Year: 2020

YC-backed Giveaway lets folks give away their unused or unnecessary items in a marketplace. Unlike other buy/sell or donation platforms, Giveaway uses a virtual currency on the platform to reward people for listing their products for free on the app.

Users earn Karma coins each time they list an item on the website. Folks can then use that Karma to claim items listed on the app.

The first person to try to claim an item offers zero Karma for the item. From there, a countdown begins, allowing others to offer more Karma for the item until the clock runs out. The user who offered the most Karma gets to claim the item. They are then connected to the giver via the app and can set a time and place to meet for the transaction. The person who claimed the item can inspect it and then approve the transaction, triggering the exchange of Karma coin.

Users can also rate and review each other on the platform for the quality of their items.

The app promotes giving items away to earn Karma but does offer a flow for purchasing the virtual currency. One Karma coin is equal to about $.30.

Giveaway was founded by Artem Artemiuk, Siarhei Lepchankou, and Siarhei Stasilovich. The idea came to them when traveling in Austria and coming across a store that allowed customers to choose one item for free.

After building the platform, the trio launched the app in their home market of Belarus and saw strong early growth. Since, Giveaway has expanded to Russia, Ukraine, Kazakhstan, and now the United States.

Artemiuk, Giveaway CEO, said that the company is laser focused on pre-moderation, which uses a combination of machine learning and human input to ensure that inappropriate items don’t make it on the platform, including drugs, tobacco, alcohol, and weapons.

In terms of business model, Giveaway takes a percentage of all Karma coins purchased on the platform, which account for about 30 percent of all Karma. Giveaway also sees the opportunity to generate revenue through an enterprise product within the app, allowing big corporations to opt for Giveaway over sometimes costly recycling options, and pay for the opportunity to do so.

Giveaway has raised $150K from Y Combinator and will present at the accelerator’s upcoming demo day.

YC-backed Giveaway lets folks give away their unused or unnecessary items in a marketplace. Unlike other buy/sell or donation platforms, Giveaway uses a virtual currency on the platform to reward people for listing their products for free on the app.

Users earn Karma coins each time they list an item on the website. Folks can then use that Karma to claim items listed on the app.

The first person to try to claim an item offers zero Karma for the item. From there, a countdown begins, allowing others to offer more Karma for the item until the clock runs out. The user who offered the most Karma gets to claim the item. They are then connected to the giver via the app and can set a time and place to meet for the transaction. The person who claimed the item can inspect it and then approve the transaction, triggering the exchange of Karma coin.

Users can also rate and review each other on the platform for the quality of their items.

The app promotes giving items away to earn Karma but does offer a flow for purchasing the virtual currency. One Karma coin is equal to about $.30.

Giveaway was founded by Artem Artemiuk, Siarhei Lepchankou, and Siarhei Stasilovich. The idea came to them when traveling in Austria and coming across a store that allowed customers to choose one item for free.

After building the platform, the trio launched the app in their home market of Belarus and saw strong early growth. Since, Giveaway has expanded to Russia, Ukraine, Kazakhstan, and now the United States.

Artemiuk, Giveaway CEO, said that the company is laser focused on pre-moderation, which uses a combination of machine learning and human input to ensure that inappropriate items don’t make it on the platform, including drugs, tobacco, alcohol, and weapons.

In terms of business model, Giveaway takes a percentage of all Karma coins purchased on the platform, which account for about 30 percent of all Karma. Giveaway also sees the opportunity to generate revenue through an enterprise product within the app, allowing big corporations to opt for Giveaway over sometimes costly recycling options, and pay for the opportunity to do so.

Giveaway has raised $150K from Y Combinator and will present at the accelerator’s upcoming demo day.

Amazon and others have raised awareness of how the in-store shopping experience can be sped up (and into the future) using computer vision to let a person pay for and take away items without ever interacting with a cashier, human or otherwise. Today, a startup is announcing funding for its own take on how to use AI-based video detection get more insights out of the retail experience. Deep North, which has built an analytics platform that builds insights for retailers based on the the videos from the CCTV and other cameras that those retailers already use, is today announcing that it has raised $25.7 million in funding, a Series A round that it plans to use to continue expanding its platform.

