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Police are flying surveillance over Washington. Where were they last week?

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As the world watched rioters take over the US Capitol on January 6, the lack of security was chilling. Some active police officers stood their ground but were outnumbered and defenseless. Other video showed an officer appearing to wave members of a pro-Trump mob beyond a police barrier; some were even filmed taking selfies with the invaders. 

Ahead of the inauguration, however, the government is responding with a show of force that includes ramping up surveillance measures that likely were not in place ahead of the riot.

Multiple surveillance aircraft have been tracked over DC in the last few days, according to data from flight-tracking websites ADS-B Exchange and Flight Aware and monitored by MIT Technology Review. A surveillance plane registered to Lasai Aviation, a contractor of the US Army, likely equipped with highly sensitive radar was logged circling Capitol airspace in a racetrack motion for several hours in the middle of the day on January 13. The same type of plane, also registered to Lasai Aviation, was previously spotted in Latvia near the border of Russia and Belarus. The Department of Defense has denied that the plane belongs to the US military. 

Screenshot of the surveillance plane from ADS-B Exchange

In addition, two helicopters registered to the US Department of the Interior and operated by the US Park Police have been flying over the city. One has been spotted almost every day since January 10 and another was tracked in the air on January 11-13. The Park Police said the flights were part of routine maintenance, and the helicopters are frequent fliers in the city. There have also been regular reports of DC Metropolitan police helicopters over Washington since January 6.

This is not the first time such vehicles have been deployed in the skies above Congress in the past year. Over the summer, for example, the National Guard used an RC-26B reconnaissance craft carrying infrared and electro-optical cameras to monitor the Black Lives Matter protests in Washington; it had previously been used for reconnaissance in Iraq and Afghanistan. 

Jay Stanley, a senior policy analyst at the ACLU, says that the mob at the Capitol “was an attack on the core functions of our democracy.” From a civil liberties perspective, he says, increased surveillance is “certainly justified” to protect democracy, though transparency and policies around the use of technologies are essential. “We should scrutinize and interrogate the necessity for aerial surveillance in any situation”, he says. 

But the level of surveillance and show of force at the Capitol stand in marked contrast to the apparent lack of security in place ahead of January 6. A search by MIT Technology Review found evidence of only one helicopter run by the DC police in the skies at the time of the Capitol mob. Currently, thousands of troops are stationed inside and outside the building, and the situational response is taking on a formality and sophistication akin to a military operation. While Stanley cautions that it is unlikely that increased surveillance would have dramatically changed the course of the assault, the disparity between then and now has left many experts wondering what went wrong before the Capitol riot, and why.

“There just didn’t seem to be any kind of a response,” says Seth Stoughton, an associate professor of criminology at the University of South Carolina. “That looks like a planning, leadership, or command-and-control failure.”

So what should have happened, and what went wrong? 

Advance notice to a heavily-funded force

The potential threat on January 6 might have surprised some, but the danger was known and visible to law enforcement. According to the Washington Post, the FBI’s Norfolk Field Office sent a situational awareness report on January 5 about credible threats of violence at the Capitol. Hotels were booked up in the area, and there had been weeks of online discussion about organized violence. A leader of the Proud Boys was arrested in Washington, DC, two days before the rally with high-capacity firearm magazines. And most of all, of course, President Trump had been falsely telling his supporters for months that the election had been stolen from him, and that followers would have to “liberate” states. On the morning of the riot, he addressed the crowd and told them, “You will never take back our country with weakness.”

Despite all this, the US Capitol Police had prepared for a typical free-speech rally with only scattered violence, such as small fights breaking out in large crowds. There are no reports of standard surveillance measures used ahead of potentially violent large-scale events, such as police videographers or pole camera set-ups, and only one helicopter registered to the DC Police to perform aerial surveillance. Body cameras on police also appeared to be used sparingly, as the Capitol police do not wear them.

