Meet the company that’s looking to make non-surgical male birth control a reality

While the male birth control pill is still a fiction (that may never become fact), a new company called Contraline is working to make at least one non-surgical, reversible birth control procedure a reality.

The new technology is aiming to be one small (snip-less) step for men, and one giant leap for male contraception.

Based in Charlottesville, Va., Contraline is the culmination of four years of research conducted by the company’s chief executive Kevin Eisenfrats at the University of Virginia.

Ever since Eisenfrats shadowed operating room physicians in his senior year at the Academy of Allied Health Science high school in his hometown of Monmouth, NJ the now 23-year-old chief executive was fascinated by reproductive health.

“There are so many problems at the center of reproductive medicine and biomedical enginering that really come with no solutions,” Eisenfrats says.

In fact, the young CEO’s entrance essay to UVA was on the male birth control pill and why it didn’t exist.

Eisenfrats graduated with a degree in nano-medicine engineering and immediately began working with his co-founder John Herr (a longtime professor at the University of Virginia who died in 2015) on the Contraline technology.

The two men developed a reversible procedure that uses a gel injected into the vas deferens to literally block sperm during ejaculation. “For lack of a better word, the guy is literally shooting blanks,” he says.

Unlike other procedures, which rely on surgery to inject the gel into the canal that conveys sperm to the urethra, the Contraline procedure uses ultrasound as a guidance. The gel the two men developed is ultrasound visible (so it can be injected) and is dissolvable so that the procedure is reversible.

It’s important to note that the gel won’t prevent the transmission of sexually transmitted diseases. “The people this is for are couples in a long term relationship,” says Eisenfrats. Although, he adds, most of his friends want to get Contraline-d themselves.

Other companies, like the non-profit Parsemus Foundation (the makers of Vasalgel), are also working with a polymer gel, but still rely on surgery to insert the gel.

According to Eisenfrats, Contraline is plowing fertile ground when it comes to the potential market it’s addressing.

“This is basically the male birth control of the future,” he says.

The company has raised $2.5 million from investors including Abstract Ventures, Jaffray Woodriff, the Virginia Center for Innovative Technology, Jason Calacanis, and the strategic investor Afton Scientific, a vial filling and sterilization company. Founders Fund lead the latest investment.

It’s the second seed round for the company, which is bound to only raise seed financing (since it’s a contraceptive company) Eisenfrats joked.

 For Cyan Banister, who shepherded the deal through to investment for Founders Fund, happening on Contraline was a combination of luck and persistence. The company had turned up as the best of the Y Combinator Fellowship companies in a search conducted by Founders Fund’s interns.

Banister put a note to herself on a post-it reminding her to check in on the company, and she periodically did. She began conversations with the young startup August 2016 and the latest investment closed in March.

“I just kept checking back,” Banister told me.

In the seven months since those conversations began, Contraline brought on the urology specialist Dr. Paul Turek as an advisor (and now Chief Medical Officer) who validated that the company had been making significant strides.

“He validated that there were very few people working on that problem. Nobody was really making progress in birth control for men,” Banister says. “I believe that men want more options over their reproductive choices.”

With assurances in place from experts in the field of urology, and a careful vetting by Founders Fund’s own chief scientist, Banister was ready to cut the check.

That money has gone a lot farther in the company’s home base of Virginia than it would in San Francisco, the founding chief executive said. “We have our own 2200 square foot lab. The amount of space we have would be $1 million in San Francisco,” says Eisenfrats.

There are about 500,000 vasectomies performed in the U.S. every year and 22.5 million men relying on temporary contraceptives. “The contraceptive industry is $18 billion and growing,” says Eisenfrats. “[Our procedure] is a $7 billion opportunity in the U.S. [and] contraception is a global issue.”

According to Banister, the company’s plans extend beyond just male contraception. “There are things you can do with the gel for female reproductive health,” she said.

For now, the company still has a long way to go before the treatment will be generally available. A rat study is currently underway (“What I will say, is that the rats are loving it,” says Eisenfrats), but the company will conduct a large animal study this year.

Contraline will conduct clinical trials beginning in 2019 and hopes to be on the market by 2021, Eisenfrats said.

The company is one of a growing number of technology startups focused on male reproductive health. Just yesterday we wrote about YO, a “sperm selfie” startup, which is competing with Trak, another device that’s looking at the health of a man’s “fallopian swim team”.