Deep North’s AI currently measures such parameters as daily entries and exits; occupancy; queue times; conversions and heat maps — a list and product roadmap that it’s planning to continue growing with this latest investment. It says that using cameras to build its insights is more accurate and scalable than current solutions that include devices like beacons, RFID tags, mobile networks, smartphone tracking and shopping data. A typical installation takes a weekend to do.

The funding is being led by London VC Celeres Investments (backer of self-driving startup Phantom AI, among others), with participation also from Engage, AI List Capital and others. The startup is not disclosing its valuation, and previously Deep North has not disclosed how much it has raised.

Previously known as VMAXX, the Bay Area-based startup, according to CEO and co-founder Rohan Sanil, currently is in use by customers in the US and Europe. It does not disclose customer names, but Sanil said the list includes shopping centers, retailers, commercial real estate businesses and transportation hubs.

There are a number of retail analytics plays on the market today, but up to now the vast majority of them have been based on using other kinds of  non-visual (and non-video) data to build their pictures of how a business is working, including logs of sales, card payments, in-store beacons, in-store WiFi and smartphone usage.

This list is, indeed, extensive and already provides a startling amount of data on the average shopper, but it has its drawbacks. Some people don’t use in-store WiFi; beacons are not as ubiquitous as CCTV; certain shopping data is a false positive, in the sense that if you don’t buy anything, it’s harder to track why not and where everything went wrong in getting you to shop; and perhaps most importantly you can’t see how shoppers are behaving, where they are looking and walking.

“The data collected [by these other means] is only 30-60% accurate and then extrapolated,” Sanil notes in a blog post. And that is not the only challenge. “The other is the enormous cost of the technology along with the software – which requires a team of programmers to get anything beyond stock analysis – plus being locked into a single vendor.”

Video systems “make a lot more sense,” he adds, and so does using those that are already installed in retailers’ locations. “The customers we see have no interest in deploying and paying for additional infrastructure, when the average store has several cameras already, and a typical big box store has dozens. Making our vision work means quantifying what a camera can see – and seeing through the cameras already in use.” The company typically integrates with 60-70% of a company’s installed cameras to run its analytics.

It’s that differentiation that has attracted investors. “Deep North’s platform allows retailers to gain real time insights on data points that were previously unattainable in the physical world. By leveraging existing video footage to understand activity and behavior, operators can now make informed decisions with the help of their prescriptive analytics engine,” said Azhaan Merchant of Celeres Investments, in a statement.

CCTV has had a problematic profile in the world of data privacy, where people pinpoint it as enemy number one in our rapidly expanding surveillance economy, and have ironically pointed out that it rarely is fit for the purpose it was originally set out to serve, which is deterring and identifying shoplifters. It’s notable to me that Deep North doesn’t actually ever use the term CCTV. (“Customers use a variety of terms for their cameras including CCTV, camera networks and loss prevention cameras so we’ve chosen to use a broader term that encompasses them,” a spokesperson said.)

Whatever you choose to call them, if a retailer has already made the leap into having these cameras installed, using them for analytics gives that business another way of getting a better return on investment. Sanil says that in any case, its platform is respectful of privacy.

“Deep North is not able to ascertain the identity of any individual captured via in-store footage,” he said. “We have no capability to link the metadata to any single individual. Further, Deep North does not capture personally identifiable information (PII) and was developed to govern and preserve the integrity of each and every individual by the highest possible standards of anonymization. Deep North does not retain any PII whatsoever, and only stores derived metadata that produces metrics such as number of entries, number of exits, etc. Deep North strives to stay compliant with all existing privacy policies including GDPR and the California Consumer Privacy Act.” (It has operations in Europe where it would need to comply with GDPR.)

Still, Deep North’s combination of computer vision with retail technology is a signal of a bigger trend. Many providers of security cameras have started to incorporate retail analytics into their wider offerings, and those that are concentrating on check out, like Amazon but also startups like Trigo, are likely also to consider this area too. Longer term, as retailers, but also their IT providers, look to get more intelligence about how their businesses are working in a bid for better margins, we’re likely to see even more players in this space.

For Deep North, that might mean also expanding into a wider set of products that not only are able to generate insights into how people shop, but then to use to those to build recommendations into how stores are laid out, or prompts to shoppers for what they might consider next as they browse.

Hello and welcome back to our regular morning look at private companies, public markets and the gray space in between.

A few weeks ago, Uber and Lyft, kicking bags of the 2019 stock market and regularly cited as examples of venture-backed excess, were back to fighting form.

