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محتوای ارائه شده توسط Australian Broadcasting Corporation. تمام محتوای پادکست شامل قسمت‌ها، گرافیک‌ها و توضیحات پادکست مستقیماً توسط Australian Broadcasting Corporation یا شریک پلتفرم پادکست آن‌ها آپلود و ارائه می‌شوند. اگر فکر می‌کنید شخصی بدون اجازه شما از اثر دارای حق نسخه‌برداری شما استفاده می‌کند، می‌توانید روندی که در اینجا شرح داده شده است را دنبال کنید.https://fa.player.fm/legal
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What is AI ‘model collapse’?

14:06
 
اشتراک گذاری
 

Manage episode 447083705 series 3323475
محتوای ارائه شده توسط Australian Broadcasting Corporation. تمام محتوای پادکست شامل قسمت‌ها، گرافیک‌ها و توضیحات پادکست مستقیماً توسط Australian Broadcasting Corporation یا شریک پلتفرم پادکست آن‌ها آپلود و ارائه می‌شوند. اگر فکر می‌کنید شخصی بدون اجازه شما از اثر دارای حق نسخه‌برداری شما استفاده می‌کند، می‌توانید روندی که در اینجا شرح داده شده است را دنبال کنید.https://fa.player.fm/legal

Artificial Intelligence chatbots have come such a long way in a really short time.

Each release of ChatGPT brings new features, like voice chat, along with updates to the training data fed into the systems, supposed to make them smarter.

But are more leaps forward a sure thing? Or could the tools actually get dumber?

Today, Aaron Snoswell from the generative AI lab at the Queensland University of Technology discusses the limitations of large language models like ChatGPT.

He explains why some observers fear ‘model collapse’, where more mistakes creep in as the systems start ‘inbreeding’, or consuming more AI created content than original human created works.

Aaron Snoswell says these models are essentially pattern matching machines, which can lead to surprising failures.

He also discusses the massive amounts of data required to train these models and the creative ways companies are sourcing this data.

The AI expert also touches on the concept of artificial general intelligence and the challenges in achieving it.

Featured:

Aaron Snoswell, senior research fellow at the generative AI lab at the Queensland University of Technology

Key Topics:

  • Artificial Intelligence
  • ChatGPT
  • Large Language Models
  • Model Collapse
  • AI Training Data
  • Artificial General Intelligence
  • Responsible AI Development
  • Generative AI
  continue reading

458 قسمت

Artwork

What is AI ‘model collapse’?

ABC News Daily

317 subscribers

published

iconاشتراک گذاری
 
Manage episode 447083705 series 3323475
محتوای ارائه شده توسط Australian Broadcasting Corporation. تمام محتوای پادکست شامل قسمت‌ها، گرافیک‌ها و توضیحات پادکست مستقیماً توسط Australian Broadcasting Corporation یا شریک پلتفرم پادکست آن‌ها آپلود و ارائه می‌شوند. اگر فکر می‌کنید شخصی بدون اجازه شما از اثر دارای حق نسخه‌برداری شما استفاده می‌کند، می‌توانید روندی که در اینجا شرح داده شده است را دنبال کنید.https://fa.player.fm/legal

Artificial Intelligence chatbots have come such a long way in a really short time.

Each release of ChatGPT brings new features, like voice chat, along with updates to the training data fed into the systems, supposed to make them smarter.

But are more leaps forward a sure thing? Or could the tools actually get dumber?

Today, Aaron Snoswell from the generative AI lab at the Queensland University of Technology discusses the limitations of large language models like ChatGPT.

He explains why some observers fear ‘model collapse’, where more mistakes creep in as the systems start ‘inbreeding’, or consuming more AI created content than original human created works.

Aaron Snoswell says these models are essentially pattern matching machines, which can lead to surprising failures.

He also discusses the massive amounts of data required to train these models and the creative ways companies are sourcing this data.

The AI expert also touches on the concept of artificial general intelligence and the challenges in achieving it.

Featured:

Aaron Snoswell, senior research fellow at the generative AI lab at the Queensland University of Technology

Key Topics:

  • Artificial Intelligence
  • ChatGPT
  • Large Language Models
  • Model Collapse
  • AI Training Data
  • Artificial General Intelligence
  • Responsible AI Development
  • Generative AI
  continue reading

458 قسمت

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