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Twitter bags deep learning talent behind London startup, Fabula AI

Twitter has just announced it has picked up London-based Fabula AI. The deep learning startup has been developing technology to try to identify online disinformation by looking at patterns in how fake stuff vs genuine news spreads online — making it an obvious fit for the rumor-riled social network.

Social media giants remain under increasing political pressure to get a handle on online disinformation to ensure that manipulative messages don’t, for example, get a free pass to fiddle with democratic processes.

Facebook, Google and Twitter told to do more to fight fake news ahead of European elections

Twitter says the acquisition of Fabula will help it build out its internal machine learning capabilities — writing that the UK startup’s “world-class team of machine learning researchers” will feed an internal research group it’s building out, led by Sandeep Pandey, its head of ML/AI engineering.

This research group will focus on “a few key strategic areas such as natural language processing, reinforcement learning, ML ethics, recommendation systems, and graph deep learning” — now with Fabula co-founder and chief scientist, Michael Bronstein, as a leading light within it.

Bronstein is chair in machine learning & pattern recognition at Imperial College, London — a position he will remain while leading graph deep learning research at Twitter.

Fabula’s chief technologist, Federico Monti — another co-founder, who began the collaboration that underpin’s the patented technology with Bronstein while at the University of Lugano, Switzerland — is also joining Twitter.

“We are really excited to join the ML research team at Twitter, and work together to grow their team and capabilities. Specifically, we are looking forward to applying our graph deep learning techniques to improving the health of the conversation across the service,” said Bronstein in a statement.

“This strategic investment in graph deep learning research, technology and talent will be a key driver as we work to help people feel safe on Twitter and help them see relevant information,” Twitter added. “Specifically, by studying and understanding the Twitter graph, comprised of the millions of Tweets, Retweets and Likes shared on Twitter every day, we will be able to improve the health of the conversation, as well as products including the timeline, recommendations, the explore tab and the onboarding experience.”

Terms of the acquisition have not been disclosed.

We covered Fabula’s technology and business plan back in February when it announced its “new class” of machine learning algorithms for detecting what it colloquially badged ‘fake news’.

Its approach to the problem of online disinformation looks at how it spreads on social networks — and therefore who is spreading it — rather than focusing on the content itself, as some other approaches do.

Fabula has patented algorithms that use the emergent field of “Geometric Deep Learning” to detect online disinformation — where the datasets in question are so large and complex that traditional machine learning techniques struggle to find purchase. Which does really sound like a patent designed with big tech in mind.

Fabula likens how ‘fake news’ spreads on social media vs real news as akin to “a very simplified model of how a disease spreads on the network”.

One advantage of the approach is it looks to be language agnostic (at least barring any cultural differences which might also impact how fake news spread).

Back in February the startup told us it was aiming to build an open, decentralised “truth-risk scoring platform” — akin to a credit referencing agency, just focused on content not cash.

It’s not clear from Twitter’s blog post whether the core technologies it will be acquiring with Fabula will now stay locked up within its internal research department — or be shared more widely, to help other platforms grappling with online disinformation challenges.

The startup had intended to offer an API for platforms and publishers later this year.

But of course building a platform is a major undertaking. And, in the meanwhile, Twitter — with its pressing need to better understand the stuff its network spreads — came calling.

A source close to the matter told us that Fabula’s founders decided that selling to Twitter instead of pushing for momentum behind a vision of a decentralized, open platform because the exit offered them more opportunity to have “real and deep impact, at scale”.

Though it is also still not certain what Twitter will end up doing with the technology it’s acquiring. And it at least remains possible that Twitter could choose to make it made open across platforms.

“That’ll be for the team to figure out with Twitter down the line,” our source added.

A spokesman for Twitter did not respond directly when we asked about its plans for the patented technology but he told us: “There’s more to come on how we will integrate Fabula’s technology where it makes sense to strengthen our systems and operations in the coming months.  It will likely take us some time to be able to integrate their graph deep learning algorithms into our ML platform. We’re bringing Fabula in for the team, tech and mission, which are all aligned with our top priority: Health.”