After encouraging Q3 2019 reports from both ride-hailing giants that included fresh profitability promises and timelines, Uber upped the ante by moving its profitability goal up when it reported Q4 results earlier this year. Shares of the famous company rallied. When Lyft failed to mimic the declaration in its own Q4 earnings report, it was dinged by investors. But from the time of their Q3 2019 earnings reports to recently, Uber and Lyft were coming back up for air.

Suddenly, it was perfectly reasonable to be optimistic about the two ride-hailing companies that had become more famous for their sticky losses than their growth potential; as the pair had matured from upstart to public company, their money-losing methods appeared increasingly permanent, making the Q3 2019 and Q4 2019 profit declarations investor balm.

But after the rally came the novel coronavirus and COVID-19. Since then, the two companies have lost huge amounts of ground. Their shares fell 9.8% (Uber) and 11.8% (Lyft) yesterday alone. In pre-market trading this morning, they are down even more. I wanted to get my head around what could be causing this, so let’s run through each company’s most recent profit forecasts, results, share price gains and losses, and what investors are telling the world through their recent selloff. (Hint: DoorDash’s IPO probably isn’t happening soon.)

Portland-based micromobility startup Ride Report just closed a $10 million round led by Unusual Ventures to better facilitate relationships between cities and operators.

Ride Report works by monitoring micromobility vehicles across cities — currently 70 worldwide — to enable legislators to better understand the impact micromobility has on their respective cities. Ride Report, in partnership with operators, offers cities data, reporting and monitoring tools to support policy guidance.

“Micromobility is entering a difficult point in its history,” Ride Report CEO Williams Henderson told TechCrunch. “We’re very bullish on the needs that citizens and residents have around more efficient modes of transportation that get them from point A to point B, but there are some growing pains.”

That’s why Ride Report is focused on building a more collaborative and trusting relationship between private operators and public entities. With the additional funding, the plan is to grow the team and start focusing on emerging markets.

“The good news is everyone is kind of in the same boat when it comes to how to manage micromobility,” Henderson said. “It’s such a new thing that there isn’t really a playbook. That’s good news because it’s rare in working with government officials and regulatory bodies that you have so much room to experiment. There will be unique constraints in Europe around privacy and GDPR, but I’m excited about that aspect because Europe has shown the way forward for the U.S.”

Ride Report currently works with 70 cities, including Portland, Oregon, Austin, Texas and New Zealand. On the operator side, Ride Report works with 19 companies including Bird, Lime and Lynx.

“We’re entering an era of cooperation that’s going to open up the entire micromobility sector,” Unusual Ventures Partner Andy Johns said in a statement. “That gets to the core of what Ride Report is about and their belief in the future of mobility — that operators and cities will increasingly work together to help the industry grow.”

Ride Report is not the only company trying to help cities make sense of micromobility. Populus, which has $3.85 million in funding, helps cities access vehicle and trip data from shared-mobility operators. But there seems to be room, given the sheer number of micromobility companies operating throughout hundreds of cities.

Legionfarm, a YC-backed company, is looking to bring coaches to the competitive gaming world. Esports teams at the very top often have coaches, but the rest of the massive competitive gaming scene has to find a way to improve on their own, either via sheer time played or with creative new training platforms.

There is a huge demand for skilled teammates that can help you hone your skills, while at the same time, there is a broad community of near-pro gamers who haven’t landed a spot on an esports team and want to earn a living with their skills.

Legionfarm is a platform built to solve both problems.

The company was founded by Alex Belyankin, who is a former pro gamer and was once in the top .01 percent of World of Warcraft players.

Competitive gamers can sign up to become a coach on the platform, going through a process that looks at their stats within a particular title. Less than the top 0.1 percent are accepted as coaches and told how to manage sessions, including asking the customer’s goal at the beginning of the session.

On the other side, gamers can pay to play with one (or two) of these coaches in hour-long increments. Legionfarm allows users to specify if they want to play with two coaches, one coach and a friend, or one coach and another customer.

Users can also determine what kind of lobby they want to enter, such as a public or a ranked lobby.

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Here’s how it works.

When a user buys a session on the website, they are given instructions to join a Discord bot, which puts them in game chat with the coaches and asks for their gamertag for that specific title. The coaches then invite the customer to a lobby, and fire up the match.

