The Modern World Has Finally Become Too Complex for Any of Us to Understand


This post is curated by Keith Teare. It was written by Tim Maughan. The original is [linked here]

No One’s Driving

Vast systems, from automated supply chains to high-frequency trading, now undergird our daily lives — and we’re losing control of all of them

A photo collage of a shipping dock, a graph of a stock market activity, and an automated warehouse
Photo illustration, sources: Jesper Klausen/Science Photo Library/Sukanya Sitthikongsak/yoh4nn/Getty Images

Welcome to No One’s Driving — a column by novelist and tech writer Tim Maughan about how to understand a world governed by systems and technologies that are spiraling out of control.

One of the dominant themes of the last few years is that nothing makes sense. Donald Trump is president, QAnon has mainstreamed fringe conspiracy theories, and hundreds of thousands are dead from a pandemic and climate change while many Americans do not believe that the pandemic or climate change are deadly. It’s incomprehensible.

I am here to tell you that the reason so much of the world seems incomprehensible is that it is incomprehensible. From social media to the global economy to supply chains, our lives rest precariously on systems that have become so complex, and we have yielded so much of it to technologies and autonomous actors that no one totally comprehends it all.

In other words: No one’s driving. And if we hope to retake the wheel, we’re going to have to understand, intimately, all of the ways we’ve lost control. This is the first entry in a series — called, yes, No One’s Driving — that aims to do exactly that. Each month, we’ll examine a technological system that has grown too complex to be understood by, well, just about any one person, and break down how it has spiraled out of control, why that is dangerous, and what we might do about it.

Most of us do not spend a lot of time thinking about the huge, complex systems that keep our technologically dependent society running. And with very good reason. It takes a certain amount of faith and belief — in ourselves, in capitalism, in the digital platforms that mediate our interactions with it, and in the infrastructures that support all of the above — in order to wake up and get through every day. But eating breakfast, pulling on our business-casual Zoom-appropriate shirts — all those mundane acts are made possible by an almost unfathomably complex, algorithmically calibrated, partly automated, and partly sweatshop-labor-dependent global supply chain.

There are currently over 17 million shipping containers in circulation globally, and at any given time, about 5 or 6 million shipping containers cross the sea. The U.S. alone imports over 20 million shipping containers’ worth of products a year. While it’s common to talk about iPhones and high-end sneakers when we talk about imports from China and Asia, the truth is the vast majority of those containers are stuffed which much more mundane goods: socks, umbrellas, pencils, paper, packing materials, bedsheets, fruit, car parts, frozen food, pharmaceuticals — the endless inventory of physical items that make our modern lives possible.

Just as vast and complex, and intrinsically linked to the supply chain, is another sprawling but mostly invisible system: the global financial markets. It’s a vast, highly technologized network linking banks, government agencies, hedge funds, regulatory bodies, stock markets, dark pools, exchanges, news services, and millions of individual human traders and analysts. It has grown to a level of complexity that makes it unknowable by any single human intelligence — everything moves at far too great a speed and scale.

The average daily trading volume on the New York Stock Exchange generally spans between 2 billion and 6 billion shares, with the average daily trading value in 2013 being approximately $169 billion. And the only way to deal with a market of this size and complexity has been a relentless adoption of automation — and the increased handing over of day-to-day analysis and decision-making to software. And in an industry like finance, which is preoccupied entirely with growth, these systems have led to an exponential increase in complexity — while human traders would traditionally average five trades a day, high-frequency trading algorithms can make 10,000 trades every second.

