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Making artificial intelligence practical, productive & accessible to everyone


Practical AI Practical AI #277

Vectoring in on Pinecone

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2024-07-10T17:30:00Z #ai +2 🎧 14,055

Daniel & Chris explore the advantages of vector databases with Roie Schwaber-Cohen of Pinecone. Roie starts with a very lucid explanation of why you need a vector database in your machine learning pipeline, and then goes on to discuss Pinecone’s vector database, designed to facilitate efficient storage, retrieval, and management of vector data.

Practical AI Practical AI #276

Stanford's AI Index Report 2024

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2024-07-02T19:45:00Z #ai 🎧 21,189

We’ve had representatives from Stanford’s Institute for Human-Centered Artificial Intelligence (HAI) on the show in the past, but we were super excited to talk through their 2024 AI Index Report after such a crazy year in AI! Nestor from HAI joins us in this episode to talk about some of the main takeaways including how AI makes workers more productive, the US is increasing regulations sharply, and industry continues to dominate frontier AI research.

Practical AI Practical AI #274

The perplexities of information retrieval

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2024-06-19T16:30:00Z #ai +2 🎧 23,521

Daniel & Chris sit down with Denis Yarats, Co-founder & CTO at Perplexity, to discuss Perplexity’s sophisticated AI-driven answer engine. Denis outlines some of the deficiencies in search engines, and how Perplexity’s approach to information retrieval improves on traditional search engine systems, with a focus on accuracy and validation of the information provided.

Practical AI Practical AI #273

Using edge models to find sensitive data

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2024-06-13T16:45:00Z #ai +1 🎧 23,069

We’ve all heard about breaches of privacy and leaks of private health information (PHI). For healthcare providers and those storing this data, knowing where all the sensitive data is stored is non-trivial. Ramin, from Tausight, joins us to discuss how they have deploy edge AI models to help company search through billions of records for PHI.

Practical AI Practical AI #272

Rise of the AI PC & local LLMs

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2024-06-04T18:45:00Z #ai +2 🎧 31,792

We’ve seen a rise in interest recently and a number of major announcements related to local LLMs and AI PCs. NVIDIA, Apple, and Intel are getting into this along with models like the Phi family from Microsoft. In this episode, we dig into local AI tooling, frameworks, and optimizations to help you navigate this AI niche, and we talk about how this might impact AI adoption in the longer term.

Practical AI Practical AI #271

AI in the U.S. Congress

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2024-05-29T14:30:00Z #ai +2 🎧 23,815

At the age of 72, U.S. Representative Don Beyer of Virginia enrolled at GMU to pursue a Master’s degree in C.S. with a concentration in Machine Learning.

Rep. Beyer is Vice Chair of the bipartisan Artificial Intelligence Caucus & Vice Chair of the NDC’s AI Working Group. He is the author of the AI Foundation Model Transparency Act & a lead cosponsor of the CREATE AI Act, the Federal Artificial Intelligence Risk Management Act & the Artificial Intelligence Environmental Impacts Act.

We hope you tune into this inspiring, nonpartisan conversation with Rep. Beyer about his decision to dive into the deep end of the AI pool & his leadership in bringing that expertise to Capitol Hill.

Practical AI Practical AI #269

Full-stack approach for effective AI agents

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2024-05-15T14:00:00Z #ai 🎧 25,679

There’s a lot of hype about AI agents right now, but developing robust agents isn’t yet a reality in general. Imbue is leading the way towards more robust agents by taking a full-stack approach; from hardware innovations through to user interface. In this episode, Josh, Imbue’s CTO, tell us more about their approach and some of what they have learned along the way.

Practical AI Practical AI #267

Private, open source chat UIs

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2024-04-30T20:45:00Z #ai +2 🎧 25,674

We recently gathered some Practical AI listeners for a live webinar with Danny from LibreChat to discuss the future of private, open source chat UIs. During the discussion we hear about the motivations behind LibreChat, why enterprise users are hosting their own chat UIs, and how Danny (and the LibreChat community) is creating amazing features (like RAG and plugins).