To be clear, Legionfarm coaches are not coming from the same pool of streamers and pro gamers we’ve come to know and cheer on in the esports world. Rather, Legionfarm seeks out the very best and most skilled amateur players based on the publisher’s rankings and stats to become coaches. These are people who otherwise aren’t making money via Twitch or a salary via an esports organization, but are still in the top 0.1 percent of gamers by skill.

In other words, Legionfarm is creating pro gamers, rather than hiring them.

The average cost of a session is $16/hour, with Legionfarm taking half of the revenue and the rest going to the coach.

Legionfarm currently offers nine titles to choose from, including Apex Legends, Fortnite, CoD: Modern Warfare 2019, League of Legends, and Destiny 2. The company has run more than 300,000 gaming sessions with its 7,000 coaches.

Legionfarm is currently available via the web and through a Facebook Messenger bot, with plans to launch an app soon. Founder and CEO Alex Belyankin also teased new functionality that would allow Twitch viewers to request a session with the streamer directly from the chat.

Legionfarm has raised a total of $1.7 million from TMT Investments and Y Combinator, and will present at Y Combinator’s upcoming demo day.

For a political campaign, it’s not enough to pull together an army of bright-eyed, venti-caffeinated canvassers—you’ve got to tell them which doors to knock on. In Texas, the Democratic party is spearheading a data experiment that, if it works, could turn an emerging battleground state’s electoral outlook indigo by doing just that.

In other states, parties rely on imperfect national datasets to determine who might become a Democratic voter, a critical function that optimizes the valuable time volunteers and coordinators spend convincing would-be voters to show up to the polls. But for a state like Texas, the normal models don’t work very well—and in true Texas fashion, the Lone Star State is going its own way.  

Texas Democratic Party Targeting Director Hudson Cavanaugh told TechCrunch that his small team of strategists will leverage a new home-brewed machine learning model to mobilize the new voters the party views as mission critical. 

“We’re working on registering literally millions of voters across the state,” Cavanaugh said. 

Lauren Pully, the state party’s data and analytics director, began bringing together resources for a better way of targeting voters in 2018. Cavanaugh was brought into the mix fresh out of a New York startup early last fall to build it out and by primary season, the pair had their own proprietary model ready to go. 

Known as the “Texas model,” the data science project blends insights on the state’s unique voter makeup with a machine learning algorithm that can learn as it goes. The model helps coordinators determine a given person’s likely partisanship, a critical piece of knowledge for allocating campaign resources.

Powered by open source Python packages developed at Google and other machine learning hubs, the project eschews the normal path for state parties, which generally hire expensive outside data firms that come up with cookie cutter models trained on national datasets. 

“It’s kind of a data scientist’s dream,” Cavanaugh told TechCrunch. “We build models and they’re immediately tested in fields all across the state.”

According to Cavanaugh, normal partisanship models aren’t flexible and can’t be retrained to keep up with changes to state voter files and new data collected by campaign workers. Instead, “We’re using Texas to predict Texas,” Cavanaugh told TechCrunch. “And we’re already outperforming any of the national models.”

From a voter registration standpoint, a few things make Texas unique (likely more if you ask a Texan). For one, the state holds an open primary, meaning that Texas voters can cast a vote in either party’s primary, but not both. That fact, coupled with a massive influx of people moving into the state presents a logistical challenge for the Texas Democratic Party as it tracks potential voters.

Now in action, the Texas model has already flagged 600,000 additional potential Democratic voters, people the traditional off-the-shelf model missed. Party representatives believe that somewhere between two-thirds and three-quarters of the 600,000 are likely Democrats, many of them new Texas residents, young voters and people of color. The new model fits hand-in-glove with the Texas Democrats’ newly announced initiative to register 2.6 million new voters.

“We think it’s going to be the X-factor turning Texas blue,” Abhi Rahman, communications director for the Texas Democrats, told TechCrunch. 

According to Hudson, the state’s campaign stakeholders are also board, proud to have a uniquely Texan secret weapon in the quest for a blue Texas. Hudson they’ve shown “tremendous” level of engagement with the tool.

In Texas, the Republican electoral base, which skews older and whiter, has not blossomed along with the state’s population numbers. For Democrats, that presents a uniquely Texas-sized opportunity—and one not far out of reach. In 2018, Texas Senator Ted Cruz narrowly survived a Democratic challenge from Beto O’Rourke, hanging on by a remarkable 215,000 votes. 

