Archiv für den Monat April 2016

Most Important Job Positions For Creating A Culture Of Innovation

If you’re changing the world, you’re working on important things. You’re excited to get up in the morning. You want to be working on meaningful, impactful projects.

The role of the recruiter is no longer just to find talent. It is to understand and empathize with their applicants, and then help make their experience better.

Netflix believes the best thing they can do for employees is hire only „A“ players to work alongside them. Excellent colleagues trump everything else.

At Pixar he conceived of a program that lets employees choose from 14 classes per week, including ballet, improv, drawing, and painting skills, computer programming, belly dancing, and color theory. This keeps Pixar’s talent learning and growing, thus making better films.

the shift toward culture may be gaining prominence as small businesses struggle to compete for talent with larger counterparts in the areas of plump paychecks and generous benefits packages. They’re beginning to recognize culture for the trump card it is, particularly with millennials used to interactive, stimulating environments.“

We all fear the job that looks great on paper and is a nightmare in practice. What makes some companies great to work for and others a disaster? The answer: good workplace culture. It’s the difference between Google and Yahoo, Costco, and the Department of Corrections. Studies have shown that office culture is one of the most revealing indicators of workplace satisfaction. How can companies be intentional about building and nurturing a good workplace culture?

The short answer: Hire for the right roles. Some people believe that founders are the only ones who can create company culture. It’s true that founders are usually responsible for creating the original values. Consider how Larry Page and Sergey Brin from Google defined the way they wanted their first dozen employees to feel at work. In fact many of the best-loved parts of the culture started before Google had 50 employees.

But as a company grows, there are still opportunities for cultural recalibration. Here are seven roles of people who help define, harness, reflect, and embody culture. Think of them as the new faces of organizational culture.

1. The Gardener

Exemplar: Company Founder(s)
Google cofounders Larry Page and Sergey Brin had one intention for Google’s culture: They wanted to create a company that felt like their experience at Stanford’s graduate school. Page and Brin famously hired a chef to cook for Google’s first employees, a perk they had grown to love at Stanford University’s dining halls.

Beyond the free food, Google tried to mimic the actual experience and culture of being a grad student. Page observed, „When you’re a grad student, you can work on whatever you want. And the projects that were really good got a lot of people really wanting to work on them. We’ve taken that learning to Google, and it’s been really, really helpful. If you’re changing the world, you’re working on important things. You’re excited to get up in the morning. You want to be working on meaningful, impactful projects.“

Page and Brin are examples of founders who have helped nurture Google’s culture. Several culture theorists use the term „gardening“ when talking about fostering good workplace culture. A few years ago, the New York Times columnist Thomas Friedman spoke with Amazon CEO Jeff Bezos about trends in technology and leadership. Friedman wrote that Bezos believes „the job of the company leader is now changing fast. ‘You have to think of yourself not as a designer but as a gardener’—seeding, nurturing, inspiring, cultivating the ideas coming from below, and then making sure people execute them.“

Google has retained many parts of its unique startup culture because Page and Brin understood that the company’s culture needed care and nurturing. The most important thing the gardener can do is to write down the company’s cultural values and share them within the company. Page and Brin wrote Google’s values when the company was just a few years old.

2. The Sage

Exemplar: Venture Capitalist
It was 2012, and Airbnb cofounders Brian Chesky, Joe Gebbia, and Nathan Blecharczyk had just closed their Series C funding round with investor Peter Thiel. Thiel cofounded PayPal and now runs Palantir Technologies. Thiel is known for his business aptitude, and he frequently writes about his philosophical (and sometimes controversial) viewpoints, including his support of libertarianism and his belief that companies should operate with a flat structure and share company data with all employees. The Airbnb cofounders invited Thiel to their office in San Francisco. To help you picture this scene, it’s important to know that the conference rooms in the Airbnb office are designed to look like real Airbnb apartment listings from cities including New York, Berlin, and Hong Kong. They invited Thiel into the „Berlin Room“ (decorated with ornate baroque wallpaper and a rococo couch) to show him various metrics. In the middle of the conversation, Chesky asked Thiel what his single most important piece of advice for them was.

Thiel replied, „Don’t fuck up the culture.“

Thiel is an example of a sage, a wise veteran who has been through the trenches of starting a company before. The most important thing a sage can do is to remind a company to focus on culture. Founders often feel like they have no time to focus on company culture, when it is actually the most important thing they should be focused on. Jerry Colonna, a former venture capitalist at Flatiron Partners and current CEO coach, is known as the Yoda of Silicon Valley. His Yoda wisdom? „Even if you are not intentional about your culture, you will still have one.“

3. The Empathizer

Exemplar: The Recruiter
Let’s say I’ve just stayed at an Airbnb, and I’ve had a great experience using the service. I’m on the website, leaving a review, and I navigate down to the careers page. I already have a job I love, but I’m just curious (we’ve all been there). Within two minutes, I have learned what Airbnb’s cultural values are and specifically what traits and values Airbnb is looking for in candidates. But what really hooks me is learning what it’s like to work at Airbnb. I see that employees get to have „fireside chats“ with industry leaders and musicians like Will.I.Am. I learn what it’s like for employees to work at Airbnb every day. And not just employees, in the generic sense. Specifically, videos on what it’s like for interns, developers, and even moms to work at Airbnb. There’s also a huge section on what the engineering culture is like (hilariously, at

Airbnb has carefully mapped out what comes next. Jill Riopelle, head of recruiting, used a design technique called journey mapping to gain empathy for the candidates going through Airbnb’s job application process. She hosted a brainstorming session in the Airbnb lunch room, and asked Airbnb employees to reflect on their own best and worst hiring moments. Next, they brainstormed how they wanted applicants to feel at each point and mapped out the ideal process for both the applicant and the hiring team. Based on these ideas for an „ideal process“ Airbnb made the communication process with applicants more high touch (applicants get more updates, and aren’t wondering when the company will respond). When applicants first apply, they receive a warm acknowledgement message via email. The email „outlines next steps and suggests what candidates could do in the interim (watch company culture videos, read our FAQs, and more).“ Airbnb started offering rejected applicants a chance to get feedback on the phone, which helps applicants stay positive toward the company, even if they didn’t get a job. The result? The company has more people applying a second time around, but with more experience and understanding of which roles would be right for them. It’s as if the recruiter is offering an olive branch, or playing the role of a coach or therapist.