Practical AI Practical AI #266

Mamba & Jamba

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2024-04-24T15:45:00Z #ai +1 🎧 23,383

First there was Mamba… now there is Jamba from AI21. This is a model that combines the best non-transformer goodness of Mamba with good ‘ol attention layers. This results in a highly performant and efficient model that AI21 has open sourced! We hear all about it (along with a variety of other LLM things) from AI21’s co-founder Yoav.

Practical AI Practical AI #265

Udio & the age of multi-modal AI

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2024-04-16T18:20:00Z #ai +2 🎧 25,575

2024 promises to be the year of multi-modal AI, and we are already seeing some amazing things. In this “fully connected” episode, Chris and Daniel explore the new Udio product/service for generating music. Then they dig into the differences between recent multi-modal efforts and more “traditional” ways of combining data modalities.

Practical AI Practical AI #263

Should kids still learn to code?

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2024-04-02T20:00:00Z #ai +3 🎧 25,740

In this fully connected episode, Daniel & Chris discuss NVIDIA GTC keynote comments from CEO Jensen Huang about teaching kids to code. Then they dive into the notion of “community” in the AI world, before discussing challenges in the adoption of generative AI by non-technical people. They finish by addressing the evolving balance between generative AI interfaces and search engines.

Practical AI Practical AI #261

Prompting the future

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2024-03-20T13:45:00Z #ai +2 🎧 30,158

Daniel & Chris explore the state of the art in prompt engineering with Jared Zoneraich, the founder of PromptLayer. PromptLayer is the first platform built specifically for prompt engineering. It can visually manage prompts, evaluate models, log LLM requests, search usage history, and help your organization collaborate as a team. Jared provides expert guidance in how to be implement prompt engineering, but also illustrates how we got here, and where we’re likely to go next.

Practical AI Practical AI #260

Generating the future of art & entertainment

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2024-03-12T17:00:00Z #ai +3 🎧 24,749

Runway is an applied AI research company shaping the next era of art, entertainment & human creativity. Chris sat down with Runway co-founder / CTO, Anastasis Germanidis, to discuss their rise and how it’s defining the future of the creative landscape with its text & image to video models. We hope you find Anastasis’s founder story as inspiring as Chris did.

Practical AI Practical AI #259

YOLOv9: Computer vision is alive and well

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2024-03-06T17:00:00Z #ai 🎧 25,590

While everyone is super hyped about generative AI, computer vision researchers have been working in the background on significant advancements in deep learning architectures. YOLOv9 was just released with some noteworthy advancements relevant to parameter efficient models. In this episode, Chris and Daniel dig into the details and also discuss advancements in parameter efficient LLMs, such as Microsofts 1-Bit LLMs and Qualcomm’s new AI Hub.

Practical AI Practical AI #257

Leading the charge on AI in National Security

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2024-02-20T15:15:00Z #ai +2 🎧 25,147

Chris & Daniel explore AI in national security with Lt. General Jack Shanahan (USAF, Ret.). The conversation reflects Jack’s unique background as the only senior U.S. military officer responsible for standing up and leading two organizations in the United States Department of Defense (DoD) dedicated to fielding artificial intelligence capabilities: Project Maven and the DoD Joint AI Center (JAIC).

Together, Jack, Daniel & Chris dive into the fascinating details of Jack’s recent written testimony to the U.S. Senate’s AI Insight Forum on National Security, in which he provides the U.S. government with thoughtful guidance on how to achieve the best path forward with artificial intelligence.

Practical AI Practical AI #256

Gemini vs OpenAI

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2024-02-14T20:00:00Z #ai +2 🎧 29,768

Google has been releasing a ton of new GenAI functionality under the name “Gemini”, and they’ve officially rebranded Bard as Gemini. We take some time to talk through Gemini compared with offerings from OpenAI, Anthropic, Cohere, etc.

