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Mixtape podcast: Artificial intelligence and disability

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Welcome back to Mixtape, the TechCrunch podcast that looks at the human element that powers technology.

For this episode we spoke with Meredith Whittaker, co-founder of the AI Now Institute and Minderoo Research Professor at NYU; Mara Mills, associate professor of Media, Culture and Communication at NYU and co-director of the NYU Center for Disability Studies; and Sara Hendren, professor at Olin College of Engineering and author of the recently published What Can a Body Do: How We Meet the Built World.
It was a wide-ranging discussion about artificial intelligence and disability. Hendren kicked us off by exploring the distinction between the medical and social models of disability:

So in a medical model of disability, as articulated in disability studies, the idea is just that disability is a kind of condition or an impairment or something that’s going on with your body that takes it out of the normative average state of the body says something in your sensory makeup or mobility or whatever is impaired, and therefore, the disability kind of lives on the body itself. But in a social model of disability, it’s just an invitation to widen the aperture a little bit and include, not just the body itself and what it what it does or doesn’t do biologically. But also the interaction between that body and the normative shapes of the world.

When it comes to technology, Mills says, some companies work squarely in the realm of the medical model with the goal being a total cure rather than just accommodation, while other companies or technologies – and even inventors – will work more in the social model with the goal of transforming the world and create an accommodation. But despite this, she says, they still tend to have “fundamentally normative or mainstream ideas of function and participation rather than disability forward ideas.”

“The question with AI, and also just with old mechanical things like Brailers I would say, would be are we aiming to perceive the world in different ways, in blind ways, in minoritarian ways? Or is the goal of the technology, even if it’s about making a social, infrastructural change still about something standard or normative or seemingly typical? And that’s — there are very few technologies, probably for financial reasons, that are really going for the disability forward design.”

As Whittaker notes, AI by its nature is fundamentally normative.

“It draws conclusions from large sets of data, and that’s the world it sees, right? And it looks at what’s most average in this data and what’s an outlier. So it’s something that is consistently replicating these norms, right? If it’s trained on the data, and then it gets an impression from the world that doesn’t match the data it’s already seen, that impression is going to be an outlier. It won’t recognize that it won’t know how to treat that. Right. And there are a lot of complexities here. But I think, I think that’s something we have to keep in mind as sort of a nucleus of this technology, when we talk about its potential applications in and out of these sorts of capitalist incentives, like what is it capable of doing? What does it do? What does it act like? And can we think about it, you know, ever possibly in company encompassing the multifarious, you know, huge amounts of ways that disability manifests or doesn’t manifest.”

We talked about this and much much more on the latest episode of Mixtape, so you click play above and dig right in. And then subscribe wherever you listen to podcasts.

 

 

 

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

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Snowflake latest enterprise company to feel Wall Street’s wrath after good quarter

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Snowflake reported earnings this week, and the results look strong with revenue more than doubling year-over-year.

However, while the company’s fourth quarter revenue rose 117% to $190.5 million, it apparently wasn’t good enough for investors, who have sent the company’s stock tumbling since it reported Wednesday after the bell.

It was similar to the reaction that Salesforce received from Wall Street last week after it announced a positive earnings report. Snowflake’s stock closed down around 4% today, a recovery compared to its midday lows when it was off nearly 12%.

Why the declines? Wall Street’s reaction to earnings can lean more on what a company will do next more than its most recent results. But Snowflake’s guidance for its current quarter appeared strong as well, with a predicted $195 million to $200 million in revenue, numbers in line with analysts’ expectations.

Sounds good, right? Apparently being in line with analyst expectations isn’t good enough for investors for certain companies. You see, it didn’t exceed the stated expectations, so the results must be bad. I am not sure how meeting expectations is as good as a miss, but there you are.

It’s worth noting of course that tech stocks have taken a beating so far in 2021. And as my colleague Alex Wilhelm reported this morning, that trend only got worse this week. Consider that the tech-heavy Nasdaq is down 11.4% from its 52-week high, so perhaps investors are flogging everyone and Snowflake is merely caught up in the punishment.

Snowflake CEO Frank Slootman pointed out in the earnings call this week that Snowflake is well positioned, something proven by the fact that his company has removed the data limitations of on-prem infrastructure. The beauty of the cloud is limitless resources, and that forces the company to help customers manage consumption instead of usage, an evolution that works in Snowflake’s favor.

“The big change in paradigm is that historically in on-premise data centers, people have to manage capacity. And now they don’t manage capacity anymore, but they need to manage consumption. And that’s a new thing for — not for everybody but for most people — and people that are in the public cloud. I have gotten used to the notion of consumption obviously because it applies equally to the infrastructure clouds,” Slootman said in the earnings call.

