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Can AI Bring Both Speed and Accuracy: Josh Broyde of AI21 Labs

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Manage episode 429415589 series 3068634
Contenuto fornito da Greg Lambert & Marlene Gebauer, Greg Lambert, and Marlene Gebauer. Tutti i contenuti dei podcast, inclusi episodi, grafica e descrizioni dei podcast, vengono caricati e forniti direttamente da Greg Lambert & Marlene Gebauer, Greg Lambert, and Marlene Gebauer o dal partner della piattaforma podcast. Se ritieni che qualcuno stia utilizzando la tua opera protetta da copyright senza la tua autorizzazione, puoi seguire la procedura descritta qui https://it.player.fm/legal.

This week, we are joined by Joshua Broyde, PhD and Principal Solutions Architect at AI21 Labs. Broyde discusses AI21 Labs' work in developing foundation models and AI systems for enterprise use, with a focus on their latest model, Jamba-Instruct.

Josh explains the concept of foundation models and how they differ from traditional AI models. He highlights AI21 Labs' work with financial institutions on use cases like term sheet generation and financial document Q&A. The conversation explores the challenges and benefits of training models on company-specific data versus using retrieval augmented generation (RAG) techniques.

The interview delves into the development of Jamba Instruct, a hybrid model combining Mamba and Transformer architectures to achieve both speed and accuracy. Broyde discusses the model's performance, industry reaction, and potential applications.

Safety and security considerations for AI models are addressed, with Broyde explaining AI21 Labs' approach to implementing guardrails and secure deployment options for regulated industries. The discussion also covers the balance between model quality and cost, and the trend towards matching specific models to appropriate tasks.

Josh also shares his thoughts on future developments in the field, including the potential for agent-based approaches and increased focus on cost optimization in AI workflows.

Listen on mobile platforms: ⁠⁠⁠⁠⁠⁠⁠⁠⁠Apple Podcasts⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠Spotify⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠YouTube⁠⁠⁠⁠⁠⁠⁠

Contact Us:

Twitter: ⁠⁠⁠⁠⁠@gebauerm⁠⁠⁠⁠⁠, or ⁠⁠⁠⁠⁠@glambert⁠⁠⁠⁠⁠

Email: geekinreviewpodcast@gmail.com

Music: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠⁠⁠⁠⁠⁠

Transcript on 3 Geeks

  continue reading

268 episodi

Artwork
iconCondividi
 
Manage episode 429415589 series 3068634
Contenuto fornito da Greg Lambert & Marlene Gebauer, Greg Lambert, and Marlene Gebauer. Tutti i contenuti dei podcast, inclusi episodi, grafica e descrizioni dei podcast, vengono caricati e forniti direttamente da Greg Lambert & Marlene Gebauer, Greg Lambert, and Marlene Gebauer o dal partner della piattaforma podcast. Se ritieni che qualcuno stia utilizzando la tua opera protetta da copyright senza la tua autorizzazione, puoi seguire la procedura descritta qui https://it.player.fm/legal.

This week, we are joined by Joshua Broyde, PhD and Principal Solutions Architect at AI21 Labs. Broyde discusses AI21 Labs' work in developing foundation models and AI systems for enterprise use, with a focus on their latest model, Jamba-Instruct.

Josh explains the concept of foundation models and how they differ from traditional AI models. He highlights AI21 Labs' work with financial institutions on use cases like term sheet generation and financial document Q&A. The conversation explores the challenges and benefits of training models on company-specific data versus using retrieval augmented generation (RAG) techniques.

The interview delves into the development of Jamba Instruct, a hybrid model combining Mamba and Transformer architectures to achieve both speed and accuracy. Broyde discusses the model's performance, industry reaction, and potential applications.

Safety and security considerations for AI models are addressed, with Broyde explaining AI21 Labs' approach to implementing guardrails and secure deployment options for regulated industries. The discussion also covers the balance between model quality and cost, and the trend towards matching specific models to appropriate tasks.

Josh also shares his thoughts on future developments in the field, including the potential for agent-based approaches and increased focus on cost optimization in AI workflows.

Listen on mobile platforms: ⁠⁠⁠⁠⁠⁠⁠⁠⁠Apple Podcasts⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠Spotify⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠YouTube⁠⁠⁠⁠⁠⁠⁠

Contact Us:

Twitter: ⁠⁠⁠⁠⁠@gebauerm⁠⁠⁠⁠⁠, or ⁠⁠⁠⁠⁠@glambert⁠⁠⁠⁠⁠

Email: geekinreviewpodcast@gmail.com

Music: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠⁠⁠⁠⁠⁠

Transcript on 3 Geeks

  continue reading

268 episodi

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