And those platforms of technology and software that glue all these huge networks together have become a complex system themselves. The internet might be the system that we interact with in the most direct and intimate ways, but most of us have little comprehension of what lies behind our finger-smudged touchscreens, truly understood by few. Made up of data centers, internet exchanges, huge corporations, tiny startups, investors, social media platforms, datasets, adtech companies, and billions of users and their connected devices, it’s a vast network dedicated to mining, creating, and moving data on scales we can’t comprehend. YouTube users upload more than 500 hours of video every minute — which works out as 82.2 years of video uploaded to YouTube every day. As of June 30, 2020, there are over 2.7 billion monthly active Facebook users, with 1.79 billion people on average logging on daily. Each day, 500 million tweets are sent— or 6,000 tweets every second, with a day’s worth of tweets filling a 10-million-page book. Every day, 65 billion messages are sent on WhatsApp. By 2025, it’s estimated that 463 million terabytes of data will be created each day — the equivalent of 212,765,957 DVDs.

So, what we’ve ended up with is a civilization built on the constant flow of physical goods, capital, and data, and the networks we’ve built to manage those flows in the most efficient ways have become so vast and complex that they’re now beyond the scale of any single (and, arguably, any group or team of) human understanding them. It’s tempting to think of these networks as huge organisms, with tentacles spanning the globe that touch everything and interlink with one another, but I’m not sure the metaphor is apt. An organism suggests some form of centralized intelligence, a nervous system with a brain at its center, processing data through feedback loops and making decisions. But the reality with these networks is much closer to the concept of distributed intelligence or distributed knowledge, where many different agents with limited information beyond their immediate environment interact in ways that lead to decision-making, often without them even knowing that’s what they’re doing.

Back in 2014 I spent some time investigating the supply chains for goods from China, and I spent a week on a huge container ship. One of the most striking things I saw was how much day-to-day, minute-to-minute decision-making was mediated by technology. Every human in the supply chain — from crane drivers up to the captain of the ship I was on — was constantly receiving instructions from unseen, distant, management algorithms. Displays told crane drivers which containers to pick up and where to place them, while the captain received automated emails about course corrections. What was fascinating — and slightly unnerving — was how these instructions were accepted and complied with without question, by skilled professionals, without any explanation of the decision processes that were behind them.

The captain of the container vessel would regularly receive automated emails telling him to slow down the ship. It’s impossible to know why the shipping company’s algorithms decided this was for the best — the captain himself didn’t know. But he could speculate: Maybe the staff or systems at the terminal ahead reported delays with off-loading, or a mechanical hitch. Or maybe the algorithm saw the delays coming in advance because the GPS trackers on other containers showed delivery trucks stuck in gridlock outside the port. Maybe it decided to slow everything down because a customer deprioritized their order. Or that a change somewhere else in another link of the supply chain meant that getting their shipment from another source became a cheaper or quicker option. Or the cost of oil fluctuated just enough that burning it at the ship’s current rate became inefficient. Or maybe it was all of these reasons simultaneously, or none of them. The point is that we don’t know, the captain of the ship itself didn’t know, and that nobody may know — but that didn’t stop the decision being made.

Which is fine, right? There are a lot of people — executives, traders, investors, and tech developers chief among them — who would argue that it’s better than fine; it’s good. We should be happy about this. There’s food and clothes in the stores, money in the ATMs, stories on our Instagram. And yep, getting those things there was really really complicated, but it doesn’t matter, ultimately, because humans didn’t have to worry about it all — it just takes care of itself. I mean, what could possibly go wrong?

Firstly, and most obviously, parts or all of these systems can simply fail. As we all know, the more complicated something is, the more ways something can go wrong. We’ve had a few opportunities recently to see examples of this happening. Just this year we’ve watched the supply chains struggle under the pressures of the Covid-19 pandemic, leading to shortages and misallocations of everything from protective masks to flour to toilet paper.

The fallout from Covid has had an even more devastating effect on the global economy — although we’ve seen the markets come close to collapse without the help of a global disaster, such as during the 2008 financial crisis. And the internet is certainly prone to failures, perhaps most starkly illustrated by the WannaCry ransomware attack of 2017, which is said to have affected more than 200,000 computers across 150 countries, causing billions of dollars’ worth of damage and lost earnings. Interestingly, one of the industries hit hardest by malware attacks that year was shipping, with them crippling parts of the supply chain as companies like Maersk were forced to watch their networks grind to a halt. What’s worrying is that while none of these were catastrophic failures, and the networks eventually recovered, in some cases it took years of expert analysis and debate to work out what actually went wrong, exactly because of how complex these systems are to understand.