Snowflake has to manage expectations, something that translated into a dozen customers paying $5 million or more per month to Snowflake. That’s a nice chunk of change by any measure. It’s also clear that while there is a clear tilt toward the cloud, the amount of data that has been moved there is still a small percentage of overall enterprise workloads, meaning there is lots of growth opportunity for Snowflake.

What’s more, Snowflake executives pointed out that there is a significant ramp up time for customers as they shift data into the Snowflake data lake, but before they push the consumption button. That means that as long as customers continue to move data onto Snowflake’s platform, they will pay more over time, even if it will take time for new clients to get started.

So why is Snowflake’s quarterly percentage growth not expanding? Well, as a company gets to the size of Snowflake, it gets harder to maintain those gaudy percentage growth numbers as the law of large numbers begins to kick in.

I’m not here to tell Wall Street investors how to do their job, anymore than I would expect them to tell me how to do mine. But when you look at the company’s overall financial picture, the amount of untapped cloud potential and the nature of Snowflake’s approach to billing, it’s hard not to be positive about this company’s outlook, regardless of the reaction of investors in the short term.

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A first look at Coursera’s S-1 filing

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After TechCrunch broke the news yesterday that Coursera was planning to file its S-1 today, the edtech company officially dropped the document Friday evening.

Coursera was last valued at $2.4 billion by the private markets, when it most recently raised a Series F round in October 2020 that was worth $130 million.

Coursera’s S-1 filing offers a glimpse into the finances of how an edtech company, accelerated by the pandemic, performed over the past year. It paints a picture of growth, albeit one that came at steep expense.

Revenue

In 2020, Coursera saw $293.5 million in revenue. That’s a roughly 59% increase from the year prior when the company recorded $184.4 million in top line. During that same period, Coursera posted a net loss of nearly $67 million, up 46% from the previous year’s $46.7 million net deficit.

Notably the company had roughly the same noncash, share-based compensation expenses in both years. Even if we allow the company to judge its profitability on an adjusted EBITDA basis, Coursera’s losses still rose from 2019 to 2020, expanding from $26.9 million to $39.8 million.

To understand the difference between net losses and adjusted losses it’s worth unpacking the EBITDA acronym. Standing for “earnings before interest, taxes, depreciation and amortization,” EBITDA strips out some nonoperating costs to give investors a possible better picture of the continuing health of a business, without getting caught up in accounting nuance. Adjusted EBITDA takes the concept one step further, also removing the noncash cost of share-based compensation, and in an even more cheeky move, in this case also deducts “payroll tax expense related to stock-based activities” as well.

For our purposes, even when we grade Coursera’s profitability on a very polite curve it still winds up generating stiff losses. Indeed, the company’s adjusted EBITDA as a percentage of revenue — a way of determining profitability in contrast to revenue — barely improved from a 2019 result of -15% to -14% in 2020.

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The owner of Anki’s assets plans to relaunch Cozmo and Vector this year

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Good robots don’t die — they just have their assets sold off to the highest bidder. Digital Dream Labs was there to sweep up IP in the wake of Anki’s premature implosion, back in 2019. The Pittsburgh-based edtech company had initially planned to relaunch Vector and Cozmo at some point in 2020, launching a Kickstarter campaign in March of last year.

The company eventually raised $1.8 million on the crowdfunding site, and today announced plans to deliver on the overdue relaunch, courtesy of a new distributor.

“There is a tremendous demand for these robots,” CEO Jacob Hanchar said in a release. “This partnership will complement the work our teams are already doing to relaunch these products and will ensure that Cozmo and Vector are on shelves for the holidays.”

I don’t doubt that a lot of folks are looking to get their hands on the robots. Cozmo, in particular, was well-received, and sold reasonably well — but ultimately (and in spite of a lot of funding), the company couldn’t avoid the fate that’s befallen many a robotics startup.

It will be fascinating to see how these machines look when they’re reintroduced. Anki invested tremendous resources into bringing them to life, including the hiring of ex-Pixar and DreamWorks staff to make the robots more lifelike. A lot of thought went into giving the robots a distinct personality, whereas, for instance, Vector’s new owners are making the robot open-source. Cozmo, meanwhile, will have programmable functionality through the company’s app.

It could certainly be an interesting play for the STEM market that companies like Sphero are approaching. It has become a fairly crowded space, but at least Anki’s new owners are building on top of a solid foundation, with the fascinating and emotionally complex toy robots their predecessors created.

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