Mice & Machine Learning Help Map the Mind

In a new paper co-authored by Infinia ML Chief Scientist Larry Carin and published in the journal Cell, machine learning gave scientists a new way to understand and treat depressed brains. Today, mice are the subjects. Humans could be next.

DURHAM, N.C., Mar. 1, 2018 — Mice brains and machine learning may lead to a new way to treat depression, according to a new paper published in the journal Cell and co-authored by Infinia ML Chief Scientist Larry Carin, Ph.D.

The paper describes how scientists measured electrical signals in the brains of both observably resilient, active mice and observably depressed, inactive mice. The complexity and scale of the available data, gathered from 18 regions of the brain, then required advanced machine learning for analysis. In effect, scientists trained a learning algorithm to map each brain’s connections. They found a pattern in the resilient mice that differed from the depressed.

Larry Carin, Ph.D.
Infinia ML Chief Scientist Larry Carin, Ph.D.

“We wanted to understand the traffic flow of a healthy brain,” said Carin, the project’s machine learning lead. “That had not been done before, and machine learning helped us overcome that key technical challenge.”

This new understanding of the brain’s electrical system brings new potential for treatment in mice. More importantly, the research lays groundwork for future advances in human mental health. When scientists measure the relevant patterns in human brains, advanced machine learning could help them assess and treat depression.

Meanwhile, Carin’s company, Infinia ML, is already busy applying machine learning techniques to biological and medical breakthroughs from cancer detection to genetic screening.

“Machine learning offers new ways for us to understand our bodies and minds,” said Carin. “And the best part is, we’re just getting started.”

About Infinia ML

Infinia ML empowers companies to make smarter decisions and automate complex business processes by leveraging the latest breakthroughs in machine learning. Infinia ML has a team of leading AI researchers and deep learning experts that have published hundreds of peer-reviewed papers through top machine learning conferences and journals.

Backed by noted private equity firm Carrick Capital Partners, the Durham, North Carolina company is led by CEO Robbie Allen, an experienced AI entrepreneur, and Chief Scientist Lawrence Carin, Ph.D., the Duke University Vice Provost for Research and Professor of Electrical and Computer Engineering. Learn more.

Is Your Business Ready for Machine Learning?

 

Are you ready to implement advanced machine learning solutions in your organization?

Your team’s ability to lower costs, increase efficiency, and achieve new breakthroughs will be shaped by its machine learning background, your data policies, and, most importantly, the actual data you’ll use.

Here are some questions to help you think through your machine learning readiness. At Infinia ML, we use a version of this survey before helping potential clients think through the possibilities. Before you work with us – or any machine learning expert – it’s helpful to know where your team is starting from.

Machine Learning Background

What is your biggest machine learning business need? Why do you think machine learning is the solution?

Have you implemented machine learning before? If so, what frameworks did you use (e.g., Tensorflow, PyTorch, etc.)? What was the result?

How many people on your team have machine learning ability at the following levels:

  • Beginner
  • Intermediate
  • Expert

What machine learning techniques most interest you?

  • Classification
  • Numeric Prediction
  • Natural Language Processing
  • Deep Learning
  • Image Recognition
  • Other
Data Policies

What tools or programming languages does your team use to query, manipulate, and report on data?

What are the job titles on the team that works with the data? (Business Analyst, Data Scientist, Software Engineer, etc.)

Do you use third-party or public data sets? If not, are you open to the idea?

What are your data governance processes?

Your Data

Who owns the data (your company, a third party, the public domain, etc.)?

What kind of data is it?

  • Numeric
  • Text
  • Images
  • Video
  • Other (please describe):

How quickly can your team access the data?

  • Immediately
  • Upon request
  • After getting approval
  • Don’t know

How often is your data updated?

How big is the data set?

Who manages the data?

How is the data stored (local MySQL, AWS S3, Hadoop, etc.)

How sensitive is the data?

—

Are you ready to talk about advanced machine learning? So are we. We look forward to hearing from you!

The Infinia ML Interview Preparation Guide

Three people talking a whiteboard.