Nor were resources an issue. The United States Capitol Police, or USCP, is one of the most well-funded police forces in the country. It is responsible for security across just 0.4 square miles of land, but that area hosts some of the most high-profile events in American politics, including presidential inaugurations, lying-in-state ceremonies, and major protests. The USCP is well-staffed, with 2,300 officers and civilian employees, and its annual budget is at least $460 million—putting it among the top 20 police budgets in the US. In fact, it’s about the size of the Atlanta and Nashville police budgets combined. For comparison, the DC Metropolitan Police Department—which works regularly with the USCP and covers the rest of the District’s 68 square miles—has a budget of $546 million

The USCP is different from state and local departments in other important ways, too. As a federal agency that has no residents inside its jurisdiction, for example, it answers to a private oversight board and to Congress—and only Congress has the power to change its rules and budgets. Nor is it subject to transparency laws such as the Freedom of Information Act, which makes it even more veiled than the most opaque departments elsewhere in the country. 

All of this means there is little public information about the tools and tactics that were at the USCP’s disposal ahead of the riots. 

But “they have access to some pretty sophisticated stuff if they want to use it,” says Stoughton. That includes the resources of other agencies like the Secret Service, the FBI, the Department of Homeland Security, the Department of the Interior, and the United States military. (“We are working [on technology] on every level with pretty much every agency in the country,” the USCP’s then-chief said in 2015, in a rare acknowledgment of the force’s technical savvy.)

What should have happened

With such resources at its disposal, the Capitol Police would likely have made heavy use of online surveillance ahead of January 6. Such monitoring usually involves not just watching online spaces, but tracking known extremists who had been at other violent events. In this case, that would include the “Unite the Right” rally in Charlottesville, Virginia, in 2017 and the protest against coronavirus restrictions at the Michigan state capitol in 2020. 

Exactly what surveillance was happening before the riots is unclear. The FBI turned down a request for a comment, and the USCP did not respond. “I’d find it very hard to believe, though, that a well-funded, well-staffed agency with a pretty robust history of assisting with responding to crowd control situations in DC didn’t do that type of basic intelligence gathering,” says Stoughton. 

Ed Maguire, professor of criminal justice at Arizona State University, is an expert on protests and policing. He says undercover officers would usually operate in the crowd to monitor any developments, which he says can be the most effective surveillance tool to manage potentially volatile situations—but that would require some preparedness and planning that perhaps was lacking. 

Major events of this kind would usually involve a detailed risk assessment, informed by monitoring efforts and FBI intelligence reports. These assessments determine all security, staffing, and surveillance plans for an event. Stoughton says that what he sees as inconsistency in officers’ decisions to retreat or not, as well as the lack of an evacuation plan and the clear delay in securing backup, point to notable mistakes. 

This supports one of the more obvious explanations for the failure: that the department simply misjudged the risk. 

What seems to have happened

It appears that Capitol Police didn’t coordinate with the Park Police or the Metropolitan Police ahead of the rally—though the Metropolitan Police were staffed at capacity in anticipation of violence. Capitol Police Chief Steven Sund, who announced his resignation in the wake of the riots, also asserts that he requested additional National Guard backup on January 5, though the Pentagon denies this.

The USCP has also been accused of racial bias, along with other police forces. Departments in New York, Seattle, and Philadelphia are among those looking into whether their own officers took part in the assault, and the Capitol Police itself suspended “several” employees and will investigate 10 officers over their role.

But one significant factor that might have altered the volatility of the situation, Maguire says, is that police clashes with the Proud Boys in the weeks and days before the event, including a violent rally in Salem, Oregon, and the arrest of the white supremacist group’s leader, Henry Tarrio, fractured the right wing’s assumption that law enforcement was essentially on their side. On January 5, Maguire had tweeted about hardening rhetoric and threats of violence as this assumption started to fall apart. 

 “That fraying of the relationship between the police and the right in the few days leading up to this event, I think, are directly implicated in the use of force against police at the Capitol,” he says. In online comments on video of the confrontation in Oregon, he says, it’s clear there’s “a sense of betrayal” among the Proud Boys.

“A land grab for new powers”

Despite all the problems in the immediate response to the assault, investigations and arrests of the rioters have been taking place. The Capitol grounds are well-fitted with surveillance tools, many of which will be called on as investigations continue. A sea of Wi-Fi networks and cell towers capture mobile-phone data, and an expansive fleet of high-tech cameras covers most of the building. 

As of January 16, the FBI has collected 140,000 pieces of social media through an online portal asking for tips and images from the mob. The agency also has access to facial recognition software from ClearviewAI, which reported a spike in use of its tool in the days after the riot.

