The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)

Today we’re joined by Charlene Chambliss, Machine Learning Engineer at Primer AI. 

Charlene, who we also had the pleasure of hosting at NLP Office Hours during TWIMLfest, is back to share some of the work she’s been doing with NLP. In our conversation, we explore her experiences working with newer NLP models and tools like BERT and HuggingFace, as well as whats she’s learned along the way with word embeddings, labeling tasks, debugging, and more. We also focus on a few of her projects, like her popular multi-lingual BERT project, and a COVID-19 classifier. 

Finally, Charlene shares her experience getting into data science and machine learning coming from a non-technical background, and what the transition was like, and tips for people looking to make a similar shift.

In this special episode of the podcast, we're joined by Kevin Stumpf, Co-Founder and CTO of Tecton, Willem Pienaar, an engineering lead at Gojek and founder of the Feast Project, and Maxime Beauchemin, Founder & CEO of Preset, for a discussion on Feature Stores for Accelerating AI Development.

In this panel discussion, Sam and our guests explored how organizations can increase value and decrease time-to-market for machine learning using feature stores, MLOps, and open source. We also discuss the main data challenges of AI/ML, and the role of the feature store in solving those challenges.

The complete show notes for this episode can be found at twimlai.com/go/432.

In this special edition of the podcast, we're joined by Shalini Kantayya, the director of Coded Bias, and Deb Raji and Meredith Broussard, who both contributed to the film.

In this panel discussion, Sam and our guests explored the societal implications of the biases embedded within AI algorithms. The conversation discussed examples of AI systems with disparate impact across industries and communities, what can be done to mitigate this disparity, and opportunities to get involved.

Our panelists Shalini, Meredith, and Deb each share insight into their experience working on and researching bias in AI systems and the oppressive and dehumanizing impact they can have on people in the real world.


The complete show notes for this film can be found at twimlai.com/go/431

Today we’re joined by Dileep George, Founder and the CTO of Vicarious.

Dileep, who was also a co-founder of Numenta, works at the intersection of AI research and neuroscience, and famously pioneered the hierarchical temporal memory. In our conversation, we explore the importance of mimicking the brain when looking to achieve artificial general intelligence, the nuance of “language understanding” and how all the tasks that fall underneath it are all interconnected, with or without language.

We also discuss his work with Recursive Cortical Networks, Schema Networks, and what’s next on the path towards AGI!

Today we’re joined by Sushil Thomas, VP of Engineering for Machine Learning at Cloudera.

Over the summer, I had the pleasure of hosting Sushil and a handful of business leaders across industries at the Cloudera Virtual Roundtable. In this conversation with Sushil, we recap the roundtable, exploring some of the topics discussed and insights gained from those conversations. Sushil gives us a look at how COVID19 has impacted business throughout the year, and how the pandemic is shaping enterprise decision making moving forward. 

We also discuss some of the key trends he’s seeing as organizations try to scale their machine learning and AI efforts, including understanding best practices, and learning how to hybridize the engineering side of ML with the scientific exploration of the tasks. Finally, we explore if organizational models like hub vs centralized are still organization-specific or if that’s changed in recent years, as well as how to get and retain good ML talent with giant companies like Google and Microsoft looming large.

The complete show notes for this episode can be found at https://twimlai.com/go/429.

Today we’re joined by Devin Singh, a Physician Lead for Clinical Artificial Intelligence & Machine Learning in Pediatric Emergency Medicine at the Hospital for Sick Children (SickKids) in Toronto, and Founder and CEO of HeroAI.

In our conversation with Devin, we discuss some of the interesting ways that Devin is deploying machine learning within the SickKids hospital, the current structure of academic research, including how much research and publications are currently being incentivized, how little of those research projects actually make it to deployment, and how Devin is working to flip that system on it's head. 

We also talk about his work at Hero AI, where he is commercializing and deploying his academic research to build out infrastructure and deploy AI solutions within hospitals, creating an automated pipeline with patients, caregivers, and EHS companies. Finally, we discuss Devins's thoughts on how he’d approach bias mitigation in these systems, and the importance of having proper stakeholder engagement and using design methodology when building ML systems.

The complete show notes for this episode can be found at twimlai.com/go/428.

Today we’re joined by Roland Memisevic, return podcast guest and Co-Founder & CEO of Twenty Billion Neurons. 

We last spoke to Roland in 2018, and just earlier this year TwentyBN made a sharp pivot to a surprising use case, a companion app called Fitness Ally, an interactive, personalized fitness coach on your phone. 

In our conversation with Roland, we explore the progress TwentyBN has made on their goal of training deep neural networks to understand physical movement and exercise. We also discuss how they’ve taken their research on understanding video context and awareness and applied it in their app, including how recent advancements have allowed them to deploy their neural net locally while preserving privacy, and Roland’s thoughts on the enormous opportunity that lies in the merging of language and video processing.

The complete show notes for this episode can be found at twimlai.com/go/427.

Today we’re joined by Jon Wang, a medical student at UCSF, and former Gates Scholar and AI researcher at the Bill and Melinda Gates Foundation.

In our conversation with Jon, we explore a few of the different ways he’s attacking various public health issues, including improving the electronic health records system through automating clinical order sets, and exploring how the lack of literature and AI talent in the non-profit and healthcare spaces, and bad data have further marginalized undersupported communities.

We also discuss his work at the Gates Foundation, which included understanding how AI can be helpful in lower-resource and lower-income countries, and building digital infrastructure, and much more.

The complete show notes for this episode can be found at twimlai.com/go/426.

Digital imagery is pervasive today. More than a billion images per day are produced and uploaded to social media sites, with many more embedded within websites, apps, digital documents, and eBooks. Engaging with digital imagery has become fundamental to participating in contemporary society, including education, the professions, e-commerce, civics, entertainment, and social interactions.

However, most digital images remain inaccessible to the 39 million people worldwide who are blind. AI and computer vision technologies hold the potential to increase image accessibility for people who are blind, through technologies like automated image descriptions.

The speakers share their perspectives as people who are both technology experts and are blind, providing insight into future directions for the field of computer vision for describing images and videos for people who are blind.

To check out the video of this panel, visit here!

The complete show notes for this episode can be found at twimlai.com/go/425

Today we’re joined by Frank Zhao, Senior Director of Quantamental Research at S&P Global Market Intelligence.

In our conversation with Frank, we explore how he came to work at the intersection of ML and finance, and how he navigates the relationship between data science and domain expertise. We also discuss the rise of data science in the investment management space, examining the largely under-explored technique of using unstructured data to gain insights into equity investing, and the edge it can provide for investors.

Finally, Frank gives us a look at how he uses natural language processing with textual data of earnings call transcripts and walks us through the entire pipeline.

The complete show notes for this episode can be found at twimlai.com/go/424.