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NextMind’s Dev Kit for mind controlled-computing offers a rare ‘wow’ factor in tech



NextMind debuted its Dev Kit hardware at CES last year, but the hardware is now actually shipping out, and the startup shared with me the production version to take a test drive. The NextMind controller is a sensor that reads electrical signals from your brain’s visual cortex, and translates those into input signals for a connected PC. A lot of companies have developed novel input solutions that use either eye-tracking or electrical impulse input from the body, but NextMind’s is the first I’ve tried that worked instantly and wonderfully, providing a truly amazing experience of a kind that’s hard to find in the current world of relatively mature computing paradigms.

The basics

NextMind’s developer kit is just that – a product aimed at developers that’s meant to give them everything they need to get building software that works with NextMind’s hardware and APIs. It includes the NextMind sensor which works with a range of headgear including simple straps, Oculus VR headsets, and even baseball hats, along with the software and SDK required to make it work on your PC.

Image Credits: NextMind

The package that NextMind provided me included the sensor, a fabric headband, a Surface PC with the engine pre-installed, and a USB gamepad for use with one of the company’s pre-build software demos.

The sensor itself is lightweight, and can operate for up to eight hours continuously on a single charge. It can charge via USB-C, and its software is compatible with both Mac and PC, along with Oculus, HTC Vive and also Microsoft’s HoloLens.

Design and features

The NextMind sensor itself is surprisingly small and light – it fits in the palm of your hand, with two arms that extend slightly beyond that. It features an integrated clip mount that can be used to attach it to just about anything to secure it to your head. In terms of fit, you just need to ensure that the 9 sets of two-pronged electrode sensors make contact with your skin, which NextMind provides instructions on doing by essentially making sure it straps snugly to your head, and then ‘combing’ the device slightly (moving it up and down to get your hair out of the way).

It wears comfortably, though you will notice the electrodes pressing into your skin, especially over longer use periods. The ability to use a standard baseball cap with the clip makes it super convenient to install and wear, and it worked with the Oculus Rift and Oculus Quest headstraps easily and instantly, too.

Image Credits: NextMind

Setup was a breeze. I was guided by NextMind’s co-creators, but the app provides clear instructions as well. There’s a calibration process during which you look at an animation being displayed on the host PC, which helps the sensor identify the specific signals that your occipital lobe is emitting when performing the target behaviour that you’ll later use to actually interact with NextMind-optimized software.

Here’s where it’s worth pausing to explain how NextMind is actually ‘reading your thoughts’: The sensor basically learns what it looks like when your brain is engaged in what the company calls “active, visual focus.” It does this using a common signal that it overlays on controllable elements of a software’s graphical user interface. That way, when you focus on a specific item, it can translate that into a ‘press’ action, or a ‘hold and move,’ or any other number of potential output results.

NextMind’s system is elegantly simple in conception, which is probably why it feels so powerful and rich in use. After the calibration process, I immediately jumped into the demos and was performing a range of actions effectively with my brain. First was media playback and window management on a desktop, and from there I moved on to composing music, entering a pin on a number pad, and playing multiple games, including a platformer where my mind control was supplementing my physical input on a USB gamepad to create a whole new level of fun and complex gameplay that wouldn’t be possible otherwise.

This is a Dev Kit, so the included software is just a small sampling of what could be possible with NextMind eventually, now that developers are able to build their own. What’s amazing is that the included samples are breathtaking on their own, providing an overall experience that is mind-bending in all the best possible ways. Imagining a future where NextMind hardware is even smaller and a seamless part of an overall computing experience that also includes traditional input is tantalizing, indeed.

Bottom line

NextMind’s Dev Kit is definitely just that – a Dev Kit. It’s intended for developers who are going to use it to write their own software that will take advantage of this unique, safe and convenient form of brain-computer interface (BCI). The kit retails for 399.00 € (around $487 USD), and is now shipping. NextMind has plans to eventually consumerise the product, and to work with other OEMs as well on implementations, but for now, even in this state, it’s an awe-inspiring glimpse into what could well be the next major shift in our daily computing paradigm.

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



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



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.


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



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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