AI Podcast in 26.1 Minutes

Brian and Don welcome a much anticipated guest for this episode, Professor Fernando Perez joins us for an episode of 26.1 AI Podcast. Dr. Perez speaks about his journey, the community, and all the challenges along the way. Fernando shares in his inimitable style, how he journeyed from straight laced physicist in pursuit of an academic career to doggedly ignoring naysayers and creating one of the most important components of the modern PyData stack. One personal challenge during this journey was losing a friend Dr. John Hunter. John also influenced your host Brian Ray. Though John missed collaborating when Fernando set out with IPython because of conflicts from prior commitments, the two joined in later to collaborate on advancing tools data scientists use every day now. Sit back and enjoy Fernando's dexterity on multiple topics as hosts Brian Ray and Don Sheu hold on for the ride for your benefit listener.

[Part 1 of 2] Listeners join in for a wonderful conversation in this episode. Our guests Matthew Rocklin and Hugo Bowne-Anderson are extending access to powerful distributed computing for more data users with their startup Coiled (https://coiled.io/). Data scientists with a two minute download of Coiled’s software (https://cloud.coiled.io/) can scale their work to the cloud. We discuss during the episode how conversations with the open source community resembles early customer conversations commonly used by entrepreneurs in a lean startup framework. Dask’s creator and Coiled founder Matthew described his software design approach that has a decided minimalist bent. A great benefit for users of popular Python libraries because of Matt’s approach is a familiar interface when using Dask or Coiled to extend the power of popular PyData stack tools. Our conversation turns to how Coiled has the capability to extend more computation power to many casual users of Python who are interested in solving data problems pragmatically without rebuilding a data factory every time. [Join us next week for Part 2]

Tileli Amimeur changed direction from a fast track traditional software career based on intriguing invitation to apply coding to biology. This shift followed study in undergrad and grad schools at University of Texas, and a string of jobs with top notch traditional technology companies. Now Tileli is happily applying computation in search of important cures with an interdisciplinary team of AI experts, biologists, and chemical engineers. A must listen no matter your day job. Listen for an understanding of how AI is touching every point of human experience, including coding proteins for cures.

Our prior guest e2f CEO Michel Lopez introduced this week's guest. Intento founder Konstantin Savenkov walks us through a tutorial on how to buy and sell AI. A dense episode worth a listen both for anyone considering buying AI for an enterprise, and founders seeking to sell an AI product to buyers. Intento serves companies making sense of 32 different possible translation vendors. Intento identified the complexity presented to buyers by such a large population of possible vendors as a good market opportunity for building a company. For startups seeking to find product market fit, Konstantin shares step by step the series of decisions that led Intento to concentrate on helping companies with selecting machine translations vendors. We discuss some practical advice on pitfalls many enterprises encounter trying to force procurement process built for buying traditional software onto decisions on new work processes created by AI products.

Our guest Kingsley Ndoh, MD has a global health project centered in Ondo state in Nigeria, where he endeavors to collect the largest set of cancer related data on people of African descent. We discuss during the episode, before algorithmic bias, how biased decisions about data collection has fatal consequences for cancer patients of African descent. Dr. Ndoh speaks about how Black Panther star Chadwick Boseman was far younger than current guidelines in the United States for early screening of colon cancer. Perhaps guidelines would change for the age to start early screening of cancer if we had the data on diverse populations. Listen all the way through for a consequential discussion that may help guide you as you practice your profession. Dr. Ndoh started out life in Jos, Nigeria. After training as a physician, he pursued his systems level interest in healthcare with further study at the University of Washington. He completed a masters in public health at UW, and since completing the degree he's joined the faculty.