The role of the recruiter is no longer just to find talent. It is to understand and empathize with their applicants, and then help make their experience better.

4. The Talent Guru

Exemplar: HR Manager
In 2009, Netflix published its seminal culture deck. Ostensibly an internal-only document that was slipped out to Slideshare, it immediately drew massive attention from the business world. The person behind this deck was former chief talent officer Patty McCord. McCord was willing to question all the old-school rules of traditional HR. In 2014, Harvard Business Review published McCord’s approach to „reinventing“ human resources. McCord helped Netflix attract top talent by coming up with a new approach: „Hire, reward, and tolerate only fully formed adults.“ Netflix believes the best thing they can do for employees is hire only „A“ players to work alongside them. Excellent colleagues trump everything else.

McCord let go of people whose skills no longer fit with the company. To keep their „A“ players happy, she instituted policies that provided freedom, responsibility, and excellent benefits that are flexible around employees’ needs. Instead of creating benefits packages based on HR rules and policies, McCord created benefits packages based on the company’s values and employees‘ core motivations.

The role of the chief talent officer is no longer to blindly push through outdated HR policies. Instead, talent gurus must reinvent the company’s policies to match the company’s cultural values and employees‘ personal values. Most importantly, talent gurus create the narrative that defines how a company aligns its actions (the what) with its values (the how).

5. The Dean

Exemplar: Learning and Developing Leader
Here’s how Randy Nelson describes himself on his LinkedIn page: „I work with organizations to make the best use of the people, wisdom, and skills they already have, want to attract, and need to develop. I help build amplifiers out of groups, using appropriate and dynamic mixtures of training and education, traditional skills, and innovative technology, flexible programs, and high standards. In addition to increased productivity and effectiveness, hijinks and shenanigans sometimes result.“

Nelson was the dean of Pixar University for 12 years, and now he is the director of Apple University. Nelson’s role is creating professional development programs that not only train employees but actually help educate employees. At Pixar, he conceived of a program that lets employees choose from 14 classes per week, including ballet, improv, drawing, and painting skills, computer programming, belly dancing, and color theory. This keeps Pixar’s talent learning and growing, thus making better films.

Pixar president Ed Catmull writes in his book, Creativity, Inc., that the magic of Pixar University „wasn’t that the class material directly enhanced our employees’ job performance. Instead, there was something about an apprentice lighting technician sitting alongside an experienced animator, who in turn was sitting next to someone who worked in legal or accounting or security—that proved immensely valuable. In the classroom setting, people interacted in a way they didn’t in the workplace. They felt free to be goofy, relaxed, open, vulnerable. Hierarchy did not apply, and as a result, communication thrived. Simply by providing an excuse for us all to toil side by side, humbled by the challenge of sketching a self-portrait or writing computer code or taming a lump of clay, Pixar University changed the culture for the better.“

Deans can play the role of fostering collaboration and creativity. They can help employees regain the mindset of being students again. When we’re learning, we retain a sense of possibility— and that sense of possibility is integral to Pixar’s whimsical success.

6. The Storyteller

Exemplar: Collective Voice of Individual Storytellers
How does Ideo attract talent and clients? Ideo has widely shared stories about the firm’s „special sauce“—its processes, rituals, and values. Ideo’s leaders have published a dozen books, several sets of tools, and countless videos and articles about what it’s like to work at Ideo. You might think that by sharing its proprietary methods Ideo could lose business. Who is to say that another consulting firm won’t just copy what Ideo is doing?

In reality, publishing this information has only attracted more talent and more clients to Ideo. In fact, most of Ideo’s talent and clients come to Ideo, rather than Ideo seeking them out. The company has a very small recruiting budget, and only has a few recruiters (for a firm of 700 people, this is unusual). Instead of constantly attending recruiting fairs, Ideo aims to reach potential talent through stories. Ideo’s currency is in stories. Thus, it understands the tremendous value of having more than just one set of individuals sharing stories. Ideo encourages all employees to be storytellers.

Stories humanize companies. The role of the storyteller is to share his or her company’s inner personality and narrative with the broader world. At Ideo, there is room for many different voices, all sharing their own personal story as it relates to Ideo’s larger narrative. Ideo’s most well-known stories include books by Ideo founder David Kelley and his brother, Tom Kelley, CEO Tim Brown, and partner Jane Fulton Suri. But many other Ideo authors tell stories through videos, articles, case studies, and podcasts, including Fred Dust, David Aycan, Diego Rodriguez, Paul Bennett, Sina Mossayeb, Joe Brown, Roshi Givechi, Ingrid Fetell Lee, Ashlea Powell, and Duane Bray, to name a few. Each story has helped clarify and exemplify Ideo’s collective culture, mindsets, and values.

7. The Questioner

Exemplar: The Diversity Lead
A huge part of a company’s organizational culture is its hiring practices. Trying to increase diversity is like trying to change culture: Both are much harder to do when a company has become a midsize or large company. If a company is intentional about its culture and diversity when it’s small, the value of diversity will be baked into the company’s DNA.

