Q. How does your company help people?

A. Kyso bridges the gap between data and the real world.

 

 This is how it works:

 

-Anyone can upload or create a data science studies, making them shareable with the world

 

-Kyso renders those studies as readable posts so they can be shared with both technical people and non-technical people.

 

-Anyone that comes across an interesting study published in kyso can clone to reuse and extend it really fast, so data-scientists can stop constantly reinventing the wheel.

Q. Where were you when the idea for your company was born? What were you doing?

A. I previously founded a research group in Europe that used machine learning to detect contaminants in water in real time.

An issue that my team and I constantly faced was that there was no good way to convert from data-science tools to publishing & sharing tools, meaning everyone on our team shared studies in different ways.

There was no central platform for publishing our data-science, which meant my team didn't even read the best versions of each other’s studies, and couldn’t reuse them -  we wasted so much time building everything from scratch. This is why we started Kyso.

 

Q. What’s the hardest obstacle your company has faced so far? Have you overcome it, and if so how?

A. When we were originally accepted to the Techstars W’18 program, we knew that a huge focus for the duration of the program was going to be dedicated to growing Kyso’s community, and to do this we decided it was time to make our first hire. This is difficult for a small startup, as we didn’t have a huge network from which we could choose. More so than having good qualifications in marketing and growth, the most important requirement from us was the energy and commitment that person brought to such an early-stage startup. After speaking with a few great candidates, we eventually settled on Eoin’s friend, Kyle. We discussed our ideas, vision, and our future plan for Kyso, and realized that Kyle brought with him all of the qualities we were searching for, and then some. One month later he was part of the team. Great decision.

 

 

Q. What’s the hardest personal obstacle you’ve faced in building your company? Have you overcome it, and if so how?

A. I come from Ronda, a small town in the south of Spain, where everyone knows each other. The total population of Ronda is about half of the Financial District in Manhattan alone, so you can imagine the difficulty I had in adjusting to life in NY, especially when also dealing with the fast-paced journey that is the Techstars program. The different culture, language, and being so far from close family and friends was, at first, hard to get used to.

 

Luckily, I have an awesome team and the friends I made at Techstars made everything so much easier. My fellow founders and other alumni treated me like family. I think a strong support structure is important in the world of entrepreneurship.

 

 

Q. What do you want to be remembered for?

A. At Kyso we are aiming to revolutionize the way people publish, share and consume data science. The world is becoming exponentially driven by data. The number of data scientists around the world is going to increase exponentially over the next few decades. And these data scientists need a central hub to build and share their work. Kyso is the easiest way to do that. Driving the next generation of data science is how we intend to make a difference.

 

Helena Domo

Co-Founder - Kyso

KYSO 

Unification Through Data Visualization

Writer: Jessica Hamlin

KYSO

Unification Through Data Visualization

Writer: Jessica Hamlin

Data Science: a field that can seem quite intimidating to the average inquirer. But as the world becomes increasingly consumed by the analysis, creation, use and misuse of data, it’s becoming increasingly important that professional grade analytical tools become available and accessible to the average person.  

 

Kyso is a rapidly expanding start-up company that aims to do just that—bridging the gap between the technical and non-technical worlds by allowing users to upload reusable data-science studies in the form of blog posts.

 

Kyso allows its members to use and share data science models, which not only means that data scientists now have a more efficient method of recording data, but also that an amateur data-analyst can have access to professional tools to facilitate discovery. The blog structure makes posts accessible to the general public and creates consistency in a world fraught with inconsistent methods of data visualization: Kyso is a one-stop-shop for all-things data.

 

Studies posted on Kyso’s website can be duplicated by other users and used for further research. Whether you’re analyzing the fluctuations of the automobile industry or simply curious about the effects of changing weather patterns on the amount of bicyclists on the road, Kyso provides a platform that renders accessible information that was previously only possessed by a select few.

Kyso presents the unique opportunity for users to share information and findings, creating the potential for a faster and more collaborative route to unveiling critical and unparalleled discoveries. We sat down with Kyso’s Co-Founder & COO Helena Domo to learn more about the company's revolutionary ideas about the future of data visualization and analysis.

Q. How would you define Kyso as a company in one phrase or a sentence?

A. Kyso is a community platform for data scientists, to create, publish and share reusable data-science studies. Our users can upload existing jupyter notebooks to Kyso, where they are published straight to the web and rendered as beautiful blog posts. Published studies can then be cloned and extended using our cloud jupyter data-science environment.

"A strong support structure is important in the world of entrepreneurship."

In a world of uncertainty, Kyso provides a hub of coherence. As the company embarks upon the journey of a start-up, it is driven by an all-encompassing purpose: unification through data visualization.​

Data Science: a field that can seem quite intimidating to the average inquirer. But as the world becomes increasingly consumed by the analysis, creation, use and misuse of data, it’s becoming increasingly important that professional grade analytical tools become available and accessible to the average person.  

