal enterprise worth hundreds of millions. In May 2016, long before the BlackBerry wiretap went up and the investigation into the cartel had begun in earnest, U.S. authorities intercepted 1,940 pounds of coke near the Guatemalan-Mexico border, worth another $30 million.
Despite such successes, DeVillers told Forbes the American government will never interdict its way to ending the drug trade. “We can only disrupt it,” he added. “And if we turn the tools used by the cartels to run their organization against them, we do just that.”
-Thomas Brewster; Forbes
How Virtual Therapy Apps Are Trying To Disrupt The Mental Health Industry
Millions of Americans deal with mental illness each year, and more than half of them go untreated. As the mental health industry has grown in recent years, so has the number of tech startups offering virtual therapy, which range from online and app-based chatbots to video therapy sessions and messaging.
Still a nascent industry, with most startups in the early seed-stage funding round, these companies say they aim to increase access to qualified mental health care providers and reduce the social stigma that comes with seeking help.
While the efficacy of virtual therapy, compared with traditional in-person therapy, is still being hotly debated, its popularity is undeniable. Its most recognizable pioneers, BetterHelp and TalkSpace, have enrolled nearly 700,000 and more than 1 million users respectively. And investors are taking notice.
Funding for mental health tech startups has boomed in the past few years, jumping from roughly $100 million in 2014 to more than $500 million in 2018, according to Pitchbook. In May of this year, the subscription-based online therapy platform Talkspace raised an additional $50 million, bringing its total funding to just under $110 million since its 2012 inception.
The ubiquity of smartphones, coupled with the lessening of the stigma associated with mental health treatment have played a large role in the growing demand for virtual therapy. Of the various services offered on the Talkspace platform, “clients by far want asynchronous text messaging,” says Neil Leibowitz, the company’s chief medical officer.
Users seem to prefer back-and-forth messaging that isn’t restricted to a narrow window of time over face-to-face interactions. At BetterHelp, founder Alon Matas notes that older users are more likely to go for phone and video therapy sessions, whereas younger users favor text messaging.
“Each generation is getting progressively more mobile-native,” says John Prendergass, an associate director at Ben Franklin Technology Partners’ healthcare investment group, “so I think we’re going to see people become increasingly more accustomed, or predisposed, to a higher level of comfort in seeking care online.”
The ease and convenience of virtual therapy is another draw, particularly for busy people or those who live in rural areas with limited access to therapy and a range of care options.
Alison Darcy, founder and CEO of Woebot, a free automated chatbot that uses artificial intelligence to provide therapeutic services without the direct involvement of humans, says that with Woebot and other similar services, there is no need to schedule appointments weeks in advance and users can receive real-time coaching at the moment they need it, unlike traditional therapy. The sense of anonymity online can also lead to more openness and transparency and attracts people who normally wouldn’t seek therapy.
Along with stigma, the cost of therapy has historically acted as a barrier to accessing quality mental-health care. Health insurance is often unlikely to cover therapy sessions. In most cities, sessions run about $75 to $150 each, and can go as high as $200 or more in places like New York City. Web therapists don’t have to bear the expense of brick-and-mortar offices, filing paperwork or marketing their services, and these savings can be passed on to clients.
BetterHelp offers a $200-a-month membership that includes weekly live sessions with a therapist and unlimited messaging in between, while Talkspace’s cheapest monthly subscription at $260-a-month, offers unlimited text, video and audio messaging.
But virtual therapy, particularly text-based therapy, is not suitable for everyone. Nor is it likely to make traditional therapy obsolete. “Online therapy isn’t good for people who have severe mental and relational health issues, or any kind of psychosis, deep depression or violence,” says Christiana Awosan, a licensed marriage and family therapist.
At her New York and New Jersey offices, she works predominantly with black clients, a population that she says prefers face-to-face meetings. “This community is wary of mental health in general because of structural discrimination,” Awosan says. “They pay attention to nonverbal cues and so they need to first build trust in-person.”
