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Turing nabs $32M more for an AI-based platform to source and manage engineers remotely

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As remote work continues to solidify its place as a critical aspect of how businesses exist these days, a startup that has built a platform to help companies source and bring on one specific category of remote employees, engineers, is taking on some more funding to meet demand.

Turing — which has built an AI-based platform to help evaluate prospective, but far-flung, engineers, bring them together into remote teams, and then manage them for the company — has picked up $32 million in a Series B round of funding led by WestBridge Capital. Its plan is as ambitious as the world it is addressing is wide: an AI platform to help define the future of how companies source IT talent to grow.

“They have a ton of experience in investing in global IT services, companies like Cognizant and GlobalLogic,” said co-founder and CEO Jonathan Siddharth of its lead investor in an interview the other day. “We see Turing as the next iteration of that model. Once software ate the IT services industry, what would Accenture look like?”

It currently has a database of some 180,000 engineers covering around 100 or so engineering skills including React, Node, Python, Agular, Swift, Android, Java, Rails, Golang, PHP, Vue, devops, machine learning, data engineering and more.

In addition to WestBridge, other investors in this round included Foundation Capital, Altair Capital, Mindset Ventures, Frontier Ventures, and Gaingels. There is also a very long list of high profile angels participating, underscoring the network that the founders themselves have amassed. It includes unnamed executives from Google, Facebook, Amazon, Twitter, Microsoft, Snap, and other companies as well as Adam D’Angelo (Facebook’s first CTO and CEO at Quora), Gokul Rajaram, Cyan Banister and Scott Banister, Beerud Sheth (the founder of Upwork), among many others (I’ll run the full list below).

Turing is not disclosing its valuation. But as a measure of its momentum, it was only in August that the company raised a seed round of $14 million, led by Foundation. Siddharth said that the growth has been strong enough in the interim that the valuations it was getting and the level of interest compelled the company to skip A altogether and go straight for its Series B.

The company now has 180,000 developers signed up from across 10,000 cities to its platform (compared to 150,000 back in August). Some 50,000 of them have gone through automated vetting on the Turing platform, and the task will now be to bring on more companies to tap into that trove of talent.

Or, “We are demand-constrained,” which is how Siddharth describes it. At the same time, it’s been growing revenues and growing its customer base, jumping from revenues of $9.5 million in October to $12 million in November, increasing 17x since first becoming generally available 14 months ago. Current customers include VillageMD, Plume, Lambda School, Ohi Tech, Proxy, and Carta Healthcare.

Remote work=immediate opportunity

A lot of people talk about remote work today in the context of people no longer able to go into their offices as part of the effort to curtail the spread of Covid-19. But in reality another form of it has been in existence for decades.

Offshoring and outsourcing by way of help from third parties — such as Accenture and other systems integrators  — are two ways that companies have been scaling and operating, paying sums to those third parties to run certain functions or build out specific areas instead of shouldering the operating costs of employing, upsizing and sometimes downsizing that labor force itself.

Turing is essentially tapping into both concepts. On one hand, it has built a new way to source and run teams of people, specifically engineers, on behalf of others. On the other, it’s using the opportunity that has presented itself in the last year, to open up the minds of engineering managers and others to consider the idea of bringing on people they might have previously insisted work in their offices, to now work for them remotely, and still be effective.

Siddarth, who co-founded the company with Vijay Krishnan (who is the CTO) know the other side of the coin all too well. They are both from India, and both relocated to the Valley first for school (post-graduate degrees at Stanford) and then work at a time when moving to the Valley was effectively the only option for ambitious people like them to get employed by in large, global tech companies, or build startups, effectively what could become large, global tech companies.

“Talent is universal, but opportunities are not,” Siddarth said to me earlier this year when describing the state of the situation.

A previous startup co-founded by the pair — content discovery app Rover — highlighted to them a gap in the market. They built the startup around a remote and distributed team of engineers, which helped them keep costs down while still recruiting top talent. Meanwhile, rivals were building teams in the Valley. “All our competitors in Palo Alto and the wider area were burning through tons of cash, and it’s only worse now. Salaries have skyrocketed,” he said.

After Rover was acquired by Revcontent, a recommendation platform that competes against the likes of Taboola and Outbrain, they decided to turn their attention to seeing if they could build a startup based on how they had, basically, built their own previous startup.

There are a number of companies that have been tapping into the different aspects of the remote work opportunity, as it pertains to sourcing talent and how to manage it.