Enter Slack: a company that started thinking about diversity when it was only two years old. Slack is a workplace communication and messaging app used by organizations like the New York Times, NASA, Airbnb, Buzzfeed, and Spotify. Slack was cofounded by four white men, but CEO Stewart Butterfield made diversity a priority once the company reached 40 employees. Slack was growing quickly, and they needed to hire quickly. When companies need to hire quickly, there is a tendency to hire people who come from employee networks, which leads to hiring people who are similar to current employees.

Slack’s vice president for people and policy, Anne Toth, is trying to break that cycle. She released a diversity report, which is unusual for such a young company. At the time of the release in September 2015, the company only had 250 employees. Its first strategy for breaking the cycle is to continuously look at its diversity hiring numbers and then make immediate adjustments, rather than waiting until the end of the year. According to PBS, Toth asks questions like, „Are we promoting women and people of color at the same rate? Are we retaining them at the same rate? Are we paying them equitably? Are they as engaged as other employees across the board?“

Slack’s second strategy is to change the types of questions interviewers ask candidates. Slack has stopped asking questions that produce answers that cannot be objectively evaluated. For example, one problematic question is, „What do you do for fun?“ What a candidate does for fun isn’t relevant to that candidate’s ability to do work. Not only is this question not helpful for an interview, but it can actually lead to unconscious bias.


The richness of these personas is that anyone can adopt them, regardless of specific job function. Any of these approaches would benefit almost any role or organization. For example, applying a gardening approach is a useful mindset that extends beyond founders; many other roles can help build a narrative around how the company puts its values into practice.

What are the takeaway lessons that we can learn from all of these roles, regardless of your own role? One idea is to look for ways to take on one of these faces for an activity, a project, or just a day. Alternatively you can look for ways to engage with your organization at a larger level with a new lens. At Ideo, a group of creative employees came together as „gardeners“ to create a series of videos designed to bring to life each of Ideo’s values. These videos helped plant seeds for new employees to learn about Ideo’s culture in a cinematic way. Regardless of your role, you can play a role in shaping your company’s culture. Anyone can adopt the lens of a dean, questioner, or storyteller in some capacity.

Why do these new faces matter? Workplace culture is becoming increasingly important, and increasingly shaped by a wider group of employees. Steelcase explains that „the shift toward culture may be gaining prominence as small businesses struggle to compete for talent with larger counterparts in the areas of plump paychecks and generous benefits packages. They’re beginning to recognize culture for the trump card it is, particularly with millennials used to interactive, stimulating environments.“ According to a recent study from Workforce Institute and WorkplaceTrends, employees feel they have more influence over culture than ever before (although managers and HR professionals disagree). Millennials, in particular, feel that the power to shape culture lies not with the executive leaders or the HR team but with the people doing the work. It’s clear that in order to attract, retain, and engage the modern workforce, companies need to focus on culture. Thankfully, there are an expanding number of roles and people who can help with this.

We’re curious: What other faces of culture does your organization have? How are your employees adopting these new roles and faces?


Elon Musk: we’ll ultimately be in the position where almost everyone will be able to afford a Tesla

The Internet is still waking up from the madness that was the Model 3 unveiling, but Tesla CEO is – as always – looking towards the future. While in Norway recently, Musk talked about Tesla’s upcoming EV. No, not the 3, but the even cheaper and smaller electric vehicle that will be coming out after the 3 debuts. Musk said the following, talking about the Model 3 (to start):

I’m super excited about being able to produce a car that most people can afford. And there will be future cars that are even more affordable down the road, but, with something like the Model 3, it’s designed such that roughly half of the people will be able to afford the car. Then, with fourth generation and smaller cars, we’ll ultimately be in the position where almost everyone will be able to afford the car.

You can hear it for yourself at about 12 minutes into the video above. It’s worth watching the whole thing, because Musk also mentions fossil fuel subsidies, that mysterious mass transit solution thing and
dying on Mars.

What’s most interesting about Musk’s comments about Tesla’s future is that he may not be around to steer the ship when this next EV arrives. Musk has said that he will remain the Tesla CEO at least until the Model 3 production has ramped up, but after that, who knows. As he said a year and a half ago, „I will never leave Tesla forever, but I may not be CEO forever. Nobody should be CEO forever.“

Silicon Valley legend Bill Campbell – leadership advice

Bill Campbell, widely known in Silicon Valley as „The Coach,“ died on Tuesday after a long battle with cancer.

Before entering the tech industry, Campbell served as head football coach at Columbia University and maintained a pep-talk approach when dealing with executives. Campbell’s illustrious career included a stint as an Apple executive and board member, and he served as CEO and chairman of Intuit.

He became not only an adviser to but also a close friend of power players like late Apple CEO Steve Jobs, Google cofounders Larry Page and Sergey Brin, and Twitter and Square CEO Jack Dorsey.

As Kleiner Perkins Caufield & Byers partner Randy Komisar said in an episode of his „Ventured“ podcast, Campbell’s executive-coaching style was akin to that of a psychiatrist, asking the right questions to steer his subjects to their own conclusions rather than giving mandates.

Campbell preferred to stay out of the spotlight, but we’ve collected some of his best leadership advice from relatively recent interviews.

These lessons shed light on why he was such a valuable coach to have.

Know that great products drive success. Everything else is a supporting function

Campbell was adamant that the greatest marketing in the world was useless if it didn’t advertise an excellent product. It’s why he was a fierce advocate for granting engineers creative freedom.

