abalaji
Joined 10 years ago
Joined 10 years ago
https://www.pangram.com/history/93691929-63c0-4c18-a620-e0b7...
Even though the result is often coherent and confidently synthesizes information from multiple experiences, it can also hallucinate, suffer from recency bias, or accidentally merge memories from different decades. AFAICT, without access to the underlying telemetry, human responses are for entertainment purposes only.
Making content platform "native" and garner attention is hard work and while their first party content might be great, it isn't great "X" content which is part of the problem. There are many examples of legacy organizations optimizing for the platform and garner a lot of attention:
https://x.com/JohnCarreyrou/status/2041737922458599477?s=20
Also, people want to hear from individuals or a distinct voice, not an organization:
Focus on the 3 pronged shape. It is unique in all 4 orientations. You can use this to filter out bad rotations. Then use adjacencies to filer out the rest.
https://blacksmithgu.github.io/obsidian-dataview/
I often want to answer questions like:
- When was the last time I chatted with this person - What did we talk about - Who haven't I spoken to in a while
There is a cult understanding that Instagram ads are highly relevant and quite useful at times and WhatsApp ads have the same possibility. But the messaging is quite poor.
Does anyone know if there are well established scaling laws for reasoning models similar to chinchilla scaling. (i.e. is the above claim valid?)
[ my public key: https://keybase.io/abalaji; my proof: https://keybase.io/abalaji/sigs/6ZE68eBh5A9HTuUYP59JitdDb5igrMVBOi7gKFulYmw ]