Month: August 2021

Fleets weren’t long for this world, but Twitter’s product teams aren’t slowing down on bringing new stuff to Spaces, the company’s own take on audio rooms. Twitter introduced Spaces in a limited test last year, expanding the Clubhouse copycat feature more broadly to anyone with at least 600 followers in May.

Now, Twitter is giving Space hosts the ability to add two co-hosts, who they can rope in through an invite system. Spaces will allow one main host, two additional co-hosts and up to 10 speakers. Additional co-hosts will make the task of moderation much more manageable, as they’ll be able to vet speaker requests, tap speakers and give anyone in the Space the boot.

With Fleets out of the picture, Twitter’s Spaces are the only feature for now that lives above the main feed in the Twitter app. That virtual real estate, which has echoes of Instagram’s Stories, draws the eye to anything that a social network wants its users to check out first. Twitter also began rolling out a dedicated tab to make it easier to discover Spaces, surfacing live audio rooms in real time in a central location.

A number of major apps spliced live audio chat rooms into their platforms in light of Clubhouse’s breakout run. In June, Spotify launched Greenroom, a standalone app that allows people to create 1,000-person voice events. Naturally, Facebook also launched its own spin on live audio rooms (called Live Audio Rooms) in June. Discord, already a leader in voice-based chat, added its own Clubhouse-like event channels in March. Twitter followed the same trend with Spaces, but unlike with Fleets, it looks like the company plans to continue supporting the relatively new feature.

Source: Tech Crunch

In a company’s early days, the difference between C-level executives and the rest of the organization is simple — employees can walk away from a failure, but the leaders cannot. Under these conditions, certain kinds of people thrive in leadership roles and can take a company from ideation to production.

While there’s no magic formula for what works and what doesn’t, successful startups share common traits in terms of the way their foundational leadership teams are built.

We’ve all experienced what it looks like on the negative end of the spectrum — people making points simply to hear their own voice, leaders competing for credit and clashing agendas. When people would rather be heard than contribute, the output suffers. Members of a healthy leadership team are unafraid to let others have the limelight, because they trust the mission and the culture they’ve built together.

We are all imperfect human beings, founders included. There are always going to be moments that leaders can’t predict, and mistakes come with the territory. The right leadership team should be able to mitigate the unexpected, and sometimes make the future easier to predict. Putting the right people in the right roles early on can be the difference between success and failure — and that starts at the top.

Start by determining who will lead as CEO

Investors love founder-CEOs, and founders are often fantastic candidates for this role. But not everyone can do it well, and more importantly, not everyone wants to.

Startup founders should ask themselves a few questions before they lose sleep over the prospect of handing over the reigns:

• Do I even want to be CEO? If yes, for how long?
• Can I maximize the potential of the company if I’m not the CEO?
• Am I really the best person for this job at this stage?

An honest self-assessment is necessary and this is something that only exceptional and selfless founders are capable of. In many cases, founders decide they need outside help to fill the role. While a CEO may not be your first hire — or even one of the first five — the person you choose will ultimately occupy your organization’s most critical leadership role, so choose wisely.

What to look for: Ambitious vision grounded in execution reality. Your CEO should have hands-on experience that allows them to see around corners, predict pitfalls and identify opportunities.

What to watch out for: Leaders who lack respect for the founding vision or the ability to hire and balance an executive team quickly. A good CEO should be able to manage short-term cash flow and go-to-market needs without compromising the true north, while building a foundation and culture for the long term.

Then, hire a leader for your engineering team

Source: Tech Crunch

Japanese startup ispace has raised $46 million in a fresh round of Series C funding as it looks to complete three lunar lander missions in three years.

The funding will go toward the second and third of the planned missions, scheduled for 2023 and 2024. The first mission, which ispace aims to conduct in the latter half of 2022, is being furnished by earlier financing.

