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Innhold levert av Hugo Bowne-Anderson. Alt podcastinnhold, inkludert episoder, grafikk og podcastbeskrivelser, lastes opp og leveres direkte av Hugo Bowne-Anderson eller deres podcastplattformpartner. Hvis du tror at noen bruker det opphavsrettsbeskyttede verket ditt uten din tillatelse, kan du følge prosessen skissert her https://no.player.fm/legal.
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Episode 34: The AI Revolution Will Not Be Monopolized

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Manage episode 435691712 series 3317544
Innhold levert av Hugo Bowne-Anderson. Alt podcastinnhold, inkludert episoder, grafikk og podcastbeskrivelser, lastes opp og leveres direkte av Hugo Bowne-Anderson eller deres podcastplattformpartner. Hvis du tror at noen bruker det opphavsrettsbeskyttede verket ditt uten din tillatelse, kan du følge prosessen skissert her https://no.player.fm/legal.

Hugo speaks with Ines Montani and Matthew Honnibal, the creators of spaCy and founders of Explosion AI. Collectively, they've had a huge impact on the fields of industrial natural language processing (NLP), ML, and AI through their widely-used open-source library spaCy and their innovative annotation tool Prodigy. These tools have become essential for many data scientists and NLP practitioners in industry and academia alike.

In this wide-ranging discussion, we dive into:

• The evolution of applied NLP and its role in industry
• The balance between large language models and smaller, specialized models
• Human-in-the-loop distillation for creating faster, more data-private AI systems
• The challenges and opportunities in NLP, including modularity, transparency, and privacy
• The future of AI and software development
• The potential impact of AI regulation on innovation and competition

We also touch on their recent transition back to a smaller, more independent-minded company structure and the lessons learned from their journey in the AI startup world.

Ines and Matt offer invaluable insights for data scientists, machine learning practitioners, and anyone interested in the practical applications of AI. They share their thoughts on how to approach NLP projects, the importance of data quality, and the role of open-source in advancing the field.

Whether you're a seasoned NLP practitioner or just getting started with AI, this episode offers a wealth of knowledge from two of the field's most respected figures. Join us for a discussion that explores the current landscape of AI development, with insights that bridge the gap between cutting-edge research and real-world applications.

LINKS

Check out and subcribe to our lu.ma calendar for upcoming livestreams!

  continue reading

40 episoder

Artwork
iconDel
 
Manage episode 435691712 series 3317544
Innhold levert av Hugo Bowne-Anderson. Alt podcastinnhold, inkludert episoder, grafikk og podcastbeskrivelser, lastes opp og leveres direkte av Hugo Bowne-Anderson eller deres podcastplattformpartner. Hvis du tror at noen bruker det opphavsrettsbeskyttede verket ditt uten din tillatelse, kan du følge prosessen skissert her https://no.player.fm/legal.

Hugo speaks with Ines Montani and Matthew Honnibal, the creators of spaCy and founders of Explosion AI. Collectively, they've had a huge impact on the fields of industrial natural language processing (NLP), ML, and AI through their widely-used open-source library spaCy and their innovative annotation tool Prodigy. These tools have become essential for many data scientists and NLP practitioners in industry and academia alike.

In this wide-ranging discussion, we dive into:

• The evolution of applied NLP and its role in industry
• The balance between large language models and smaller, specialized models
• Human-in-the-loop distillation for creating faster, more data-private AI systems
• The challenges and opportunities in NLP, including modularity, transparency, and privacy
• The future of AI and software development
• The potential impact of AI regulation on innovation and competition

We also touch on their recent transition back to a smaller, more independent-minded company structure and the lessons learned from their journey in the AI startup world.

Ines and Matt offer invaluable insights for data scientists, machine learning practitioners, and anyone interested in the practical applications of AI. They share their thoughts on how to approach NLP projects, the importance of data quality, and the role of open-source in advancing the field.

Whether you're a seasoned NLP practitioner or just getting started with AI, this episode offers a wealth of knowledge from two of the field's most respected figures. Join us for a discussion that explores the current landscape of AI development, with insights that bridge the gap between cutting-edge research and real-world applications.

LINKS

Check out and subcribe to our lu.ma calendar for upcoming livestreams!

  continue reading

40 episoder

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