Row 5005

Row ID: 5005 | Dataset Entry | Axioma AXP Content Repository

Content Data

This page contains data entry 5005 from the Axioma AXP content repository. The structured data below represents the complete record for this entry.

I'm really impressed with Meta's smart moves in Virtual Reality and their big-picture thinking for the next decade. However, their decision to add large language models (LLMs) to apps like Instagram, Threads, Facebook, and WhatsApp has me scratching my head a bit.

Generally, people hop onto these platforms to chat and get entertained (Watch people get hit by cars on Instagram Reels), not for heavy-duty tasks like studying or research, which are typical uses for LLMs. Trying to do homework or deep dives into topics on a buzzing social media site? That sounds pretty distracting.

I think Meta could really hit it out of the park if they used LLMs to boost their advertising game instead. Imagine an LLM that helps advertisers craft killer campaigns or dig deeper into understanding their audiences. Sort of like Palantir’s software of gathering data and using an LLM to sort it and understand it better; but with consumers and their buying habits. That could really amp up what Meta offers to businesses and drive their growth much more effectively.

I still think META is a big buy since their forward PE is in the 20’s and Mark Zuckerberg has a great vision for the company, besides this move; Solid buy.

If anyone disagrees with me please let me know!

FieldValue
text I'm really impressed with Meta's smart moves in Virtual Reality and their big-picture thinking for the next decade. However, their decision to add large language models (LLMs) to apps like Instagram, Threads, Facebook, and WhatsApp has me scratching my head a bit. Generally, people hop onto these platforms to chat and get entertained (Watch people get hit by cars on Instagram Reels), not for heavy-duty tasks like studying or research, which are typical uses for LLMs. Trying to do homework or de…
label r/investing
dataType post
communityName r/investing
datetime 2024-04-24
username_encoded Z0FBQUFBQm5LakwyRW1uMkhxN0l6b0U2ekFsa0lWUV93dUxVMmpfbk5oVURVTTY4c3Y1ZjZXdFRFRjgzRm85TkQ0RFJ3Qnozck04RE5zSV94N2JBaVpJelVSY3JTeU42ZWc9PQ==
url_encoded Z0FBQUFBQm5Lak9GT3lZaTNGRk5GcXJIN1AzVjNWQkJ4TWlZMzd2Nnp1dGxuUkhmSHpEMHVuWk16UHFQMFFQaU9oYkpvVU1HTHp2ZkdEdG9qME9DRC1sdF9jTFJqRE9KNnpGUXJQN0FNUFV0cDlYNFhCVVdFUGJXZzdBamkzZkNpV25ZUFl3VVNpWTdZQ0JFaTNNM0dpSlNHYzllWjlOc3BJamg0U0NMVG42bldyWWNyVnp2d3hzaHQwRFdPWjRUREFyQkY2NHdtS1BW

Raw Record

{
  "text": "I'm really impressed with Meta's smart moves in Virtual Reality and their big-picture thinking for the next decade. However, their decision to add large language models (LLMs) to apps like Instagram, Threads, Facebook, and WhatsApp has me scratching my head a bit.\n\nGenerally, people hop onto these platforms to chat and get entertained (Watch people get hit by cars on Instagram Reels), not for heavy-duty tasks like studying or research, which are typical uses for LLMs. Trying to do homework or deep dives into topics on a buzzing social media site? That sounds pretty distracting.\n\nI think Meta could really hit it out of the park if they used LLMs to boost their advertising game instead. Imagine an LLM that helps advertisers craft killer campaigns or dig deeper into understanding their audiences. Sort of like Palantir’s software of gathering data and using an LLM to sort it and understand it better; but with consumers and their buying habits. That could really amp up what Meta offers to businesses and drive their growth much more effectively.\n\nI still think META is a big buy since their forward PE is in the 20’s and Mark Zuckerberg has a great vision for the company, besides this move; Solid buy.\n\nIf anyone disagrees with me please let me know!",
  "label": "r/investing",
  "dataType": "post",
  "communityName": "r/investing",
  "datetime": "2024-04-24",
  "username_encoded": "Z0FBQUFBQm5LakwyRW1uMkhxN0l6b0U2ekFsa0lWUV93dUxVMmpfbk5oVURVTTY4c3Y1ZjZXdFRFRjgzRm85TkQ0RFJ3Qnozck04RE5zSV94N2JBaVpJelVSY3JTeU42ZWc9PQ==",
  "url_encoded": "Z0FBQUFBQm5Lak9GT3lZaTNGRk5GcXJIN1AzVjNWQkJ4TWlZMzd2Nnp1dGxuUkhmSHpEMHVuWk16UHFQMFFQaU9oYkpvVU1HTHp2ZkdEdG9qME9DRC1sdF9jTFJqRE9KNnpGUXJQN0FNUFV0cDlYNFhCVVdFUGJXZzdBamkzZkNpV25ZUFl3VVNpWTdZQ0JFaTNNM0dpSlNHYzllWjlOc3BJamg0U0NMVG42bldyWWNyVnp2d3hzaHQwRFdPWjRUREFyQkY2NHdtS1BW"
}
Explore Dataset Explore Row

Entry Information