Our guest for this episode shares with us the challenges their firm e2f faces when collecting data for training voice AI applications. Michel Lopez started early on and researched AI and taught the subject in Saudi Arabia and Thailand before the advent of cloud. Instead of practicing AI following teaching, he took a left turn into applying his multilingual skills to performing translations for technology companies. Serendipity brought Michel a new opportunity when a translation customer asked for help collecting voice data. Voice is our computational interaction for the future. Take a peek on how we're getting to this future in this latest episode of 26.1 AI Podcast

Our guest this week Shreya Nallapati founded an organization to help prevent mass shootings. From the #NeverAgainTech website, a quote from Shreya explaining her passion for this project, "I founded this organization after hearing Emma Gonzalez's powerful speech. Growing up with Columbine, I was tired of hearing friends and family being impacted, without being able to do anything about it. So I naturally took the areas I am specialized in, artificial intelligence and data mining. Currently, over 105 teenagers, policymakers, and industry professionals are participating in this project." Importantly, Shreya contrasts #NeverAgainTech against vendors selling tech to law enforcement. Included in the comparison is what #NeverAgainTech has done to ensure they're not part of the problem with introducing a new form of bias with AI. In this episode, learn more about this rising star in AI. Thank you to our friend Ruthe Farmer of CSforALL and Last Mile Education Fund for introducing this week's guest.

Our guest this week on 26.1 AI Podcast is the long time Open Source Guru Ian Bicking. If you are a Python developer and ever typed, "pip," at the command line you can thank Ian. On this episode, he speaks on voice as a computing interface and some of the etiquette of addressing our assistants. How soon will AI improve to the point of being emotionally manipulative with users? Do you want to grade essays turned in by college students, cheating with GPT-3?

Our host Brian Ray's staff colleague David Law joins with a special treat. David has led development of an open source project titled "data⎰describe". This Python package accelerates exploratory data analysis. David also shares how he transitioned from studying material science at Cornell to completing a masters in data science at Northwestern and practicing as a data scientist at Maven Wave. We manage to add to the episode, how AI experts feel about riding in a self driving car, right now.

During the episode we discuss something Professor Beck is passionate about, getting more scholars into the data science fold. University of Washington's eScience Institute launched in 2008. Its practice has changed over the years as it examines how to extract knowledge and useful actionable information from data. An effort that started out serving engineering and science disciplines, now includes arts and humanities scholars. David helps foster the interdisciplinary sharing of knowledge to apply data approaches across many subject matters. We explore how Dr. Beck's undergraduate computer science studies set the ground for what turned out to be a search to deliver impact for the good of society. Great work happening at the University of Washington and in with David's personal research. Hear about it in the latest episode of 26.1 AI Podcast.

Our friend Ruthe Farmer the Chief Strategy Officer of CSforALL and founder of Last Mile Fund brought to our attention amazing women of her network embarking on careers in data, analytics, ml, and artificial intelligence. First in an upcoming series, we have Divya Nagaraj join us from Houston as she completes her Facebook internship remotely during COVID-19. For the upcoming academic term, Divya will matriculate in her sophomore year at Stanford. She shares with us some of the work she's doing in a research lab at Stanford that touches on computing and medical research. Listen this week and get a glimpse at the coming wave of new talent.

International tour continues with a stop in Singapore with a Korean managing partner of a venture fund subsidiary of a Japanese ecommerce and fintech giant. Our 21st episode of our 2nd season is your most globalized episode ever.

Brian and Don have worked hard over many years building community for Pythonistas. Wonder how many folks in the Python community knows about Uruguay as a hotbed of Python use. Tryolabs has been slinging Python and ML for the past ten years. Besides helping nearshore customers in the U.S. solve business challenges with AI, Tryolabs spun out a successful startup, MonkeyLearn. Ernesto Rodriguez di Paolo our guest for this episode presented MonkeyLearn for a PyCon Startup Row event hosted by Grace Law and SF Python. MonkeyLearn won over an impressive judging panel to win a place at PyCon Montreal 2015. Judging panel included bethanye McKinney Blount, founder of Compaas; Leah Culver, founder of Breaker; Bebe Chueh, founder of Atrium LTS; Kat Manalac, partner at Y Combinator; and Christine Spang, founder of Nylas.

