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Even though it’s a vast sector in the midst of transformation, manufacturing is often overlooked by early-stage investors. We surveyed top VCs in the industry to gather their perspectives on the challenges and opportunities facing manufacturing.
Traditionally, manufacturing companies are capital-intensive and can be slow to implement new technology and processes. The investors in the survey below acknowledge the long-standing barriers facing founders in this space, yet they see large opportunities where startups can challenge incumbents.
These investors noted that the pandemic is bringing overnight change in the manufacturing world; old rules are being rewritten in the face of worker safety, remote work and the need for increased automation. According to Eclipse Ventures founder Lior Susan, “COVID-19 has exposed the systemic vulnerabilities inherent to manufacturing and supply chain and, as such, significant opportunities for innovation. The market was lukewarm for a long time — it’s time to turn up the heat.”
What trends are you most excited about in manufacturing from an investing perspective?
Digital solutions that offer manufacturers greater agility and resilience will become major areas of focus for investors. For example, manufacturers still reliant on manual assembly were unable to build products when factories closed due to the coronavirus lockdown. While nothing would have kept production at 100%, the ability to quickly pivot and engage software-defined processes would have allowed manufacturing lines to continue building with a skeleton crew (especially important for any facility required to implement social distancing). Such systems have remote monitoring capabilities and computer vision systems to flag defeats in real-time and halt production if necessary.
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I see far more research articles than I could possibly write up. This column collects the most interesting of those papers and advances, along with notes on why they may prove important in the world of tech and startups.
In this edition: a new type of laser emitter that uses metamaterials, robot-trained dogs, a breakthrough in neurological research that may advance prosthetic vision and other cutting-edge technology.
Twisted laser-starters
We think of lasers as going “straight” because that’s simpler than understanding their nature as groups of like-minded photons. But there are more exotic qualities for lasers beyond wavelengths and intensity, ones scientists have been trying to exploit for years. One such quality is… well, there are a couple names for it: Chirality, vorticality, spirality and so on — the quality of a beam having a corkscrew motion to it. Applying this quality effectively could improve optical data throughput speeds by an order of magnitude.
The trouble with such “twisted light” is that it’s very difficult to control and detect. Researchers have been making progress on this for a couple of years, but the last couple weeks brought some new advances.
First, from the University of the Witwatersrand, is a laser emitter that can produce twisted light of record purity and angular momentum — a measure of just how twisted it is. It’s also compact and uses metamaterials — always a plus.
The second is a pair of matched (and very multi-institutional) experiments that yielded both a transmitter that can send vortex lasers and, crucially, a receiver that can detect and classify them. It’s remarkably hard to determine the orbital angular momentum of an incoming photon, and hardware to do so is clumsy. The new detector is chip-scale and together they can use five pre-set vortex modes, potentially increasing the width of a laser-based data channel by a corresponding factor. Vorticality is definitely on the roadmap for next-generation network infrastructure, so you can expect startups in this space soon as universities spin out these projects.
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Talk of an economic downturn can be frightening, especially one precipitated by a pervasive health crisis. At times, I’m overwhelmed by the images of countless patients on life-support and the near-endless streams of statistics regurgitating bad news.
Having started in venture at the beginning of two recessions, I’ve seen how the startup industry functions during economic trouble. My second day of work at Charles River Ventures was September 11th, 2001. My first project, analyzing the VC industry, propelled the firm to return more than 60% of its fund to investors, going from a $1.2 billion fund to $450 million. In May 2008, Mike Maples and I founded Floodgate in the midst of the Great Recession. We learned that great founders won’t wait for a better economic moment to start a company.
While we are currently embroiled in personal and professional circumstances unimaginable even three months ago, these very challenges will form the basis of incredibly innovative ideas. In order for the world to move forward, we need our greatest minds to imagine a brighter future and create solutions to make it a reality.
When I analyze our society and novel health situation, one thing is certain: COVID-19 is a paradigm-shifting event, creating massively accelerated social and economic change.
Our current situation is unique. It’s not merely a cyclical economic event, nor is it a standalone health crisis. What we are experiencing is not just an inflection point: it’s a societal phase-change unlike anything we have ever seen. We face an epic choice of how we move forward, and the decisions we make today will shape an entire generation.
Here’s why: COVID-19 is prompting us to reset many of our most fundamental behaviors. These changes are impacting our financial system, with effects visible throughout our homes, businesses and even the concept of “workplace” itself.