The Series C was led by Japanese VC firm Incubate Fund, with additional investment from partnerships managed by Innovation Engine, funds managed by SBI Investment Co., Katsunori Sago, Aizawa Investments and funds managed by HiJoJo Partners and Aizawa Asset Management. Incubate Fund’s investments in ispace stretch back to the company’s seed round in 2014.

Ispace’s total funding now stands at $195.5 million.

The company said last month it had started building the lunar landing flight module for the 2022 mission at a facility owned by space launch company ArianeGroup, in Lampoldshausen, Germany. The lander for that first mission, the Hakuto-R, will take three months to reach the moon, largely to save costs and additional weight from propellant. It will deliver a 22-pound rover for Saudi Arabia’s Mohammed bin Rashid Space Center, a lunar robot for the Japan Aerospace Exploration Agency and payload from three Canadian companies. The lander will reach the moon aboard a SpaceX Falcon 9 rocket.

The 7.5 foot-tall Hakuto-R will also be used in the second mission in 2023, to deposit a small ispace rover that will collect data to support the company’s subsequent missions to the moon. For the final mission, the Toyko-based startup is developing a larger lander in the United States.

Ispace describes its long-term goal as being a “gateway for private sector companies to bring their business to the Moon.” The company has particular interest in helping spur a space-based economy, noting on its website that the moon’s water resources represent “untapped potential.”

Source: Tech Crunch

Two decades after businesses first started deploying AI solutions, one can argue that they’ve made little progress in achieving significant gains in efficiency and profitability relative to the hype that drove initial expectations.

On the surface, recent data supports AI skeptics. Almost 90% of data science projects never make it to production; only 20% of analytics insights through 2022 will achieve business outcomes; and even companies that have developed an enterprisewide AI strategy are seeing failure rates of up to 50%.

But the past 25 years have only been the first phase in the evolution of enterprise AI — or what we might call Enterprise AI 1.0. That’s where many businesses remain today. However, companies on the leading edge of AI innovation have advanced to the next generation, which will define the coming decade of big data, analytics and automation — Enterprise AI 2.0.

The difference between these two generations of enterprise AI is not academic. For executives across the business spectrum — from healthcare and retail to media and finance — the evolution from 1.0 to 2.0 is a chance to learn and adapt from past failures, create concrete expectations for future uses and justify the rising investment in AI that we see across industries.

Two decades from now, when business leaders look back to the 2020s, the companies who achieved Enterprise AI 2.0 first will have come to be big winners in the economy, having differentiated their services, scooped up market share and positioned themselves for ongoing innovation.

Framing the digital transformations of the future as an evolution from Enterprise AI 1.0 to 2.0 provides a conceptual model for business leaders developing strategies to compete in the age of automation and advanced analytics.

Enterprise AI 1.0 (the status quo)

Starting in the mid-1990s, AI was a sector marked by speculative testing, experimental interest and exploration. These activities occurred almost exclusively in the domain of data scientists. As Gartner wrote in a recent report, these efforts were “alchemy … run by wizards whose talents will not scale in the organization.”

Source: Tech Crunch

Facebook shut down accounts belonging to two academic researchers late Tuesday, cutting off their ability to study political ads and misinformation on the world’s biggest social network.

The company accused the academics of engaging in “unauthorized scraping” and compromising user privacy on the platform, claims that Facebook’s many critics are slamming as a thin pretense for killing the transparency work.

The company took action against Laura Edelson and Damon McCoy, two well-known researchers affiliated with NYU’s Cybersecurity for Democracy project who have long sparred with the company. The move cuts off their access to Facebook’s Ad Library — one of the company’s only meaningful transparency efforts to date — and data on popular posts from the social media monitoring service CrowdTangle.

Facebook has a history with Edelson and McCoy. The company served the pair cease and desist letters just weeks before the 2020 election, calling on the team to disable an opt-in browser tool called Ad Observer and unpublish their findings. Ad Observer is a browser tool anyone can install that’s designed to give researchers a rare glimpse into how Facebook targets the ads that have transformed it into a trillion-dollar company.