Mode raises $3M Series A to put sensor data in the cloud

True Ventures has led the $3 million round for Mode, a real-time database that gives companies instant access to sensor data. GigaOm founder and True Ventures partner Om Malik has joined the startup’s board of directors as part of the deal.

Sensor data is collected from vehicles, cell phones, appliances, medical equipment and other machines. Businesses deploying these sensors, however, often don’t have back-end databases or tools to understand what that data means for the real world.

San Mateo-based Mode wants to help them make sense of it by moving the hoards of sensor data to the cloud, where they can better understand their devices and derive actionable insights. For now, Mode is targeting the solar, medical and manufacturing industries.

“We focus on data collection because we want to address common infrastructure challenges and let customers spend their time utilizing data for their businesses,” said Gaku Ueda, Mode co-founder and Twitter’s former director of engineering.

Ueda and co-founder Ethan Kan, who was previously the director of engineering at gaming startup 50Cubes, have a long history of friendship. True Ventures’ Malik says that’s part of what attracted him to the company.

“Companies are not a straight line,” Malik told TechCrunch. “You go through ups and downs. If you have a good co-founder, you have someone to get you through it.”

The round brings Mode’s total funding to $5 million. The company, which is also backed by Kleiner Perkins, Compound.vc and Fujitsu, will use the Series A financing to connect additional sensors to the cloud and expand its team.

Building a great startup requires more than genius and a great invention

Many entrepreneurs assume that an invention carries intrinsic value, but that assumption is a fallacy.

Here, the examples of the 19th and 20th century inventors Thomas Edison and Nikola Tesla are instructive. Even as aspiring entrepreneurs and inventors lionize Edison for his myriad inventions and business acumen, they conveniently fail to recognize Tesla, despite having far greater contributions to how we generate, move and harness power. Edison is the exception, with the legendary penniless Tesla as the norm.

Universities are the epicenter of pure innovation research. But the reality is that academic research is supported by tax dollars. The zero-sum game of attracting government funding is mastered by selling two concepts: Technical merit, and broader impact toward benefiting society as a whole. These concepts are usually at odds with building a company, which succeeds only by generating and maintaining competitive advantage through barriers to entry.

In rare cases, the transition from intellectual merit to barrier to entry is successful. In most cases, the technology, though cool, doesn’t give a fledgling company the competitive advantage it needs to exist among incumbents and inevitable copycats. Academics, having emphasized technical merit and broader impact to attract support for their research, often fail to solve for competitive advantage, thereby creating great technology in search of a business application.

Of course there are exceptions: Time and time again, whether it’s driven by hype or perceived existential threat, big incumbents will be quick to buy companies purely for technology. Cruise/GM (autonomous cars), DeepMind/Google (AI) and Nervana/Intel (AI chips). But as we move from 0-1 to 1-N in a given field, success is determined by winning talent over winning technology. Technology becomes less interesting; the onus is on the startup to build a real business.

If a startup chooses to take venture capital, it not only needs to build a real business, but one that will be valued in the billions. The question becomes how a startup can create a durable, attractive business, with a transient, short-lived technological advantage.

Most investors understand this stark reality. Unfortunately, while dabbling in technologies which appeared like magic to them during the cleantech boom, many investors were lured back into the innovation fallacy, believing that pure technological advancement would equal value creation. Many of them re-learned this lesson the hard way. As frontier technologies are attracting broader attention, I believe many are falling back into the innovation trap.

Investing in frontier technology is (and isn’t) cleantech all over again

So what should aspiring frontier inventors solve for as they seek to invest capital to translate pure discovery to building billion-dollar companies? How can the technology be cast into an unfair advantage that will yield big margins and growth that underpin billion-dollar businesses?