As a global pandemic, the virus itself has spread to nearly every country in the world.
Between February 20 and March 26, 100% of the world’s 20 largest economies implemented government-mandated social distancing. Globally, the number of scheduled airline flights is down 64%. In some countries, like Spain and Germany, flight numbers are down by more than 90%.
Since the timeline for lifting government restrictions is unclear — and even then, scientists are uncertain how the virus will spread — the question lingers: How long will this go on?
COVID-19’s impact is uncertain, long-term and potentially undulating, affecting every facet of our lives. You can’t simply wait it out with the expectation that industries will rebound. In 2001, September 11 felt pervasive, but its economic impact ultimately stemmed from just one single incident and the resulting fear… and that one single incident still cost more than three trillion dollars. How much larger will COVID-19 be?
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It was not long ago that the world watched World Chess Champion Garry Kasparov lose a decisive match against a supercomputer. IBM’s Deep Blue embodied the state of the art in the late 1990s, when a machine defeating a world (human) champion at a complex game such as chess was still unheard of.
Fast-forward to today, and not only have supercomputers greatly surpassed Deep Blue in chess, they have managed to achieve superhuman performance in a string of other games, often much more complex than chess, ranging from Go to Dota to classic Atari titles.
Many of these games have been mastered just in the last five years, pointing to a pace of innovation much quicker than the two decades prior. Recently, Google released work on Agent57, which for the first time showcased superior performance over existing benchmarks across all 57 Atari 2600 games.
The class of AI algorithms underlying these feats — deep-reinforcement learning — has demonstrated the ability to learn at very high levels in constrained domains, such as the ones offered by games.
The exploits in gaming have provided valuable insights (for the research community) into what deep-reinforcement learning can and cannot do. Running these algorithms has required gargantuan compute power as well as fine-tuning of the neural networks involved in order to achieve the performance we’ve seen.
Researchers are pursuing new approaches such as multi-environment training and the use of language modeling to help enable learning across multiple domains, but there remains an open question of whether deep-reinforcement learning takes us closer to the mother lode — artificial general intelligence (AGI) — in any extensible way.
While the talk of AGI can get quite philosophical quickly, deep-reinforcement learning has already shown great performance in constrained environments, which has spurred its use in areas like robotics and healthcare, where problems often come with defined spaces and rules where the techniques can be effectively applied.
In robotics, it has shown promising results in using simulation environments to train robots for the real world. It has performed well in training real-world robots to perform tasks such as picking and how to walk. It’s being applied to a number of use cases in healthcare, such as personalized medicine, chronic care management, drug discovery and resource scheduling and allocation. Other areas that are seeing applications have included natural language processing, computer vision, algorithmic optimization and finance.
The research community is still early in fully understanding the potential of deep-reinforcement learning, but if we are to go by how well it has done in playing games in recent years, it’s likely we’ll be seeing even more interesting breakthroughs in other areas shortly.
If you’ve ever navigated a corn maze, your brain at an abstract level has been using reinforcement learning to help you figure out the lay of the land by trial and error, ultimately leading you to find a way out.
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Matt Ocko, co-founder of venture firm Data Collective (DCVC), was among a small group of VCs viewed as alarmists when they began tweeting about the coronavirus’s imminent appearance in the U.S. back in January.
In retrospect, those individuals were prescient, so we spoke with Ocko last week about why he was so certain the U.S. was about to get walloped by COVID-19, and asked how some of the startups in DCVC’s portfolio — which has long had a strong biotech focus — are trying to get us back to a state of normalcy.
This conversation has been edited for length.
TechCrunch: You were tweeting about COVID-19 back in January; I almost canceled a flight out of San Francisco because of your [expressed concern about a flight bound for SFO from Wuhan, China]. What did you see that the rest of us missed?
Matt Ocko: My family has been working with the Chinese government at a reasonably high level since the late 1970s, starting with my dad, and I kind of grew up in that environment. And at a relatively young age, as a professional [in the 1990s], I started pro bono helping my dad, who’s a Chinese legal expert, on things like constructing the laws around China’s Nasdaq equivalent, its stock markets, the joint dollar-renminbi investment legislation, advice on technology development and venture capital development.
I’m not an anti-China hawk by any means. But I do have an understanding of some of the idiosyncrasies of Chinese culture reflected in its government, the same way every country has its idiosyncrasies.