If you’re preparing to interview for a technical position at Infinia ML, here’s a heads up on what to expect.

We’re a machine learning company that values learning. In fact, our interview candidates sometimes say things like this:

“. . . I actually learned a lot by thinking through the problems . . .”

“This was a better process than my dissertation defense.”

 “I learned more about machine learning during this interview than I have in the last several years.”

Presentation

As part of the interview, you’ll give a 45-minute presentation to our team. The first five minutes should give an overview of your background. You’ll then have 30 minutes to cover a topic of your choosing, like a project you’ve worked on or your academic research.  In addition to technical depth, we want to understand how you think through a problem. 10 minutes of Q&A will follow your talk.

You can assume a technical audience, and supporting slides will be helpful. Feel free to bring a computer or email slides in advance to your hiring manager. 

Discussion Sessions

Beyond the presentation, we’ll have several small-group discussions to help us assess your:

  • Theoretical/conceptual understanding of machine learning
  • Ability to map theory to real-world challenges
  • Data/coding abilities
  • Cultural fit with our team

Come prepared to be challenged, but know that our team is very friendly and wants you to succeed.

Logistics

Our office is located in Research Triangle Park. The address is 1009 Slater Road, Durham, NC 27703. You can find a map on our contact page.

You can park for free in the lot next to our building. Go through the main entrance and up the elevator to the third floor. Turn left to face the hallway, turn right to go down the hallway, and you’ll find Suite 390 in an alcove on the left. Our space is WAY bigger than that door would have you believe. Please ring the bell and we’ll let you in.

We look forward to meeting you soon!

If you have any other questions, please contact your hiring manager.

Machine Learning Strategy Workshop

Infinia ML offers a one-day, in-person strategy session to help your team learn how machine learning can best add value to your business. CEO Robbie Allen leads the day along with Chief Scientist, Dr. Larry Carin, one of the world’s most prolific authors of advanced ML research.

Each Strategy Day is highly interactive and customized to add value to both business executives and technical experts. Participants will leave the Strategy Day understanding ML’s business potential – and how to distinguish hype from reality.

Participants will also receive a written assessment of their team’s most promising ML projects, including specific implementation steps.

Contact us to learn more.

Sample Agenda

9:00 – 9:15         Welcome

                                      Introducing participants’ ML experience and their goals for the day.

 

9:15 – 9:45         Machine Learning Overview

                                      Introducing ML’s development and the current state of the art.

 

9:45 – 10:15       Idea Brainstorming

                                      Building a list of potential business challenges that ML could solve.

 

10:15 – 10:30     Break

 

10:30 – 11:00     Data Overview

                                      Assessing the data required to create the identified solutions.

 

11:00 – 11:30     Data Deep Dive

                                      Analyzing the technical attributes of available company data.

 

11:30 – 12:00     Most Promising Projects

                                      Debating the highest priority projects, given impact and data.

 

12:00 – 12:15     Break

 

12:15 – 1:15        Lunch and Learn

                                      Diving deep on a chosen technical topic with Chief Scientist Larry Carin.

 

1:15 – 1:45          ML in Practice

                                      Revealing practical lessons on business deployment.

 

1:45 – 2:15          Deployment Discussion

                                      Identifying specific business pitfalls and planning to overcome them.

 

2:15 – 2:30          Break

 

2:30 – 3:00          A Glimpse of What’s Next

                                      Exploring the cutting edge of ML research with Chief Scientist Larry Carin.

 

3:00 – 3:30          Recap and Next Steps

                                      Summarizing the day’s key points, to be delivered in writing the next day.

 

3:30 – 5:00          Flex Time As Needed

 

Many companies have a five-to-ten year backlog of meaningful ML implementations that could automate complex business processes, make existing staff more efficient, and provide new capabilities that were previously not possible.

But while ML is easy to get excited about, it is hard to do well or even initiate. Contact us to learn more about hosting a Machine Learning Strategy Day.