Source: Intuit

Trust your managers, and make sure they trust their subordinates

At companies Campbell worked at, he would aim to eliminate tensions between product managers and engineers by building a culture of trust, where managers knew that engineers were in the best position to find a solution and engineers knew managers were in the best position to guide them to that goal.

Source: Intuit

Experiment, but never at the cost of your existing business

Campbell was close friends with Ron Johnson, the Apple executive whose attempt at relaunching J.C. Penney in 2012-2013 failed miserably because, as Campbell said, he tried starting from scratch.

Source: Intuit

Spend your days doing, not planning

„Writing a list of things and checking dates and all that, that’s a bunch of bulls—, you can take the last 10 minutes of your day and do that,“ he said.

The vast majority of your day as a leader should be spent working with your team.

Source: Intuit

Your company must have unifying product principles

Even while evolving, you must ensure that your company retains its unique identity by sticking to fundamental creative principles.

„That’s what Apple does brilliantly,“ Campbell said. „Everyone knows where the design principles are trending.“

Source: Intuit

It is imperative that you stop infighting as soon as it arises

Campbell said that internal warfare „brings companies to their knees“ and that it is the CEO’s job to end tensions immediately. He said that Apple under CEO John Sculley, before Steve Jobs was brought back in to lead his company, was marked by turf wars and power grabs.

„The political problem just goes down through the organization,“ Campbell said. „Everybody’s paralyzed by the fighting that top executives have, all the time.“

He recommended that CEOs bring their warring parties into the same room and give them a deadline for settling their disputes, or else they would step in and make the decision for them.

Source: Intuit

Determine cultural values from the outset and then model them

Values allow employees to hold each other accountable, and the CEO must embody the values, or else no one will follow them.

Source: „Venture“ podcast

Evaluate your managers by what their employees think of them

Regularly survey your employees to ensure that their managers are upholding the company’s values and guiding, rather than interfering with, their work.

Source: „Venture“ podcast

Maintain a culture of respect

Campbell placed prime importance on respect when leading or consulting with a company.

For example, he said, „Larry Page takes great, great pride in making sure that [executives he hires] are humble about what they do.“

If someone continuously disrespects their colleagues to the point where they feel their opinions aren’t heard, then that person needs to be let go.

Source: „Venture“ podcast

Be honest with your team

The reason why Campbell was not only greatly respected in the Valley but also deeply admired on a personal level was because he spent time building relationships with those he worked with.

To him, the best leaders are straightforward with their praise and criticism, so that there are no illusions holding someone back from success.

Source: Fortune

How to Successfully Manage Teams

Managing a team is a rewarding task that offers unique benefits and challenges. What follows are six ways to ensure you are successful at managing any kind of team.

Careful Selection

If possible, screen candidates based on a fair and standard format. This could be an entrance interview with basic questions about motivation, work styles and core competencies. Even if there are no choices, an initial interview with existing team members will allow everyone to understand preferences and backgrounds, which will help new team members better fit in and adapt to the subculture.

Proper Training

Some leaders have unrealistic expectations about employee performance and learning capacity. This means they expect employees to instantly become proficient with complex tasks and technologies that may take weeks to master. Regardless of competency, employees must be given time to process information and ask questions. This is a great way to introduce new ideas and to challenge existing, inefficient processes.

Team leaders can continue their professional development by getting an advanced degree, like a master’s degree that pertains to their career field. No matter what your field, a master’s degree can help you gain the necessary leadership experience to make a difference.

Learn Project Management

Every supervisor and team leader should be familiar with the basic principles of project management. However, they must also be prepared to train and help team members master these project management techniques and systems. One good solution is to use popular project management software. This will help team leaders better manage assignments and scheduling, as well as increase productivity and accountability.

Empower Employees

Employees need to be empowered to perform their jobs without direct supervision. This will reduce the supervisors’ work load, but can only occur when there are formal procedures and parameters that guide employees through the decision making process. Avoid micromanaging and setting up employees to fail through setting unrealistic standards.

Set Goals

Some team leaders only focus on daily operations, so they lose focus on the big picture. This can be remedied through quarterly goals collectively created by team members. These goals should be reviewed during every meeting  to realign focus and energy. Be sure to offer team members rewards for reaching the goals.

Set an Open Door Policy

New employees naturally make more mistakes if they are uncomfortable asking questions or for feedback. Team leaders can continue their professional development by getting a degree like a Master’s of Civil Engineering. No matter what your field, a master’s degree can help you gain the necessary leadership experience to make a difference.

Finally, build a team subculture that welcomes change and innovation. If you want your team to be successful, you need to take steps to better yourself and improve your skills too. These tips can help you be a more effective leader.

6 Tips to Successfully Manage Teams

The brightest minds in AI research – Machine Learning

In AI research,  brightest minds aren’t driven by the next product cycle or profit margin – They want to make AI better, and making AI better doesn’t happen when you keep your latest findings to yourself.

Inside OpenAI, Elon Musk’s Wild Plan to Set Artificial Intelligence Free


THE FRIDAY AFTERNOON news dump, a grand tradition observed by politicians and capitalists alike, is usually supposed to hide bad news. So it was a little weird that Elon Musk, founder of electric car maker Tesla, and Sam Altman, president of famed tech incubator Y Combinator, unveiled their new artificial intelligence company at the tail end of a weeklong AI conference in Montreal this past December.

But there was a reason they revealed OpenAI at that late hour. It wasn’t that no one was looking. It was that everyone was looking. When some of Silicon Valley’s most powerful companies caught wind of the project, they began offering tremendous amounts of money to OpenAI’s freshly assembled cadre of artificial intelligence researchers, intent on keeping these big thinkers for themselves. The last-minute offers—some made at the conference itself—were large enough to force Musk and Altman to delay the announcement of the new startup. “The amount of money was borderline crazy,” says Wojciech Zaremba, a researcher who was joining OpenAI after internships at both Google and Facebook and was among those who received big offers at the eleventh hour.