But the lack of transparency into police tools, tactics, policies, and execution makes any attempt at connecting the dots speculation. Experts have been calling for formal investigations into exactly what happened ahead of January 6, because transparency into the intelligence analysis and operational decisions is the only way to determine the key points of failure. On January 15, the inspectors general of the Departments of Justice, Defense, the Interior and Homeland Security announced a joint investigation into the federal response.

As the inauguration of Joe Biden ramps up, all eyes will be on whether the security professionals are prepared. And their eyes will likely be on us, too, as surveillance continues to increase, though it’s unlikely the public will know about the true nature of that surveillance anytime soon. 

Stanley suggests we should remain vigilant about the impact of the fallout from the Capitol, cautioning that “the people who want various security powers and toys and so forth use an emergency to try and get it. We saw that after 9/11 and I think there’s going to be some of that now too.” 

He echoes the calls for investigation and transparency into the Capitol police on January 6, but suggests that people remain skeptical. “Don’t let this become a land grab for new powers and surveillance activities because of the law enforcement’s very failures,” he says.

Lyron Foster is a Hawaii based African American Musician, Author, Actor, Blogger, Filmmaker, Philanthropist and Multinational Serial Tech Entrepreneur.

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Personal skin problems leads founder to launch skincare startup Nøie, raises $12M Series A

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Inspired by his own problems with skin ailments, tech founder Daniel Jensen decided there had to be a better way. So, using an in-house tech platform, his Copenhagen-based startup Nøie developed its own database of skin profiles, to better care for sensitive skin.

Nøie has now raised $12m in a Series A funding round led by Talis Capital, with participation from Inventure, as well as existing investors including Thomas Ryge Mikkelsen, former CMO of Pandora, and Kristian Schrøder Hart-Hansen, former CEO of LEO Pharma’s Innovation Lab.

Nøie’s customized skincare products target sensitive skin conditions including acne, psoriasis and eczema. Using its own R&D, Nøie says it screens thousands of skincare products on the market, selects what it thinks are the best, and uses an algorithm to assign customers to their ‘skin family’. Customers then get recommendations for customized products to suit their skin.

Skin+Me is probably the best-known perceived competitor, but this is a prescription provider. Noie is non-prescription.

Jensen said: “We firmly believe that the biggest competition is the broader skincare industry and the consumer behavior that comes with it. I truly believe that in 2030 we’ll be surprised that we ever went into a store and picked up a one-size-fits-all product to combat our skincare issues, based on what has the nicest packaging or the best marketing. In a sense, any new company that emerges in this space are peers to us: we’re all working together to intrinsically change how people choose skincare products. We’re all demonstrating to people that they can now receive highly-personalized products based on their own skin’s specific needs.”

Of his own problems to find the right skincare provider, he said: “It’s just extremely difficult to find something that works. When you look at technology, online, and all our apps and everything, we got so smart in so many areas, but not when it comes to consumer skin products. I believe that in five or 10 years down the line, you’ll be laughing that we really used to just go in and pick up products just off the shelf, without knowing what we’re supposed to be using. I think everything we will be using in the bathroom will be customized.”

Beatrice Aliprandi, principal at Talis Capital, said: “For too long have both the dermatology sector and the skincare industry relied on the outdated ‘one-size-fits-all’ approach to addressing chronic skin conditions. By instead taking a data-driven and community feedback approach, Nøie is building the next generation of skincare by providing complete personalization for its customers at a massive scale, pioneering the next revolution in skincare.”

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Comms expert and VC Caryn Marooney will detail how to get attention at TC Early Stage

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We’re thrilled to announce Caryn Marooney is speaking at our upcoming TechCrunch Early Stage virtual event in July. She spoke with us last year and we had to have her back.

Just look at her resume. She was the co-founder and CEO of The Outcast Agency, one of Silicon Valley’s best-regarded public relations firms. She left her company to serve as VP of Global Communication at Facebook, which she did for eight years, overseeing communication for Facebook, Instagram, WhatsApp and Oculus. In 2019 she joined Coatue Management as a general partner, where she went on to invest in Startburst, Supabase, Defined Networks and others.

Needless to say, Marooney is one of the Valley’s experts on getting people’s attention — a skill that’s critical when running a startup, nonprofit or school bake sale.