Talent productivity: In this age of automation, human talent is scarce, and there is incredible value attributed to retaining and maximizing human creativity. Leading companies seek to gain an advantage by attracting the very best talent. If your technology can help you make more scarce talent more productive, or help your customers become more productive, then you are creating an unfair advantage internally, while establishing yourself as the de facto product for your customers.

Great companies such as Tesla and Google have built tools for their own scarce talent, and build products their customers, in their own ways, can’t do without. Microsoft mastered this with its Office products in the 1990s through innovation and acquisition, Autodesk with its creativity tools, and Amazon with its AWS Suite. Supercharging talent yields one of the most valuable sources of competitive advantage: switchover cost.  When teams are empowered with tools they love, they will loathe the notion of migrating to shiny new objects, and stick to what helps them achieve their maximum potential.

Marketing and distribution efficiency: Companies are worth the markets they serve. They are valued for their audience and reach. Even if their products in of themselves don’t unlock the entire value of the market they serve, they will be valued for their potential to, at some point in the future, be able to sell to the customers that have been tee’d up with their brands. AOL leveraged cheap CD-ROMs and the postal system to get families online, and on email.

Dollar Shave Club leveraged social media and an otherwise abandoned demographic to lock down a sales channel that was ultimately valued at a billion dollars. The inventions in these examples were in how efficiently these companies built and accessed markets, which ultimately made them incredibly valuable.

Network effects: Its power has ultimately led to its abuse in startup fundraising pitches. LinkedIn, Facebook, Twitter and Instagram generate their network effects through internet and Mobile. Most marketplace companies need to undergo the arduous, expensive process of attracting vendors and customers. Uber identified macro trends (e.g. urban living) and leveraged technology (GPS in cheap smartphones) to yield massive growth in building up supply (drivers) and demand (riders).

Our portfolio company Zoox will benefit from every car benefiting from edge cases every vehicle encounters: akin to the driving population immediately learning from special situations any individual driver encounters. Startups should think about how their inventions can enable network effects where none existed, so that they are able to achieve massive scale and barriers by the time competitors inevitably get access to the same technology.

Offering an end-to-end solution: There isn’t intrinsic value in a piece of technology; it’s offering a complete solution that delivers on an unmet need deep-pocketed customers are begging for. Does your invention, when coupled to a few other products, yield a solution that’s worth far more than the sum of its parts? For example, are you selling a chip, along with design environments, sample neural network frameworks and data sets, that will empower your customers to deliver magical products? Or, in contrast, does it make more sense to offer standard chips, licensing software or tag data?

If the answer is to offer components of the solution, then prepare to enter a commodity, margin-eroding, race-to-the-bottom business. The former, “vertical” approach is characteristic of more nascent technologies, such as operating robots-taxis, quantum computing and launching small payloads into space. As the technology matures and becomes more modular, vendors can sell standard components into standard supply chains, but face the pressure of commoditization.

A simple example is personal computers, where Intel and Microsoft attracted outsized margins while other vendors of disk drives, motherboards, printers and memory faced crushing downward pricing pressure. As technology matures, the earlier vertical players must differentiate with their brands, reach to customers and differentiated product, while leveraging what’s likely going to be an endless number of vendors providing technology into their supply chains.

A magical new technology does not go far beyond the resumes of the founding team.

What gets me excited is how the team will leverage the innovation, and attract more amazing people to establish a dominant position in a market that doesn’t yet exist. Is this team and technology the kernel of a virtuous cycle that will punch above its weight to attract more money, more talent and be recognized for more than it’s product?

Golden Gate Ventures closes new $100M fund for Southeast Asia

Singapore’s Golden Gate Ventures has announced the close of its newest (and third) fund for Southeast Asia at a total of $100 million.

