Company-wide AI adoption can take a lot of persuasion. Rehgan Avon talks to host Jon Krohn about why AI has become necessary for forward-thinking businesses and the steps to implement AI in an institution so that everyone benefits.

Additional materials: www.superdatascience.com/698

Interested in sponsoring a SuperDataScience Podcast episode? Visit JonKrohn.com/podcast for sponsorship information.

The Super Data Science Podcast: Machine Learning | AI | Success

698: How Firms Can Actually Adopt A.I., with Rehgan Avon

Model deployment, data warehouse options for running models, and how to best leverage BI tools: Harry Glaser and Jon Krohn discuss Modelbit’s capabilities to automate ML models from notebooks into production-ready models, reducing the time and effort in ‘translating’ information from one mode to another. Harry’s conversation with host Jon Krohn expanded on the importance of automating this task, and how developments in ML modeling have widened access to entire teams to analyze data, whatever their level of expertise.

This episode is brought to you by the AWS Insiders Podcast (https://pod.link/1608453414). Interested in sponsoring a SuperDataScience Podcast episode? Visit JonKrohn.com/podcast for sponsorship information.

In this episode you will learn:
• What the modern data stack is [03:28]
• Version control for data scientists [13:30]
• CI/CD, load balancing and logging [20:38]
• Snowflake vs. Redshift [30:10]
• How tools like Looker and Tableau help monitor models [35:26]

Additional materials: www.superdatascience.com/699

699: The Modern Data Stack, with Harry Glaser

Yoga and Hindu mythology: This special episode continues the thread of our centenary episodes, SDS 500: Yoga Nidra with Jes Allen and SDS 600: Yoga Nidra Practice with Steve Fazzari, which talked through guided meditation techniques to help improve posture, sleep, and expand consciousness. Inspired by these sessions, host Jon Krohn explores Hindu mythology via Alan Watts’ “The Dream of Life”.

Additional materials: www.superdatascience.com/700

Interested in sponsoring a SuperDataScience Podcast episode? Visit JonKrohn.com/podcast for sponsorship information.

700: "The Dream of Life" by Alan Watts

Dr. Raluca Ada Popa, renowned computer scientist, entrepreneur, and President of Opaque Systems, joins Jon Krohn to share her insights on securely interacting with AI APIs like OpenAI's GPT-4, the pros and cons of open vs. closed-source AI development, and the seamless operation of compute pipelines across multiple clouds.

This episode is brought to you by AWS Inferentia (https://go.aws/3zWS0au) and by Modelbit (https://modelbit.com), for deploying models in seconds. Interested in sponsoring a SuperDataScience Podcast episode? Visit JonKrohn.com/podcast for sponsorship information.

In this episode you will learn:
• What is a confidential computing platform? [04:31]
• How to get started with confidential computing [12:10]
• The challenges of confidential computing and LLMs [21:11]
• How to safeguard your data while using commercial LLMs like GPT-4 [38:00]
• Open-source vs closed-source [52:28]
• Raluca's PreVail cybersecurity company [1:01:50]
• Combining entrepreneurship and academic career [1:04:03]
• DARE Program [1:10:39]

Additional materials: www.superdatascience.com/701

701: Generative A.I. without the Privacy Risks (with Prof. Raluca Ada Popa)

This week, Jon Krohn is examining Meta's newly released open-source large language model, Llama 2, highlighting its commercial prospects, immense capacity, model variety, and unique 'time awareness' feature. He also discusses its innovative two-stage RLHF approach that enhances its performance.

Additional materials: www.superdatascience.com/702

Interested in sponsoring a SuperDataScience Podcast episode? Visit JonKrohn.com/podcast for sponsorship information.

702: Llama 2 — It's Time to Upgrade your Open-Source LLM

Statistics history, interdisciplinarity, and data and society. Chris Wiggins talks with Jon Krohn about the power dynamics of data, the transformation of the field of biology through data-driven approaches to genetic sequencing, and the New York Times’ data science team’s cutting-edge approach to accommodating its tech stack.

This episode is brought to you by the AWS Insiders Podcast (https://pod.link/1608453414) and by Modelbit (https://modelbit.com), for deploying models in seconds. Interested in sponsoring a SuperDataScience Podcast episode? Visit JonKrohn.com/podcast for sponsorship information.

In this episode you will learn:
• The importance of the humanities in data science [09:18]
• How data science “rearranges” power [17:19]
• An overview of How Data Happened [20:36]
• The controversial nature of Bayes theorem [29:16]
• Why we need to consider data ethics [34:00]
• How biology came to adopt data science into its field [45:44]
• The data science tech stack at the New York Times [49:18]

Additional materials: www.superdatascience.com/703

703: How Data Happened: A History, with Columbia Prof. Chris Wiggins

Take on the world of GPT and learn to develop your own, commercially successful Large Language Models (LLMs) with Jon Krohn’s comprehensive, guided training video for generative AI. Get to grips with the technology, learn which tools to use, and find out how to get an eye for business-viable models with Jon’s (ad-)free educational video.

Additional materials: www.superdatascience.com/704

Interested in sponsoring a SuperDataScience Podcast episode? Visit JonKrohn.com/podcast for sponsorship information.

704: Jon’s “Generative A.I. with LLMs” Hands-on Training

Join Jon Krohn as he chats with Syngenta Group's Feroz Sheikh, Jeremy Groeteke, and Thomas Jung about the digital revolution in agriculture. Learn how data science is evolving farming, from precision techniques to global food solutions. A compelling blend of tech meets nature.