They include the likes of Remote (raised $35 million in November), Deel ($30 million raised in September), Papaya Global ($40 million also in September), Lattice ($45 million in July), and Factorial ($16 million in April), among others.

What’s interesting about Turing is how it’s trying to address and provide services for the different stages you go through when finding new talent. It starts with an AI platform to source and vet candidates. That then moves into matching people with opportunities, and onboarding those engineers. Then, Turing helps manage their work and productivity in a secure fashion, and also provides guidance on the best way to manage that worker in the most compliant way, be it as a contractor or potentially as a full-time remote employee.

The company is not freemium as such but gives people two weeks to trial people before committing to a project. So unlike an Accenture, Turing itself tries to build in some elasticity into its own product, not unlike the kind of elasticity that it promises its customers.

It all sounds like a great idea now, but interestingly, it was only after remote work really became the norm around March/April of this year that the idea really started to pick up traction.

“It’s amazing what Covid has done. It’s led to a huge boom for Turing,” said Sumir Chadha, MD for WestBridge Capital, in an interview. For those who are building out tech teams, he added, there is now “No need for to find engineers and match them with customers. All of that is done in the cloud.”

“Turing has a very interesting business model which today is especially relevant,” said Igor Ryabenkiy, Managing Partner at Altair Capital, in a statement. “Access to the best talent worldwide and keeping it well-managed and cost-effective make the offering attractive for many corporations. The energy of the founding team provides fast growth for the company, which will be even more accelerated after the B-round.”

PS. I said I’d list the full, longer list of investors in this round. In these Covid times, this is likely the biggest kind of party you’ll see for a while. In addition to those listed above, it included [deep breath] Founders Fund, Chapter One Ventures (Jeff Morris Jr), Plug and Play Tech Ventures (Saeed Amidi), UpHonest Capital (​Wei Guo, Ellen Ma​), Ideas & Capital (Xavier Ponce de León), 500 Startups Vietnam (Binh Tran and Eddie Thai), Canvas Ventures (Gary Little), B Capital (Karen Appleton P​age, Kabir Narang), Peak State Ventures (​Bryan Ciambella, Seva Zakharov)​, Stanford StartX Fund, Amino C​apital, ​Spike Ventures, Visary Capital (Faizan Khan), Brainstorm Ventures (Ariel Jaduszliwer), Dmitry Chernyak, Lorenzo Thione, Shariq Rizvi, Siqi Chen, Yi Ding, Sunil Rajaraman, Parakram Khandpur, Kintan Brahmbhatt, Cameron Drummond, Kevin Moore, Sundeep Ahuja, Auren Hoffman, Greg Back, Sean Foote, Kelly Graziadei, Bobby Balachandran, Ajith Samuel, Aakash Dhuna, Adam Canady, Steffen Nauman, Sybille Nauman, Eric Cohen, Vlad V, Marat Kichikov, Piyush Prahladka, Manas Joglekar, Vladimir Khristenko, Tim and Melinda Thompson, Alexandr Katalov, Joseph and Lea Anne Ng, Jed Ng, Eric Bunting, Rafael Carmona, Jorge Carmona, Viacheslav Turpanov, James Borow, Ray Carroll, Suzanne Fletcher, Denis Beloglazov, Tigran Nazaretian, Andrew Kamotskiy, Ilya Poz, Natalia Shkirtil, Ludmila Khrapchenko, Ustavshchikov Sergey, Maxim Matcin, and Peggy Ferrell.

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

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Elon Musk says Tesla Semi is ready for production, but limited by battery cell output

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Tesla CEO Elon Musk said on the company’s 2020 Q4 earnings call that all engineering work is now complete on the Tesla Semi, the freight-hauling semi truck that the company is building with an all-electric powertrain. The company expects to begin deliveries of Tesla Semi this year, the company said in its Q4 earnings release, and Musk said the only thing limiting their ability to produce them now is the availability of battery cells.

“The main reason we have not accelerated new products – like for example Tesla Semi – is that we simply don’t have enough cells for it,” Musk said. “If we were to make the Semi right now, and we could easily go into production with the Semi right now, but we would not have enough cells for it.”

Musk added that the company does expect to have sufficient cell volume to meet its needs once it goes into production on its 4680 battery pack, which is a new custom cell design it created with a so-called ‘tables’ design that allows for greater energy density and therefore range.