On the other hand, we also have to worry about these systems working too well. These networks were built — or, perhaps more accurately, they evolved — to be as efficient as possible, and as we’ve seen from the above examples we’ve abdicated a lot of decision-making to them in order to achieve that goal. But what we’ve not bestowed them with is an ability to make ethical decisions and moral judgments when doing so.

The global supply chains, with their mega-scale engineering projects and infrastructures, exist primarily because global wealth inequality makes it cheap to have stuff made in certain countries — even when you have to ship it halfway across the globe to sell it for a profit. By leveraging stark gaps in wages and standards of living as efficiently as it can, the supply chain network is actively enforcing that global inequality.

The same is also true for the global financial markets, which unblinkingly focus on creating wealth and growth, regardless how many companies and their workers might fall by the wayside, how many pensions schemes might be jeopardized, or even how many climate-wrecking carbon emissions are produced. And on the internet, streaming platforms like Spotify and YouTube provide us with unlimited entertainment content whenever we desire it, but at the expense of musicians and creators who struggle to earn a living wage. And then there’s the baked-in biases and lack of transparency in algorithmic decision-making, and how that impacts everything from YouTube recommendations to student grading and predictive policing.

Ceding control to vast unaccountable networks not only risks those networks going off the rails, it also threatens democracy itself. If we are struggling to understand or influence anything more than very small parts of them, this is also increasingly true for politicians and world leaders. Like the captain of the container ship, politicians and voters have less and less control over how any of these networks run. Instead they find themselves merely managing very small parts of them — they certainly don’t seem to be able to make drastic changes to those networks (which are mainly owned by private corporate industries anyway) even though they have a very direct impact on their nations’ economies, policies, and populations. To paraphrase the filmmaker Adam Curtis, instead of electing visionary leaders, we are in fact just voting for middle managers in a complex, global system that nobody fully controls.

The result of this feels increasingly like a democratic vacuum. We live in an era where voters have record levels of distrust for politicians, partly because they can feel this disconnect — they see from everyday reality that, despite their claims, politicians can’t effect change. Not really. They might not understand why, exactly, but there’s this increasing sense that leaders have lost the ability to make fundamental changes to our economic and social realities. The result is a large body of mainstream voters that wants to burn down the status quo. They want change, but don’t see politicians being able to deliver it. It feels like they’re trapped in a car accelerating at full throttle, but no one is driving.

They may not be able to do much about it, but there are mainstream politicians and elected leaders who see this vacuum for what it is — and see how it provides them with a political opportunity. Figures like Donald Trump and Boris Johnson certainly don’t believe in patching up the failures of this system — if anything, they believe in accelerating the process, deregulating, handing more power to the networks. No, for them this is a political vacuum that can be filled with blame. With finger-pointing and scapegoating. It is an opportunity to make themselves look powerful by pandering to fears, by evoking nationalism, racism, and fascism.

Donald Trump has still not conceded the 2020 election despite Joe Biden’s clear victory, and is leaning in part on the fact that the United States has a complex and sometimes opaque voting system that most of the public doesn’t understand to spread conspiracy theories about glitchy or malfeasant voting machines switching or deleting millions of votes. It’s perhaps no coincidence that some of the highest-profile figures on the right — like ex-Trump-adviser Steve Bannon or Brexit Party leader Nigel Farage — have backgrounds in the financial industry. These are political players who have seen how complicated things have become and can sense the gap in public comprehension but want to fill it with chaos and conspiracies rather than explanations.

So what’s to be done about all this? Over the coming months I’m going to both locate ways that we can try to increase our knowledge of the seemingly unknowable, as well as find strategies to counter the powerlessness and anxiety the system produces. Along the way I’m going to be talking to a lot of experts about everything from automated shipping and algorithmic trading to financial regulation and political resistance, as well as taking deep dives into how emerging technologies like artificial intelligence and quantum computing could make things better — or a lot worse. I hope you’ll join me as we explore how our systems work, how their complexities impact our lives, and how we can regain some agency within them.