She said it best last year: “People just fundamentally aren’t walking around caring about this new startup — actually, nobody does.” So how do you get people to care? That’s the trick and why we’re having her back to speak on this evergreen topic.

Watch her presentation from 2020 here. It’s fantastic.

One of the great things about TC Early Stage is that the show is designed around breakout sessions, with each speaker leading a chat around a specific startup core competency (like fundraising, designing a brand, mastering the art of PR and more). Moreover, there is plenty of time for audience Q&A in each session.

Pick up your ticket for the event, which goes down July 8 and 9, right here. And if you do it today, you’ll save a cool $100 off of your registration.


 

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Lightmatter’s photonic AI ambitions light up an $80M B round

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AI is fundamental to many products and services today, but its hunger for data and computing cycles is bottomless. Lightmatter plans to leapfrog Moore’s law with its ultra-fast photonic chips specialized for AI work, and with a new $80M round the company is poised to take its light-powered computing to market.

We first covered Lightmatter in 2018, when the founders were fresh out of MIT and had raised $11M to prove that their idea of photonic computing was as valuable as they claimed. They spent the next three years and change building and refining the tech — and running into all the hurdles that hardware startups and technical founders tend to find.

For a full breakdown of what the company’s tech does, read that feature — the essentials haven’t changed.

In a nutshell, Lightmatter’s chips perform certain complex calculations fundamental to machine learning in a flash — literally. Instead of using charge, logic gates, and transistors to record and manipulate data, the chips use photonic circuits that perform the calculations by manipulating the path of light. It’s been possible for years, but until recently getting it to work at scale, and for a practical, indeed a highly valuable purpose has not.

Prototype to product

It wasn’t entirely clear in 2018 when Lightmatter was getting off the ground whether this tech would be something they could sell to replace more traditional compute clusters like the thousands of custom units companies like Google and Amazon use to train their AIs.

“We knew in principle the tech should be great, but there were a lot of details we needed to figure out,” CEO and co-founder Nick Harris told TechCrunch in an interview. “Lots of hard theoretical computer science and chip design challenges we needed to overcome… and COVID was a beast.”

With suppliers out of commission and many in the industry pausing partnerships, delaying projects, and other things, the pandemic put Lightmatter months behind schedule, but they came out the other side stronger. Harris said that the challenges of building a chip company from the ground up were substantial, if not unexpected.

A rack of Lightmatter servers.

Image Credits: Lightmatter

“In general what we’re doing is pretty crazy,” he admitted. “We’re building computers from nothing. We design the chip, the chip package, the card the chip package sits on, the system the cards go in, and the software that runs on it…. we’ve had to build a company that straddles all this expertise.”

That company has grown from its handful of founders to more than 70 employees in Mountain View and Boston, and the growth will continue as it brings its new product to market.

Where a few years ago Lightmatter’s product was more of a well-informed twinkle in the eye, now it has taken a more solid form in the Envise, which they call a ‘general purpose photonic AI accelerator.” It’s a server unit designed to fit into normal datacenter racks but equipped with multiple photonic computing units, which can perform neural network inference processes at mind-boggling speeds. (It’s limited to certain types of calculations, namely linear algebra for now, and not complex logic, but this type of math happens to be a major component of machine learning processes.)

Harris was reticent to provide exact numbers on performance improvements, but more because those improvements are increasing than that they’re not impressive enough. The website suggests it’s 5x faster than an NVIDIA A100 unit on a large transformer model like BERT, while using about 15 percent of the energy. That makes the platform doubly attractive to deep-pocketed AI giants like Google and Amazon, which constantly require both more computing power and who pay through the nose for the energy required to use it. Either better performance or lower energy cost would be great — both together is irresistible.

It’s Lightmatter’s initial plan to test these units with its most likely customers by the end of 2021, refining it and bringing it up to production levels so it can be sold widely. But Harris emphasized this was essentially the Model T of their new approach.

“If we’re right, we just invented the next transistor,” he said, and for the purposes of large-scale computing, the claim is not without merit. You’re not going to have a miniature photonic computer in your hand any time soon, but in datacenters, where as much as 10 percent of the world’s power is predicted to go by 2030, “they really have unlimited appetite.”

The color of math

A Lightmatter chip with its logo on the side.