“A Semi would use typically five times the number of cells that a car would use, but it would not sell for five times what a car would sell for, so it kind of would not make sense for us to do the Semi right now,” Musk said. “But it will absolutely make sense for us to do it as soon as we can address the cell production constraint.”

That constraint points to the same conclusion for the possibility of Tesla developing a van, Musk added, and the lifting of the constraint will likewise make it possible for Tesla to pursue the development of that category of vehicle, he said.

Tesla has big plans for “exponentially” ramping cell production, with a goal of having production capacity infrastructure in place for a Toal of 200 gigawatt hours per year by 2022, and a target of being able to actually produce around 40% of that by that year (with future process improvements generating additional gigawatt hours of cell capacity  in gradual improvements thereafter).

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Pro-Trump Twitter figure arrested for spreading vote-by-text disinformation in 2016

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The man behind a once-influential pro-Trump account is facing charges of election interference for allegedly disseminating voting disinformation on Twitter in 2016.

Federal prosecutors allege that Douglass Mackey, who used the name “Ricky Vaughn” on Twitter, encouraged people to cast their ballot via text or on social media, effectively tricking others into throwing away those votes.

According to the Justice Department, 4,900 unique phone numbers texted a phone number Mackey promoted in order to “vote by text.” BuzzFeed reported the vote-by-text scam at the time, noting that many of the images were photoshopped to look like official graphics from Hillary Clinton’s presidential campaign.

Some of those images appeared to specifically target Black and Spanish-speaking Clinton supporters, a motive that tracks with the account’s track record of white supremacist and anti-Semitic content. The account was suspended in November 2016.

At the time, the mysterious account quickly gained traction in the political disinformation ecosystem. HuffPost revealed that the account was run by Mackey, the son of a lobbyist, two years later.

“… His talent for blending far-right propaganda with conservative messages on Twitter made him a key disseminator of extremist views to Republican voters and a central figure in the alt-right’ white supremacist movement that attached itself to Trump’s coattails,” HuffPost’s Luke O’Brien reported.

Mackey, a West Palm Beach resident, was taken into custody Wednesday in Florida.

“There is no place in public discourse for lies and misinformation to defraud citizens of their right to vote,” Acting U.S. Attorney for the Eastern District of New York Seth D. DuCharme said.

“With Mackey’s arrest, we serve notice that those who would subvert the democratic process in this manner cannot rely on the cloak of Internet anonymity to evade responsibility for their crimes.”

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Tesla is willing to license Autopilot and has already had “preliminary discussions” about it with other automakers

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Tesla is open to licensing its software, including its Autopilot highly-automated driving technology, and the neural network training it has built to improve its autonomous driving technology. Tesla CEO Elon Musk revealed those considerations on the company’s Q4 earnings call on Wednesday, adding that the company has in fact already “had some preliminary discussions about licensing Autopilot to other OEMs.”

The company began rolling out its beta version of the so-called ‘full self-driving’ or FSD version of Autopilot late last year. The standard Autopilot features available in general release provide advanced driver assistance (ADAS) which provide essentially advanced cruise control capabilities designed primarily for use in highway commutes. Musk said on the call that he expects the company will seek to prove out its FSD capabilities before entering into any licensing agreements, if it does end up pursuing that path.

Musk noted that Tesla’s “philosophy is definitely not to create walled gardens” overall, and pointed out that the company is planning to allow other automakers to use its Supercharger networks, as well as its autonomy software. He characterized Tesla as “more than happy to license” those autonomous technologies to “other car companies,” in fact.

One key technical hurdle required to get to a point where Tesla’s technology is able to demonstrate true reliability far surpassing that of a standard human driver is transition the neural networks operating in the cars and providing them with the analysis that powers their perception engines is to transition those to video. That’s a full-stack transition across the system away from basing it around neural nets trained on single cameras and single frames.

To this end, the company has developed video labelling software that has had “a huge effect on the efficiency of labeling,” with the ultimate aim being enabling automatic labeling. Musk (who isn’t known for modesty around his company’s achievements, it should be said) noted that Tesla believes “it may be the best neural net training computer in the world by possibly an order of magnitude,” adding that it’s also “something we can offer potentially as a service.”

Training huge quantities of video data will help Tesla push the reliability of its software from 100% that of a human driver, to 200% and eventually to “2,000% better than the average human,” Musk said, while again suggesting that it won’t be a technological achievement the company is interested into keeping to themselves.

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