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Pllay adds $1M in funding for skill-based video game wagering

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cofounder of Pllay

Pllay has raised $1 million in funding for its skill-based video game wagering platform. Pllay enables gamers to wager on 1-on-1 duels.

Viridian Equity Partners and investor Gayle Jennings-O’Byrne led the new round. The funding comes in addition to the $3 million that Pllay raised in November, when it announced that it raised money from James McGuckin’s Screen Play Ventures and other angel investors including NBA All-Star Bradley Beal, Obsidian Works head Chad Easterling, and GE Power Portfolio CEO Russell Stokes.

The Philadelphia company will use the money to hire people, improve its user experience, develop tech, and accelerate user acquisition. So far this year, new matches played have increased tenfold, new registered users have doubled, and the average wager size per match has increased to over $20, said CEO Shawn Gunn said in an interview with GamesBeat.

“What really drew them to us is our perspective on gaming from a monetization layer, and how that connects into a lot of their relationships with brands, in particular, quick service franchises,” Gunn said. “Part of our roadmap is around not just the wagering aspect, but we believe in finding a multitude of ways to reward gamers as they’re in a match. And so part of that outside of the wagering piece is to pull mainstream brands into that conversation helps that helps the users.”

The team created a peer-to-peer wagering platform on a mobile phone, where players wager on matches played on other platforms. This kind of skill-based play, which is not considered gambling because it doesn’t have purely random results, is legal in 39 states now. Pllay has hundreds of thousands of users now.

The industry has a lot of competing platforms, but Gunn said that his company has figured out how to verify who won a match in a 1-on-1 duel.

In the past, it was too easy for one player to fail to pay on the wager. But Gunn said Pllay can monitor a match on Twitch with AI and then determine which of the two players won. And after holding the money in escrow before the match, it can make immediate payment as soon as verification is complete.

“We wanted to clean that friction up,” Gunn said. “We can certify the winner.”

Pllay targets only people who are 18 or older with its mobile app, and it runs checks on people ahead of time when they put money into the system. The company abides by anti-money laundering laws to fight against fraud. (This is technology that online gambling sites also use.) Pllay also removes any minors who try to get into matches.

“We help the brands find ways to have a one to one conversation with this really tough demographic when it comes to attracting and engaging,” Gunn said. “They were super interested in our perspective of going after the amateur competitive gaming market. There’s a high level of consumerism in that audience.”

When someone wins, they get 100% of the funds wagered, as Pllay doesn’t claim a fee. But it can make money through advertising and brand partnerships.

Above: Christine Krzyzanowski is cofounder of Pllay

Image Credit: Pllay

Pllay’s AI computer vision specializes in real-time monitoring of matches, making it a kind of virtual referee that certifies wins and losses and creates a safe environment for gamers to wager with confidence while removing any concerns they won’t get paid, Gunn said.

Currently, players can wager on Call of Duty: Modern Warfare, Madden 21, FIFA 21, NBA 2K21, and Fortnite on Xbox and PlayStation consoles. Compatibility with more titles will be announced soon.

Gunn has 20 years of experience in venture-backed startups and enterprises. He has had five exits over the years that generated $1 billion in value. Christine Krzyzanowski, a 15-year veteran in brand strategy, said in an interview with GamesBeat that she was glad to have the support of a female investor.

Jennings-O’Byrne, the investor in the new round, is the general partner of the WOCstar Fund, which focuses on women-led businesses.

“On the female initiative side, you hear a lot about women starting to break barriers in the esports and gaming,” said Krzyzanowski. “We really focus on the casual amateur gamer too. So to see women supporting other women and funds supporting other women is very important.”

Pllay has about 20 people.

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Lora DiCarlo launches crowdfunding campaign for sexual wellness products

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Lora DiCarlo launches crowdfunding campaign for sexual wellness products

Join GamesBeat Summit 2021 this April 28-29. Register for a free or VIP pass today.


Lora DiCarlo, the sexual wellness startup at the center of a trade show dustup in 2019, has launched a crowdfunding campaign to raise more money to make its microrobotic pleasure devices.

The Bend, Oregon-based company is raising money via a regulation crowdfunding offering on Republic, and it’s can raise anywhere from $25,000 to $5 million in the “my first time” campaign. After launching it this morning, the company has already raised more than $48,000, and the campaign should expire in 79 days.

Lora DiCarlo gained attention at CES 2019 after the Consumer Technology Association banned the company’s first female-oriented sex toy, Osé, from the show. In May 2019, the CTA updated its policy to make CES more “welcoming and inclusive,” and the sex toy was credited with kicking off a positive conversation about female empowerment and female-run startups.

The company already has investors like actress Cara Delevingne (co-owner of Lora DiCarlo), Romulus Capital, VU Fund, and Gaingels. Republic is a SEC-registered investment platform for investors seeking high growth investment returns in highly-vetted startups.