[In China’s case], it’s a focus on face and reputation and extreme sensitivity to negative perception or shame or humiliation at every level of government and culture. And so there’s [an] unfortunate trend — and not a universal one — for people to manage upwards, especially in the government, and tell their higher-ups what they want to hear to avoid shame, to avoid the loss of reputation and to kick the can down the road or hope that circumstances on the ground change favorably in the face of denial or equivocation.
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One of the best tools we have to slow the spread of the coronavirus is, as you have no doubt heard by now, contact tracing. But what exactly is contact tracing, who does it and how, and do you need to worry about it?
In short, contact tracing helps prevent the spread of a virus by proactively finding people at higher risk than others due to potential exposure, notifying them if possible, and quarantining them if necessary. It’s a proven technique, and smartphones could help make it even more effective — but only if privacy and other concerns can be overcome.
Contact tracing has been done in some form or another as long as the medical establishment has understood the nature of contagious diseases. When a person is diagnosed with an infectious disease, they are asked whom they have been in contact with over the previous weeks, both in order to determine who may have been infected by them and perhaps where they themselves were infected.
Until very recently, however, the process has relied heavily on the recall of people who are in a highly stressful situation and, until prompted, were probably not paying special attention to their movements and interactions.
This results in a list of contacts that is far from complete, though still very helpful. If those people can be contacted and their contacts likewise traced, a network of potential infections can be built up without a single swab or blood drop, and lives can be saved or important resources better allocated.
You might think that has all changed now what with modern technology and all, but in fact contact tracing being done at hospitals right now is almost all still of the memory-based kind — the same we might have used a hundred years ago.
It certainly seems as if the enormous digital surveillance apparatus that has been assembled around us over the last decade should be able to accomplish this kind of contact tracing easily, but in fact it’s surprisingly useless for anything but tracking what you are likely to click on or buy.
While it would be nice to be able to piece together a contagious person’s week from a hundred cameras spread throughout the city and background location data collected by social media, the potential for abuse of such a system should make us thankful it is not so easy as that. In other, less dire circumstances the ability to track the exact movements and interactions of a person from their digital record would be considered creepy at best, and perhaps even criminal.
But it’s one thing when an unscrupulous data aggregator uses your movements and interests to target you with ads without your knowledge or consent — and quite another when people choose to use the forbidden capabilities of everyday technology in an informed and limited way to turn the tide of a global pandemic. And that’s what modern digital contact tracing is intended to do.
All modern mobile phones use wireless radios to exchange data with cell towers, Wi-Fi routers, and each other. On their own, these transmissions aren’t a very good way to tell where someone is or who they’re near — a Wi-Fi signal can travel 100 to 200 feet reliably, and a cell signal can go miles. Bluetooth, on the other hand, has a short range by design, less than 30 feet for good reception and with a swiftly attenuating signal that makes it unlikely to catch a stray contact from much further out than that.
We all know Bluetooth as the way our wireless earbuds receive music from our phones, and that’s a big part of its job. But Bluetooth, by design, is constantly reaching out and touching other Bluetooth-enabled devices — it’s how your car knows you’ve gotten into it, or how your phone detects a smart home device nearby.
Bluetooth chips also make brief contact without your knowledge with other phones and devices you pass nearby, and if they aren’t recognized, they delete each other from their respective memories as soon as possible. But what if they didn’t?
The type of contact tracing being tested and deployed around the world now uses Bluetooth signals very similar to the ones your phone already transmits and receives constantly. The difference is it just doesn’t automatically forget the other devices it comes into contact with.
Assuming the system is working correctly, what would happen when a person presents at the hospital with COVID-19 is basically just a digitally enhanced version of manual contact tracing. Instead of querying the person’s fallible memory, they query the phone’s much more reliable one, which has dutifully recorded all the other phones it has recently been close enough to connect to. (Anonymously, as we’ll see.)
Those devices — and it’s important to note that it’s devices, not people — would be alerted within seconds that they had recently been in contact with someone who has now been diagnosed with COVID-19. The notification they receive will contain information on what the affected person can do next: Download an app or call a number for screening, for instance, or find a nearby location for testing.
The ease, quickness, and comprehensiveness of this contact tracing method make it an excellent opportunity to help stem the spread of the virus. So why aren’t we all using it already?