When the time comes, Founders Fund’s Banister has a good idea who the first patient will be.

Talla service bot lets IT ease into AI

Talla, a Cambridge, Mass. startup, wants to help companies ease into artificial intelligence, and they have come up with a new service assistant bot that gives companies whatever degree of intelligence-fueled power they are looking for.

The tool, called ServiceAssistant, works as an IT or HR help desk inside of Slack or Microsoft Teams and gives customers a few options on how to use it. First of all, you can run it like a traditional service desk. The user sends requests through ServiceAssistant where it gets processed and answered by a human.

In the second scenario, the customer eases into automation where the ServiceAssistant provides an automated answer, which gets checked by a human before being sent through to the questioner, or at the highest level of automation the system simply sends an answer when the confidence threshold is above a certain level set by the customer.

CEO and co-founder Rob May says the company deliberately used an in-house service model instead of live customers because after reviewing the technology, he felt that the current Natural Language Processing (NLP) technology was better suited to this approach.

The Talla ServiceAssistant looks like any user on Slack or Microsoft Teams. As with any Slack or Teams bot, employees can interact with it by asking questions. If it’s tuned to be an HR assistant, for example, an employee might ask, “Do we have Labor Day off?” If the system has been configured to answer automatically, it’s the kind of question that it can answer with a high degree of certainty and can simply tell the employee yes or no.

In an IT Help Desk approach, the questions could get trickier such as, “How I get access to QuickBooks?” In this case, the system might find multiple matches, and if it were set for automated responses, it could ask the questioner to choose the most relevant one, or it could ask if they want to open a help desk ticket to move to the question to a human for processing.

The system is tuned to ask questions when it doesn’t understand and to learn from the responses. Since people ask questions in non-standard ways, the system can also learn that “Are we open Labor Day?” is the same as “Do we have Labor Day off?” or “Is the office closed on Labor Day?”

 May says even in companies where there are high usage rates for Slack or Teams, there could be as many as 20 percent of employees not using that tool, so they’ve also built a Web App and allow email, but the ultimate goal is to get people into the conversational tools to ask the questions — and do it in an automated way as possible.

The company wants to be more than a conversational bot, however. It wants to be a central place for processing IT and HR requests. That means having a ticket system, a knowledge base and the ability to broadcast to employees, for example, when the system is going down for maintenance or the office is closed for a holiday.

May says among his customers Slack is definitely the more popular of the two offerings today, but he believes it’s important to look at the different conversational tools and continually assess where that market is going as it’s still being established.

“What does that [conversational market] fragmentation look like int two years is one of our biggest strategic worries,” May says.

The company is very much a startup with 16 employees. It’s raised $4.5 million. May was previously co-founder at Backupify, a cloud startup that was sold to Datto in 2014.

The training helps in acquiring qualities that are expected from a scrum master.

A certified scrum product owner is the responsible person of the business who governs the success and failure of the product and at the same time liable for the return of investment. He should be laced with foresight and should be capable of leading his team towards achievement of the goals of the company. He should be clear in his strategies and capable of presenting his views in a most impressive and influential way. To nurture these qualities in a person csp Training does a remarkable job. It helps in cultivating all the qualities that he needs to become a scrum master through its virtual classroom. To help him with best education the teaching is imparted by certified scrum alliance. To add on to his learning, hand on practices and real life experiences are shared so that he gets the, better idea of all the concepts and techniques of the scrum.

Image result for The training helps in acquiring qualities that are expected from a scrum master.

For all those aspirants who wish to become a scrum master and take their business to the next level, csp Training in Boston do a remarkable job. Have a look at the qualities that an aspirant grab while undergoing the training.

  • Becomes a responsible person- The tools and techniques are clearly explained to him. His work in the business is explained to him. He is entrusted with the responsibility of completing projects within stipulated time. He manages to do so after learning from the teachers thus making a responsible person who can take up aresponsibility of handling any project.
  • Becomes more presentable- During the training period he is given hand on experiences and how he can motivate his team members towards the accomplishment of the goals, this is where he picks up the quality of making himself clear to his team. He makes clear his expectations from them and then set small targets. These small targetshelp him keep an eye on the progress of the project, thus enabling him to take a needful decision at the time of crises.
  • What should come first- The scrum master is clear in his working as to what he should start with during his project. This is the classroom training that helped him mange his work and priories accordingly. He motivates his team members to follow the track that complete the project within time.
  • Communication skill-This is the governing factor for any business. A scrum master is able to communicate well with the team members and product owners. The clarity of expectations helps him briefly explain his requirement to the team members. For this he plans daily meetings and convey his messages to the team members. It also helps him keep check on the progress made on the previous day.
  • Bridges the gap between the customer and the stakeholder- With continuous check on the working process, he is able to assure that the right product will be delivered and the project is heading towards the success. He should ensure them that the expected returns on investments could be obtained from the project.