“We really feel like it’s an amazing opportunity,” said Lora Haddock, the CEO and founder of Lora DiCarlo, in an interview with VentureBeat. “There are not a lot of ways to invest in sexual health and wellness. So we want to better everyone’s sex lives and what better way to be able to do that and then to allow everybody to participate. We’ve taken an inclusive and transparent approach.”

Allied Market Research estimated the sex tech market at $74 billion.

Above: Lora DiCarlo’s line of sexual wellness products.

Image Credit: Lora DiCarlo

After CES changed its policy, sex toy makers such as Lora DiCarlo, OhMiBod, and Lioness were able to exhibit at CES 2020 in January. The show has continued to deny entrance to porn companies after those groups split off and formed their own show years ago. During the past couple of years, Lora DiCarlo has designed 11 products based on its microrobotic engine.

“Our engineering team has gone from a rickety car to a very well oiled machine in the last few years,” Haddock said. “Now we can dump ideas into this hopper and quickly synthesize them in a productive manner. We listen to the problems that people say they have, and we try to solve them.”

Lora DiCarlo started out creating high-tech sex toys in partnership with Oregon State University’s College of Engineering. Osé is a complex product with hundreds of parts. Its flexible body and custom controls allow people, either alone or with a partner, to simultaneously stimulate the G-spot and the clitoris to create a blended orgasm.

“Our mission is really rooted in just doing eradicating that stigma around sexuality and allowing people to just feel more empowered,” Haddock said.

Lora DiCarlo has also launched a sexual wellness coaching program called WellSx that complements the Osé family of devices. Haddock and other employees at the company got trained in sexual education for the purpose of offering the service. Haddock said the team welcomes constant feedback for its products.

“We were actually able to make some pretty awesome improvements to really better approach a wider berth of of physiology,” Haddock said, regarding the launch of the first product.

Founded in 2017, Lora DiCarlo has 25 employees, not counting contractors, and has raised $6 million. In 2020, the company reported revenues of $7.5 million and it has shipped more than 50,000 products to date. The company has 13 patents.

Lora DiCarlo offers direct-to-consumer delivery in 37 countries with product availability in over 400 retail stores in major markets including  the U.S., the United Kingdom, Europe, and Japan. The brand also recently launched a new collection of warming sextech and has additional products set to debut later this year. Funds raised will support continued product development, global marketing, and sales.

Regarding the success so far of the fundraising, Haddock said, “This is not a niche industry. It’s not going away.”

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Cloudera partners with Nvidia to expand GPU usage across AI applications

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Comparison of CPU and GPU workloads

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Cloudera and Nvidia announced a collaboration that will allow organizations to use GPUs in more areas across the AI development lifecycle.

Cloudera will integrate its Cloudera Data Platform with Nvidia’s accelerated Apache Spark 3.0 libraries. The integration will make it easier to add machine learning workflows to processes and create architectures without requiring GPU customization. Enterprises will be able to make changes to their data science workflows without having to also update the Nvidia integration manually.

GPUs have shown tremendous promise in enhancing the data science side of AI development, enabling enterprises to run some types of workloads on top of GPUs. However, analytics often involve processes that span multiple teams, forcing enterprises to invest in customizing GPU integrations for those use cases.

Gartner has predicted that creating new architecture patterns that help operationalize data science and ML pipelines will be one of the major trends in 2021.

Benefits to accelerating GPUs

The partnership will allow enterprises to use GPUs across modern data workflows that span data preparation, data science, and analytics tasks. The typical workflow includes many steps including data ingestion, data curation, data pipeline automation, data science exploration, model development, testing, deployment, model monitoring and retraining, and delivery into the business. Cloudera has been busy in making these processes and the handoffs between them much easier over the last year.

The Apache Spark 3.0 libraries are accelerated using Nvidia’s RAPIDS platform, which will dramatically accelerate much of the boring prep work required to bring new machine learning models into production. For example, the US Internal Revenue Service is already seeing a threefold improvement in data science workflows for fraud detection, said Joe Ansaldi, IRS technical branch chief for the Research Applied Analytics & Statistics Division, in a statement.

Speeding up data preparation tasks and training models faster will save on infrastructure costs as well. GPU-accelerated Apache Spark 3 runs natively on CDP and can plug into high performance compute tools, Cloudera said.

Above: Comparing the CPU and GPU powered workflows.

Image Credit: Cloudera

Cloudera’s data portfolio

Cloudera was a trailblazer in the development of data lakes built on top of the Hadoop platform. Cloudera merged with Hortonworks, another Hadoop vendor, in 2018 and combined the technologies into a modern architecture called the Cloudera Data Platform (CDP). At the time, many speculated this spelled the end of Hadoop data warehouses, but Cloudera has continued to innovate and extend Hadoop into a more nimble workflow.