This episode is brought to you by AWS Inferentia (https://go.aws/3zWS0au) and by Modelbit (https://modelbit.com), for deploying models in seconds. Interested in sponsoring a SuperDataScience Podcast episode? Visit JonKrohn.com/podcast for sponsorship information.

In this episode you will learn:
• What is precision agriculture? [09:43]
• What is computational agronomy? [12:30]
• How Syngenta helps growers optimize yields [21:37]
• How to bridge the gap between R&D and out in the real world [33:58]
• What is generative chemistry? [37:52]
• How generative chemistry accelerates the discovery of new compounds [41:55]
• How you could make a big social impact in agriculture with data science [56:22]
• How to go about designing ML models for agriculture [1:00:27]

Additional materials: www.superdatascience.com/705

705: Feeding the World with ML-Powered Precision Agriculture

Attention and transformers in LLMs, the five stages of data processing, and a brand-new Large Language Models A-Z course: Kirill Eremenko joins host Jon Krohn to explore what goes into well-crafted LLMs, what makes Transformers so powerful, and how to succeed as a data scientist in this new age of generative AI.

This episode is brought to you by Intel and HPE Ezmeral Software Solutions (https://hpe.com/ezmeral/chatwithyourdata), and by Prophets of AI (https://prophetsofai.com), the leading agency for AI experts. Interested in sponsoring a SuperDataScience Podcast episode? Visit https://passionfroot.me/superdatascience for sponsorship information.

In this episode you will learn:
• Supply and demand in AI recruitment [08:30]
• Kirill and Hadelin's new course on LLMs, “Large Language Models (LLMs), Transformers & GPT A-Z” [15:37]
• The learning difficulty in understanding LLMs [19:46]
• The basics of LLMs [22:00]
• The five building blocks of transformer architecture [36:29]
- 1: Input embedding [44:10]
- 2: Positional encoding [50:46]
- 3: Attention mechanism [54:04]
- 4: Feedforward neural network [1:16:17]
- 5: Linear transformation and softmax [1:19:16]
• Inference vs training time [1:29:12]
• Why transformers are so powerful [1:49:22]

Additional materials: www.superdatascience.com/747

747: Technical Intro to Transformers and LLMs, with Kirill Eremenko

Encoders, cross attention and masking for LLMs: SuperDataScience Founder Kirill Eremenko returns to the SuperDataScience podcast, where he speaks with Jon Krohn about transformer architectures and why they are a new frontier for generative AI. If you’re interested in applying LLMs to your business portfolio, you’ll want to pay close attention to this episode!

This episode is brought to you by Ready Tensor, where innovation meets reproducibility (https://www.readytensor.ai/), by Oracle NetSuite business software (netsuite.com/superdata), and by Intel and HPE Ezmeral Software Solutions (http://hpe.com/ezmeral/chatbots). Interested in sponsoring a SuperDataScience Podcast episode? Visit https://passionfroot.me/superdatascience for sponsorship information.

In this episode you will learn:
• How decoder-only transformers work [15:51]
• How cross-attention works in transformers [41:05]
• How encoders and decoders work together (an example) [52:46]
• How encoder-only architectures excel at understanding natural language [1:20:34]
• The importance of masking during self-attention [1:27:08]

Additional materials: www.superdatascience.com/759

759: Full Encoder-Decoder Transformers Fully Explained, with Kirill Eremenko

Pytorch benefits, how to get funding for your AI startup, and managing scientific silos: In our new series for SuperDataScience, “In Case You Missed It”, host Jon Krohn engages in some “reinforcement learning through human feedback” of his own with need-to-hear sound bites from past SDS episodes!

Additional materials: www.superdatascience.com/772

Interested in sponsoring a SuperDataScience Podcast episode? Visit passionfroot.me/superdatascience for sponsorship information.

772: In Case You Missed It in March 2024

Hear Jon Krohn’s favorite five clips from his April interviews. Chief Scientist at Posit PBC Hadley Wickham on the subtle differences between Python and R. Professor of Business Analytics Barrett Thomas walks through the variables that companies should consider when using drones or any other tech to improve their business operations and bottom line. Aleksa Gordić, Founder of Runa AI believes an overhaul of the current educational system is long overdue. Bernard Marr discusses the future of GenAI and its impact on the world of work. And SuperDataScience founder Kirill Eremenko gives a lively workshop on gradient boosting.


Additional materials: www.superdatascience.com/782

Interested in sponsoring a SuperDataScience Podcast episode? Visit passionfroot.me/superdatascience for sponsorship information.

782: In Case You Missed It in April 2024

The latest machine learning, A.I., and data career topics from across both academia and industry are brought to you by host Dr. Jon Krohn on the Super Data Science Podcast.

As the quantity of data on our planet doubles every couple of years and with this trend set to continue for decades to come, there's an unprecedented opportunity for you to make a meaningful impact in your lifetime. In conversation with the biggest names in the data science industry, Jon cuts through hype to fuel that professional impact.

Whether you're curious about getting started in a data career or you're a deep technical expert, whether you'd like to understand what A.I. is or you'd like to integrate more data-driven processes into your business, we have inspiring guests and lighthearted conversation for you to enjoy.

We cover tools, techniques, and implementation tricks across data collection, databases, analytics, predictive modeling, visualization, software engineering, real-world applications, commercialization, and entrepreneurship − everything you need to crush it with data science.

New tracks tagged #SuperDataScience