In this episode we discuss with Alex how executives should think about the decision of buying of-the shelf software solution vs. building the solution in-house, by yourself or with a partner. The conversation includes an overview of the pros and cons of each from both financial and technical perspective. We leave the audience with some actionable advice on how to go through the decision calculus on the question that increasingly faces today’s CXO’s who are looking to take their firms through the digital transformation. Alex Vayner is a Partner and Americas Data & AI Practice Leader for PA Consulting Group, a global innovation consultancy with a mission to bring ingenuity to life. He consults Fortune 1000 companies on becoming insight-driven enterprises through the use of machine learning techniques, Artificial Intelligence and cognitive technologies.

Our 26.1 AI Podcast's global tour continues with a visit with Chris Loy founder of London startup Datasine. Datasine applies machine learning to help companies talk with their customers more meaningfully and at scale. From Datasine's website, "We use machine learning, psychology and cutting edge tech to understand people and the content that appeals to them, and to help our users revolutionise how they engage with their customers at massive scale." Chris shares his personal journey of starting out at Oxford as a student of general physics, moving later as part of a combined bachelors and masters program into astrophysics and particle physics. After working in general programming jobs, Chris started the transition to becoming an expert in machine learning with a degree from University College London with a MSc degree in machine learning.

Brian and Don host Just One Giant Lab founder Leo Blondel. JOGL melds open source software practices with scientific research. Members can treat their research projects like software engineers commit code. Also community spin up groups for research projects like an OpenCovid19 group. From the JOGL website, "[This is] a JOGL program that develops open-source and low-cost tools and methodologies that are safe and easy to use in response to the COVID-19 pandemic. The OpenCovid19 program is powered by a global community of 4000+ volunteers and experts who create solutions to better prevent, detect, and treat COVID-19, and to help forecast the pandemic’s evolution." Brian and Don learn from Leo that Montpellier is France's tech capital. The city is home to many of America's tech giants' offices.

Our 31st episode is our first international exploration visiting with Phaze Ventures's Managing Partner Masoud Al -- Rawahi. Headquartered in Muscat, Oman, Masoud and his partners are building up a tech ecosystem from scratch. They are determined to chart the path forward for an economy tethered solidly to the current carbon economy. Learn about the bits and bots opportunities for making traditional oil business cleaner. One pain point technologists are solving is a better solution for handling wastewater. Phaze Ventures and Masoud have secured a partnership with Oman's largest firm and employer, Petroleum Development Oman. Through this partnership, entrepreneurs gain access to a gusher of data flowing from devices connected to delivering carbon products to the world. Oman invites the world's innovators to investigate the blue ocean opportunities available in a market catching up to the world's more developed startup centers.

Dr. Beverly Wright talks about how she stays connected to Universities and Institutes. She explains how Corporate America can connect better with schools and activate the students for purposes of gaining insight into organization's data and promoting recruiting brand awareness amongst students. Dr. Wright brings over twenty years of research, analytics, and insights experience from corporate, consulting and academia.

Don Miner speaks candidly about his AI firm being acquired by the large entity Atos where he joins host, Brian Ray. He was an early innovator in Big Data and quickly moved into the AI space. Today he continues to innovate yet still finds time to teach on his passion topics to the local university.

Gert De Geyter started his journey towards AI, modeling our galaxy as a notable astrophysics scholar. to He transitioned from academia to solving business problems using AI at Deloitte Belgium. He is now in the United State with Deloitte Consulting, based out of NYC. During this episode, Dr. De Geyter speaks about the universe of AI (pun intended by Brian Ray) and how it translates to adding business value in his practice. In this episode we cover everything from lightwaves to beer, and potatoes. Fries are Belgian!