 

Infinia ML’s First Published Papers

When Dr. Hongteng Xu joined our team, we announced that he would “continue his academic research inside Infinia ML, developing the intellectual foundation for advanced business solutions.”

Now, we’re pleased to share that Dr. Xu has already begun rolling out his research, and his work has been accepted by two prestigious conferences taking place this spring.

“Benefits from Superposed Hawkes Processes” will appear at the 21st International Conference on Artificial Intelligence and Statistics (AISTATS). The gathering is one of the top machine learning conferences, with a paper acceptance rate of just 33%.

Dr. Hongteng Xu
Hongteng Xu, Ph.D.

Dr. Xu and his co-authors, who include Infinia ML Chief Scientist Larry Carin, Ph.D., showed the potential to solve the “cold start” problem for recommendation systems. In other words, it may help the kind of systems that suggest products, movies, or music make better recommendations for new users haven’t given the system much data to work with.

Another of Xu’s papers, “Learning an Inverse Tone Mapping Network with a Generative Adversarial Regularizer,” has been accepted by the 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), a top signal processing conference.

In this paper, Xu and his collaborators proposed a new deep learning technique for inverse tone mapping, a process which helps digital images achieve better visual quality. Their innovation beats the state-of the-art tone mapping methods.

Congratulations Dr. Xu – we’re proud to have you on our team, and we look forward to sharing more of your research with the world!

Machine Learning Startup Adds More Duke University Talent

Hongteng Xu, Ph.D., Joins Infinia ML to Publish Cutting-Edge Research and Implement Machine Learning for Enterprise Clients

DURHAM, N.C., Feb. 13, 2018 /PRNewswire/ — Infinia ML, which helps businesses redefine the possibilities of human potential with advanced machine learning, today announced the hiring of Duke University postdoctoral researcher Hongteng Xu, Ph.D., to its data science team.

Xu is the sixth Infinia ML data scientist affiliated with Duke University. Co-founder and Chief Scientist Larry Carin, Ph.D., is Duke’s Vice Provost for Research and Professor of Electrical and Computer Engineering. Infinia ML data scientist Ricardo Henao is an Assistant Professor of Biostatistics and Bioinformatics at the university.

Hongteng Xu, Ph.D.

Xu will continue his academic research inside Infinia ML, developing the intellectual foundation for advanced business solutions. In addition, Xu will assist on select enterprise projects, helping some of the world’s biggest companies reduce costs, increase efficiency, and bring new breakthroughs to the market.

“I am excited to join Infinia ML for two reasons,” said Dr. Xu. “The first is the team’s unparalleled machine learning expertise. The second is the chance to apply my research, creating practical business solutions for the world’s toughest data challenges.”

Dr. Xu holds six patents and has been widely published in the field of machine learning. With his hiring, the Infinia ML team holds a combined total of 35 granted patents, six Ph.D.s, and over 500 published papers.

“In a field driven by academic focus and intellectual firepower, Dr. Xu is one of machine learning’s brightest rising stars,” said Carin, who is himself one of the world’s most-published ML researchers. “The work that Dr. Xu will publish through prominent journals and conferences will put Infinia ML on the front lines of industry innovation and business solutions.”

About Infinia ML

Infinia ML empowers companies to make smarter decisions and automate complex business processes by leveraging the latest breakthroughs in machine learning. Infinia ML has a team of leading AI researchers and deep learning experts that have published hundreds of peer-reviewed papers through top machine learning conferences and journals.

Backed by noted private equity firm Carrick Capital Partners, the Durham, North Carolina company is led by CEO Robbie Allen, an experienced AI entrepreneur, and Chief Scientist Lawrence Carin, Ph.D., the Duke University Vice Provost for Research and Professor of Electrical and Computer Engineering.