In fact digital contact tracing using the above method (or something very like it) has already been implemented with millions of users, apparently to good effect, in east Asia, which of course was hit by the virus earlier than the U.S. and Europe.
In Singapore the TraceTogether app was promoted by the government as the official means for contact tracing. South Korea saw the voluntary adoption of a handful of apps that tracked people known to be diagnosed. Taiwan was able to compare data from its highly centralized healthcare system to a contact tracing system it began work on during the SARS outbreak years ago. And mainland China has implemented a variety of tracking procedures through mega-popular services like WeChat and Alipay.
While it would be premature to make conclusions on the efficacy of these programs while they’re still underway, it seems at least anecdotally to have improved the response and potentially limited the spread of the virus.
But east Asia is a very different place from the U.S.; we can’t just take Taiwan’s playbook and apply it here (or in Europe, or Africa, etc.), for myriad reasons. There are also valid questions of privacy, security, and other matters that need to be answered before people, who for good reason are skeptical of the intentions of both the government and the private sector, will submit to this kind of tracking.
Right now there are a handful of efforts being made in the U.S., the largest profile by far being the collaboration between arch-rivals Apple and Google, which have proposed a cross-platform contact tracing method that can be added to phones at the operating system.
The system they have suggested uses Bluetooth as described above, but importantly does not tie it to a person’s identity in any way. A phone would have a temporary ID number of its own, and as it made contact with other devices, it exchanges numbers. These lists of ID numbers are collected and stored locally, not synced with the cloud or anything. And the numbers also change frequently so no single one can be connected to your device or location.
If and only if a person is determined to be infected with the virus, a hospital (not the person) is authorized to activate the contact tracing app, which will send a notification to all the ID numbers stored in the person’s phone. The notification will say that they were recently near a person now diagnosed with COVID-19 — again, these are only ID numbers generated by a phone and are not connected with any personal information. As discussed earlier, the people notified can then take whatever action seems warranted.
MIT has developed a system that works in a very similar way, and which some states are reportedly beginning to promote among their residents.
Naturally even this straightforward, decentralized, and seemingly secure system has its flaws; this article at the Markup gives a good overview, and I’ve summarized them below:
Contact tracing is an important part of the effort to curb the spread of the coronavirus, and whatever method or platform is decided on in your area — it may be different state to state or even between cities — it is important that as many people as possible take part in order to make it as effective as possible.
There are risks, yes, but the risks are relatively minor and the benefits would appear to outweigh them by orders of magnitude. When the time comes to opt in, it is out of consideration for the community at large that one should make the decision to do so.
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NASA and Planet have deemed their pilot partnership a success, and the result is that NASA will extend its contract with Planet to provide the company’s satellite imagery of Earth to all research programs funded by the agency. NASA had signed an initial contract last April with Planet to provide Planet imagery to a team of 35 researchers working on tracking what are known as “Essential Climate Variables,” or ECVs.
The ECV trial showed that Planet’s imagery was useful in tracking and providing insight into a number of different Earth-based environmental events, including landslides in the Himalayan mountain range. During the study, one of the key ingredients in helping researchers detect early warning signs was the Planet satellite constellation’s high revisit rate, which means the frequency with which it photographs a specific area over time.
Planet’s data covers the entire Earth at least once per day, and includes even areas of the planet not typically included in Earth observation passes by other satellites and providers, like the Arctic. Its frequency, along with its coverage and degree of detail, all combine to make it a valuable resource to anyone conducting Earth science work, which means it’s very good news that it’s now available to hundreds more scientists working on dozens more projects.
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The fact that so many people are stuck at home makes for strange opportunities. Italy’s confined populace has taken to singing from the balconies — and now researchers are asking them to use those same balconies to help accomplish a bit of citizen science.
The project, created by the Italian National Research Council, aims to take widespread samples of light pollution in the country. The question of “light trespass,” or how much light from outside our homes reaches inside them, isn’t a particularly easy one to test without access to those homes. So they’re asking people to collect that information themselves.
Using their phone and a special app, some 7,000 Italians participated in an initial run of the experiment two weeks ago. All they needed to do was turn off all the lights in their place, go to their window or balcony, and point their phone at the brightest light source they could see.
The resulting data showed that the average light trespass in Italian cities is nearly twice that of homes in the country — not exactly surprising, but it’s important for even supposedly obvious conclusions to be quantified and supported with evidence. Sure, it’s brighter in the city — but how much brighter? What type of light is it? More data means better understanding of even the most basic questions.
