Practical AI

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Making artificial intelligence practical, productive & accessible to everyone

Practical AI Practical AI #232

Legal consequences of generated content

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2023-07-18T18:30:00Z #ai +2 🎧 31,076

As a technologist, coder, and lawyer, few people are better equipped to discuss the legal and practical consequences of generative AI than Damien Riehl. He demonstrated this a couple years ago by generating, writing to disk, and then releasing every possible musical melody. Damien joins us to answer our many questions about generated content, copyright, dataset licensing/usage, and the future of knowledge work.

Practical AI Practical AI #231

A developer's toolkit for SOTA AI

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2023-07-12T21:00:00Z #ai +2 🎧 28,781

Chris sat down with Varun Mohan and Anshul Ramachandran, CEO / Cofounder and Lead of Enterprise and Partnership at Codeium, respectively. They discussed how to streamline and enable modern development in generative AI and large language models (LLMs). Their new tool, Codeium, was born out of the insights they gleaned from their work in GPU software and solutions development, particularly with respect to generative AI, large language models, and supporting infrastructure. Codeium is a free AI-powered toolkit for developers, with in-house models and infrastructure - not another API wrapper.

Practical AI Practical AI #230

Cambrian explosion of generative models

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2023-07-06T17:30:00Z #ai +3 🎧 29,690

In this Fully Connected episode, Daniel and Chris explore recent highlights from the current model proliferation wave sweeping the world - including Stable Diffusion XL, OpenChat, Zeroscope XL, and Salesforce XGen. They note the rapid rise of open models, and speculate that just as in open source software, open models will dominate the future. Such rapid advancement creates its own problems though, so they finish by itemizing concerns such as cybersecurity, workflow productivity, and impact on human culture.

Practical AI Practical AI #229

Automated cartography using AI

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2023-06-28T14:30:00Z #ai +1 🎧 28,847

Your feed might be dominated by LLMs these days, but there are some amazing things happening in computer vision that you shouldn’t ignore! In this episode, we bring you one of those amazing stories from Gabriel Ortiz, who is working with the government of Cantabria in Spain to automate cartography and apply AI to geospatial analysis. We hear about how AI tooling fits into the GIS workflow, and Gabriel shares some of his recent work (including work that can identify individual people, invasive plant species, building and more from aerial survey data).

Practical AI Practical AI #228

From ML to AI to Generative AI

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2023-06-21T13:30:00Z #ai +2 🎧 35,448

Chris and Daniel take a step back to look at how generative AI fits into the wider landscape of ML/AI and data science. They talk through the differences in how one approaches “traditional” supervised learning and how practitioners are approaching generative AI based solutions (such as those using Midjourney or GPT family models). Finally, they talk through the risk and compliance implications of generative AI, which was in the news this week in the EU.

Practical AI Practical AI #226

Accidentally building SOTA AI

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2023-06-06T20:45:00Z #ai +2 🎧 27,509

Lately.AI has been working for years on content generation systems that capture your unique “voice” and are tailored to your unique audience. At first, they didn’t know that they were going to build an AI system, but now they have a state-of-the-art generative platform that provides much more than “prompting” out of thin air. Lately.AI’s CEO Kate explain their journey, her perspective on generative AI in marketing, and much more in this episode!

Practical AI Practical AI #225

Controlled and compliant AI applications

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2023-05-31T17:00:00Z #ai +2 🎧 27,799

You can’t build robust systems with inconsistent, unstructured text output from LLMs. Moreover, LLM integrations scare corporate lawyers, finance departments, and security professionals due to hallucinations, cost, lack of compliance (e.g., HIPAA), leaked IP/PII, and “injection” vulnerabilities.

In this episode, Chris interviews Daniel about his new company called Prediction Guard, which addresses these issues. They discuss some practical methodologies for getting consistent, structured output from compliant AI systems. These systems, driven by open access models and various kinds of LLM wrappers, can help you delight customers AND navigate the increasing restrictions on “GPT” models.

Practical AI Practical AI #224

Data augmentation with LlamaIndex

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2023-05-23T16:15:00Z #ai +1 🎧 29,234

Large Language Models (LLMs) continue to amaze us with their capabilities. However, the utilization of LLMs in production AI applications requires the integration of private data. Join us as we have a captivating conversation with Jerry Liu from LlamaIndex, where he provides valuable insights into the process of data ingestion, indexing, and query specifically tailored for LLM applications. Delving into the topic, we uncover different query patterns and venture beyond the realm of vector databases.

