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Twitch expands its rules against hate and abuse to include behavior off the platform
Twitch will start holding its streamers to a higher standard. The company just expanded its hate and harassment policy, specifying more kinds of bad behavior that break its rules and could result in a ban from the streaming service.
The news comes as Twitch continues to grapple with reports of abusive behavior and sexual harassment, both on the platform and within the company itself. In December, Twitch released an updated set of rules designed to take harassment and abuse more seriously, admitting that women, people of color and the LGBTQ+ community were impacted by a “disproportionate” amount of that toxic behavior on the platform.
Twitch’s policies now include serious offenses that could pose a safety threat, even when they happen entirely away from the streaming service. Those threats include violent extremism, terrorism, threats of mass violence, sexual assault and ties to known hate groups.
The company will also continue to evaluate off-platform behavior in cases that happen on Twitch, like an on-stream situation that leads to harassment on Twitter or Facebook.
“While this policy is new, we have taken action historically against serious, clear misconduct that took place off service, but until now, we didn’t have an approach that scaled,” the company wrote in a blog post, adding that investigating off-platform behavior requires additional resources to address the complexity inherent in those cases.
To handle reports for its broadened rules, Twitch created a dedicated email address (OSIT@twitch.tv) to handle reports about off-service behavior. The company says it has partnered with a third-party investigative law firm to vet the reports it receives.
Twitch cites its actions against former President Donald Trump as the most high-profile instance of off-platform behavior resulting in enforcement. The company disabled Trump’s account following the attack on the U.S. Capitol and later suspended him indefinitely, citing fears that he could use the service to incite violence.
It’s hard to have a higher profile than the president, but Trump isn’t the only big time banned Twitch user. Last June, Twitch kicked one of its biggest streamers off of the platform without providing an explanation for the decision.
Going on a year later, no one seems to know why Dr. Disrespect got the boot from Twitch, though the company’s insistence that it only acts in cases with a “preponderance of evidence” suggests his violations were serious and well corroborated.
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Okta expands into privileged access management and identity governance reporting
Okta today announced it was expanding its platform into a couple of new areas. Up to this point, the company has been known for its identity access management product, giving companies the ability to sign onto multiple cloud products with a single sign on. Today, the company is moving into two new areas: privileged access and identity governance
Privileged access gives companies the ability to provide access on an as-needed basis to a limited number of people to key administrative services inside a company. This could be your database or your servers or any part of your technology stack that is highly sensitive and where you want to tightly control who can access these systems.
Okta CEO Todd McKinnon says that Okta has always been good at locking down the general user population access to cloud services like Salesforce, Office 365 and Gmail. What these cloud services have in common is you access them via a web interface.
Administrators access the speciality accounts using different protocols. “It’s something like secure shell, or you’re using a terminal on your computer to connect to a server in the cloud, or it’s a database connection where you’re actually logging in with a SQL connection, or you’re connecting to a container, which is the Kubernetes protocol to actually manage the container,” McKinnon explained.
Privileged access offers a couple of key features including the ability to limit access to a given time window and to record a video of the session so there is an audit trail of exactly what happened while someone was accessing the system. McKinnon says that these features provide additional layers of protection for these sensitive accounts.
He says that it will be fairly trivial to carve out these accounts because Okta already has divided users into groups and can give these special privileges to only those people in the administrative access group. The challenge was figuring out how to get access to these other kinds of protocols.
The governance piece provides a way for security operations teams to run detailed reports and look for issues related to identity. “Governance provides exception reporting so you can give that to your auditors, and more importantly you can give that to your security team to make sure that you figure out what’s going on and why there is this deviation from your stated policy,” he said.
All of this when combined with the $6.5 billion acquisition of Auth0 last month is part of a larger plan by the company to be what McKinnon calls the identity cloud. He sees a market with several strategic clouds and he believes identity is going to be one of them.
“Because identity is so strategic for everything, it’s unlocking your customer, access, it’s unlocking your employee access, it’s keeping everything secure. And so this expansion, whether it’s customer identity with zero trust or whether it’s doing more on the workforce identity with not just access, but privileged access and identity governance. It’s about identity evolving in this primary cloud,” he said.
While both of these new products were announced today at the company’s virtual Oktane customer conference, they won’t be generally available until the first quarter of next year.
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Building and leading an early-stage sales team with Zoom CRO Ryan Azus
This year at Early Stage, TechCrunch spoke with Zoom Chief Revenue Officer (CRO) Ryan Azus about building an early-stage sales team. Azus is perhaps best known for leading the video-calling giant’s income arm during COVID-19, but his experience building RingCentral’s North American sales organization from the ground up made him the perfect guest to chat with about building an early-stage sales team.