Learning everything about the Scala and apache spark

Spark is a popular framework that is used for implementing the concepts of cluster computing. But due to its high level functionalities, it is often used on the YARN framework of Hadoop. The main aim of spark is to give the needed speed to the process of computation. For anyone who is planning to work on the concepts of big data analytics, the apache spark and Scala online certification will come in handy.

Image result for Learning everything about the Scala and apache spark

If you sign up for apache spark and Scala online training in Boston, you are expected to know the basics concepts of Scala, a programming language used for the development of web applications. When it comes to data computation and analysis, the problems were faced due to slow speed of the queries and algorithms. With the help of spark, this process helps in improving the way memory storage is done and how the process of fault recovery is made efficient.

If you want to understand the basics, you should begin from the concepts of the RDD. RDD is the resilient distributed dataset which is used for the data abstraction following the core concepts. RDD is basically a collection of objects that are defined in the process of development. The concept here is simple; the RDD is divided into a variety of partitions. The computation of these partitions is done with the help of different nodes that are defined in the data cluster. Since we are talking in context to Scala, the RDD will contain objects that are based on the top of Scala.

Since the RDD play an important role, you either needs to create new RDDs as and when required or modifications is done as per the requirements. The process of data distribution is very sorted and done with uniformity across all the clusters to ensure that the operations take place in the desired manner.

The areas of applications of apache spark with Scala are quite a man and since there are a very low amount of compatibility issues, one doesn’t need to worry about it in any possible situations. It is composed of various components like Spark Streaming, GraphX, Spark SQL, etc. these are nothing but the libraries that cover wide range of topics and thus most of your requirements related to development could be taken care of with the help of them instead of doing it on your own.

There are a lot of added advantages when you use the apache spark with Scala. One of such aspects is the compatibility. The development of apache spark is done in Scala itself and therefore when you use it for your development related needs, the task would not just get simplified but the concepts of compatibility would also come in handy. If you have any knowledge about the Scala, you will know that it is one of the easiest languages to write and implement and due to this, the problems related to complexities have widely reduced leading to high level of security and reliability.

Uber Said to Be Rethinking Its Car Leasing Strategy in India as Driver Incomes Drop

Global ride-hailing firm Uber Technologies is rethinking its car leasing strategy in India, its second-biggest market, as drivers have returned dozens of leased cars early after the company cut incentives, people familiar with the matter told Reuters.

Uber had planned to buy 15,000 new cars last year and lease them out in a bid to attract more drivers – a strategy it has used in other markets – but it suspended the scheme for a while in December after leasing just a third of that total.

Uber Said to Be Rethinking Its Car Leasing Strategy in India as Driver Incomes Drop

After burning through millions of dollars over three years in a battle for market share with local rival Ola, backed by Japan’s Softbank, Uber has cut the incentives it gives to drivers and raised the fares it charges passengers.

The incentives – from free smartphones to cash bonuses worth as much as double a day’s fares – meant drivers could earn as much as Rs. 120,000 ($1,838) a month.

Those incentive payments have been pared back, in some cases to as little as 10 percent of fare income. Ride fares have risen to Re. 1.5 per minute of travel from Re. 1.

The incentives and, to an extent, the leasing scheme aimed at drivers without their own cars, boosted Uber’s driver numbers, helping it rapidly gain around 30 percent market share.

Uber has faced challenges elsewhere in Asia, but the stakes are high in India’s $12 billion taxi market, a key area after it exited China last year, and one where CEO Travis Kalanick has said it expects to be profitable soon.

Uber has said its services are in 29 Indian cities and it has more than 250,000 drivers on its platform, but it lags Ola, which says it operates in more than 100 cities with about 550,000 drivers.

