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AI News (updated July 2024)

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Manage episode 432363521 series 3575018
Content provided by Polly Allen. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Polly Allen or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

A quick glimpse into what happened in the world of AI in July 2024!

THE SHOW

AI After Hours with Polly Allen and Yuying Chen-Wynn is an irreverent attempt to 'edutain' about the latest AI headlines & tools!

THE LINKS

Recommendations

Check out my ‘Path to AI Product Leader’ masterclass on August 6th: https://www.aicareerboost.com/master-ai-leadership

Polly Allen

LinkedIn: ⁠https://www.linkedin.com/in/pollymallen/⁠

AI Career Boost: ⁠https://www.aicareerboost.com/⁠

Yuying Chen-Wynn

LinkedIn: ⁠https://www.linkedin.com/in/yuyingchenwynn/⁠

Blog: https://yuying.substack.com/

TAKEAWAYS

  • LAMA 3.1, with 405 billion parameters, is the largest language model to date and outperforms other benchmark models.
  • Export blocks on AI compute GPUs raise questions about the access of Chinese companies to US-based cloud providers.
  • Smaller language models are gaining popularity due to their ability to be deployed on devices, lower cost, and specialized use cases.
  • Prompt chaining is an engineering pattern that involves using multiple prompts to improve the performance and accuracy of language models.
  • Developers are exploring prompt chaining and agentic AI to enhance the capabilities of language models. Prompt chaining involves feeding the output of one language model into the next prompt, while agentic AI refers to AI that figures out the steps itself.
  • Prompt chaining has potential for impact in content generation and writing, while agentic AI is still in early stages of development.
  • The AI bubble is not bursting, and AI is still in its early stages with a lot of potential for growth and innovation.
  • Investors should be more sensible in their evaluation of AI companies, and patience is needed for AI to reach its full potential.
  continue reading

13 episodes

Artwork
iconShare
 
Manage episode 432363521 series 3575018
Content provided by Polly Allen. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Polly Allen or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

A quick glimpse into what happened in the world of AI in July 2024!

THE SHOW

AI After Hours with Polly Allen and Yuying Chen-Wynn is an irreverent attempt to 'edutain' about the latest AI headlines & tools!

THE LINKS

Recommendations

Check out my ‘Path to AI Product Leader’ masterclass on August 6th: https://www.aicareerboost.com/master-ai-leadership

Polly Allen

LinkedIn: ⁠https://www.linkedin.com/in/pollymallen/⁠

AI Career Boost: ⁠https://www.aicareerboost.com/⁠

Yuying Chen-Wynn

LinkedIn: ⁠https://www.linkedin.com/in/yuyingchenwynn/⁠

Blog: https://yuying.substack.com/

TAKEAWAYS

  • LAMA 3.1, with 405 billion parameters, is the largest language model to date and outperforms other benchmark models.
  • Export blocks on AI compute GPUs raise questions about the access of Chinese companies to US-based cloud providers.
  • Smaller language models are gaining popularity due to their ability to be deployed on devices, lower cost, and specialized use cases.
  • Prompt chaining is an engineering pattern that involves using multiple prompts to improve the performance and accuracy of language models.
  • Developers are exploring prompt chaining and agentic AI to enhance the capabilities of language models. Prompt chaining involves feeding the output of one language model into the next prompt, while agentic AI refers to AI that figures out the steps itself.
  • Prompt chaining has potential for impact in content generation and writing, while agentic AI is still in early stages of development.
  • The AI bubble is not bursting, and AI is still in its early stages with a lot of potential for growth and innovation.
  • Investors should be more sensible in their evaluation of AI companies, and patience is needed for AI to reach its full potential.
  continue reading

13 episodes

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