We asked him about when founders should step aside from leading their startup’s sales org, how to build a working sales culture, hiring diversely, how to pick customer segments and how to build a playbook.
Below, TechCrunch has compiled a number of key comments from Azus, and afterward we’ve included the full video from the interview as well as a transcript. Let’s go!
When should founders let others run sales?
Nearly every startup leans on its CEO as its first salesperson. After all, who else knows the product and can talk it up like the startup’s leader? But having the CEO as point-person for sales scales poorly. So, when is the right time to have someone else step in?
Fairly early on. First off, CEOs need to solve customer needs. And so it’s important to be very hands-on for a while to really understand while you’re trying to figure out product-market fit. And then bringing in some of those sales people as you start seeing something [good].
Part of it is also knowing what type of salesperson you need. [ … ] Who is your core audience? What persona are you going after? And trying to find people that know and understand selling something that’s primarily very transactional to small businesses, [or] e-commerce lead, or selling something that’s more enterprise — those are different animals, different segments that you’re going after. One mistake [startups make] is hiring the wrong type of salesperson. (Time stamp: 5:29)
How much product-market fit is enough?
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How to kick the 10 worst startup habits with Fuel Capital’s Leah Solivan
Fuel Capital General Partner Leah Solivan joined us at TechCrunch Early Stage 2021 to talk about how to avoid early mistakes in building your startup. Solivan has ample experience on both sides of the fence, as she founded TaskRabbit and led it to exit through an acquisition by Ikea in 2017. She shared a list of 10 things to avoid in total, but here are some highlights of what to watch out for.
Share your ideas freely
Solivan urged founders to not be shy about sharing their ideas, as some people can tend to be secretive about their startup concept. The notion that giving up your idea somehow means you’ll end up with more competition is not a legitimate concern in the end, Solivan said. Instead, sharing that idea with as many people as you can is much more likely to generate positive results than negative.
I can’t tell you how many times I would be giving a presentation. And someone after the presentation would come up to me and say, oh my goodness, I had this same idea for TaskRabbit, like 10 years ago. And I’d be like, great! What did you do with that idea? And I think the point is, is that the idea itself isn’t the magic — the magic is in the execution of your idea and actually turning that idea into a business. (Time stamp: 01:42)
- You might just have missed the best time to sell your startup
- 15 things founders should know before accepting funding from a corporate VC
Take everyone’s advice, but make the call
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Streamlit nabs $35M Series B to expand machine learning platform
As a company founded by data scientists, Streamlit may be in a unique position to develop tooling to help companies build machine learning applications. For starters, it developed an open-source project, but today the startup announced an expanded beta of a new commercial offering and $35 million in Series B funding.
Sequoia led the investment with help from previous investors Gradient Ventures and GGV Capital. Today’s round brings the total raised to $62 million, according to the company.
Data scientists can download the open-source project and build a machine learning application, but it requires a certain level of technical aptitude to make all the parts work. Company co-founder and CEO Adrien Treuille says that so far the company has 20,000 monthly active developers using the open-source tooling to develop streaming apps, which have been viewed millions of times.
As they have gained that traction, they have customers who would prefer to use a commercial service. “It’s great to have something free and that you can use instantly, but not every company is capable of bridging that into a commercial offering,” Treuille explained.
Company COO and co-founder Amanda Kelly says that the commercial offering called Streamlit for Teams is designed to remove some of the complexity around using the open-source application. “The whole [process of] how do I actually deploy an app, put it in a container, make sure it scales, has the resources and is securely connected to data sources […] — that’s a whole different skill set. That’s a DevOps and IT skill set,” she said.
What Streamlit for Teams does is take care of all that in the background for end users, so they can concentrate on the app building part of the equation without help from the technical side of the company to deploy it.
Sonya Huang, a partner at Sequoia, who is leading the firm’s investment in Streamlit, says that she was impressed with the company’s developer focus and sees the new commercial offering as a way to expand usage of the applications that data scientists have been building in the open-source project.
“Streamlit has a chance to define a better interface between data teams and business users by ushering in a new paradigm for interactive, data-rich applications,” Huang said.
They have data scientists at big-name companies like Uber, Delta Dental and John Deere using the open-source product already. They have kept the company fairly lean with 27 employees up until now, but the plan is to double that number in the coming year with the new funding, Kelly says.
She says that the founding team recognizes that it’s important to build a diverse company. She admits that it’s not always easy to do in practice when as a young startup you are just fighting to stay alive, but she says that the funding gives them the luxury to step back and begin to hire more deliberately.