The Modern World Has Finally Become Too Complex for Any of Us to Understand was originally published in OneZero on Medium, where people are continuing the conversation by highlighting and responding to this story.

ThoughtRiver nabs $10M to speed up deal-making with AI contract review


This post is by Natasha Lomas from Fundings & Exits – TechCrunch

ThoughtRiver, a London-based legaltech startup that’s applying AI to speed up contract pre-screening, has announced a $10 million Series A round of funding led by Octopus Ventures. Existing seed investors Crane, Local Globe, Entrée Capital, Syndicate Room, and angel investor Duncan Painter also participated in the round.

The UK startup is one of a number applying AI to automate work that would otherwise be done by legal professions with the aim of boosting operational efficiency. Other startups playing in the space include the likes of Kira Systems, LawGeex and Luminance to name a few.

ThoughtRiver argues it has a different focus vs the majority of contract view companies because it’s focusing on pre-signature contracts — with the aim of making securing a deal faster. “Almost all others are just employed to pull data from existing contracts. ThoughtRiver is as much in demand by Sales teams as it is by Legal,” a spokesman told us.

The Series A investment comes after twelve month’s of what it’s billed as significant growth for the 2015-founded startup, which says its automated contract review software is now being used by the likes of G4S, Singtel and DB Schenker. It launched a service at the end of 2017 and now has more than 25 customers around the world, per the spokesman.

It also trumpets inking a strategic partnership with professional services firm PwC — which will see the latter developing a service for its clients powered by ThoughtRiver’s software, according to a press release.

ThoughtRiver touts up to 95% in time and 80% in cost savings vs an initial contract review that’s carried out by in-house lawyers. And ‘faster contract reviews sum to increased deal flow velocity’ is its overarching claim.

On the tech side, ThoughtRiver has created an ontology of contract legal logic, couched as a series of detailed questions which, combined with its natural language processing (NLP) engine, enables its software to pre-screen contracts by generating a risk assessment. It will also suggest tweaks to the legalese to remediate problems, including via a plug-in for Microsoft Word, where customers’ in-house lawyers may prefer to work.

Other benefits the startup touts are data extraction to power contract analytics at scale — such as for due diligence or to assess the impact of regulatory change. Its sale pitch also suggests that easy access to an overview of contractual positions helps customers by enabling better-informed business relationships.

Image credit: ThoughtRiver

ThoughtRiver has already established offices in New York, Singapore, London, Cambridge and Auckland. It says the new funding will be put towards further growth in the US market, where it will be dialling up sales and marketing efforts. Expanding integrations with major tech partners is also on the cards.

Commenting on the funding in a statement, Akriti Dokania, early stage investor at Octopus Ventures, said: “While the legal sector has been slow to adopt AI compared to other industries, ThoughtRiver has a proven business model based on solving a fundamental issue for lawyers. By using an advanced Natural Language Processing engine to drive faster contract reviews and acceleration of deal flow and business growth, legal professionals can work more efficiently than ever. We are thrilled to support the ThoughtRiver team with its plans for global expansion as the firm disrupts an established market and set of processes.”

The Future of Supply Chain Automation


This post is by Dorothy Neufeld from Visual Capitalist

How Fast Are Supply Chains Truly Automating?

The Future of Supply Chain Automation

As Amazon continues to set the bar for efficiency by integrating an astounding spectrum of automation technology, it’s becoming increasingly apparent that traditional supply chain models are ripe for disruption.

For this reason, companies around the world are now rethinking their warehouse and distribution systems, with automation taking center stage.

Today’s infographic from Raconteur highlights the state of automation across global supply chains, while also providing an outlook for future investment.