Business shift
Two people with knowledge of the matter said Uber miscalculated the impact that the reduced incentives would have on drivers’ earnings, especially those making lease payments.

At an open meeting for staff in December, around the time the incentives were being reduced, Uber’s India chief Amit Jain said the buying-for-lease scheme was being temporarily suspended while the company evaluated its leasing strategy, one of the sources said.

Uber did not comment on Reuters queries related to Jain’s announcement or the impact of the incentives cuts on its leasing programme.

Raj Beri, business head for leasing in India, said the scheme was set up to help drivers without cars get on its platform and make money. “We are very pleased with our progress toward this goal so far, and look forward to introducing the opportunity to more prospective driver partners this year,” he said in a statement.

In a recent blog post on Uber’s website, Jain defended the cuts to driver incentives and signaled a strategic shift for India. “We can shift from startup mode to a more sustainable business model,” he wrote.

“No benefit in leasing”
Leasing is only a small part of Uber’s overall supply in India, but is seen as a way to lock drivers on to its platform for longer, and stop them switching to Ola.

To lease a new small car through Uber’s scheme, drivers pay a Rs. 33,000 ($499) deposit – less than what they would pay to buy a car from a dealer with a bank loan. But weekly payments of about Rs. 5,500 over three years add up to nearly double what drivers would pay to service a car loan.

That wasn’t an issue when incentives were high.

Several Uber drivers said they feel trapped as a surge in the number of cars on Uber’s platform has led to fewer rides, at a time when incentives have been cut, making it harder to keep up lease payments.

“I’ll not be able to save even Rs. 10,000 a month,” said Arjun Chouhan, 38, an Uber driver in Delhi who has leased a car. “There’s no benefit in leasing. What if I’m unwell? They don’t listen.”

In a dusty car lot on Delhi’s outskirts, guards told Reuters that dozens of cars standing idle belonged to Uber and had been returned by drivers.

When Reuters phoned Xchange Leasing, Uber’s local leasing arm that has an office near the car park, officials said no new cars were currently being leased out. One said the priority was to lease those cars returned by drivers, and it could be 2-3 months before new cars would again be offered.

An Uber spokesman said the company doesn’t comment on “anonymous speculation”.

As part of its review, Uber may reduce the three-year lease term and let two drivers share the rent on a car, one of the sources said.

Uber did not comment on its leasing targets or the future of the scheme.

“People left well-paying jobs to drive an Uber,” said Sandeep, another Delhi driver, adding his monthly ride income has nearly halved to Rs. 60,000 in two years, despite working longer hours.

“We were tempted at the thought of becoming millionaires.”

Twitter Says It’s Exploring Building a Premium Version of Tweetdeck Aimed at Professionals

Twitter Inc is considering whether to build a premium version of its popular Tweetdeck interface aimed at professionals, the company said on Thursday, raising the possibility that it could collect subscription fees from some users for the first time.

Like most other social media companies, Twitter since its founding 11 years ago has focused on building a huge user base for a free service supported by advertising. Last month it reported it had 319 million users worldwide.

Twitter Says It's Exploring Building a Premium Version of Tweetdeck Aimed at Professionals

But unlike the much-larger Facebook, Twitter has failed to attract enough in advertising revenue to turn a profit even as its popularity with US President Donald Trump and other celebrities makes the network a constant centre of attention.

Subscription fees could come from a version of Tweetdeck, an existing interface that helps users navigate Twitter.

Twitter is conducting a survey “to assess the interest in a new, more enhanced version of Tweetdeck,” spokeswoman Brielle Villablanca said in a statement on Thursday.

She went on: “We regularly conduct user research to gather feedback about people’s Twitter experience and to better inform our product investment decisions, and we’re exploring several ways to make Tweetdeck even more valuable for professionals.”

There was no indication that Twitter was considering charging fees from all its users.

Word of the survey had earlier leaked on Twitter, where a journalist affiliated with the New York Times posted screenshots of what a premium version of Tweetdeck could look like.

That version could include “more powerful tools to help marketers, journalists, professionals, and others in our community find out what is happening in the world quicker,” according to one of the screenshots posted on the account @andrewtavani.

View image on TwitterView image on Twitter

Other social media firms, such as Microsoft Corp’s LinkedIn unit, already have tiered memberships, with subscription versions that offer greater access and data.