How many dollars is “borderline crazy”? Two years ago, as the market for the latest machine learning technology really started to heat up, Microsoft Research vice president Peter Lee said that the cost of a top AI researcher had eclipsed the cost of a top quarterback prospect in the National Football League—and he meant under regular circumstances, not when two of the most famous entrepreneurs in Silicon Valley were trying to poach your top talent. Zaremba says that as OpenAI was coming together, he was offered two or three times his market value.

OpenAI didn’t match those offers. But it offered something else: the chance to explore research aimed solely at the future instead of products and quarterly earnings, and to eventually share most—if not all—of this research with anyone who wants it. That’s right: Musk, Altman, and company aim to give away what may become the 21st century’s most transformative technology—and give it away for free.

Zaremba says those borderline crazy offers actually turned him off—despite his enormous respect for companies like Google and Facebook. He felt like the money was at least as much of an effort to prevent the creation of OpenAI as a play to win his services, and it pushed him even further towards the startup’s magnanimous mission. “I realized,” Zaremba says, “that OpenAI was the best place to be.”

That’s the irony at the heart of this story: even as the world’s biggest tech companies try to hold onto their researchers with the same fierceness that NFL teams try to hold onto their star quarterbacks, the researchers themselves just want to share. In the rarefied world of AI research, the brightest minds aren’t driven by—or at least not only by—the next product cycle or profit margin. They want to make AI better, and making AI better doesn’t happen when you keep your latest findings to yourself.

OpenAI is a billion-dollar effort to push AI as far as it will go.
This morning, OpenAI will release its first batch of AI software, a toolkit for building artificially intelligent systems by way of a technology called “reinforcement learning”—one of the key technologies that, among other things, drove the creation of AlphaGo, the Google AI that shocked the world by mastering the ancient game of Go. With this toolkit, you can build systems that simulate a new breed of robot, play Atari games, and, yes, master the game of Go.

But game-playing is just the beginning. OpenAI is a billion-dollar effort to push AI as far as it will go. In both how the company came together and what it plans to do, you can see the next great wave of innovation forming. We’re a long way from knowing whether OpenAI itself becomes the main agent for that change. But the forces that drove the creation of this rather unusual startup show that the new breed of AI will not only remake technology, but remake the way we build technology.

AI Everywhere
Silicon Valley is not exactly averse to hyperbole. It’s always wise to meet bold-sounding claims with skepticism. But in the field of AI, the change is real. Inside places like Google and Facebook, a technology called deep learning is already helping Internet services identify faces in photos, recognize commands spoken into smartphones, and respond to Internet search queries. And this same technology can drive so many other tasks of the future. It can help machines understand natural language—the natural way that we humans talk and write. It can create a new breed of robot, giving automatons the power to not only perform tasks but learn them on the fly. And some believe it can eventually give machines something close to common sense—the ability to truly think like a human.

But along with such promise comes deep anxiety. Musk and Altman worry that if people can build AI that can do great things, then they can build AI that can do awful things, too. They’re not alone in their fear of robot overlords, but perhaps counterintuitively, Musk and Altman also think that the best way to battle malicious AI is not to restrict access to artificial intelligence but expand it. That’s part of what has attracted a team of young, hyper-intelligent idealists to their new project.

OpenAI began one evening last summer in a private room at Silicon Valley’s Rosewood Hotel—an upscale, urban, ranch-style hotel that sits, literally, at the center of the venture capital world along Sand Hill Road in Menlo Park, California. Elon Musk was having dinner with Ilya Sutskever, who was then working on the Google Brain, the company’s sweeping effort to build deep neural networks—artificially intelligent systems that can learn to perform tasks by analyzing massive amounts of digital data, including everything from recognizing photos to writing email messages to, well, carrying on a conversation. Sutskever was one of the top thinkers on the project. But even bigger ideas were in play.

Sam Altman, whose Y Combinator helped bootstrap companies like Airbnb, Dropbox, and Coinbase, had brokered the meeting, bringing together several AI researchers and a young but experienced company builder named Greg Brockman, previously the chief technology officer at high-profile Silicon Valley digital payments startup called Stripe, another Y Combinator company. It was an eclectic group. But they all shared a goal: to create a new kind of AI lab, one that would operate outside the control not only of Google, but of anyone else. “The best thing that I could imagine doing,” Brockman says, “was moving humanity closer to building real AI in a safe way.”

Musk is one of the loudest voices warning that we humans could one day lose control of systems powerful enough to learn on their own.
Musk was there because he’s an old friend of Altman’s—and because AI is crucial to the future of his various businesses and, well, the future as a whole. Tesla needs AI for its inevitable self-driving cars. SpaceX, Musk’s other company, will need it to put people in space and keep them alive once they’re there. But Musk is also one of the loudest voices warning that we humans could one day lose control of systems powerful enough to learn on their own.

The trouble was: so many of the people most qualified to solve all those problems were already working for Google (and Facebook and Microsoft and Baidu and Twitter). And no one at the dinner was quite sure that these thinkers could be lured to a new startup, even if Musk and Altman were behind it. But one key player was at least open to the idea of jumping ship. “I felt there were risks involved,” Sutskever says. “But I also felt it would be a very interesting thing to try.”