Image Credits: Lightmatter

There are two main ways by which Lightmatter plans to improve the capabilities of its photonic computers. The first, and most insane sounding, is processing in different colors.

It’s not so wild when you think about how these computers actually work. Transistors, which have been at the heart of computing for decades, use electricity to perform logic operations, opening and closing gates and so on. At a macro scale you can have different frequencies of electricity that can be manipulated like waveforms, but at this smaller scale it doesn’t work like that. You just have one form of currency, electrons, and gates are either open or closed.

In Lightmatter’s devices, however, light passes through waveguides that perform the calculations as it goes, simplifying (in some ways) and speeding up the process. And light, as we all learned in science class, comes in a variety of wavelengths — all of which can be used independently and simultaneously on the same hardware.

The same optical magic that lets a signal sent from a blue laser be processed at the speed of light works for a red or a green laser with minimal modification. And if the light waves don’t interfere with one another, they can travel through the same optical components at the same time without losing any coherence.

That means that if a Lightmatter chip can do, say, a million calculations a second using a red laser source, adding another color doubles that to two million, adding another makes three — with very little in the way of modification needed. The chief obstacle is getting lasers that are up to the task, Harris said. Being able to take roughly the same hardware and near-instantly double, triple, or 20x the performance makes for a nice roadmap.

It also leads to the second challenge the company is working on clearing away, namely interconnect. Any supercomputer is composed of many small individual computers, thousands and thousands of them, working in perfect synchrony. In order for them to do so, they need to communicate constantly to make sure each core knows what other cores are doing, and otherwise coordinate the immensely complex computing problems supercomputing is designed to take on. (Intel talks about this “concurrency” problem building an exa-scale supercomputer here.)

“One of the things we’ve learned along the way is, how do you get these chips to talk to each other when they get to the point where they’re so fast that they’re just sitting there waiting most of the time?” said Harris. The Lightmatter chips are doing work so quickly that they can’t rely on traditional computing cores to coordinate between them.

A photonic problem, it seems, requires a photonic solution: a wafer-scale interconnect board that uses waveguides instead of fiber optics to transfer data between the different cores. Fiber connections aren’t exactly slow, of course, but they aren’t infinitely fast, and the fibers themselves are actually fairly bulky at the scales chips are designed, limiting the number of channels you can have between cores.

“We built the optics, the waveguides, into the chip itself; we can fit 40 waveguides into the space of a single optical fiber,” said Harris. “That means you have way more lanes operating in parallel — it gets you to absurdly high interconnect speeds.” (Chip and server fiends can find that specs here.)

The optical interconnect board is called Passage, and will be part of a future generation of its Envise products — but as with the color calculation, it’s for a future generation. 5-10x performance at a fraction of the power will have to satisfy their potential customers for the present.

Putting that $80M to work

Those customers, initially the “hyper-scale” data handlers that already own datacenters and supercomputers that they’re maxing out, will be getting the first test chips later this year. That’s where the B round is primarily going, Harris said: “We’re funding our early access program.”

That means both building hardware to ship (very expensive per unit before economies of scale kick in, not to mention the present difficulties with suppliers) and building the go-to-market team. Servicing, support, and the immense amount of software that goes along with something like this — there’s a lot of hiring going on.

The round itself was led by Viking Global Investors, with participation from HP Enterprise, Lockheed Martin, SIP Global Partners, and previous investors GV, Matrix Partners and Spark Capital. It brings their total raised to about $113 million; There was the initial $11M A round, then GV hopping on with a $22M A-1, then this $80M.

Although there are other companies pursuing photonic computing and its potential applications in neural networks especially, Harris didn’t seem to feel that they were nipping at Lightmatter’s heels. Few if any seem close to shipping a product, and at any rate this is a market that is in the middle of its hockey stick moment. He pointed to an OpenAI study indicating that the demand for AI-related computing is increasing far faster than existing technology can provide it, except with ever larger datacenters.

The next decade will bring economic and political pressure to rein in that power consumption, just as we’ve seen with the cryptocurrency world, and Lightmatter is poised and ready to provide an efficient, powerful alternative to the usual GPU-based fare.

As Harris suggested hopefully earlier, what his company has made is potentially transformative in the industry and if so there’s no hurry — if there’s a gold rush, they’ve already staked their claim.

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