Data Science Conversations

At LanguageTool, Bartmoss St Clair (Head of AI) is pioneering the use of Large Language Models (LLMs) for grammatical error correction (GEC), moving away from the tool's initial non-AI approach to create a system capable of catching and correcting errors across multiple languages. LanguageTool supports over 30 languages, has several million users, and over 4 million installations of its browser add-on, benefiting from a diverse team of employees from around the world. Episode Summary -

In this enlightening episode, Dr. Julia Stoyanovich delves into the world of responsible AI, exploring the ethical, societal, and technological implications of AI systems. She underscores the importance of global regulations, human-centric decision-making, and the proactive management of biases and risks associated with AI deployment. Through her expert lens, Dr. Stoyanovich advocates for a future where AI is not only innovative but also equitable, transparent, and aligned with human values. Julia is an Institute Associate Professor at NYU in both the Tandon School of Engineering, and the Center for Data Science. In addition she is Director of the Center for Responsible AI also at NYU. Her research focuses on responsible data management, fairness, diversity, transparency, and data protection in all stages of the data science lifecycle. Episode Summary -

Luis Moreira-Matias is Senior Director of Artificial Intelligence at sennder, Europe’s leading digital freight forwarder. At sennder, Luis founded sennAI: sennder’s organization that oversees the creation (from R&D to real-world productization) of proprietary AI technology for the road logistics industry. During his 15 years of career, Luis led 50+ FTEs across 4+ organisations to develop award-winning ML solutions to address real-world problems in various fields such as e-commerce, travel, logistics, and finance. Luis holds a Ph.D. in Machine Learning from the U. Porto, Portugal. He possesses a world-class academic track with high impact publications at top tier venues in ML/AI fundamentals, 5 patents and multiple keynotes worldwide - ranging from Brisbane (Australia) to Las Palmas (Spain).

In this episode Tarush Aggarwal, formerly of Salesforce and WeWork is back on the podcast to discuss the evolution of the Semantic layer and how that can help practitioners get results from LLMs. We also discuss how smaller ELMs (expert language models) might be the future when it comes to consistent reliable outputs from Generative AI and also the impact of all of this on traditional BI tools.

In this episode Patrick McQuillan shares his innovative Biological Model - a concept you can use to enhance data outcome in large enterprises. The concept takes the idea that the best way to design a data strategy is to align it closely with a biological system. He discusses the power of centralized information, importance of data governance, and the necessity for a common performance narrative across an organization. Episode Summary - - Biological Model Concept - Centralized vs. Decentralized Data - Data Collection and Maturity - Horizontal translation layer - Partnership with vertical leaders - Curated data layers - Data dictionary for consistency - Focusing on vital metrics - Data Flow in Organizations - Biological Model Governance - Overcoming Inconsistency and Inaccuracy

In this episode Heidi Hurst returns to talk to us about how in her current role at Pachama she is using the power of machine learning to fight climate change. She discusses her work in measuring the capacity of existing forests and reforestation projects using satellite imagery. Episode Summary 1. The importance of carbon credits verification in mitigating climate change 2. How Pachama is using machine learning and satellite imagery to verify carbon projects 3. Three types of carbon projects: avoided deforestation, reforestation, and improved forest management 4. Challenges in using satellite imagery to measure the capacity of existing forests 5. The role of multispectral imaging in measuring density of forests 6. Challenges in collecting data from dense rainforests and weather obstructions 7. The impact of machine learning on scaling up carbon verification 8. Advancements in the field of satellite imaging, particularly in small satellite constellations

Ágnes Horvát is an Assistant Professor in Communication and Computer Science at Northwestern University. Her work focuses on understanding how online networks induce biased information production, sharing and processing across digital platforms. - The new Post-normal era for science - Having an awareness of the context and values that impact scientific research Reducing the problem of miscommunication - with whom does the responsibility lie?

Modern Data Infrastructures and platforms store huge amounts of multidimensional data. But - data pipelines frequently break and a machine learning algorithm's performance is only as good as the quality and reliability of the data itself. In this episode we are joined by Lior Gavish and Ryan Kearns of Monte Carlo, to talk about how the new concept of Data Observability is advancing Data Reliability and Data Quality at Scale. Episode Summary

In this episode we are joined by Julia Stoyanovich from NYU, to talk about her work into how AI is being used in the hiring process. Whether you are responsible for hiring on behalf of a business or are a job seeker, you will find this podcast very interesting, but for very different reasons. Episode Summary

In this episode we are joined by Professor Maurizio Porfiri from NYU, to talk about his latest academic research which is using data science to uncover why sales of guns in the USA increase after a mass shooting event. His interest and research was borne from a very personal experience 14 years ago when he experienced a mass shooting event at Virginia Tech where he was studying.

In this episode we are joined by Perry Marshall to talk about his latest scientific paper entitled “Biology Transcends the Limits of Computation”. We also discuss his $10 million Evolution 2.0 Science Prize, which is the largest prize in the world in science currently. His paper pushes the boundaries in the field of evolutionary biology and his science prize is driving some truly fascinating and thought provoking implications for the development of strong AI.