Breaking the Cycle
Emboldened by the conversation with Musk, Altman, and others at the Rosewood, Brockman soon resolved to build the lab they all envisioned. Taking on the project full-time, he approached Yoshua Bengio, a computer scientist at the University of Montreal and one of founding fathers of the deep learning movement. The field’s other two pioneers—Geoff Hinton and Yann LeCun—are now at Google and Facebook, respectively, but Bengio is committed to life in the world of academia, largely outside the aims of industry. He drew up a list of the best researchers in the field, and over the next several weeks, Brockman reached out to as many on the list as he could, along with several others.

Many of these researchers liked the idea, but they were also wary of making the leap. In an effort to break the cycle, Brockman picked the ten researchers he wanted the most and invited them to spend a Saturday getting wined, dined, and cajoled at a winery in Napa Valley. For Brockman, even the drive into Napa served as a catalyst for the project. “An underrated way to bring people together are these times where there is no way to speed up getting to where you’re going,” he says. “You have to get there, and you have to talk.” And once they reached the wine country, that vibe remained. “It was one of those days where you could tell the chemistry was there,” Brockman says. Or as Sutskever puts it: “the wine was secondary to the talk.”

By the end of the day, Brockman asked all ten researchers to join the lab, and he gave them three weeks to think about it. By the deadline, nine of them were in. And they stayed in, despite those big offers from the giants of Silicon Valley. “They did make it very compelling for me to stay, so it wasn’t an easy decision,” Sutskever says of Google, his former employer. “But in the end, I decided to go with OpenAI, partly of because of the very strong group of people and, to a very large extent, because of its mission.”

The deep learning movement began with academics. It’s only recently that companies like Google and Facebook and Microsoft have pushed into the field, as advances in raw computing power have made deep neural networks a reality, not just a theoretical possibility. People like Hinton and LeCun left academia for Google and Facebook because of the enormous resources inside these companies. But they remain intent on collaborating with other thinkers. Indeed, as LeCun explains, deep learning research requires this free flow of ideas. “When you do research in secret,” he says, “you fall behind.”

As a result, big companies now share a lot of their AI research. That’s a real change, especially for Google, which has long kept the tech at the heart of its online empire secret. Recently, Google open sourced the software engine that drives its neural networks. But it still retains the inside track in the race to the future. Brockman, Altman, and Musk aim to push the notion of openness further still, saying they don’t want one or two large corporations controlling the future of artificial intelligence.

The Limits of Openness
All of which sounds great. But for all of OpenAI’s idealism, the researchers may find themselves facing some of the same compromises they had to make at their old jobs. Openness has its limits. And the long-term vision for AI isn’t the only interest in play. OpenAI is not a charity. Musk’s companies that could benefit greatly the startup’s work, and so could many of the companies backed by Altman’s Y Combinator. “There are certainly some competing objectives,” LeCun says. “It’s a non-profit, but then there is a very close link with Y Combinator. And people are paid as if they are working in the industry.”

According to Brockman, the lab doesn’t pay the same astronomical salaries that AI researchers are now getting at places like Google and Facebook. But he says the lab does want to “pay them well,” and it’s offering to compensate researchers with stock options, first in Y Combinator and perhaps later in SpaceX (which, unlike Tesla, is still a private company).

Brockman insists that OpenAI won’t give special treatment to its sister companies.
Nonetheless, Brockman insists that OpenAI won’t give special treatment to its sister companies. OpenAI is a research outfit, he says, not a consulting firm. But when pressed, he acknowledges that OpenAI’s idealistic vision has its limits. The company may not open source everything it produces, though it will aim to share most of its research eventually, either through research papers or Internet services. “Doing all your research in the open is not necessarily the best way to go. You want to nurture an idea, see where it goes, and then publish it,” Brockman says. “We will produce lot of open source code. But we will also have a lot of stuff that we are not quite ready to release.”

Both Sutskever and Brockman also add that OpenAI could go so far as to patent some of its work. “We won’t patent anything in the near term,” Brockman says. “But we’re open to changing tactics in the long term, if we find it’s the best thing for the world.” For instance, he says, OpenAI could engage in pre-emptive patenting, a tactic that seeks to prevent others from securing patents.

But to some, patents suggest a profit motive—or at least a weaker commitment to open source than OpenAI’s founders have espoused. “That’s what the patent system is about,” says Oren Etzioni, head of the Allen Institute for Artificial Intelligence. “This makes me wonder where they’re really going.”

The Super-Intelligence Problem
When Musk and Altman unveiled OpenAI, they also painted the project as a way to neutralize the threat of a malicious artificial super-intelligence. Of course, that super-intelligence could arise out of the tech OpenAI creates, but they insist that any threat would be mitigated because the technology would be usable by everyone. “We think its far more likely that many, many AIs will work to stop the occasional bad actors,” Altman says.

But not everyone in the field buys this. Nick Bostrom, the Oxford philosopher who, like Musk, has warned against the dangers of AI, points out that if you share research without restriction, bad actors could grab it before anyone has ensured that it’s safe. “If you have a button that could do bad things to the world,” Bostrom says, “you don’t want to give it to everyone.” If, on the other hand, OpenAI decides to hold back research to keep it from the bad guys, Bostrom wonders how it’s different from a Google or a Facebook.

If you share research without restriction, bad actors could grab it before anyone has ensured that it’s safe.
He does say that the not-for-profit status of OpenAI could change things—though not necessarily. The real power of the project, he says, is that it can indeed provide a check for the likes of Google and Facebook. “It can reduce the probability that super-intelligence would be monopolized,” he says. “It can remove one possible reason why some entity or group would have radically better AI than everyone else.”

But as the philosopher explains in a new paper, the primary effect of an outfit like OpenAI—an outfit intent on freely sharing its work—is that it accelerates the progress of artificial intelligence, at least in the short term. And it may speed progress in the long term as well, provided that it, for altruistic reasons, “opts for a higher level of openness than would be commercially optimal.”