Traditional wet lab approaches to find a cure for COVID-19 could take decades. Using artificial intelligence, Andrew Satz and Brett Averso are saving ImmunoPrecise Antibodies years on years and millions of dollars in an attempt to find a novel coronavirus antibody. Where Brett concentrated on the technology for our listeners, Andrew adds his CEO view on the problem they're tackling. We publish another ad-hoc COVID-19 episode for our audience, as we all work towards solutions to this pandemic. Anybody working on COVID-19 tracking and cures, please let us know. We'd love to have you on and build awareness of your efforts. Email us, tweet at us, send us basket carrying Shar-Pei couriers. Please be safe! Remember, we're urging everyone to act in a predictive way. Current state is not necessarily our future reality.

The name "EVQLV" looks itself like a amino acid sequence. Digging deeper, Don and Brian share with our listeners this fast-paced startup leading the race to find a treatment for COVID-19. Brett Averso, CTO, talks about how EVQLV with a small team of Data Scientists use Machine Learning in the cloud to run simulations that would have taken months to years in just days. Novel AI; for a novel treatment; for a novel pandemic. Keep safe, keep a distance.

Hi folks, we just wanted to check-in with everybody. Our normal publishing time is 2am, Tuesday. Last week we missed publishing an episode, because we wanted to take a moment to ponder how best to serve you during this pandemic. If you're working on data science, analytics, ML, and AI related to COVID-19, we'd love to invite you join us and get help from our audience. As we seek guests who can help you understand where we're headed, we'll publish on an ad-hoc basis. Here's to all of you staying safe! Act in a predictive way.

Bryan Hale, managing director of AI2's incubator, shares what his org is doing to support AI entrepreneurs. We discuss favorable outcomes from Seattle's AI startup ecosystem like Turi and Xnor.ai. Bryan also includes actionable advice for new founders of AI startups.

Revisit the early days of Travis Oliphant's contributions to scientific Python and by extension Python's relevance to AI. Catch-up on the high energy, current efforts of the creator of NumPy, SciPy, Numba, and Conda. Travis also founded the NumFOCUS Foundation. NumFOCUS is backing Jupyter and Pandas. In this Episode, we break our 26.1 Minutes rule for a really great and important chat with this legend of Data Science. Enjoy an extra few minutes.

Scott helps customers apply AI, NLP, and ML to reduce their technical debt. He comes from the front lines document management industry for over 20 years and provides a unique perspective into the usefulness of AI.

Brian and Don recap the most recent ten episodes of 26.1 AI Podcast. For new listeners or anybody catching up on missed episodes, this edition provides a nice index to plan your listening. For those new to AI and looking to catch up to the wave of interest engulfing business leaders, great episode to learn keywords important for your study.

During this Episode we speak with Dominique about how she repurposed her academic research in the areas of neuroscience, music cognition, psycholinguistics, and multisensory perception for her current work in data science. She speaks about her progression from tools like Matlab to open source Python-based tools. We explore the value of diversity in the workspace.

Our 19th episode's guest Denny Lee joins us to share some of the developments at Databricks. Also, he shares a persuasive argument that traditional data professionals like DBAs have a future in ML and AI.

"If you follow your passion and marry it with Data Science, it can really take you to great places," says Jason Moss. In 2013, Jason launched Metis a data science bootcamp (now a part of Kaplan). Starting in Boston as Ruby on Rails Bootcamp, Metis pivoted quickly into a Data Science Bootcamp six months later. Jason offers his opinions on the quickly changing job market tagged broadly as "Data Science." He speaks about the personal journeys of his motivated students who wish to take it to the next level. Our guest shares how curiosity drives students to do what they love and succeed n their careers.

This episode introduces our audience to perhaps one of the rarest AI practitioners, an AI serial entrepreneur. Alex Poon with his first AI startup x.ai, helped users recapture lost time spent scheduling meetings. X.ai also rehabilitated the term AI after a long winter for the discipline. Today’s visit with Alex, we revisit early days when he built x.ai and had to custom craft many tools available as readily accessible open source projects today. Our guest provides a comparison on building an AI startup a short five years ago and what's it take today. We discuss the high stakes involved when applying AI to human lives at AiCure. This week’s guest votes for AI as a positive force for advancing human knowledge and lives.