We also discuss the recent FCC decision to ban the use of AI voices in robocalls and what the decision might mean for government involvement in AI in 2024.

Practical AI Practical AI #255

Data synthesis for SOTA LLMs

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2024-02-06T22:00:00Z #ai +1 🎧 24,553

Nous Research has been pumping out some of the best open access LLMs using SOTA data synthesis techniques. Their Hermes family of models is incredibly popular! In this episode, Karan from Nous talks about the origins of Nous as a distributed collective of LLM researchers. We also get into fine-tuning strategies and why data synthesis works so well.

Practical AI Practical AI #254

Large Action Models (LAMs) & Rabbits 🐇

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2024-01-30T21:00:00Z #ai +2 🎧 27,211

Recently the release of the rabbit r1 device resulted in huge interest in both the device and “Large Action Models” (or LAMs). What is an LAM? Is this something new? Did these models come out of nowhere, or are they related to other things we are already using? Chris and Daniel dig into LAMs in this episode and discuss neuro-symbolic AI, AI tool usage, multimodal models, and more.

Practical AI Practical AI #253

Collaboration & evaluation for LLM apps

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2024-01-23T22:30:00Z #ai +1 🎧 27,099

Small changes in prompts can create large changes in the output behavior of generative AI models. Add to that the confusion around proper evaluation of LLM applications, and you have a recipe for confusion and frustration. Raza and the Humanloop team have been diving into these problems, and, in this episode, Raza helps us understand how non-technical prompt engineers can productively collaborate with technical software engineers while building AI-driven apps.

Practical AI Practical AI #252

Advent of GenAI Hackathon recap

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2024-01-17T20:00:00Z #ai 🎧 23,843

Recently, Intel’s Liftoff program for startups and Prediction Guard hosted the first ever “Advent of GenAI” hackathon. 2,000 people from all around the world participated in Generate AI related challenges over 7 days. In this episode, we discuss the hackathon, some of the creative solutions, the idea behind it, and more.

Practical AI Practical AI #251

AI predictions for 2024

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2024-01-10T19:30:00Z #ai +1 🎧 31,966

We scoured the internet to find all the AI related predictions for 2024 (at least from people that might know what they are talking about), and, in this episode, we talk about some of the common themes. We also take a moment to look back at 2023 commenting with some distance on a crazy AI year.

Practical AI Practical AI #250

Open source, on-disk vector search with LanceDB

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2023-12-19T19:40:00Z #ai +3 🎧 28,657

Prashanth Rao mentioned LanceDB as a stand out amongst the many vector DB options in episode #234. Now, Chang She (co-founder and CEO of LanceDB) joins us to talk through the specifics of their open source, on-disk, embedded vector search offering. We talk about how their unique columnar database structure enables serverless deployments and drastic savings (without performance hits) at scale. This one is super practical, so don’t miss it!

Practical AI Practical AI #249

The state of open source AI

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2023-12-12T19:45:00Z #oss +1
🎧 29,929

The new open source AI book from PremAI starts with “As a data scientist/ML engineer/developer with a 9 to 5 job, it’s difficult to keep track of all the innovations.” We couldn’t agree more, and we are so happy that this week’s guest Casper (among other contributors) have created this resource for practitioners.

During the episode, we cover the key categories to think about as you try to navigate the open source AI ecosystem, and Casper gives his thoughts on fine-tuning, vector DBs & more.

Practical AI Practical AI #248

Suspicion machines ⚙️

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2023-12-05T21:45:00Z #ai +1 🎧 26,472

In this enlightening episode, we delve deeper than the usual buzz surrounding AI’s perils, focusing instead on the tangible problems emerging from the use of machine learning algorithms across Europe. We explore “suspicion machines” — systems that assign scores to welfare program participants, estimating their likelihood of committing fraud. Join us as Justin and Gabriel share insights from their thorough investigation, which involved gaining access to one of these models and meticulously analyzing its behavior.

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