“It might still be plausible that a philanthropically motivated R&D funder would speed progress more by pursuing open science,” he says.

Like Xerox PARC
In early January, Brockman’s nine AI researchers met up at his apartment in San Francisco’s Mission District. The project was so new that they didn’t even have white boards. (Can you imagine?) They bought a few that day and got down to work.

Brockman says OpenAI will begin by exploring reinforcement learning, a way for machines to learn tasks by repeating them over and over again and tracking which methods produce the best results. But the other primary goal is what’s called “unsupervised learning”—creating machines that can truly learn on their own, without a human hand to guide them. Today, deep learning is driven by carefully labeled data. If you want to teach a neural network to recognize cat photos, you must feed it a certain number of examples—and these examples must be labeled as cat photos. The learning is supervised by human labelers. But like many others researchers, OpenAI aims to create neural nets that can learn without carefully labeled data.

“If you have really good unsupervised learning, machines would be able to learn from all this knowledge on the Internet—just like humans learn by looking around—or reading books,” Brockman says.

He envisions OpenAI as the modern incarnation of Xerox PARC, the tech research lab that thrived in the 1970s. Just as PARC’s largely open and unfettered research gave rise to everything from the graphical user interface to the laser printer to object-oriented programing, Brockman and crew seek to delve even deeper into what we once considered science fiction. PARC was owned by, yes, Xerox, but it fed so many other companies, most notably Apple, because people like Steve Jobs were privy to its research. At OpenAI, Brockman wants to make everyone privy to its research.

This month, hoping to push this dynamic as far as it will go, Brockman and company snagged several other notable researchers, including Ian Goodfellow, another former senior researcher on the Google Brain team. “The thing that was really special about PARC is that they got a bunch of smart people together and let them go where they want,” Brockman says. “You want a shared vision, without central control.”

Giving up control is the essence of the open source ideal. If enough people apply themselves to a collective goal, the end result will trounce anything you concoct in secret. But if AI becomes as powerful as promised, the equation changes. We’ll have to ensure that new AIs adhere to the same egalitarian ideals that led to their creation in the first place. Musk, Altman, and Brockman are placing their faith in the wisdom of the crowd. But if they’re right, one day that crowd won’t be entirely human.

Tesla’s Model 3 Reservations Rise to 400,000

Eager Tesla customers continue to reserve the Model 3, despite the ballooning wait times.

Reservations for Tesla’s recently unveiled, mainstream electric car, the Model 3, continue to climb.

According to a speech from Tesla’s Vice President of Business Development, Diarmuid O’Connell, this week, reservations for the car are now approaching 400,000.

That’s an eye-popping figure for an electric car that’s only been available to reserve for about two weeks and won’t start shipping until the end of 2017. Many of those reservations were made before the car was even unveiled on March 31. Now Tesla needs to figure out how to make and deliver those cars on time and budget.

Many of the later orders of the Model 3 likely won’t be fulfilled until 2019, or even into 2020 (four years from now).That’s assuming Tesla will remain on track to start shipping the car at the end of next year, too.

A driveable prototype of Tesla's Model 3.
A driveable prototype of Tesla’s Model 3. Katie Fehrenbacher/Fortune

To get that volume of cars made and delivered on time, Tesla TSLA -2.56% could have to change the way it makes its cars considerably. Tesla has only delivered a little over 100,000 cars in total over its lifetime. During O’Connell’s speech at a conference in Amsterdam, he said the rapid reservation rate gives Tesla the “visibility” and “confidence” into what it would take to build the car.

Tesla CEO Elon Musk tweeted the day after revealing the Model 3 for the first time (when the car had close to 200,000 reservations) that Tesla is “definitely going to need to rethink production planning.” Tesla will likely have to expand production at both its Fremont, Calif. factory more quickly than expected, and it will soon have to start producing a greater number of batteries at its massive battery factory still under construction outside of Reno, Nevada.

O’Connell said that Tesla is “looking at ways to amplify early production.” The company is investigating possible ways to scale up initial investments and ramp up more quickly than previously anticipated. Tesla plans to use lessons learned from the difficulties it had with manufacturing the Model X, Tesla’s SUV electric car.

That car was delayed for years, and it faced slow production at the end of 2015 and into early 2016. The company has admitted hubris for the Model X in trying to fit in too many complex features into the first version of the car.

According to estimates from Cairn Energy Research Advisors, Tesla could ship a little over 400,000 of its Model 3 cars by the end of 2020. But before 2020, production of Model 3 could likely be constrained. For example, Tesla could ship 12,200 Model 3 cars in its first production year in 2017, and another 64,660 Model 3 cars in 2018.

During O’Connell’s speech, he boasted reservations for the Model 3 “have exceeded all of our expectations as far as the rate at which we received reservations,” further describing the Model 3 as “the car for which the company was really set up to build.”

O’Connell suggested that the great demand for the Model 3 delivers a message to the rest of the auto industry that there is “incredible demand” for great electric vehicles out there. In addition, the massive demand refutes the point that other automakers have made that no one wants electric cars, he argued.

To make a reservation for a Model 3 car, Tesla customers only have to put down a fully refundable deposit of $1,000. So it’s unclear how many of the reservation holders would turn into Model 3 buyers.

If all 400,000 reservation holders bought $35,000 Model 3 cars, Tesla would have booked $14 billion in orders. That’s an unprecedented sum—not just in the auto industry, but for a launch of a product in general.