Second part of our 2 part series with Anaconda founder and CEO, Peter Wang, we get to the core reason why this podcast exists. We want everybody more literate about the tech wave that promises to fundamentally change how we live. In this session, Peter reminds us how in the atomic age, people wanted nuclear underwear. With nuclear power, though, the possible devastation is palpable for a casual observer. Do average users of AI understand that irresponsibly deployed AI can harm people, societies, and the world around us? One tableau Peter draws to illustrate how folks may underestimate the destructive power of AI, is a table and a smart speaker in the room. Most consumers using smart speakers and associated assistant personas don't know that there's massive computing power behind the interaction. We come back to humans and the importance of practitioners to become Dirk Gently holistic detectives of AI. We come to a conclusion familiar to listeners. Experts deploying AI, need to take the wider view of our work and impact on humanity.

In the Python world and in the scientific Python world especially, Peter needs no introduction. Anaconda's CEO shared with us, "Anaconda has more users than World of Warcraft, Matlab, SAS, Tableau, and Dropbox Combined." We had so much fun, our conversation ran long, long enough for 26.1 AI Podcast's first serial two part interview with a guest. During our conversation, Peter gets philosophical. As a technologist and a practitioner he discusses the hype v. reality. Our guest posits there is an, "honest path," how Peter believes technology can be leveraged for human good. A big takeaway from this episode is that there's no configuration toggle for ethical AI. Ethics starts with the human in the loop creating the AI.

For those listening and seeking information about how to launch a career in data and AI, we go deeper than any prior episode into an investigation of how folks become professionals in the space. We interview in this episode Jennifer Shin, an AI practitioner fluent in business. We touch on what launched Jennifer on her path to data and evidence. A search for answers added skills and experience in coding and analytics in our guest's toolbox. in addition to practicing AI, she's forging future leaders in the field through her teaching at NYU.

Kripa Rajshekhar joins us this week with a discussion on human centric AI. Kripa is committed to updating his knowledge on the latest in AI. He is the founder of Metonymize, a team committed to Third Wave Artificial Intelligence. They have a big win applying this AI to law. In the Summer of 2017, a Metonymize algorithm passed a "Turing Test" equivalent for patent law. The Metonymize team has a combined 100+ years of experience on the cutting edge of Artificial Intelligence. They build solutions with economics that are 10-100X better than "Big Data" reliant Machine Learning.

Today, Michael provides us our first truly futurist episode. He shares with us optimism that Apple will catch up in AI, takes us through the benefits of AI on chip, and shares with us that better algorithms will catch up to those who hold a huge data advantage.

This week we host Jim Ni for a discussion that business leaders will love. A goal for Brian and Don is to reach non-practitioners and help them drive forward AI adoption in their orgs. Thanks to Jim's concise explanation of what he's discovering with financial services firms needs, our business audience will get a lot out of our latest episode.

Don and Brian do a quick 26.1 recap of the previous 9 episodes and discuss some trends they are seeing driving this popular podcast. Good episode to start with if you haven't listened yet. Use this recap as an index to find episodes you want to listen to first.

For episode 9 of 26.1 AI Podcast, our guest Andrea Brice takes us back to early days of mobile telcom. She hacked together data science and algorithms reviewed by the C-suite at McCaw Cellular that became Cingular then AT&T Wireless. Making it all work on top of Oracle relational databases, Andrea shares how excited she was to find open source tools when she left telcom. Also our guest reminds of the engineering rigor present in telcom teams that we sorely need as AI and data science mature as practices. Though Andrea makes a strong case that data science was going on a long time before DJ Patil coined the term coined the term for the benefit of his HR colleagues and simplify the many job positions various flavors of analysts. Yet another guest of 26.1 with great insight and deserving of a series of episodes.