“Literally right before this call, I was on with a consultant who is going to come in and work with the executive team, so that we’re all super clear about what we mean [when it comes to] diversity for us and how is this actually a really core part of our company, so that we can flow that into recruiting and people and engineering practices and and make that a lived value within our company,” she said.
Streamlit for Teams is available in beta starting today. The company plans to make it generally available some time later this year.
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Snorkel AI scores $35M Series B to automate data labeling in machine learning
One of the more tedious aspects of machine learning is providing a set of labels to teach the machine learning model what it needs to know. Snorkel AI wants to make it easier for subject matter experts to apply those labels programmatically, and today the startup announced a $35 million Series B.
It also announced a new tool called Application Studio that provides a way to build common machine learning applications using templates and predefined components.
Lightspeed Venture Partners led the round with participation from previous investors Greylock, GV, In-Q-Tel and Nepenthe Capital. New investors Walden and BlackRock also joined in. The startup reports that it has now raised $50 million.
Company co-founder and CEO Alex Ratner says that data labeling remains a huge challenge and roadblock to moving machine learning and artificial intelligence forward inside a lot of industries because it is costly, labor-intensive and hard for the subject experts to carve out the time to do it.
“The not so hidden secret about AI today is that in spite of all the technological and tooling advancements, roughly 80 to 90% of the cost and time for an average AI project goes into just manually labeling and collecting and relabeling this training data,” he said.
He says that his company has developed a solution to simplify this process to make it easier for subject experts to programmatically add the labels, a process he says decreases the time and effort required to apply labels in a pretty dramatic way from months to hours or days, depending on the complexity of the data.
As the company has developed this methodology, customers have been asking for help in the next step of the machine learning process, which is taking that training data and the model and building an application. That’s where the Application Studio comes in. It could be a contract classifier at a bank or a network anomaly detector at a telco and it helps companies take that next step after data labeling.
“It’s not just about how you programmatically label the data, it’s also about the models, the preprocessors, the post processors, and so we’ve made this now accessible in a kind of templated and visual no-code interface,” he said.
The company’s products are based on research that began at the Stanford AI Lab in 2015. The founders spent four years in the research phase before launching Snorkel in 2019. Today, the startup has 40 employees. Ratner recognizes the issues that the technology industry has had from a diversity perspective and says he has made a conscious effort to build a diverse and inclusive company.
“What I can say is that we tried to prioritize it at a company level, the full team level and at a board level from day one, and to also put action behind that. So we’ve been working with external firms for internal training and audits and strategy around DEI, and we’ve made pipeline diversity a non-negotiable requirement of any of our contracts with recruiting firms,” he said.
Ratner also recognizes that automation can hard code bias into machine learning models, and he’s hopeful that by simplifying the labeling process, it can make it much easier to detect bias when it happens.
“If you start with a dozen or two dozen of what we call labeling functions in Snorkel, you still need to be vigilant and proactive about trying to detect bias, but it’s easier to audit what taught your model to change it by just going back and looking at a couple of hundred lines of code.”
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Hiro Capital puts $2.3M into team sports tracking platform PlayerData — as does Sir Terry Leahy
Hiro Capital has gradually been making a name for itself as an investor in the area know as “Digital Sports” or DSports for short. It’s now led a $2.3 million funding round in PlayerData. While the round might sound small, the area it’s going into is large and growing. Also investing in the round is Sir Terry Leahy, previously the CEO of Tesco, the largest British retailer.
Edinburgh, U.K.-based PlayerData uses wearable technology and software tracking to give grass-roots and professional sports teams feedback on their training. It can, for instance, allow coaches to replay key moments from a game, even modeling different outcomes based on player positioning.
This is Hiro Capital’s fourth DSports and “connected fitness” investment, and it joins Zwift, FitXR and NURVV. Hiro has also invested in eight games startups in the U.K., U.S. and Europe, as befits the heritage of co-founder and partner Ian Livingstone, OBE, CBE, who is the former chairman of Tomb Raider publisher Eidos plc and all-round gaming pioneer.
PlayerData says it has captured more than 10,000 team sessions across U.K. soccer and rugby, and logged over 50 million meters of play. It also has strong network effects, it says. Every time a new team encounters one using Playerdata’s platform, it generates five more clubs as users.
Roy Hotrabhvanon is co-founder and CEO of PlayerData, and is a former international-level archer. He’s joined by Hayden Ball, co-founder and CTO, a firmware and cloud infrastructure expert.