“Over the last several years, we’ve used this access to uncover systemic flaws in the Facebook Ad Library, identify misinformation in political ads including many sowing distrust in our election system, and to study Facebook’s apparent amplification of partisan misinformation,” Edelson said on Twitter.

“By suspending our accounts, Facebook has effectively ended all this work. Facebook has also effectively cut off access to more than two dozen other researchers and journalists who get access to Facebook data through our project, including our work measuring vaccine misinformation with the Virality Project and many other partners who rely on our data.”

The incident set off a fresh round of criticism about the company’s preference for opacity over transparency when it comes to some of the more dangerous behavior that the platform incubates.

By Wednesday, Facebook’s actions had attracted the attention of some members of Congress. Sen. Ron Wyden (D-OR) criticized Facebook’s decision to punish the researchers under the pretense of protecting users in light of the company’s long history of invasive privacy practices. Wyden also called Facebook’s bluff over its claim that revoking researcher access is an effort to comply with a privacy order from the FTC that the company was issued for its previous user privacy violations.

Sen. Mark Warner (D-VA) also weighed in on Facebook’s latest controversy, calling the decision “deeply concerning.” Warner praised independent researchers for “consistently [improving] the integrity and safety of social media platforms by exposing harmful and exploitative activity.”

“It’s past time for Congress to act to bring greater transparency to the shadowy world of online advertising, which continues to be a major vector for fraud and misconduct,” Warner said.

Firefox developer Mozilla came to the defense of Ad Observer on Wednesday, noting that the company “reviewed it twice, conducting both a code review and examining the consent flow” before recommending the browser extension through its storefront. In a blog post, Mozilla’s head of trust stated that Facebook’s claims “simply do not hold water.”

A number of free press organizations, researchers and misinformation experts also condemned Facebook’s decision Wednesday. “Facebook’s cavalier approach to privacy enabled it to become so dominant,” The Markup’s Julia Angwin and Nabiha Syed wrote in a joint statement.

“But now, when independent researchers want to interrogate that platform and the influence it commands, Facebook is propping up user privacy as a shield to hide behind.”

Source: Tech Crunch

Dating app maker and Tinder parent Match Group said during its Q2 earnings it will bring audio and video chat, including group live video, and other livestreaming technologies to several of the company’s brands over the next 12 to 24 months. The developments will be powered by innovations from Hyperconnect, the social networking company that this year became Match’s biggest acquisition to date when it bought the Korean app maker for a sizable $1.73 billion. 

Since then, Match Group has been relatively quiet about its specific plans for Hyperconnect’s tech or its longer-term strategy with the operation, although Tinder was briefly spotted testing a group video chat feature called Tinder Mixer earlier this summer. The move had seemed to signal some exploration of social discovery features in the wake of the Hyperconnect deal. However, Tinder told us at the time the company had no plans to bring that specific product to market in the year ahead.

On Tuesday’s earnings, Match Group offered a little more insight into the future of Hyperconnect, following the acquisition’s official close in mid-June.

According to Match Group CEO Shar Dubey, who stepped into the top job last January, the company is excited about the potential to integrate technologies Hyperconnect has developed into existing Match-owned dating apps.

This includes, she said, “AR features, self-expression tools, conversational AI and a number of what we would consider metaverse elements, which have the element to transform the online meeting and getting-to-know-each-other process,” Dubey explained, without offering further specific details about how the products would work or which apps would receive these enhancements.

Many of these technologies emerged from Hyperconnect’s lab, Hyper X — the same in-house incubator whose first product is now one of the company’s flagship apps, Azar, which joined Match Group with the acquisition.

Dubey also noted that the work to begin these tech integrations was already underway at the company.

By year-end, Match Group said it expects to have at least two of its brands integrated with technologies from Hyperconnect. A number of other brands will implement Hyperconnect capabilities by year-end 2022.

In doing so, Match aims to transform what people think of when it comes to online dating.