Our guest this week, Dr. Rajiv Shah, recently generated a lively discussion on Reddit. Subject of the debate was reproducibility of an article published in the notable science journal Nature. In this case unlike episode 7 of 26.1, where Dr. Rachael Tatman touched on her efforts to get industry AI folks to follow academia’s standards for reproducibility, Dr. Shah shared how using the same dataset as the article authors, he was unable to reproduce the results. In this case the aim of the paper's authors were to predict aftershocks of Haiti's disastrous earthquakes, a disaster the country and its people continue to struggle with today. Though we open our discussion about the buzz Raj got on Reddit, like every episode, we manage a discursive discussion in 26.1 minutes that touches on AI in manufacturing, C-level leaders getting to speed with AI practices, and the need for lay people to acquire a literacy about AI methods.

This week’s episode may be our most cerebral to date, probably thanks to hosting our first University of Washington Husky, Ph.D. graduate. Dr. Rachael Tatman shares snippets of her experience at Kaggle, stochastic approaches to ML models, errors in ML models, understanding prediction, and importance of reproducibility. A big takeaway references Dr. Tatman’s PyCon talk, “Put down the deep learning: When not to use neural networks and what to do instead.” We explore how many businesses benefit from a simple linear regression model instead of investing millions of dollars of compute time to a deep learning approach. Included with our conversation with Dr. Tatman is a discussion of linguistics and will Don ever get accurate translations of his Korean friends’ tweets in real-time. So far, our conclusion is that we’re far away from the singularity. Episode seven of 26.1 AI Podcast delivers lots of value for business leaders contemplating their future AI strategy.

This week we have Algorithmia founder and CTO Kenny Daniel. Algorithmia has grown tenfold over the past six years, and the startup just completed a $25m Series B raise in May. Perhaps our densest episode to date, we manage to pack a lot into a nearly perfect 26.1 minutes. We cover in this episode -- Algorithmia’s founding story with Kenny’s fellow founder Diego Oppenheimer, challenges bridging the culture between traditional software professionals and the current practices of AI professionals, needs for analogs for prosaic software tools tailored for AI deployment, and will the data engineer job title survive as AI matures.

This week’s guest Mark Hoffman shares how exposure to data analysis in a nuclear physics lab led to him joining years later NASA Jet Propulsion Laboratory as a data scientist. At NASA, he’s repurposed ML work he delivered on fraud detection for one of the country’s largest healthcare orgs for NASA’s projects where spacecraft sensors deliver many false alarms. Included in this episode is Mark’s experience launching a successful startup applying ML for black car services. This startup was successfully sold. Some of the computing infrastructure challenges our guest solved as part of his startup foreshadows our future guest Kenny Daniel’s episode. Kenny a founder of Algorithmia is working hard to save data sciences from the overhead of wrestling with computing infrastructure and concentrate on delivering more data science, ML, and AI, faster.

In this interview we speak with Venice, CA based tech insider Everett Carney on broad range of tech topics including blockchain, GANs for players to generate custom goods within games, and compliance around AI. Along with some future thinking and optimism about AI/Blockchain, out guest sprinkled in some precautions as well.

Meet Ramkumar Hariharan head of applied AI at macro-eyes. A startup, macro-eyes has won two Bill and Melinda Gates Foundation Grand Challenges Explorations awards. Learn how appearing on Indian television and radio contributed importantly to Ram’s journey becoming an AI practitioner and educator. Also how Ram and team deploys AI in India, Africa, and Seattle to improve medical outcomes for access to care and effective vaccination programs. Once again, learn about AI in an easily digested 26.1 minute session.

Don and Brian interview a machine learning veteran Avilay Parekh. He was one of the 60 original creators of Microsoft Windows Azure platform, has helped an IoT startup use machine learning on circuit printed socks, was an engineer at Amazon, and now is launching the ability to create 3D simulations of real life cities and places on the Unity platform for training AI models dependent on visual data.

Terrazas is the AI LA President @aila_community and Founder @grassy_vibe. Don and Brian ask Todd about his progression toward becoming a story teller in the AI Space, current involvement, travels, the LA AI Tech scene, and future events.