Long Time Coming

Let’s start by taking a look at what supply chain technologies are priorities for global industry investment in the first place:

Rank Technology % of Companies* Investing in Tech
#1 Warehouse automation 55%
#2 Predictive analytics 47%
#3 Internet of things 41%
#4 Cloud logistics 40%
#5 Artificial intelligence 28%
#6 Blockchain 22%
#7 Autonomous vehicles 16%
#8 Machine-learning 16%
#9 Fulfillment robots 11%
#10 3D printing 10%
#11 Augmented reality 7%
#12 Drones 7%
#13 Crowd-sourced delivery 6%
#14 Virtual reality and digital twins 6%
#15 Delivery robots 4%

*Based on survey of supply chain professionals in retail, manufacturing, and logistics fields

As seen above, warehouse automation has already received more investment (55%) than any other supply chain technology on the list, as companies aim to cut delivery times and improve overall margins.

Interestingly, other areas receiving significant investment—such as predictive analytics, internet of things, or artificial intelligence—are technologies that could integrate well into the optimization of supply chain automation as well.

Smoothing the Transition

While fully automated supply chains in most industries may still be a few years away, here is how companies are investing in an automated future today:

Timeline For Acquiring New Automation Tech % of Warehouse Managers Surveyed
Already have 23%
Have, looking to upgrade 8%
Within 12 months 10%
One to three years 21%
Three to five years 8%
Over five years 3%
Not looking 26%

According to the above data, over 70% have already integrated automation technology, or are planning to within the next five years. On the flip side, over a quarter of warehouse managers are not currently looking to integrate any new automation tech into their operations at all.

Adoption Rates and Growth

As supply chain automation gains momentum and industry acceptance, individual processes will have varying adoption rates.

Take order fulfillment, for instance. Here, only 4% of current operations are highly automated according to a recent survey from Peerless Research Group:

Order Fulfillment Operations (Picking and Packaging) Percentage of Respondents
Highly automated 4%
A mix of automated and manual processes 42%
Mostly or all manual 49%
Not applicable 5%

Meanwhile, 49% of operations were primarily manual, illustrating potential for growth in this particular area.

It’s worth noting that other individual supply chain components, such as conveyor belts, storage, automated guided vehicles, and shuttle systems, will all have differing trajectories for automation and growth.

Post-COVID Supply Chains

The COVID-19 pandemic has shown us that complex supply chains can become fragile under the right circumstances.

As supply chains see increased rates of automation and data collection becomes more integrated into these processes, it’s possible that future risks embedded in these systems could be mitigated.

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The post The Future of Supply Chain Automation appeared first on Visual Capitalist.

An Investing Megatrend: How Technological Breakthroughs are Shaping the Future


This post is curated by Keith Teare. It was written by Ashley Viens. The original is [linked here]

Since Apple released the first iPhone in 2007, few industries have been left unaffected.

This transformational device is a prototypical example of a technological breakthrough. It was a tipping point in turning entire business models upside-down, while also impacting our everyday lives at a more fundamental level.

New growth opportunities emerged from the ensuing disruption, while many status quo solutions were rendered obsolete.

Technological Game-Changers

Today’s infographic from BlackRock highlights the pervasive and positive impact that technological breakthroughs can have on the global economy.

Technological Breakthroughs Infographic

Fueling the Flames of Innovation

According to recent data from Accenture, it’s estimated that 71% of businesses are on the brink of being disrupted.

In fact, disruptive innovation most often emerges in two scenarios:

  • New solutions to existing problems or challenges that have proven difficult to solve
  • New competitors in highly profitable sectors with historically high returns

The occurrence of technological breakthroughs can also be accelerated

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Continue reading “An Investing Megatrend: How Technological Breakthroughs are Shaping the Future”

Our partnership with Automation Hero: empowering information workers through AI

German entrepreneur Stefan Groschupf has spent the past 25 years developing machine learning solutions for some of the most complex enterprise environments. As one of the earliest big data activists working on the Apache Hadoop project, and most recently with big data business intelligence company Datameer  – which counted over 50% of the Fortune 50 as customers – he has also proved himself able to scale companies on both sides of the Atlantic.