Infinia ML Chief Scientist Is Most Prolific Researcher At NIPS 2017

Lawrence Carin, Ph.D, is the most-published author at the Thirty-First Annual Conference on Neural Information Processing Systems (NIPS), with several papers co-authored by Infinia ML founding member Ricardo Henao

DURHAM, N.C., Dec. 4, 2017 — Infinia ML, an advanced machine learning company that delivers transformative automation solutions and predictive analytics to Fortune 500 businesses, announced today that the company’s chief scientist, Lawrence Carin, Ph.D., published ten papers at this year’s Annual Conference on Neural Information Processing Systems (NIPS). This makes Carin the most prolific researcher at the event, which brings together machine learning experts from institutions like Google, Microsoft, IBM, MIT, Stanford, and Carnegie Mellon. In fact, Carin and his co-authors contributed more papers than AI-focused organizations such as Amazon, Tencent, and OpenAI. 

Carin’s papers help advance the field of machine learning by showing that deep learning has important applications across a large range of domains, with important new ideas presented in text analysis, image synthesis, and analysis of dynamic local field potentials in the brain.

“This body of work underscores our commitment to leading this field in cutting-edge research,” explained CEO Robbie Allen. “Lawrence is one of the most respected ML scientists in the world, and the team he brought to Infinia ML is unparalleled. Their research, covering areas including generative adversarial networks (GANs), deep learning, and neuroscience, is on display at NIPS this year, showing the exceptional capabilities of our growing team,” added Allen.

Carin’s work helps Duke University contribute a total of 14 papers, which is a comparable number of papers as IBM, Facebook, and Harvard. Infinia ML founding member Ricardo Henao co-authored four papers with Carin for NIPS.

“With only 21% of papers accepted this year at NIPS, publishing ten is a fantastic achievement and we are very proud to have Dr. Carin and Dr. Henao on our Infinia ML team,” said Mike Salvino, Executive Chairman of Infinia ML.  “The talent of the team and the published research allows us to quickly deliver business impact to our Fortune 100 clients, specifically helping them decrease costs or increase their revenue.”

About Infinia ML
Infinia ML empowers companies to make smarter decisions and automate complex business processes by leveraging the latest breakthroughs in machine learning. Infinia ML has a team of leading AI researchers and deep learning experts that have published hundreds of peer-reviewed papers through top machine learning conferences and journals. Backed by noted private equity firm Carrick Capital Partners, the Durham, North Carolina company is led by CEO Robbie Allen, an experienced AI entrepreneur, and Chief Scientist Lawrence Carin, Ph.D., the Duke University Vice Provost for Research and Professor of Electrical and Computer Engineering.

Infinia ML Lands Robbie Allen As Chief Executive Officer

Founding CEO of Automated Insights to Strengthen Operations, Accelerate Growth, and Oversee Hiring Initiative to Meet Enormous Business Demand

DURHAM, N.C., Nov. 29, 2017 — Infinia ML, an advanced machine learning company that delivers transformative automation solutions and predictive analytics to Fortune 500 businesses, announced today the appointment of Robbie Allen as Chief Executive Officer. Allen rounds out a founding team of AI experts with experience across a range of industries including healthcare, security, and business process automation. Leveraging top machine learning luminary Dr. Lawrence Carin, the Duke University Vice Provost for Research and Professor of Electrical and Computer Engineering, and $10 million in funding from noted private equity firm Carrick Capital Partners, Allen will accelerate the business with aggressive hiring plans. 

“Due to the global shortage of people that understand complex machine learning techniques such as deep learning, nearly every large enterprise has a backlog of opportunity for our automation and predictive solutions,” said Allen. “Most top machine learning teams are part of west coast companies like Google, Microsoft, and Amazon. Infinia ML provides a new option for technical talent looking to work with leading ML experts in an affordable area with a high quality of living.”

Earlier in his career Allen founded and ran the first natural language generation company, Automated Insights, which Vista Equity Partners acquired in 2015. Previously, he was a Distinguished Engineer at Cisco and author of several technical books. Allen has a bachelor of science in computer science from East Carolina University, two Master’s degrees from MIT, and has been pursuing his Ph.D. in computer science with a focus on artificial intelligence at the University of North Carolina.