In the fourth quarter of 2016, Twitter posted the slowest revenue growth since it went public four years earlier, and revenue from advertising fell year-over-year. The company also said that advertising revenue growth would continue to lag user growth during 2017.

Financial markets speculated about a sale of Twitter last year, but no concrete bids were forthcoming.

Advances in AI and ML are reshaping healthcare

The healthcare technology sector has given rise to some of the most innovative startups in the world, which are poised to help people live longer, better lives. The innovations have primarily been driven by the advent of software and mobility, allowing the health sector to digitize many of the pen and paper-based operations and processes that currently slow down service delivery.

More recently, we’re seeing software become far more intelligent and independent. These new capabilities — studied under the banner of artificial intelligence and machine learning — are accelerating the pace of innovation in healthcare. Thus far, the applications of AI and ML in healthcare have enabled the industry to take on some of its biggest challenges in these areas:

  • Personal genetics
  • Drug discovery
  • Disease identification and management

Upon close evaluation of the opportunities that exist within each area, it becomes obvious that the stakes are high. As such, those that are first to market with a sustainable product differentiation and value-add will benefit tremendously.

Ushering in a new era of personal genetics

The most significant application of AI and ML in genetics is understanding how DNA impacts life. Although the last several years saw the complete sequencing of the human genome and a mastery of the ability to read and edit it, we still don’t know what most of the genome is actually telling us. Genes are constantly acting out of place in combination with other variables such as food, environment and body types.

If we are to understand what influences life and biology, we must first understand the language that is DNA. This is where ML algorithms come in and the advent of systems such as Google’s Deep Mind and IBM’s Watson. Now, more than ever, it has become possible to digest immense amounts of data (e.g. patient records, clinical notes, diagnostic images, treatment plans) and perform pattern recognition in a short period of time — which otherwise would have taken a lifetime to complete.

Businesses such as Deep Genomics are making meaningful progress in this realm. The company is developing the capability to interpret DNA by creating a system that predicts the molecular effects of genetic variation. Their database is able to explain how hundreds of millions of genetic variations can impact a genetic code.

Once a better understanding of human DNA is established, there is an opportunity to go one step further and provide personalized insights to individuals based on their idiosyncratic biological dispositions. This trend is indicative of a new era of “personalized genetics,” whereby individuals are able to take full control of their health through access to unprecedented information about their own bodies.

The technology must have access to vast amounts of data in order to better curate lifestyle changes for individuals.

Consumer genetics companies such as 23andMe and Rthm represent a few of the first movers in this domain. They have developed consumerized genetic diagnostic tools to help individuals understand their genetic makeup. With Rthm, users are able to go one step further and leverage the insights produced from their genetic test to implement changes to their everyday routine through a mobile application, all in real time.

As is the case with any application of AI/ML, the technology must have access to vast amounts of data in order to better curate lifestyle changes for individuals. Startups that are focused on mastering the delivery of personal genetics are doing so by considering the following key activities, as highlighted by Japan-based researcher Takashi Kido:

  • Acquiring reliable personal genome data and genetic risk prediction
  • Conducting behavior pattern analyses on people’s attitude to the personal genome to determine what kind of information is valuable/helpful and what type of information is damaging
  • Data mining for scientific discovery

The second point is interesting in that not all genetic information about a patient’s biological predispositions is productive. Being able to control the information in a manner that is conducive to psychological well-being is critical.

Hyper targeted drugs are the future

Another exciting application of AI/ML in healthcare is the reduction of both cost and time in drug discovery. New drugs typically take 12 to 14 years to make it to market, with the average cost hovering around $2.6 billion. During the process of drug discovery, chemical compounds are tested against every possible combination of different cell type, genetic mutation and other conditions relating to a particular ailment.

As the task of doing this is time-consuming, this limits the number of experiments or diseases that scientists can look to attack. ML algorithms can allow computers to “learn” how to make predictions based on the data they have previously processed or choose (and in some cases, even conduct) what experiments need to be done. Similar types of algorithms also can be used to predict the side effects of specific chemical compounds on humans, speeding up approvals.

San Francisco-based startup Atomwise is looking to replace test tubes with supercomputers during the drug development process. The company uses ML and 3D neural networks that sift through a database of molecular structures to uncover therapies, helping to discover the effectiveness of new chemical compounds on diseases and identifying what existing medications can be repurposed to cure another ailment.