But as Stefan saw a shift in customer demand from business intelligence to business automation, and in emerging technologies from big data to AI, he knew there was a new opportunity to be captured, and moved his sights to building the next generation of robotic process automation.  

The robotic process automation (RPA) market has seen extreme growth in the last few years, but current technology was architected over a decade ago and is limited to automating Continue reading “Our partnership with Automation Hero: empowering information workers through AI”

10 Things That Will Change Manufacturing Forever

The tension between factory workers, manufacturers and technology — building since the first robot began working the line at GM in 1961 — has reached a fever pitch.

Even the most tech-forward companies have struggled to find the right balance. In April, Tesla CEO Elon Musk blamed part of the company’s Model 3 delays on a “production hell” caused by “too many robots.”

New technologies are ushering in a new age of manufacturing: one that will help companies produce more high-quality goods faster and cheaper, while also enabling more innovation and economic opportunity.

At my firm, Lux Capital, we have been investing in automation technologies for many years. Here are ten trends and innovation spaces we see that are changing manufacturing for the better:

Automation is Coming to Commerce … And Why That’s a Good Thing

When we order something online, we want it yesterday…and for free. For this to happen, after an item is ordered, in the time it takes to stream of a Master of None episode, it needs to be picked and packed in the appropriate fulfillment warehouse, sorted and loaded onto the next departing truck, routed through transportation hubs for consolidation and deconsolidation, and finally put on a box truck for delivery to your home or place of work. Oh yeah — that doesn’t come cheap: probably $10/$15 per order.

Of course expertise in merchandising, pricing and product differentiation have been the table stakes for any commerce provider since the original general store, and whether online or offline they will never stop iterating and competing on merchandise. But giving consumers not just what they want, but how, where, and when they want it is the holy grail — and in the coming years, I believe as a

Continue reading “Automation is Coming to Commerce … And Why That’s a Good Thing”

Automation is Coming to Commerce … And Why That’s a Good Thing

When we order something online, we want it yesterday…and for free. For this to happen, after an item is ordered, in the time it takes to stream of a Master of None episode, it needs to be picked and packed in the appropriate fulfillment warehouse, sorted and loaded onto the next departing truck, routed through transportation hubs for consolidation and deconsolidation, and finally put on a box truck for delivery to your home or place of work. Oh yeah — that doesn’t come cheap: probably $10/$15 per order.

Of course expertise in merchandising, pricing and product differentiation have been the table stakes for any commerce provider since the original general store, and whether online or offline they will never stop iterating and competing on merchandise. But giving consumers not just what they want, but how, where, and when they want it is the holy grail — and in the coming years, I believe as a

Continue reading “Automation is Coming to Commerce … And Why That’s a Good Thing”

Our Investment in Spoke

Spoke Co-Founders Pratyus Patnaik, Jay Srinivasan and David Kaneda.

Over five years ago, before I joined Greylock, I was invited by several friends to angel invest in a smart phone app testing service called Appurify. Two short years later, Google acquired Appurify to build a cloud service for mobile developers. During the Appurify journey, I had the chance to work with with Jay Srinivasan, Pratyus Patnaik and David Kaneda. A lot of VCs and founders will say investing is “all about the team”. I agree, and I consider it one of the highest compliments that Jay and the team want to walk a second journey together.

One of the most important groups of people that any company serves are its employees. There are countless questions an employee may have about the latest updates on IT security protocol, where to find certain HR forms, what is company policy on travel reimbursements, or

Continue reading “Our Investment in Spoke”

Forging the Future with Metal

With its office-ready metal 3D printing system, Desktop Metal has reinvented the way engineering and manufacturing teams produce metal products and parts — from conception and prototyping all the way to mass production. Manufacturing will never be the same.

At the intersection of business, economics and politics in the United States, there is no subject more controversial than manufacturing. The media can’t decide whether to put the blame on international outsourcing or robots, and you don’t need to look much further than the White House’s PR-driven “Made in America Week” campaign to see that this is a white-hot issue. At stake is nothing less than global leadership.

