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Paulina Grnarova and Yannic Kilcher from DeepJudge.AI: Unlocking Institutional Knowledge: How AI is Transforming Legal Search (TGIR Ep. 224)

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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.

On this episode of The Geek in Review, hosts Marlene Gebauer and Greg Lambert explore innovations in legal search with Paulina Grnarova and Yannic Kilcher, co-founders of DeepJudge. This semantic search engine for legal documents leverages proprietary AI developed by experts with backgrounds from Google and academic AI research.

As PhDs from ETH Zurich, Grnarova and Kilcher recognized lawyers needed better access to institutional knowledge rather than constantly reinventing the wheel. DeepJudge moves beyond traditional keyword searches to a deeper integration of search and generative AI models like GPT-3. Partnerships provide financial support and key insights – advisors include execs from Recommind and Kira Systems while collaborations with law firms shape real-world product capabilities.

Discussing product development, Kilcher explains connecting search to language models allows generating summaries grounded in internal data without ethical or security risks of training individual models. Grnarova finds the core problem of connecting users to full knowledge translates universally across firms, though notes larger US firms devote more resources to knowledge management and data science teams.

When asked about the future of AI, Grnarova expresses excitement for AI and humans enhancing each other rather than replacing human roles. Kilcher predicts continued growth in model scale and capability, requiring innovations to sustain rapid progress. They aim to leverage academic research and industry experience to build AI that augments, not displaces, professionals.

DeepJudge stands out for its co-founder expertise and proprietary AI enabling semantic search to tap into institutional knowledge. Instead of reinventing the wheel, lawyers can find relevant precedents and background facts at their fingertips. As Kilcher states, competitive advantage lies in accumulated know-how – their technology surfaces this asset. The future of DeepJudge lies in combining search and generative models for greater insights.

Links:

Contact DeepJudge: info@deepjudge.ai⁠ Contact Us:

Twitter: ⁠⁠⁠⁠⁠@gebauerm⁠⁠⁠⁠⁠, or ⁠⁠⁠⁠⁠@glambert⁠⁠⁠⁠⁠

Threads: @glambertpod or @gebauerm66

Email: geekinreviewpodcast@gmail.com

Music: ⁠⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠⁠

Transcript

  continue reading

254 episodi

Artwork
iconCondividi
 
Manage episode 379333065 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.

On this episode of The Geek in Review, hosts Marlene Gebauer and Greg Lambert explore innovations in legal search with Paulina Grnarova and Yannic Kilcher, co-founders of DeepJudge. This semantic search engine for legal documents leverages proprietary AI developed by experts with backgrounds from Google and academic AI research.

As PhDs from ETH Zurich, Grnarova and Kilcher recognized lawyers needed better access to institutional knowledge rather than constantly reinventing the wheel. DeepJudge moves beyond traditional keyword searches to a deeper integration of search and generative AI models like GPT-3. Partnerships provide financial support and key insights – advisors include execs from Recommind and Kira Systems while collaborations with law firms shape real-world product capabilities.

Discussing product development, Kilcher explains connecting search to language models allows generating summaries grounded in internal data without ethical or security risks of training individual models. Grnarova finds the core problem of connecting users to full knowledge translates universally across firms, though notes larger US firms devote more resources to knowledge management and data science teams.

When asked about the future of AI, Grnarova expresses excitement for AI and humans enhancing each other rather than replacing human roles. Kilcher predicts continued growth in model scale and capability, requiring innovations to sustain rapid progress. They aim to leverage academic research and industry experience to build AI that augments, not displaces, professionals.

DeepJudge stands out for its co-founder expertise and proprietary AI enabling semantic search to tap into institutional knowledge. Instead of reinventing the wheel, lawyers can find relevant precedents and background facts at their fingertips. As Kilcher states, competitive advantage lies in accumulated know-how – their technology surfaces this asset. The future of DeepJudge lies in combining search and generative models for greater insights.

Links:

Contact DeepJudge: info@deepjudge.ai⁠ Contact Us:

Twitter: ⁠⁠⁠⁠⁠@gebauerm⁠⁠⁠⁠⁠, or ⁠⁠⁠⁠⁠@glambert⁠⁠⁠⁠⁠

Threads: @glambertpod or @gebauerm66

Email: geekinreviewpodcast@gmail.com

Music: ⁠⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠⁠

Transcript

  continue reading

254 episodi

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