Once blood red, the state’s shifting demographics make Texas a glittering prize for Democrats eager to see their state run blue. For a scrappy machine learning experiment seeking to shift the Lone Star state’s political fortunes, the proof will be in the pudding later in 2020.

American-listed shares are off sharply this morning, falling after a steep selloff yesterday was not staunched by a presidential address. The declines echo what happened to Asian-listed stocks earlier today.

All major American indices are now in bear-market territory, having shed the requisite 20% from recent highs. Today’s carnage is simply bleak. As we write to you, here’s where stocks are:

• Dow Jones Industrial Average (DJIA): -1,688.5, or -7.2%
• S&P 500: -191.2, or -7.0%
• Nasdaq Composite: -557.1, or -7.0%

The bad news continued for tech’s darling cohort, SaaS and cloud companies. That group of public companies is off 6.7% today, according to the Bessemer-Nasdaq cloud index. SaaS and cloud companies are now trading at one-year lows, and could approach their lows set in late-2018, early 2019 with a few more bad days’ trading. (SaaS companies were early to the bear-market trend.)

Shares of Uber and Lyft are selling heavily today, as the two American ride-hailing companies give back all their profit-promise driven gains that they’d achieved in recent months. Uber is off over 10% as of the time of writing, while Lyft, is down over 13%.

The selloff has proven to be so bad that, once again, market circuit breakers were tripped:

Cryptos, thought of at times as a hedge against other asset classes, are also sharply down, kicking that idea in the shins. Bitcoin is under $6,000, for example.

This is about as bad as it gets, in market terms. Sustained, huge selloffs of shares that are repricing a host of public companies won’t help private companies either. As their public comps’ values decline, startups will have a harder time raising at advantageous pricing, and finding exits at attractive valuations.

The IPO world appears moribund. What’s going on in venture, however, is more of an evolving picture. Given the lag in the reporting of venture rounds, it’s hard to tell how bad, or not bad, things are for private investors and startups. More on that when we have it. The story, however, remains the public markets and the return of fear.

Before leaving SoftBank-backed Zume Pizza in November 2018, co-founder Julia Collins knew what her next move would be: climate-friendly food. Today, Collins is announcing Planet FWD’s  $2.7 million seed round led by BBG Ventures with participation from Cleo Capital, Cowboy Ventures, Precursor Ventures, Kapor Capital and others.

What’s unique about this round, Collins told TechCrunch, is that 99.5% of the funds came from people of color and/or women. That was deliberate, she said. What’s also deliberate is the startup’s mission to combat climate change by building a climate-friendly food platform and snack brand.

“For me, the question has always been, how can we reform our food systems so that they work better for people and work better for the planet.” Collins said. “That’s been the thread that has connected all of my work in food. It’s always been how can we change the existing infrastructure and the ways of doing business so that we create better outcomes.”

In 2017, Collins learned she was about to become a parent — something she hadn’t expected. That’s what led to, what she describes as, a sudden shift in consciousness where she realized she would soon become responsible for another human being.

“When I learned I was going to be a parent, I decided I was going to become a climatarian,” Collins said. “So that meant not just being a vegetarian or living a plant-based lifestyle, but wanting to live a planet-based lifestyle. So I went from being a plant-based eater to a climatarian. So I started thinking about how I could make food choices that would have better outcomes for the climate.”

This is where the focus on regenerative agriculture comes in. Regenerative agriculture is a farming technique that aims to reverse the effects of climate change by capturing carbon in soil and aboveground biomass, which ultimately increases biodiversity, enriches soils and improves watersheds. But unlike organic foods, where those specific farms are relatively well-known and identified, that can’t be said for regenerative agriculture. This is where the food platform comes in.

“When it came to the regenerative food landscape, nothing had been codified or mapped yet,” Collins said. “And so, as I started to pull together the ingredients for my climate-friendly snacks. I amassed this really exhaustive library of all this information about these farms. And I thought that was really interesting because anybody who wants to create a climate-friendly food product needs a universal set of information that just wasn’t available. And here I was building it in a little spreadsheet. And so I looked up and I realized this is actually software that I’m building.”

It’s this software that is powering Planet FWD’s food production. The startup’s first product is a cracker, which launches later this year. The next product will likely be chips, Collins said.

“A lot of what we’re doing with this snack product is engaging consumers and trying out this climate-friendly positioning to see whether or not it actually resonates with people,” she said.