The critical many-trillion-dollar question: What is the future of manufacturing?

At Lux Capital, we are partnering with a number of different companies that are stepping up to answer this question, using cutting-edge technology to architect a new future. Desktop Metal is leading the charge with metal

Continue reading “Forging the Future with Metal”

Growlabs nabs $2.2M to automate outbound sales

 Just six months into its life, Growlabs, a startup using machine intelligence to support outbound sales teams, has raised a $2.2 million seed round. Founded by Ben Raffi, the creator of ticketing app Universe, Growlabs helps businesses reduce their customer acquisition costs by enabling smalls sales teams to do more with less. From his past work with Universe, Raffi knows how difficult it… Read More

Israeli Caja competes with Amazon’s robots

Caja Systems has made the startling realization that the public likes buying online and wants to make getting your items out of the warehouse even easier The e-commerce market is continually growing. The bottleneck for companies is their logistics warehouses, which have trouble maintaining a large variety of products and meeting tight supply schedules. Israeli […]

The post Israeli Caja competes with Amazon’s robots appeared first on iAngels.

The Coming Paradigm Shift in Manufacturing

The Star Trek replicator stands as the ultimate dream of on-demand manufacturing. The bad news is that despite advances in 3D printing we are many breakthroughs (including nearly abundant energy) away from realizing that dream. The good news is that we are finally finding ourselves on the cusp of a paradigm shift in manufacturing away from mass production to fast, low cost, small series (including single part) capabilities.

The shift is being led by a new crop of startups, including Plethora (metal parts), PCB:NG (circuit boards), Unmade (knitting) and Shapeways (3D printing). The common theme among these is that they are focused on automating pre- and post-production processes. For instance, Plethora has created software for translating a CAD drawing directly into the right sequence of instructions for a CNC Mill. PCB:NG has figured out how to feed a pick and place machine for runs of just a few boards. And Continue reading “The Coming Paradigm Shift in Manufacturing”

Domo Raises $131 Million, Holds Its $2 Billion Valuation

Domo founder and Chief Executive Josh James
Derek Smith

A year ago, business software vendor Domo Inc. was expecting to go public by the end of 2015, Chief Executive Josh James told VentureWire.

Domo has now raised $131 million as it waits for the markets to become more receptive to information technology companies. The company extended its last funding round, a $200 million Series D round raised in April 2015, at the same valuation and same terms, adding money from insider BlackRock Inc., Credit Suisse and unnamed family offices, some in Asia and Russia, and taking total funding to $590 million, according to Mr. James.

At a time when valuations for privately held business software companies are down more than 40% in some cases, Domo held on to its $2 billion valuation. According to The Wall Street Journal’s Startup Stock Tracker, Domo’s shares declined less than 10% in Continue reading “Domo Raises $131 Million, Holds Its $2 Billion Valuation”

Couchbase Raises $30 Million for Promise of NoSQL Databases Growth

Couchbase CEO Bob Wiederhold
Couchbase

A new category of databases developed to handle problems first seen at early Internet companies like Google Inc. and Facebook Inc. have attracted well over $500 million in funding and continue to report growth, despite the current pressure on public tech stocks.

Couchbase Inc., one of the three largest of these database companies, called NoSQL companies, has raised  $30 million in what the company says is its last private funding round before a potential IPO, according to Chief Executive Bob Wiederhold.

Mr. Wiederhold said the new round, a Series F, will take Couchbase to cash-flow positive, now considered a requirement by many investors, and should enable an IPO “in the not too distant future,” although he declined to be more specific on timing.

He also declined to comment on Couchbase’s revenue or valuation. Competitor MongoDB Inc. was valued privately in December 2014 at $1. Continue reading “Couchbase Raises $30 Million for Promise of NoSQL Databases Growth”

San Francisco Startup Brings Moneyball to Soccer

Tag.bio co-founders Tom Covington and Jesse Paquette
Tag.bio

The Italian soccer club AS Roma has won six out of its last seven games, a result that has thrilled fans.