Virtual therapy apps can still be beneficial for people with low-level anxiety, stress or insomnia, and they can also help users become aware of harmful behaviors and obtain a higher sense of well-being.
Sean Luo, a psychiatrist whose consultancy work focuses on machine learning techniques in mental health technology, says: “This why some of these companies are getting very high valuations. There are a lot of commercialization possibilities.” He adds that from a mental health treatment perspective, a virtual therapy app “isn’t going to solve your problems, because people who are truly ill will by definition require a lot more.”
Relying on digital therapy platforms might also provide a false sense of security for users who actually need more serious mental-health care, and many of these apps are ill-equipped to deal with emergencies like suicide, drug overdoses or the medical consequences of psychiatric illness. “The level of intervention simply isn’t strong enough,” says Luo, “and so these aspects still need to be evaluated by a trained professional.
– Ruth Umoh, Diversity and Inclusion Writer, Forbes Staff.
AI 50 Founders Say This Is What People Get Wrong About Artificial Intelligence
Forbes’ new list of promising artificial intelligence companies highlights how the technology is creating real value across industries like transportation, healthcare, HR, insurance and finance.
Naturally, the founders of the honoree companies are excited about the technology’s benefits and, in their roles, spend a lot of time thinking and talking about its strengths and limitations. Here’s what they think people get wrong about artificial intelligence.
Affectiva CEO Rana el Kaliouby says she’s too often encountered the idea that AI is “evil.”
“AI—like any technology in history—is neutral,” she says. “It’s what we do with it that counts, so it’s our responsibility, as an AI ecosystem, to drive it in the right direction.”
Companies need to be aware of how AI could widen bounds of inequality, she adds: “Any AI that is designed to interact with humans—Affectiva’s included—must be evaluated with regards to the ethical and privacy implications of these technologies.”
Sarjoun Skaff, CTO and cofounder of Bossa Nova Robotics, says that the biggest misconception he encounters is that artificial intelligence is actually, well, intelligent.
“The truth is much more mundane,” he says. “AI is a very good pattern-matching tool. To make it work well, though, scientists need to understand the details of how it internally works and not treat it as an ‘intelligent’ black box. At the end of the day, making good use of great pattern matching still belongs to humans.”
Similarly, Aira cofounder Suman Kanuganti says that the public has “over-inflated expectations” for artificial intelligence.
“Garry Kasparov sums it up nicely: ‘We are in the beginning of MS-DOS and people think we are Windows 10,’” Kanuganti says. “AI realistically is still like a 3-year-old child at this stage. When it works, it feels magical. It does some things well, but there’s still a long way to go.”
So, no, we are nowhere close to “artificial general intelligence,” or AGI, where machines are actually as smart as humans.
“We’re still a long way from AI having the general intelligence of even a flea,” says David Gausebeck.
Despite the tendency to overestimate what artificial intelligence can do, the difficulty of building an effective system is often underestimated, some founders say.
“The systems you need to implement and manage machine learning in production are often much more complex than the algorithms themselves,” says Algorithmia CEO Diego Oppenheimer. “You can’t throw models at a complex business problem and expect returned value. You need to build an ecosystem to manage those models and connect their intelligence to your applications.”
Put another way, you can’t just “sprinkle on some artificial intelligence like a magic sauce,” says Feedzai CEO Nuno Sebastiao.
One of the most common tropes that a handful of founders brought up was the idea that artificial intelligence is primarily a job killer.
People.ai founder Oleg Rogynskyy says that AI should be seen as a creator of new opportunities instead of a destroyer of jobs.
“In a nutshell, AI does two things: It automates repetitive low-value-add work for humans (which will indeed take low-complexity jobs away), which we think of as ‘Autopilot,’ and it guides people on how to do their work or other activities better (which makes humans more effective at what they do), which we call ‘Copilot,’” he says. “While Autopilot can take simple, repetitive and boring jobs away, Copilot is absolutely the best way to guide, train and educate humans on how to do new things.”
– By Jillian D’Onfro, Forbes
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