In 2015, the company applied its solution and uncovered two new drugs which may significantly reduce Ebola infectivity. The analysis was completed in one day — as opposed to years, which is common using traditional methods of drug development. A recent study by Insilico Medicine solidified the approach Atomwise is taking, showing that deep neural networks can be used to predict pharmacologic properties of drugs and drug repurposing.

The application of AI/ML in healthcare is reshaping the industry and making what was once impossible into a tangible reality.

Berg Health, a Boston-based biopharma company, attacks drug discovery from a different angle. Berg mines patient biological data using AI to determine why some people survive diseases, and then applies this insight to improve current therapies or create new ones.

BenevolentAI, a London-based startup, aims to expedite the drug discovery process by harnessing AI to look for patterns in scientific literature. Only a small portion of globally generated scientific information is actually used or usable by scientists, as new healthcare-related studies are published every 30 seconds. BenevolentAI enables analysis on vast amounts of data to provide experts with insights they need to dramatically expedite drug discovery and research. Recently, the company identified two potential chemical compounds that may work on Alzheimer’s, attracting the attention of pharmaceutical companies.

As advances in ML and AI continue, the future of drug discovery looks promising. A recent Google Research paper notes that using data from various sources can better determine which chemical compounds will serve as “effective drug treatments for a variety of diseases,” and how ML can save a lot of time by testing millions of compounds at scale.

Discovering and managing new diseases

Most diseases are far more than just a simple gene mutation. Despite the healthcare system generating copious amounts of (unstructured) data — which is progressively improving in quality — we have previously not had the necessary hardware and software in place to analyze it and produce meaningful insights.

Disease diagnosis is a complicated process that involves a variety of factors, from the texture of a patient’s skin to the amount of sugar that he or she consumes in a day. For the past 2,000 years, medicine has been governed by symptomatic detection, where a patient’s ailment is diagnosed based on the symptoms they are displaying (e.g. if you have a fever and stuffy nose, you most likely have the flu).

But often the arrival of detectable symptoms is too late, especially when dealing with diseases such as cancer and Alzheimer’s. With ML, the hope is that faint signatures of diseases can be discovered well in advance of detectable symptoms, increasing the probability of survival (sometimes by up to 90 percent) and/or treatment options.

The opportunities continue to grow and inspire healthcare practitioners to find new ways to enhance our health and well-being.

Freenome, a San Francisco-based startup, has created an Adaptive Genomics Engine that helps dynamically detect disease signatures in your blood. To make this possible, the company uses your freenome — the dynamic collection of genetic material floating in your blood that is constantly changing over time and provides a genomic thermometer of who you are as you grow, live and age.

When looking at disease diagnosis and treatment plans, companies such as Enlitic are focused on improving patient outcomes by coupling deep learning with medical data to distill actionable insights from billions of clinical cases. IBM’s Watson is working with Memorial Sloan Kettering in New York to digest reams of data on cancer patients and treatments used over decades to present and suggest treatment options to doctors in dealing with unique cancer cases.

In London, Google’s Deep Mind is mining through medical records of Moorfields Eye Hospital to analyze digital scans of the eye to help doctors better understand and diagnose eye disease. In parallel, Deep Mind also has a project running to help with radiation therapy mapping for patients suffering from neck and head cancer, freeing up hours of planning for oncologists to allow them to focus on more patient care-oriented tasks.

For AI/ML to become pervasive in healthcare, continued access to relevant data is essential to success. The more proprietary data a system can ingest, the “smarter” it will become. As a result, companies are going to great lengths to acquire data (which resides in an anonymized format). For example, IBM bought out healthcare analytics company Truven Health for $2.6 billion in February 2016 primarily to gain access to their repository of data and insights. In addition, they recently partnered with Medtronic to further Watson’s ability to make sense of diabetes through gaining access to real-time insulin data.

As the data becomes richer and the technology keeps advancing, the opportunities continue to grow and inspire healthcare practitioners to find new ways to enhance our health and well-being.

Mobile ad company Appodeal acquires game platform Corona Labs

Appodeal is announcing that it has acquired Corona Labs, creators of the Corona SDK for building cross-platform games and apps.

The companies say the framework has been used to build more than 10,000 games including The Lost City by Fire Maple Games and HoPiKo by Laser Dog. Appodeal, meanwhile, is a mobile ad mediation company — in other words, it helps app developers manage multiple ad networks.