Ideally, Planet FWD will be able to show there’s consumer demand for climate-friendly products, Collins said. From there, she hopes that would encourage more farmers to implement these regenerative agriculture practices. At this point, it’s unclear how many farms are focused on regenerative agriculture, but Collins has so far identified hundreds of them.

Since leaving Zume, the robotic pizza company has struggled. Earlier this year, the company was forced to lay off 360 employees and shut down its pizza-making and delivery business. Now, the company is focused solely on food packaging.

“It was very, very hard for me to decide to step away,” Collins said about leaving Zume. “It was one of the hardest things I’ve had to do. Maybe the hardest thing I’ve ever had to do professionally. I’ve had a year-and-a-half to make my peace and find distance from it, but it’s been difficult and painful to see. At some point, you have to look back and it’s hard to look back and know that I don’t have any control or influence around anything that’s happening now — either the way that it’s being messaged or the actual function of the company. I’m still an owner in the company, and I still have hope they’re going to get to a really good outcome. But I am powerless.”

Now and in the foreseeable future, Collins will be focused on climate-friendly foods and food production.

“All of us have to eat every day, but what if as a result of our eating, we were able to actually draw down carbon and reverse climate change. Much of what we talk about in terms of solutions are consume less and produce less but when it comes to food we all need to eat. What if as a result of the way you ate, you could actually contribute to the solution.”

Toys are better now. There, I said it. Don’t get me wrong, I treasure the tub of action figures gathering decades of dust in my parents’ attic, but get a load of this Super Mario Lego play set. I would have happily used up all the nights of Hanukkah on the thing.

Caveats: I haven’t seen it in person. As of the positing of this, you’ve seen exactly as much of it as I have. There are still a ton of questions Lego couldn’t answer yet during our meeting, including important stuff life pricing and timing (beyond later this year). And yet, all the nostalgia receptors are firing at once, playing a familiar selection of chip tune hits.

What the company did tell me is that the product is the result of a four-year collaboration. In Lego’s words, “it turned out to be complex to create something simple.” The “simple” thing was the same code decades of IP partners have tried — and often failed — to crack: how to best bring Super Mario Bros. into the real world. Here, it means a play set that lets kids build and play their levels — essentially taking a page out of the successful Mario Maker franchise.

The key to the set is the Mario figure. Far and away the most sophisticated of the bunch, it features four built-in LEDs (two eyes, a mouth and a chest), designed to interact with the play set. There’s even a speaker that plays recordings from long-time Mario voice, Charles Martinet. The secret sauce here are color sensors built into the bottom of the plumber’s feet. Through these, the figure determines which blocks he’s hoping on and switches his displays accordingly, whether it’s a big smile or a pained grimace.

Speaking of switches, there’s no gameplay element to Nintendo’s latest console. That’s a little disappointing from an interactive standpoint, but good for parents who can feel comfortable buying a Lego set without having to shell out for a video game system. There may, at some point, be other connected elements. Smartphone/tablet functionality seems like a no-brainer, but Nintendo and Lego haven’t revealed any of those specifics yet.

Nor will they discuss if there are other sensors on board, like a gyroscope or accelerometer, so the system knows when Mario is on the move. There are on-board batteries to power Mario’s emotions, but we can’t say yet whether he’s rechargeable or they’re replaceable. More details as we get closer to release — whenever that might be.

There’s no specific on-board scoring system that I’m aware of, and while there’s a countdown clock to finish the levels you create, you’re on the honor system as far as playing them the right way. Unless, of course, you’re playing with a friend, in which case, they’ll likely be happy to keep you honest.

There are a number of familiar faces, including Shy Guys, a very cool Piranha Plant and, of course, Yoshi, but Mario is the one piece with sensors and a brain on-board. At least for now. One of the beauties of Lego kits is that they are, by their very nature, expandable. The kit will also work just fine with standard Lego pieces, as ever.

“I have always liked LEGO products and how they help children use their imagination to play,” Nintendo’s  Executive Officer and Game Producer Takashi Tezuka said in a release tied to the announcement. “The new product we created together with the LEGO Group seeks to combine two different styles of play – one where you freely build the world of Mario and the other where you play with Mario in the very world that you have created.”

Again, more info to come, but I certainly know a lot of kids (and adults) who are going to be counting down the days on this one.