Open-sourcing generative AI

The video presents the speakers’ personal views, distancing them from any endorsement or sponsorship. It examines whether the open-source model, a key force in democratizing software access and enhancing transparency and security, will similarly impact AI. The discussion covers collaboration, control, legal, ethical aspects, and barriers to innovation as the AI sector moves towards broader development of large language models. For more insights, visit Booz Allen Hamilton.
About the speaker: Alison Smith, Director of Generative AI at Booz Allen Hamilton, leads the firm’s investments in Generative AI, ensuring alignment with operational needs. Apart from her professional role, she’s involved in her local community and has been acknowledged as a Power Woman in Code by DCFemTech. She holds an MBA from The University of Chicago Booth School of Business and a BA from Middlebury College.

 Open-sourcing generative AI

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The Future of AI: Embracing Open Source and Practical Solutions

Disclaimer: The views expressed in this video are those of the speakers, and do not represent any endorsement or sponsorship.

Open Source and the Democratization of AI

Is the open-source approach, with its emphasis on accessibility, transparency, and security, set to revolutionize the AI industry? We delve into the balance between collaboration and control, legal and ethical considerations, and the hurdles in democratizing large language model development.

About the Speaker: Alison Smith, Director of Generative AI, Booz Allen Hamilton

Alison Smith is a Director of Generative AI at Booz Allen Hamilton, driving innovative solutions for clients. With a pragmatic approach, she leads Booz Allen’s investments in Generative AI, ensuring alignment with real business needs and disseminating best practices throughout the firm.

Key Takeaways for Middle Managers:

  1. Evolve your company with AI by leveraging open-source generative AI.
  2. Identify automation opportunities and define KPIs for measurable impacts on business outcomes.
  3. Choose AI solutions that align with your needs and provide customization.
  4. Implement AI gradually, starting with a pilot and expanding usage judiciously.

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