One reason for the winning streak, according to Chris Pallotta, an investment officer at Raptor Capital Management, is the club’s relationship with a San Francisco-based analytics startup called Tag.bio.

Spun out of the University of California San Francisco, which is the UC system’s health sciences school, and founded by two amateur soccer players, Tag.bio has created software that helps AS Roma scout players, group players and analyze before a game how the opposing team is expected to perform.

“It’s like Moneyball,” said Mr. Pallotta, referring to the data-driven approach that former Oakland A’s General Manager Billy Beane brought to the sport of baseball.

Mr. Pallotta’s father is Jim Pallotta, whose family office, Raptor Group, owns the soccer Continue reading “San Francisco Startup Brings Moneyball to Soccer”

Zendrive Picks Up $13.5M to Monitor Safe Driving

Zendrive Inc. has raised $13.5 million for software that analyzes data coming off smartphone sensors to gather information on safe driving, part of a growing movement to use technology to track drivers.

The Series A round was led by Sherpa Capital, whose co-founder, Shervin Pishevar, is a board observer at the ride-sharing service Uber Technologies Inc. and a co-founder of Hyperloop Technologies Inc., which was inspired by Elon Musk.

Zendrive was founded in 2013 by two veterans of Google Inc. and Facebook Inc., which provided shuttles to take the men to and from their jobs. After Jonathan Matus, now Zendrive’s chief executive, left Facebook, he discovered what a hassle it was to drive himself, he told VentureWire in 2014, but he also realized the dearth of tools available to ensure the safety of various ride-sharing services.

Zendrive is now offering a software development kit to commercial fleets Continue reading “Zendrive Picks Up $13.5M to Monitor Safe Driving”

Startup Screen Sets Out to Limit Children’s Screen Time

Parents who want to set limits on screen time may soon find a new product to help them.

Teenagers, for example, spend on average six hours and 40 minutes in front of screens per day, according to a 2015 survey by Common Sense Media. Some parents feel that is too much.

New York startup Screen has developed a piece of hardware, coupled with a mobile application, that would allow parents to manage the use of all devices, including phones, whether they run on iOS or Android operating systems, as well as computers, television sets and game consoles. Devices could be controlled when they are in or outside the house.

The startup, incorporated as LimitScreen Inc., raised $1.9 million in a seed equity round led by Lerer Hippeau Ventures last year, Tali Orad, the company’s founder and chief executive, told VentureWire. Other investors include Advancit Capital, Novel TMT Ventures, Continue reading “Startup Screen Sets Out to Limit Children’s Screen Time”

The Daily Startup: Naritiv Scores Funding for Disappearing Ads

dailystartup_D_20090806101628.jpgArt by Mike Lucas
Advertisers have been studying Snapchat for how to get exposure to its audience. Naritiv, a startup functioning as a digital agency, has figured out  way to help brand advertisers create promotional snaps.  The company has raised $3 million to create this branded content for Snapchat. “We don’t look at Vine or Snapchat as similar at all. We look at Snapchat as the future where messaging and media come together,” said the company’s co-founder and chief executive, Daniel Altmann.

ALSO IN TODAY’S VENTUREWIRE (subscription required):

Pindrop Security Inc. picked up $75 million to bring its voice fraud authentication platform to the Internet of Things. Google Capital led the Series C round, with participation from Andreessen Horowitz, Citi Ventures, Felicis, GV (formerly Google Ventures) and Institutional Venture Partners. The company has raised $122 million to date but isn’t disclosing its valuation.

Blockchain Capital, Continue reading “The Daily Startup: Naritiv Scores Funding for Disappearing Ads”

Machine Earning

Reilly Brennan, a good friend and a keen observer of transportation related developments points out that modern vehicle is a sensor workhorse, so why not put it to work. The individual vehicle sensor data can go into a giant corpus of data and drivers should get paid for their work. He calls it machine earning! [Reilly Brennan]

The post Machine Earning appeared first on Om Malik.