The fund hit a first close in the summer, as TechCrunch reported at the time, and now it has reached full capacity. Seven-year-old Golden Gate said its LPs include existing backers Singapore sovereign fund Temasek, Korea’s Hanwha, Naver — the owner of messaging app Line — and EE Capital. Investors backing the firm for the first time through this fund include Mistletoe — the fund from Taizo Son, brother of SoftBank founder Masayoshi Son — Mitsui Fudosan, IDO Investments, CTBC Group, Korea Venture Investment Corporation (KVIC), and Ion Pacific.

Golden Gate was founded by former Silicon Valley-based trio Vinnie Lauria, Jeffrey Paine and Paul Bragiel . It has investments across five markets in Southeast Asia — with a particular focus on Indonesia and Singapore — and that portfolio includes Singapore’s Carousell, automotive marketplace Carro, P2P lending startup Funding Societies, payment enabler Omise and health tech startup AlodokterGolden Gate’s previous fund was $60 million and it closed in 2016.

Some of the firm’s exits so far include the sale of Redmart to Lazada (although not a blockbuster), Priceline’s acquisition of WoomooLine’s acquisition of Temanjalan and the sale of Mapan (formerly Ruma) to Go-Jek. It claims that its first two funds have had distributions of cash (DPI) of 1.56x and 0.13x, and IRRs of 48 percent and 29 percent, respectively.

“When I compare the tech ecosystem of Southeast Asia (SEA) to other markets, it’s really hit an inflection point — annual investment is now measured in the billions. That puts SEA on a global stage with the US, China, and India. Yet there is a youthfulness that reminds me of Silicon Valley circa 2005, shortly before social media and the iPhone took off,” Lauria said in a statement.

A report from Google and Temasek forecasts that Southeast Asia’s digital economy will grow from $50 billion in 2017 to over $200 billion by 2025 as internet penetration continues to grow across the region thanks to increased ownership of smartphones. That opportunity to reach a cumulative population of over 600 million consumers — more of whom are online today than the entire U.S. population — is feeding optimism around startups and tech companies.

Golden Gate isn’t alone in developing a fund to explore those possibilities, there’s plenty of VC activity in the region.

Some of those include Openspace, which was formerly known as NSI Ventures and just closed a $135 million fund, Qualgro, which is raising a $100 million vehicle and Golden Equator, which paired up with Korea Investment Partners on a joint $88 million fund. Temasek-affiliated Vertex closed a $210 million fund last year and that remains a record for Southeast Asia.

Golden Gate also has a dedicated crypto fund, LuneX, which is in the process of raising $10 million.

Bitcoin Breaches $7,000 in Downbeat End to Dismal Quarter

Bitcoin’s miserable quarter isn’t over yet.

The world’s biggest cryptocurrency by market value dropped below the $7,000 mark Friday morning in Asia, the first time it’s breached that level since early February, according to data compiled by Bloomberg. It fell as low as $6,912 before rebounding, trading at $7,094 as of 7:50 a.m in Hong Kong. The moves took the token’s losses in 2018 to a whopping 50 percent, and other digital assets, including rivals Ripple and Litecoin, slumped more.

In addition, regulatory pressure is mounting in the cryptocurrency space, while major social media platforms are distancing themselves from the industry. Reddit Inc., a community hub popular in the crypto community, no longer accepts payments made in Bitcoin, while Twitter Inc. confirmed Monday that it’s banning advertisements for initial coin offerings, joining Facebook and Google.

Looming over the market are sales of Bitcoin held by the trustee of Mt Gox, the now-defunct Japanese exchange. The trustee sold about $400 million in Bitcoin and Bitcoin Cash in the last few months to reimburse the exchange’s creditors, according to his recent report. The trustee had said that he will sell more of the cryptocurrency he holds. As of early March, he was sitting on more than $1 billion.

“Bitcoin is under selling pressure again and chances of its recovery are looking slim,” Naeem Aslam, the chief market analyst at TF Global Markets, said in a note. It has “slid significantly, since the tech giants’ ban on ICOs,” he noted.

The slump this year is its biggest quarterly decline since 2011. Keep in mind that Bitcoin rallied 1,400 percent last year.

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