As a result of the deal, Appodeal says the enterprise version of the Corona framework will be made available for free (other versions were already free), and that the framework will also become open source. At the same time, developers building on Corona won’t be limited to Appodeal — they’ll still be able to use any monetization platform that was previously supported, with the Corona team working to build even more ad partnerships.

“We decided to make even more of the Corona platform free because we believe that there should be more opportunities to develop mobile games of high quality on the market,” said Appodeal founder and CEO Pavel Golubev in the acquisition release. “Additionally, Corona will gradually be transformed into an open-source framework with the first components released as open-source soon after the acquisition formalities are complete.”

 Corona Labs has had a rather complicated history. Founded as Ansca Mobile in 2008, it was first acquired by Fuse Powered, then by, whose co-founder Roj Niyogi bought Corona when he left Perk last year. Niyogi said he will remain involved as a strategic advisor, while the Corona engineering team joins Appodeal.

NextGen Venture Partners just raised a $22 million fund from 83 investors

NextGen Venture Partners,  a young, Washington, D.C.-based venture firm that’s quarterbacked by a handful of investors but fueled financially by a network of hundreds of part-time investors who help with its portfolio, has raised $22 million for its debut fund. (This if you don’t count a $1 million pool of capital that it raised from its network in 2015.)

We had a quick chat with Jon Bassett, one of the firm’s five partners, late last week to talk about what NextGen is trying to create. That conversation has been edited for length.

TC: NextGen evolved from a group of angel investors, correct? Was this a formal investor group that’s just been renamed?

JB: We began as a group of young entrepreneurs based in Washington who agreed to support our companies regardless of whether we personally invested. Over time, we had friends in New York City who wanted to expand this idea, and from there NextGen began to take shape. Now, it’s a rapidly growing group of over 650 people who continue to give us an edge in sourcing, diligence, and portfolio support.

TC: Did all of them contribute to this new $22 million fund?

JB: We have 83 LPs in our fund. A large number of them are also our venture partners who invested relatively small dollars. Our anchor LP is Brown Advisory, a $60 billion asset management firm that spun out of the former investment bank Alex. Brown. We also have high-net-worth investors from Dell, Carlyle, and T Rowe Price.

TC: Eighty-three LPs is a lot of LPs to manage. Do you think in the future that you’re likely to seek out bigger checks from fewer investors?

JB: We plan to raise larger dedicated funds over time with bigger check writers, but it’s important we maintain what makes our model so unique. Our strength in deal flow and portfolio support comes from our venture partners. Also, we [do and will] continue to create SPVs where our venture partners have the opportunity to invest alongside our funds.

TC: Do investors in your network get any special rights or privileges if they more actively help your portfolio companies than other investors in the network?

JB: We’ve seen great engagement with our venture partners who participate in portfolio support and investment committees when asked. And yes, these investors are given priority in allocations into our investments. We want to incentivize the venture partners who bring us the best entrepreneurs, so the venture partner who sources the deal gets a piece of the carry on that deal as a result of the introduction.

TC: Is this a full-time job for each of you? 

We are all committed to this full-time.

TC: Are you charging your investors a typical fixed 2 per cent management fee and a 20 per cent performance fee? A  lot of smaller firms out here forego management fees until they establish more of a track record. 

JB: Our LPs are traditional 2 and 20 investors.

TC: What size checks are you writing? 

JB: Our checks range from between $250,000 to $1 million, pending the size of the opportunity.

TC: And what size ownership stake do you target?

JB: We don’t have strict ownership targets. We receive all types of opportunities through our venture partner network, and we don’t want to miss out on a great entrepreneur due to restrictions around company ownership.

TC: Are you investing primarily in East Coast companies? 

JB: We invest in U.S.- based companies.

TC: What are some of your notable investments to dates, and have you had any exits?

JB: We haven’t had any exits yet given our fund began in early 2016, but we have been very happy to find some of the best entrepreneurs by investing alongside some very prominent co-investors. Our last deal was investing alongside Sequoia in [the virtual reality therapy company] Limbix Health, which was sourced through a venture partner. We’ve also invested alongside NEA in [the smart glasses platform] APX Labs [which was recently renamed Upskill] and alongside Bessemer in Renoviso [a marketplace for home improvement professionals], and we are about to close on an investment alongside Founders Fund this week.