Cloudera added Applied ML Prototypes (AMPs), a framework for packaging AI and ML models for data scientists, to CDP earlier this year. AMPs allow teams to take the guesswork out of ML projects with prebuilt business application templates for specific use cases, and they often run on Nvidia GPU hardware. Cloudera Data Engineering (CDE) streamlines the data engineering and prep work at the start of a project. This solved common problems data engineers face, such as scheduling and orchestration of complex data, troubleshooting and performance tuning tools for data flows, and improving collaboration with analytic and data science teams.

The RAPIDS Accelerator for Apache Spark will be available in CDP Private Cloud this summer. Nvidia and Cloudera will roll out additional accelerated offerings in CDP over time, starting with Accelerated Deep Learning and Machine Learning in CDP Public Cloud in May. “This means that no matter where customers require these GPUs (from on-prem to public cloud, to hybrid cloud and beyond), they’ll be able to leverage best-in-class GPUs out of the box,” said Santiago Giraldo, Cloudera director of product marketing for data engineering and machine learning.

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Nvidia unveils rental model for DGX Station A100 mini supercomputers

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Nvidia unveils rental model for DGX Station A100 mini supercomputers

The day has come when you can rent your own mini supercomputer. When you’re done with it, you can return it to Nvidia.

That’s the plan for the company’s new cloud-native supercomputer, the Nvidia DGX Station A100. Nvidia made the announcement during the keynote speech at its GTC 2021 event.

You can use the supercomputer for a short period of time when you need it and then return it after you’re done, said Manuvir Das, head of enterprise computing at Nvidia, in a press briefing. The DGX Station is a multi-tenant supercomputer that can be shared by as many as 28 data scientists. Also announced at GTC is a new Nvidia DGX SuperPod that will be available with Nvidia’s Bluefield-2 DPUs, enabling a cloud-native supercomputer. A DGX SuperPod consists of a bunch of individual DGX Station computers.

“You can think of us progressing in two directions, one with constant innovation to raise the bar. But the other is to really democratize AI to put it in the hands of as many companies and scientists as we possibly can,” Das said. “We are also announcing for the first time a rental model. Instead of procuring a DGX Station, customers will be able to rent a station directly from Nvidia at a low monthly price point, and they can use it for as long as they choose and then return it to Nvidia. So that’s an important direction that we are taking with the Station.”

This opens the world of AI to more enterprise customers as they investigate areas such as AI, drug discovery, autonomous vehicles, and more. Those DPUs can offload, accelerate, and isolate users’ data — providing customers with secure connections to their AI infrastructure.

Nvidia DGX SuperPod will be available with Nvidia’s Bluefield-2 DPUs, enabling a cloud-native supercomputer. It’s a full bare-metal supercomputer that is also sharable. In a keynote speech at GTC 21, Nvidia CEO Jensen Huang said the company will focus on three kinds of chips: DPUs, central processing units (CPUs) like Grace, and graphics processing units (GPUs). It will alternate between Arm-based and x86-based products, he said.

“We have to make AI easier to use,” Huang said.

Above: DGX Superpod

Image Credit: Nvidia

This is the first time Nvidia is turning to a rental model for DGX Stations. The idea is to broaden AI adoption for enterprise IT departments that need to support the work of teams in multiple locations or to help academic and research institutions, which often have to grant outside organizations access to their computers. DGX Stations start at $149,000, while the DGX SuperPod starts at $7 million and scales to $60 million.

The company also announced NVIDIA Base Command, which enables multiple users and IT teams to securely access, share, and operate their DGX SuperPod infrastructure. Base Command coordinates AI training and operations on DGX SuperPod infrastructure to enable the work of teams of data scientists and developers located around the globe.

The DGX SuperPods are AI supercomputers featuring 20 or more Nvidia DGX A100 systems and Nvidia InfiniBand HDR networking. Among the latest to deploy DGX SuperPODs to power new AI solutions and services is Sony, which uses the DGX SuperPod for its corporate research team to infuse AI across the company.

Other customers are Naver, Recursion, MTS, and VinAI. Additionally, Nvidia and Schrödinger today separately announced a strategic partnership designed to harness DGX SuperPods to further accelerate drug discovery at a supercomputing scale.

Nvidia also introduced a subscription offering for the DGX Station A100. The new subscription program makes it easier for companies at every stage of growth to accelerate AI development outside the datacenter for teams working in corporate offices, research facilities, labs, and home offices.

The DGX A100 is a collection of DGXs working together as one cluster of infrastructure to produce a supercomputer, Das said. Each box is capable of 2.5 teraflops of computing power. Cloud-native, multi-tenant Nvidia DGX SuperPods will be available in Q2 through Nvidia’s global partners.

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