Practical AI Practical AI #223

Creating instruction tuned models

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2023-05-16T18:20:00Z #ai +1 🎧 27,591

At the recent ODSC East conference, Daniel got a chance to sit down with Erin Mikail Staples to discuss the process of gathering human feedback and creating an instruction tuned Large Language Models (LLM). They also chatted about the importance of open data and practical tooling for data annotation and fine-tuning. Do you want to create your own custom generative AI models? This is the episode for you!

Practical AI Practical AI #222

The last mile of AI app development

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2023-05-11T13:00:00Z #ai +3 🎧 29,565

There are a ton of problems around building LLM apps in production and the last mile of that problem. Travis Fischer, builder of open AI projects like @ChatGPTBot, joins us to talk through these problems (and how to overcome them). He helps us understand the hierarchy of complexity from simple prompting to augmentation, agents, and fine-tuning. Along the way we discuss the frontend developer community that is rapidly adopting AI technology via Typescript (not Python).

Practical AI Practical AI #221

Large models on CPUs

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2023-05-02T16:00:00Z #ai +1 🎧 30,186

Model sizes are crazy these days with billions and billions of parameters. As Mark Kurtz explains in this episode, this makes inference slow and expensive despite the fact that up to 90%+ of the parameters don’t influence the outputs at all.

Mark helps us understand all of the practicalities and progress that is being made in model optimization and CPU inference, including the increasing opportunities to run LLMs and other Generative AI models on commodity hardware.

Practical AI Practical AI #220

Causal inference

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2023-04-25T16:35:00Z #ai 🎧 28,905

With all the LLM hype, it’s worth remembering that enterprise stakeholders want answers to “why” questions. Enter causal inference. Paul Hünermund has been doing research and writing on this topic for some time and joins us to introduce the topic. He also shares some relevant trends and some tips for getting started with methods including double machine learning, experimentation, difference-in-difference, and more.

Practical AI Practical AI #219

Capabilities of LLMs 🤯

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2023-04-19T21:00:00Z #ai +1 🎧 34,949

Large Language Model (LLM) capabilities have reached new heights and are nothing short of mind-blowing! However, with so many advancements happening at once, it can be overwhelming to keep up with all the latest developments. To help us navigate through this complex terrain, we’ve invited Raj - one of the most adept at explaining State-of-the-Art (SOTA) AI in practical terms - to join us on the podcast.

Raj discusses several intriguing topics such as in-context learning, reasoning, LLM options, and related tooling. But that’s not all! We also hear from Raj about the rapidly growing data science and AI community on TikTok.

Practical AI Practical AI #218

Computer scientists as rogue art historians

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2023-04-12T13:30:00Z #ai +2 🎧 25,167

What can art historians and computer scientists learn from one another? Actually, a lot! Amanda Wasielewski joins us to talk about how she discovered that computer scientists working on computer vision were actually acting like rogue art historians and how art historians have found machine learning to be a valuable tool for research, fraud detection, and cataloguing. We also discuss the rise of generative AI and how we this technology might cause us to ask new questions like: “What makes a photograph a photograph?”

Practical AI Practical AI #217

Accelerated data science with a Kaggle grandmaster

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2023-04-04T20:00:00Z #ai +3 🎧 26,641

Daniel and Chris explore the intersection of Kaggle and real-world data science in this illuminating conversation with Christof Henkel, Senior Deep Learning Data Scientist at NVIDIA and Kaggle Grandmaster. Christof offers a very lucid explanation into how participation in Kaggle can positively impact a data scientist’s skill and career aspirations. He also shared some of his insights and approach to maximizing AI productivity uses GPU-accelerated tools like RAPIDS and DALI.

Practical AI Practical AI #216

Explainable AI that is accessible for all humans

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2023-03-28T15:30:00Z #ai 🎧 29,100

We are seeing an explosion of AI apps that are (at their core) a thin UI on top of calls to OpenAI generative models. What risks are associated with this sort of approach to AI integration, and is explainability and accountability something that can be achieved in chat-based assistants?

Beth Rudden of Bast.ai has been thinking about this topic for some time and has developed an ontological approach to creating conversational AI. We hear more about that approach and related work in this episode.

Practical AI Practical AI #215

AI search at You.com

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2023-03-15T19:15:00Z #ai +1 🎧 25,490

Neural search and chat-based search are all the rage right now. However, You.com has been innovating in these topics long before ChatGPT. In this episode, Bryan McCann from You.com shares insights related to our mental model of Large Language Model (LLM) interactions and practical tips related to integrating LLMs into production systems.

Practical AI Practical AI #214

End-to-end cloud compute for AI/ML

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2023-03-07T20:00:00Z #ai +2 🎧 24,111

We’ve all experienced pain moving from local development, to testing, and then on to production. This cycle can be long and tedious, especially as AI models and datasets are integrated. Modal is trying to make this loop of development as seamless as possible for AI practitioners, and their platform is pretty incredible!