Microsoft Research, Seeing AI

The Real Reason Microsoft Is Building So Many Computer Vision Apps

Turns out Microsoft isn’t as interested in rating mustaches or guessing ages as it is helping the visually impaired navigate the world.

For the past few years, Microsoft has been steadily releasing goofy little apps that use neural networks to perform tricks ranging from guessing your age and rating your mustache to describing photographs (often comically) and even telling you what kind of dog you look like.

But why? Entertaining though these apps are, they all seemed a little random—until a couple of weeks ago at Build 2016, when Microsoft revealed that these experiments are more than just a sum of their parts. In fact, they represent stepping stones on the road leading to Seeing AI, an augmented-reality project for the visually impaired that aims to give the blind the next best thing to sight: information.

Built by Microsoft Research, Seeing AI is an app that lives either on smartphones or Pivothead-brand smart glasses. It takes all of the tricks Microsoft developed using those „goofy“ machine learning apps and combines them into a digital Swiss Army knife for the blind. By helping the visually impaired user line up and snap a photograph using their device, the app can tell them what they’re „looking“ at; it can read menus or signs, tell you how old the person you’re talking to is, or even describe what’s happening right in front of you—say, that you’re in a park, watching a golden retriever catch an orange frisbee. Presumably, it has some excellent mustache detection skills, too.

This isn’t the first app for the blind,“ admits project lead Anirudh Koul. „But those apps are extremely limited.“ One app might be dedicated just to helping you know what color you’re looking at. Another might read menus and signs, or tell you what box you’re holding in the grocery store based on the barcode. There are even photography apps for the blind.

But the problem with all these apps is fragmentation. For a blind person, using them seamlessly is like having to screw in a different set of eyes every time you want to read a paper or identify a color. Seeing AI can do all of the above—and more—all within the same app.

Of course, having so much functionality introduces its own design challenges. According to Margaret Mitchell, Seeing AI’s vision-to-language guru, context is key when trying to decode visual information to text. „If you’re outside, for example, you don’t want it to describe the grass as a green carpet anymore than you want it to describe a blue ceiling as a clear sky when you’re indoors,“ she says. It’s also challenging to know how much information Seeing AI should give users at any given moment. Sometimes, it might be more useful to list what’s around a user, while other times, a scene-description is better, so knowing when to automatically switch between modes becomes important.

These are just some of the problems the Seeing AI team is trying to work out before their software becomes a consumer-facing product. But already, Seeing AI’s software is proving indispensable to Microsoft software engineer Saqib Shaikh, who lost his sight at the age of seven. He has helped the Seeing AI team test and tweak its software, as well as identify features that sighted people might not think of as useful, but which the visually impaired really need. For example: finding an empty seat in a restaurant. „His guidance has been amazing,“ says Mitchell. „He can exactly identify what we should be returning and why.“

Although apps that use its machine-learning algorithms are routinely released by Microsoft Garage, neither Koul nor Mitchell could say when Seeing AI would be available for everyone to download. They only say it is a „research project under development.“ But this isn’t just some silly web toy. When released, Seeing AI will be an app that can fundamentally change a person’s life, while continuing the grand tradition of accessibility pushing design forward in exciting directions.

Apple Pursues New Search Features for a Crowded App Store

Apple Inc. has constructed a secret team to explore changes to the App Store, including a new strategy for charging developers to have their apps more prominently displayed, according to people familiar with the plans.

Among the ideas being pursued, Apple is considering paid search, a Google-like model in which companies would pay to have their app shown at the top of search results based on what a customer is seeking. For instance, a game developer could pay to have its program shown when somebody looks for “football game,” “word puzzle” or “blackjack.”

Paid search, which Google turned into a multibillion-dollar business, would give Apple a new way to make money from the App Store. The growing marketing budgets of app developers such as “Clash of Clans” maker Supercell Oy have proven to be lucrative sources of revenue for Internet companies, including Facebook Inc. and Twitter Inc.

About 100 employees are working on the project, including many engineers from Apple’s advertising group iAd that’s being scaled back, said the people, who asked not to be identified because the plans are private. The effort is being spearheaded by Apple Vice President Todd Teresi, who led iAd.

If Apple goes through with the idea, “it’s going to be huge,” said Krishna Subramanian, the co-founder of Captiv8, which helps brands market using social media. “Anything that you can do to help drive more awareness to your app, to get organic downloads, is critical.”

In addition to paid search, the team is trying to improve the way customers browse in the App Store. The new search team hasn’t been working long and it’s unclear when any new changes will be introduced.

Apple declined to comment.

The App Store is a vital part of the Cupertino, California-based company’s business. The more software that customers download, the more likely they are to keep buying Apple’s products rather than switch to a phone or tablet made by another manufacturer. The store’s success was a key reason the iPhone and iPad became so popular with consumers and is central to Chief Executive Officer Tim Cook’s strategy of getting more sales from online services. Apple currently gets about 30 percent of each app sale, which is part of the $20 billion in services revenue the company generated last fiscal year.

The attempt to improve search is a sign that Apple knows the App Store has become harder for customers to navigate. First introduced in 2008, the store now has more than 1.5 million apps, with customers downloading more than 100 billion since its debut. App developers have for years urged the iPhone maker to add fresh discovery tools for users, arguing the crowded market makes it increasingly hard for people to discover new apps or build sustainable businesses.

Apple has taken steps to improve search in the past. In 2012, Apple acquired an app search-engine company named Chomp to help address the problem. In December, Cook changed the leadership of the App Store. He moved responsibility to Phil Schiller, Apple’s senior vice president of worldwide marketing, and away from Eddy Cue, the senior vice president for Internet, software and services, whose portfolio has expanded as Apple has built out new online services such as Apple Pay and Apple Music.