 

Kyso is a rapidly expanding start-up company that aims to do just that—bridging the gap between the technical and non-technical worlds by allowing users to upload reusable data-science studies in the form of blog posts.

 

Kyso allows its members to use and share data science models, which not only means that data scientists now have a more efficient method of recording data, but also that an amateur data-analyst can have access to professional tools to facilitate discovery. The blog structure makes posts accessible to the general public and creates consistency in a world fraught with inconsistent methods of data visualization: Kyso is a one-stop-shop for all-things data.

 

Studies posted on Kyso’s website can be duplicated by other users and used for further research. Whether you’re analyzing the fluctuations of the automobile industry or simply curious about the effects of changing weather patterns on the amount of bicyclists on the road, Kyso provides a platform that renders accessible information that was previously only possessed by a select few.

Kyso presents the unique opportunity for users to share information and findings, creating the potential for a faster and more collaborative route to unveiling critical and unparalleled discoveries. We sat down with Kyso’s Co-Founder & COO Helena Domo to learn more about the company's revolutionary ideas about the future of data visualization and analysis.

Cryzen: Algorithmic Trading Gets Democratized

Managing cryptocurrency market trades doesn’t have to be cryptic - or time consuming. The team at Cryzen is on the fast track to integrating machine learning and custom algorithms to investors of the cryptocurrency market, all while hosting a XEN token bounty program that supports learning coding.

4 AI Solutions for Fast-Growing Startups

Artificial intelligence has been progressing rapidly since the coining of the term in 1956. Less than a century later, it is not uncommon to find AI systems, such as the Google Home, in the workplace, and similar AI have been present on phones in the forms of Siri and Google Assistant.



Implementing AI into the workplace can be costly if the AI is built from scratch, and Daniel Faggella of Techemergence notes that the use of AI is not conducive to all business practices and should therefore be thoroughly considered before moving ahead and paying for experts in AI, such as data scientists who could cost over $100k in certain cities.

New Software Aims to Revolutionize Scheduling

Communication between employees and employers can cause conflicts in scheduling and inevitably a loss of money as a result of over- or under-staffing shifts. This is common in retail and food service, but one app called ShedWool eliminates these problems through their modern and affordable scheduling system.

Startups Turn to Micro-Influencers to Maximize Marketing ROI

The use of traditional influencer campaigns on Instagram, Twitter and Youtube are an effective means to capture a target audience. Accounts with followers of 500,000+, like Instagrammer @kimberelymargarita_, make an estimated average of $2,000 per sponsored post, and some influencers with followers in the millions could make $25,000 per sponsored post.

Secretive A.R. Startup Magic Leap Unveils Its First Product

After almost four years of developing their mixed reality tech in secret, or as they called it, ‘stealth mode,’ and raising a total of $2.3 billion dollars in investment, Magic Leap has finally released its first product.

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Q. It’s 10 years in the future and you sit down at your desk to work. What are you working on?

A. I love what we’re doing at Kyso, helping to increase collaboration and transparency in the world of data science. When I imagine myself 10 years from now, I am still involved in this space, perhaps designing the next-generation tool that will improve data visualisation. Fundamentally, I am excited about continuing to help people tell interesting and important stories with data.

 

Q. What is it that makes your company unique? Why do you think people have taken an interest in it?

A.So, there are a lot of other companies in this space, providing jupyter-hosted cloud solutions. However, what makes Kyso unique is that we are a community where people are reusing and publishing better studies all the time, as opposed to a simple platform where you need to build models from scratch. At Kyso, we have also abstracted away all of the devops required to use a lot of other platforms - we take care of the entire underlying infrastructure, allowing our users to focus solely on the data science.

Q. Employment Status: Are you currently hiring, and if so what positions?

A.Yes, we are currently looking to hire a Backend/API Engineer over the next few months. This hire will do the following:

 

Design, build, and maintain APIs across Kyso’s offering.

 

Connect with cloud systems such as AWS and GCP to run data-science environments.

Build and manage container images and run container clusters to host our environments.

 

Experience required:

 

Experience with docker and containers, and running them in the cloud.

 

Experience with AWS cloud systems and networking.

 

Anyone who is interested should contact us at eoin@kyso.io

 

MOAD COMPUTER 

Artificial Intelligence -- Intelligently Designed

Widespread concern over our eventual AI overlords begs the question: what kinds of minds will engineer these complex, intelligent systems? The likes of Rahul Remanan seem up to the challenge. After graduating from India’s most prestigious medical University, receiving a Doctorate in Neurology from Cornell, founding Nanoveda, a company developing ground-breaking cancer therapies, and Ekaveda, a tech-based think tank, Remanan is turning his attention to AI. Founding Moad Computers, he builds the hardware that runs sophisticated neural nets for American enterprises.

 

We sat down to talk to Remanan about how his AI company is selling businesses what is perhaps the most valuable commodity: intelligence.