“Robbie combines a proven operations background with a deep technical understanding of AI, machine learning, and neural networks.  His experiences, which include growing a company in the AI space from the ground up, are exactly what our team needs to meet market demand and serve our rapidly growing client base including enterprise and Fortune 500 companies,” said Lawrence Carin, Infinia ML chief scientist.

“Because of the caliber of Lawrence and the company’s core nucleus of machine learning experts, Infinia ML is in a unique position to attract and train technical experts interested in learning about ML. This is a critical differentiator. Unlike most companies that are limited by the shortage of senior engineers with AI and ML experience, we can leverage our team’s expertise to train our workforce,” Allen explained.  “I’m very excited about the opportunity to work with Lawrence and build a leading machine learning company,” he added.

About Infinia ML

Infinia ML empowers companies to make smarter decisions and automate complex business processes by leveraging the latest breakthroughs in machine learning. Infinia ML has a team of leading AI researchers and deep learning experts that have published hundreds of peer-reviewed papers through top machine learning conferences and journals. The Durham, North Carolina company is led by CEO Robbie Allen, an experienced AI entrepreneur, and Chief Scientist Lawrence Carin, Ph.D., the Duke University Vice Provost for Research and Professor of Electrical and Computer Engineering.

Carrick Capital Partners & Duke’s Lawrence Carin Launch Machine Learning Business

Carrick Invests $10 Million to Deliver Advanced and Transformative Machine Learning Capabilities to Fortune 500 Businesses

SAN FRANCISCO and NEWPORT BEACH, Calif., Sept. 13, 2017  — Carrick Capital Partners, an investment firm focused on technology-enabled businesses including SaaS, Software, BPO and Transaction Processing, today announced their partnership with Lawrence Carin, PH.D., Duke University’s Vice Provost for Research and Professor of Electrical and Computer Engineering, to build a machine learning (ML) company that leverages Carin’s highly sought-after team of Artificial Intelligence (“AI”) experts.

Chief Scientist Larry Carin
Chief Scientist Larry Carin

 

The company will focus on three industries (services, security and healthcare) and three horizontals (text/contracts, images/video and voice/speech).  Deliberately entering the market as a technology services company, the ML business will attain additional marquee clients, capital, and market feedback to fortify their proprietary platform for ultimately establishing a SaaS-based ML offering to serve a rapidly accelerating AI market.

“Larry’s expertise as one of the top ML luminaries in the world and the world class research team of ML scientists he has assembled are unparalleled. They have a track record of empowering companies to reduce required resources, increase efficiency, achieve breakthrough thinking, and predict market conditions impacting business decisions,” explained Carrick Capital Partners Operating Partner Mike Salvino who worked with Larry Carin to deliver machine learning technology to drive business innovation when Salvino was Group Chief Executive at Accenture Operations.

“Carrick has unique and extensive experience building Built for Purpose companies from the ground up.  I’ve been extremely impressed by their knowledge of the process and their ABV (Approach to Building Value).  The resources, networks, market strategy and operational expertise Carrick brings to the table are tremendously valuable in building and ultimately growing and scaling this business,” said Lawrence Carin who will serve as Chief Scientist of the new machine learning company.

“Machine Learning is a very promising area, but there are few established market leaders that have achieved scale.  We are excited by the opportunity to collaborate with this exceptional team to build a great company that will capitalize on a significant market opportunity and deliver great value to Fortune 500 businesses as well as companies within the Carrick portfolio,” added Carrick Capital Partners Co-founder Marc McMorris.

Marc McMorris and Mike Salvino will join Larry Carin as active members of the company’s board.

About Carrick Capital Partners

Headquartered in San Francisco and Newport Beach, Carrick Capital Partners is a growth-oriented investment firm that utilizes ABV (Approach to Building Value) to operationally scale fast-growing, technology-enabled businesses. Carrick adds value by taking a concentrated approach and dedicating significant resources post-investment.  Leveraging decades of experience, Carrick helps scale great companies that deliver excellent returns for investors, stimulating economic growth and positively impacting the industry landscape. Working directly with CEOs and entrepreneurs, Carrick fulfills a vital need for investment capital and growth expertise.