PlayerData app. Image Credits: PlayerData
In a statement Hotrabhvanon said: “Our mission is to bring fine-grained data and insight to clubs across team sports, helping them supercharge their game-making, improve player performance, and avoid injury… Our ultimate goal is to implement cutting-edge insights from pioneering wearables that are applicable to any team in any discipline at any level.”
Cherry Freeman, co-founding partner at Hiro, says: “PlayerData ticks all of our key boxes: a huge TAM with over 3 million grass-roots clubs; a deep moat built on shared player data, machine learning and highly actionable predictive algorithms; compelling customer network effects; and a really impressive yet humble founding team.”
The PlayerData news forms part of a wider growth in digital sports, which includes such breakout names as Peloton, Tonal, Mirror and Hiro’s portfolio investment, Zwift. With the pandemic putting an emphasis on both home workouts and general health, the fascination with digital measurement of performance now has a growing grip on the sector.
Speaking to TechCrunch, Freeman added: “We think there are something like 3 million teams that are potential customers for PlayerData. Obviously the number of runners is enormous, and they only need to get a small slice of that market to have a very, very large business. At the end of the day everyone, everyone works out, even if you just go for a walk, so the target market’s huge and they started with running but their technology is applicable to a whole raft of other sports.”
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Authentic Artists is building virtual, AI-powered musicians
Chris McGarry, who previously led music integration at Facebook’s Oculus, is taking a new approach to bringing music into the virtual world with his startup Authentic Artists.
McGarry pointed to virtual celebrities like Lil Miquela and virtual concerts like Travis Scott’s giant event in Fortnite as setting the stage for Authentic Artists. In a sense, the startup represents a combination of those ideas, creating virtual musicians who perform their own concerts — initially in Twitch — and can respond to audience requests.
“We are very intentionally not trying to create a digital facsimile of what already exists,” he said. “We want to use new tools to create new art, new experiences, new culture. The appeal is that these artists can really be vehicles for collaboration with the audience, so that [audience members] can selectively shape the live show.”
In fact, Authentic Artists has already held some test concerts on Twitch, and McGarry said the team was “frankly, sort of blown away by the response,” with average watch time of 35 minutes.
It will be unveiling its next generation of virtual artists in Twitch concerts starting on April 14, co-hosted by (human) Twitch streamers, who will introduce the concept to audiences — though McGarry said there’s potential for more collaboration between virtual and human stars in the future.
There are a number of different pieces to the Authentic Artists platform, working together to animate a virtual musician, generate their music and allow them to respond to audience feedback, whether that’s increasing the intensity of a song, decreasing the tempo or fast-forwarding to the next song.
“Music is the lifeblood of our vision, and accordingly, we’ve invested significantly in the core audio engine,” McGarry said. He emphasized that the platform is not simply recombining music loops composed by humans, but rather generating music on its own: “We want [our virtual artists] to have autonomy, we want them to be real.”
It sounds like the team is still putting the final touches on the new artists, so I didn’t get to see a full concert experience. Instead, McGarry and his team presented renderings of these artists (including a half-human cyborg and a giant iguana) and their virtual venues, and they demonstrated the music engine, creating new compositions on-the-fly while adjusting different parameters. As McGarry put it, “These are all original compositions, generated and produced as we sit here, with no manual intervention.”
Authentic Artists is backed by investors including OVO Fund, James Murdoch’s Lupa Systems, Mixi Group and Mike Shinoda of Linkin Park. McGarry said he’s currently more focused on finding product-market fit than on the business model, but he sees opportunities to make money through avenues such as branded music and decentralized finance/NFTs in the future.
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Swyft raises $17.5 million to bring same-day delivery to all the retailers that aren’t Amazon
Thanks to major players like Amazon and Walmart, we’ve become accustomed to next- or same-day delivery. But the pandemic has also renewed our interest in buying from smaller businesses and retailers.
Swyft, a company that has just raised $17.5 million in a Series A, helps retailers of any size provide affordable same-day delivery. The round was co-led by Inovia Capital and Forerunner Ventures, with participation from Shopify and existing investors Golden Ventures and Trucks VC.
Swyft is a marketplace, connecting a network of shipping carriers with vendors. But the company also provides software to those carriers to make them more efficient, and turns them into a vast network that allows them to pick up more inventory without adding to their infrastructure.
In other words, several regional carriers may play a part in delivering a parcel shipped via Swyft without making any big changes to their original routes or adding new drivers, trucks, etc.
To date, major players in both shipping and retail have dominated this space, thanks in large part to their ability to deliver quickly. Swyft is looking to amass an army, for lack of a better term, comprised of all of the smaller players, including mom and pop retailers and vendors as well as smaller, regional carriers. Banded together through software, these carriers and retailers can match the scale and influence of the behemoths without spending a fortune.