In this episode we are joined by Arnon Houri Yafin, an Israeli entrepreneur who is the founder of a company called Zzapp Malaria, which recently won the AI XPRIZE sponsored by IBM Watson. Their work in using AI to eliminate malaria in Africa is both interesting and inspirational. Episode Summary

In this episode we are joined by the Director of AI and Data Operations at XPRIZE whose career path into the world of AI is fascinating. Neama Dadkhahnikoo shares his journey from his early days at Boeing back in 2005, through start up ventures, Techspert and Caregivers Direct, and re-training right through to the present day at XPRIZE. He reveals how anyone has the potential to make a real difference in using AI to help solve real world problems.

In this episode we are joined by an industry veteran who has worked for some of the biggest names in the enterprise Data world. Tarush Aggarwal shares his journey from his early days at Salesforce and then WeWork, right through to the present day. He reveals how to set Data Science & Engineering up for success in both small and large organisations. Episode Summary

In this episode we discuss the rapidly developing field of Satellite Imaging. Our guests on this show are Heidi Hurst & Jerry He. They are two remarkable industry Data Scientists with a strong academic pedigree and experience in the field of Satellite Image Processing. Heidi is based in Washington DC and Jerry is based in New York. Join us as they discuss their journey into Satellite Imaging and share with us the latest developments in this fascinating and evolving area of Data Science. Episode Summary RESOURCES: Cool Visual - One Hour of active Satellites orbiting Earth: https://www.reddit.com/r/dataisbeautiful/comments/j7pj62/oc_one_hour_of_active_satellites_orbiting_earth/?utm_source=share&utm_medium=ios_app&utm_name=iossmf DOTA - https://captain-whu.github.io/DOTA/ - Open dataset for object detection in overhead imagery COwC - https://gdo152.llnl.gov/cowc/ - Cars Overhead with Context - specific detection dataset for car counting algorithms xView - http://xviewdataset.org/ - dataset put together by the National Geospatial Intelligence Agency for an object detection challenge, including some particularly rare classes

Every so often on the podcast we will bring you something a little bit different. This episode is part two of our conversation with Esports Legends TLO & MaNa. They are professional Starcraft II players and they tell us the story of what it was like to compete against Google DeepMinds AlphaStar AI agent. This is a fascinating discussion about the technical capability of AI agents and about the psychology involved when Humans take on the machines. Episode Summary Resources: Deepmind Alphastar Videos: https://deepmind.com/research/open-source/alphastar-resources TLO Profile: - https://liquipedia.net/starcraft2/TLO MaNa Profile: - https://liquipedia.net/starcraft2/MaNa

Every so often on the podcast we will bring you something that is a little bit different. This episode is part one of a conversation with Esports Legends TLO & MaNa. They are professional Starcraft II players and they tell us the story of what it was like to compete against Google DeepMinds AlphaStar AI agent. This is a fascinating discussion about the technical capability of AI agents and about the psychology involved when Humans take on the machines. Episode Summary Resources: Deepmind Alphastar Videos: https://deepmind.com/research/open-source/alphastar-resources TLO Profile: - https://liquipedia.net/starcraft2/TLO MaNa Profile: - https://liquipedia.net/starcraft2/MaNa

This is Part Two of our conversation about Deep Fakes with two experts in their respective fields. We talk to Dr Eileen Culloty of the Institute for Future Media and Journalism at Dublin City University and Dr Stephane Lathuiliere of Telecom Paris. EPISODE SUMMARY: Resources: Video of First Order Motion Model For Video Animation: https://www.youtube.com/watch?v=u-0cQ-grXBQ&ab_channel=AliaksandrSiarohin PROVENANCE program: https://fujomedia.eu/provenance/

This is Part one of our conversation about Deep Fakes with two experts in their respective fields. We talk to Dr Eileen Culloty of the Institute for Future Media and Journalism at Dublin City University and Dr Stephane Lathuiliere of Telecom Paris. Stephane reveals what is possible and what is not possible technically with current Deep Fakes Technology. Eileen helps us cut through the hype about Deep Fakes and tells us about their real world social and political impact. EPISODE SUMMARY: RESOURCES: Video of First Order Motion Model For Video Animation: https://www.youtube.com/watch?v=u-0cQ-grXBQ&ab_channel=AliaksandrSiarohin PROVENANCE program: https://fujomedia.eu/provenance/

This is Part 2 of our conversation with Professor Philipp Koehn of Johns Hopkins University. Professor Koehn is one of the world’s leading experts in the field of Machine Translation & NLP. In this episode we delve into commercial applications of machine translation, open source tools available and also take a look into what to expect in the field in the future. Episode Summary: Resources: Philipp Koehn latest book - Neural Machine Translation - Amazon link: https://www.amazon.com/Neural-Machine-Translation-Philipp-Koehn/dp/1108497322 Omniscien Technologies - Leading Enterprise Provider of machine translation services: https://omniscien.com/ Open Source tools: - Fairseq https://fairseq.readthedocs.io/en/latest/ - Marian https://marian-nmt.github.io/ - OpenNMT https://opennmt.net/ - Sockeye https://awslabs.github.io/sockeye/ Translated texts (parallel data) for training: - OPUS http://opus.nlpl.eu/ - Paracrawl https://paracrawl.eu/ Two papers mentioned about excessive use of computing power to train NLP models: - GPT-3 https://arxiv.org/abs/2005.14165 - Roberta https://arxiv.org/abs/1907.11692