“With this experiment, we wanted to bring citizens closer to measurement techniques, to let them see the often complex process and allow them to participate in the scientific method,” Alessandro Farini, one of the organizers of the experiment, told Nature. (I contacted the researchers for more information but have not heard back.)
The experiment was so successful that #scienzasulbalcone, or “science on the balcony,” is having an encore — new measurements taken last week and a final one tomorrow night. The team issued revised instructions to its participants in order to better characterize the data they bring in.
Anyone interested in helping is asked to find a light bulb they can easily check the wattage on, then calibrate their phone by leaving only that light on and using their phone’s ambient light sensor to measure its output. This will help calibrate the system, since some phones are more sensitive to light than others. Once they’re done, they can make another measurement out their window or off the balcony, and submit that.
If you’re interested in taking part, you can find the instructions in Italian here; English instructions are here, but I don’t think it is intended to be a global effort just yet.
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In the time of COVID-19, much of what transpires from the science world to the general public relates to the virus, and understandably so. But other domains, even within medical research, are still active — and as usual, there are tons of interesting (and heartening) stories out there that shouldn’t be lost in the furious activity of coronavirus coverage. This last week brought good news for several medical conditions as well as some innovations that could improve weather reporting and maybe save a few lives in Cambodia.
Arrhythmia is a relatively common condition in which the heart beats at an abnormal rate, causing a variety of effects, including, potentially, death. Detecting it is done using an electrocardiogram, and while the technique is sound and widely used, it has its limitations: first, it relies heavily on an expert interpreting the signal, and second, even an expert’s diagnosis doesn’t give a good idea of what the issue looks like in that particular heart. Knowing exactly where the flaw is makes treatment much easier.
Ultrasound is used for internal imaging in lots of ways, but two recent studies establish it as perhaps the next major step in arrhythmia treatment. Researchers at Columbia University used a form of ultrasound monitoring called Electromechanical Wave Imaging to create 3D animations of the patient’s heart as it beat, which helped specialists predict 96% of arrhythmia locations compared with 71% when using the ECG. The two could be used together to provide a more accurate picture of the heart’s condition before undergoing treatment.
Another approach from Stanford applies deep learning techniques to ultrasound imagery and shows that an AI agent can recognize the parts of the heart and record the efficiency with which it is moving blood with accuracy comparable to experts. As with other medical imagery AIs, this isn’t about replacing a doctor but augmenting them; an automated system can help triage and prioritize effectively, suggest things the doctor might have missed or provide an impartial concurrence with their opinion. The code and data set of EchoNet are available for download and inspection.
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Flagship Pioneering, the Boston-based biotech incubator and holding company, said it has raised $1.1 billion for its Flagship Labs unit.
Flagship, which raised $1 billion back in 2019 for growth-stage investment vehicles, develops and operates startups that leverage biotechnology innovation to provide goods and services that improve human health and promote sustainable industries.
“We’re honored to have the strong support of our existing Limited Partners, as well as the interest from a select group of new Limited Partners, to support Flagship’s unique form of company origination during this time of unprecedented economic uncertainty,” said Noubar Afeyan, the founder and chief executive of Flagship Pioneering, in a statement.
In addition to its previous focus on health and sustainability, Flagship will use the new funds to focus on new medicines, artificial intelligence and “health security,” which the company says is “designed to create a range of products and therapies to improve societal health defenses by treating pre-disease states before they escalate,” according to Afeyan.
Flagship companies are already on the forefront of the healthcare industry’s efforts to stop the COVID-19 pandemic. Portfolio company Moderna is one of the companies leading efforts to develop a vaccine for the novel coronavirus which causes COVID-19.
In the 20 years since its launch, Flagship has 15 wholly owned companies and another 26 growth-stage companies among its portfolio of investments.
New companies include: Senda Biosciences, Generate Biomedicines, Tessera Therapeutics, Cellarity, Cygnal Therapeutics, Ring Therapeutics and Integral Health. Growth companies developed or backed by Flagship include Ohana Biosciences, Kintai Therapeutics and Repertoire Immune Medicines.
Two of the companies in the Flagship Labs portfolio have already had initial public offerings in the past two years, the company said. Kaleido Biosciences and Axcella Health raised public capital in 2019, and Moderna Therapeutics conducted a $575 million secondary offering earlier this year.
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