Erik from Modal joins us in this episode to help us understand how we can run or deploy machine learning models, massively parallel compute jobs, task queues, web apps, and much more, without our own infrastructure.

Practical AI Practical AI #213

Success (and failure) in prompting

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2023-02-28T21:15:00Z #ai +1 🎧 26,249

With the recent proliferation of generative AI models (from OpenAI, co:here, Anthropic, etc.), practitioners are racing to come up with best practices around prompting, grounding, and control of outputs.

Chris and Daniel take a deep dive into the kinds of behavior we are seeing with this latest wave of models (both good and bad) and what leads to that behavior. They also dig into some prompting and integration tips.

Practical AI Practical AI #212

Applied NLP solutions & AI education

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2023-02-22T15:15:00Z #ai +2 🎧 24,210

We’re super excited to welcome Jay Alammar to the show. Jay is a well-known AI educator, applied NLP practitioner at co:here, and author of the popular blog, “The Illustrated Transformer.” In this episode, he shares his ideas on creating applied NLP solutions, working with large language models, and creating educational resources for state-of-the-art AI.

Practical AI Practical AI #211

Serverless GPUs

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2023-02-14T21:30:00Z #ai +2 🎧 23,600

We’ve been hearing about “serverless” CPUs for some time, but it’s taken a while to get to serverless GPUs. In this episode, Erik from Banana explains why its taken so long, and he helps us understand how these new workflows are unlocking state-of-the-art AI for application developers. Forget about servers, but don’t forget to listen to this one!

Practical AI Practical AI #210

MLOps is alive and well

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2023-02-07T21:00:00Z #ai +2 🎧 22,822

Worlds are colliding! This week we join forces with the hosts of the MLOps.Community podcast to discuss all things machine learning operations. We talk about how the recent explosion of foundation models and generative models is influencing the world of MLOps, and we discuss related tooling, workflows, perceptions, etc.

Practical AI Practical AI #209

3D assets & simulation at NVIDIA

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2023-01-31T20:00:00Z #nvidia +1
🎧 21,508

What’s the current reality and practical implications of using 3D environments for simulation and synthetic data creation? In this episode, we cut right through the hype of the Metaverse, Multiverse, Omniverse, and all the “verses” to understand how 3D assets and tooling are actually helping AI developers develop industrial robots, autonomous vehicles, and more. Beau Perschall is at the center of these innovations in his work with NVIDIA, and there is no one better to help us explore the topic!

Practical AI Practical AI #208

GPU dev environments that just work

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2023-01-24T21:30:00Z #ai +1 🎧 21,169

Creating and sharing reproducible development environments for AI experiments and production systems is a huge pain. You have all sorts of weird dependencies, and then you have to deal with GPUs and NVIDIA drivers on top of all that! brev.dev is attempting to mitigate this pain and create delightful GPU dev environments. Now that sounds practical!

Practical AI Practical AI #207

Machine learning at small organizations

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2023-01-17T20:15:00Z #ai +1 🎧 26,619

Why is ML is so poorly adopted in small organizations (hint: it’s not because they don’t have enough data)? In this episode, Kirsten Lum from Storytellers shares the patterns she has seen in small orgs that lead to a successful ML practice. We discuss how the job of a ML Engineer/Data Scientist is different in that environment and how end-to-end project management is key to adoption.

Practical AI Practical AI #205

NLP research by & for local communities

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2023-01-03T20:15:00Z #ai +2 🎧 19,724

While at EMNLP 2022, Daniel got a chance to sit down with an amazing group of researchers creating NLP technology that actually works for their local language communities. Just Zwennicker (Universiteit van Amsterdam) discusses his work on a machine translation system for Sranan Tongo, a creole language that is spoken in Suriname. Andiswa Bukula (SADiLaR), Rooweither Mabuya (SADiLaR), and Bonaventure Dossou (Lanfrica, Mila) discuss their work with Masakhane to strengthen and spur NLP research in African languages, for Africans, by Africans.

The group emphasized the need for more linguistically diverse NLP systems that work in scenarios of data scarcity, non-Latin scripts, rich morphology, etc. You don’t want to miss this one!

Practical AI Practical AI #203

AI competitions & cloud resources

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2022-12-07T21:00:00Z #ai +2 🎧 20,389

In this special episode, we interview some of the sponsors and teams from a recent case competition organized by Purdue University, Microsoft, INFORMS, and SIL International. 170+ teams from across the US and Canada participated in the competition, which challenged students to create AI-driven systems to caption images in three languages (Thai, Kyrgyz, and Hausa).

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