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LLMs in 2024: A Year in Review

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Manage episode 459604266 series 3362138
Content provided by Paris Childress and Hop Online. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Paris Childress and Hop Online 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://podcastplayer.com/legal.

This 2024 blog post reviews advancements in Large Language Models (LLMs). Key themes include the breaking of the GPT-4 barrier, with multiple organizations surpassing its capabilities; significant improvements in model efficiency and price reductions, making LLMs more accessible; the rise of multimodal models incorporating vision, audio, and even live video; and the emergence of inference-scaling "reasoning" models. The author also discusses challenges like the prevalence of "slop" (unwanted, unreviewed AI-generated content), the difficulty of using LLMs effectively, and the uneven distribution of LLM knowledge. The overall purpose is to summarize the year's progress in the field, highlighting both achievements and remaining obstacles.

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157 episodes

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Manage episode 459604266 series 3362138
Content provided by Paris Childress and Hop Online. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Paris Childress and Hop Online 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://podcastplayer.com/legal.

This 2024 blog post reviews advancements in Large Language Models (LLMs). Key themes include the breaking of the GPT-4 barrier, with multiple organizations surpassing its capabilities; significant improvements in model efficiency and price reductions, making LLMs more accessible; the rise of multimodal models incorporating vision, audio, and even live video; and the emergence of inference-scaling "reasoning" models. The author also discusses challenges like the prevalence of "slop" (unwanted, unreviewed AI-generated content), the difficulty of using LLMs effectively, and the uneven distribution of LLM knowledge. The overall purpose is to summarize the year's progress in the field, highlighting both achievements and remaining obstacles.

  continue reading

157 episodes

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