Swyft was co-founded by Aadil Kazmi (CEO), Zeeshan Hamid (head of Engineering) and Maraz Rahman (head of Sales). Kazmi and Hamid both spent their careers at Amazon, working on data and last-mile operations for the behemoth. Rahman was an early employee at a YC-backed proptech startup.
The trio started asking themselves early last year why retailers weren’t able to offer same-day delivery and chose to tackle the gap they discovered.
The key ingredient to Swyft is not its aggregation of couriers, but the software it provides to them. Because Swyft is increasing demand for these carriers, it also needs to make them more efficient. The back-end software allows carriers to digitize or automate a good deal of what they’re traditionally doing by hand.
Kazmi says that Swyft is able to come in anywhere between 25-30% cheaper than the incumbent option.
“I don’t know what percent of your purchases are from Amazon, but for me it’s like 150%,” said Eurie Kim. “I’d prefer to buy elsewhere with the pandemic, and support local and independent brands, but Amazon’s trained us all to have fast and free shipping. It feels like an opportunity where the consumer experience is really lacking and the burden on merchants and retailers is extremely heavy.”
Swyft currently has 16 full-time employees; 12% percent are female and 75% are people of color, according to the company.
Since April 2020, Swyft has facilitated the delivery of more than 180,000 packages, and expanded gross margin from 78% to 82%, thanks in large part to revenue from the software side of the business and a zero-asset model.
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Blue dot raises $32M for AI that helps businesses manage their tax accounting
Artificial intelligence has become a fundamental cornerstone of how a lot of business software works, providing a useful boost in reading, understanding and using the often-fragmented trove of data that organizations generate these days. In the latest development, an Israeli startup called Blue dot, which uses AI to help companies handle their tax accounting, is announcing $32 million in funding to continue its growth, specifically addressing the demand from companies for more user-friendly tools to help read and correctly itemize expenses for tax purposes.
“The tax sector is very complicated, and we are playing in a very large space, but it’s a huge revolution,” Blue dot’s CEO and co-founder Isaac Saft said in an interview. “Business and enterprise accounting is just not going to look the same in the future as it does today.”
The funding is being led by Ibex Investors in partnership with Lutetia Technology Partners, with past investors La Maison Partners, Viola and Target Global also contributing. Blue dot rebranded only last week from its original name, VATBox (part of the funding will be used to help Blue dot move deeper into the U.S. market, where the concept of VAT is not quite so ubiquitous: there is no national sales tax and states determine the rates themselves).
PitchBook notes that under its previous name, the startup last raised money in 2017, a $20 million Series B led by Viola at a $120 million post-money valuation.
While Blue dot is not disclosing valuation today, it’s likely to be significantly higher than this based on some of its engagements. In addition to customers like Amazon, tobacco giant BAT and Dell, it also has a partnership with one of the bigger names in expense accounting, SAP Concur, which uses Blue dot to power its expense data entry tool to automatically read charges and figure out how to itemize them so that employees or accountants don’t need to go through the pain of that themselves.
As Saft describes it, part of what is propelling his company’s business is the bigger trend of consumerization and the role that it has played in enterprise services: the working world has picked up a lot of technology tools, led by the smartphone, to help them organize their personal lives, and a lot of what they are being “served” through technology is increasingly personalized with lower barriers of entry, whether its on e-commerce sites, entertainment or social media. In the working world, people can often be frustrated as a result with how much work something like expenses can involve — a process that gets ever more complicated the more strict tax regimes become.
Blue dot’s approach is to essentially view the tax accounting process as something that can be improved with AI to make it easier for people to use — whether those people are workers itemizing their expenses, or accountants auditing them and running those through even bigger accounting processes. With a machine learning system that both takes into account a company’s own internal compliance and company policies, and the wider tax and regulatory framework, Blue dot helps “read” an expense and figure out how to notate it, how much tax should be accounted and where, and so on.
This is especially important as the process of entering and managing expenses gets pushed out to the people spending the money, rather than dedicated accountants handling that work on their behalf. An awareness of how modern offices are functioning today and evolving is one reason why investors were interested here.
“We believe Blue dot can change the way organizations worldwide manage accounting and its tax implications for their expenses,” Gal Gitter, a partner at Ibex, said in a statement. “There’s been a major market shift away from centralization of enterprise functions, including procurement. As that accelerates, more companies will be looking for ways to replace costly and complex manual processes with digital, automated solutions that use data and AI to essentially enable transactions to report themselves, which Blue dot delivers.”
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