TC: I see you also invested in the transportation startup Hyperloop One, which interested me largely because you participated in such a big round. Why?

JB: It was large, but we invested in an early stage that we believe is consistent with our other investments. A core group of our venture partners are very early employees of SpaceX and alerted us to a very talented group of SpaceX engineers who were leaving the company to bring to life Elon Musk’s Hyperloop proposal. These venture partners were angel investing in the round and wanted to include our larger network.

TC: You have offices in Virginia and Washington, both of which have come a long way in terms of its tech ecosystem. Where does it still have ground to make up, in your opinion?

JB: We still don’t have the giant tech companies that anchor an ecosystem to create lots of millionaires with industry knowledge and skills to go out and start the next generation of companies.

How IIoT is revolutionizing utilities

The Industrial Internet of Things (IIoT) is creating huge opportunities in the water and wastewater industries, adding value to both the utility and the consumer. Connected machines are reshaping the way these utilities operate, allowing them to make smarter and more informed decisions. By driving up innovation, water utilities are driving down cost. Here’s what they’re up to.

Treating water and wastewater requires chemical processes that can now be monitored more accurately using digital data collection. These digital transformations are taking the guesswork out of chemical processing and allow utilities to optimize the amount of chlorine dollars spent to maintain safe levels — saving time, money and empowering operators to make fewer mistakes.

Another IIoT development, a new SaaS application that’s set to launch later this month, will calculate wastewater clarifier tank performance — providing quick analysis on a critical step in the wastewater process. The tool, called ClariFind, alerts utilities as they’re getting close to a failure before they experience it. ClariFind will predict when sludge will overflow and be released. This kind of problem causes EPA issues and fines that can run in the millions of dollars. It will also be able to predict a thickening failure, which is when the effluent doesn’t settle correctly and creates a costly sludge blanket in the tank. ClariFind is just one part of a water operations suite of productivity enhancers — solutions as a service.

Predictive analytics are also solving monitoring problems that were not previously possible for utilities. For example, there are a large number of pumps that are commonly found within water facilities, and digitized data is making it possible for companies to accurately predict when these pumps might fail — ahead of time. It’s similar to the predictive analytic technology used in jet engine checks between airline flights. This cloud-based application easily connects to pumps and helps companies avoid costly and inconvenient failures, allowing engineers to schedule controlled maintenance rather than reactive maintenance.

Concepts are in the works to apply this type of predictive technology to residential properties as well, in order to help home owners and property managers predict sump pump failures, for instance, before the basement floods. This technology will be a must-have asset for seasonal homes that don’t have inhabitants year-round. Utilities are leading the way in pilot stages for this type of residential technology.

 Safety procedures are also being monitored and enforced more closely by keeping track of them using digitized technology. In Florida, the water division of the Orlando Utilities Commission is using IIoT technology to remind employees of protocol procedures when dangerous chlorine leaks are detected. The safety procedure is sent to a worker’s device to be confirmed before access to the contaminated area is granted.

Both private companies and government agencies are utilizing IIoT technology to increase efficiency and profitability in water. GE has launched an industrial platform called Predix, a cloud-based platform as a service (PaaS) that enables asset performance management on an industrial scale. For water utilities, Predix will help utilities organize time-series data to monitor asset functionality.

The Environmental Protection Agency has technology that will be used to create a new way to digitally improve the monitoring of water age and water quality. This is a very important issue for consumers because when water ages and sits in a pipe for too long, water quality goes down — which was one part of the problem at play in the Flint water crisis. We expect an analogous approach to the way Google Maps handles traffic to represent the water age, enabling municipalities to monitor this more easily.

Running a water utility is becoming more like running a business. Utilities are no longer solely relying on customers for funding, they’re collaborating and looking at alternative revenue streams to supplement cost. While power utilities have been leading the way on alternative revenue streams, water utilities are now following suit. The District of Columbia Water and Sewer Authority (DC Water) has begun to commercialize their intellectual property, giving them a new revenue channel. For example, they are commercializing their water ammonia versus nitrate algorithm (which is something that keeps the right chemical balance needed for breaking down wastewater) and selling it to other treatment plants.

Partnerships between technology companies and utility companies are facilitating innovation and developing solutions to become cleaner and more efficient at a rapid pace. It truly is a transformative time in the industry, and the results couldn’t be more pure — better drinking water for everyone.