To date, online dating has been a fairly static experience across the industry, where apps focus largely on profiles and photos, and then offer some sort of matching technique — whether swipes or quizzes or something else. Tinder, in more recent years, began to break out of that mold as it innovated with an array of different experiences, like its choose-your-own-adventure in-app video series, “Swipe Night,” video profiles, instant chat features (via Tinder’s product, Hot Takes) and others. But it still lacked some of the real-time elements that people have when meeting one another in the real world.

This is an area where Match believes Hyperconnect can help to improve the online dating experience.

“One of the holy grails for us in online dating has always been to bridge the disconnect that happens between people chatting online and then meeting someone in person,” Dubey said. “These technologies will eventually allow us to build experiences that will help people determine if they have that much elusive chemistry or not… Our ultimate vision here is for people to never have to go on a bad first date again,” she added.

Of course, Match Group’s positioning of the Hyperconnect deal as being more interesting because the innovation it brings — and not just the standalone apps it operates — also comes at a time when those apps have not met the company’s expectations on revenue.

In the second half the of 2021, Match Group said it expects Hyperconnect to contribute to $125 to $135 million in revenue — a financial outlook that the company admits reflects some pullback. It attributed this largely to COVID impacts, particularly in the Asia-Pacific region where Hyperconnect’s apps operate. Other impacts to Hyperconnect’s growth included a more crowded marketplace and Apple’s changes to IDFA (Identifier for Advertisers), which has impacted a number of apps — including other social networking apps, like Facebook.

While Match still believes Hyperconnect will post “solid revenue growth” in 2021, it said that these new technology integrations into the Match Group portfolio are now “a higher priority” for the company.

Match Group posted mixed earnings in Q1, with revenue of $707.8 million, above analyst estimates, but earnings per share of 46 cents, below projections of 49 cents a share. Paying customers grew 15% to 15 million, up from 13 million in the year-ago quarter. Shares declined by 7% on Wednesday morning, following the earnings announcement.

Source: Tech Crunch

Superintelligence, roughly defined as an AI algorithm that can solve all problems better than people, will be a watershed for humanity and tech.

Even the best human experts have trouble making predictions about highly probabilistic, wicked problems. And yet those wicked problems surround us. We are all living through immense change in complex systems that impact the climate, public health, geopolitics and basic needs served by the supply chain.

Just determining the best way to distribute COVID-19 vaccines without the help of an algorithm is practically impossible. We need to get smarter in how we solve these problems — fast.

Superintelligence, if achieved, would help us make better predictions about challenges like natural disasters, building resilient supply chains or geopolitical conflict, and come up with better strategies to solve them. The last decade has shown how much AI can improve the accuracy of our predictions. That’s why there is an international race among corporations and governments around superintelligence.

Highly credible think tanks like Deepmind and OpenAI say that the path to superintelligence is visible. Last month, Deepmind said reinforcement learning (RL) could get us there, and RL is at the heart of embodied AI.

What is embodied AI?

Embodied AI is AI that controls a physical “thing,” like a robot arm or an autonomous vehicle. It is able to move through the world and affect a physical environment with its actions, similar to the way a person does. In contrast, most predictive models live in the cloud doing things such as classifying text or images, steering flows of bits without ever moving a body through three-dimensional space.

For those who work in software, including AI researchers, it is too easy to forget the body. But any superintelligent algorithm needs to control a body because so many of the problems we confront as humans are physical. Firestorms, coronaviruses and supply chain breakdowns need solutions that aren’t just digital.

All the crazy Boston Dynamics videos of robots jumping, dancing, balancing and running are examples of embodied AI. They show how far we’ve come from early breakthroughs in dynamic robot balancing made by Trevor Blackwell and Anybots more than a decade ago. The field is moving fast and, in this revolution, you can dance.

What’s blocked embodied AI up until now?

Challenge 1: One of the challenges when controlling machines with AI is the high dimensionality of the world — the sheer range of things that can come at you.

Source: Tech Crunch